(BIM) Application in Architecture, Engineering and Construction (AEC) Industry in Gaza Strip

الجامـــــعة اإلسالميـة – غـــــــزة (Islamic University of Gaza (IUG عمـــــــادة الدراســات العليـــــــــا Higher Education Deanship كـلـــــــــية الهنــدســـــــــــــــــــة Faculty of Engineering قســــــــم الهندســة المدنيـــــــــــة Civil Engineering Department إدارة المشروعــات الهندسيــــــــة Construction Project Management

An investigation into Building Information Modeling (BIM) application in Architecture, Engineering and Construction (AEC) industry in Gaza strip

البحث في تطبيق تكنولوجيا نمذجت معلوماث البناء )BIM( في صناعت التصميم وتشييد البناء في قطاع غزة

Submitted by:

Lina Ahmed Ata AbuHamra

Supervised by:

Prof. Dr. Adnan Ali Enshassi Distinguished Prof. of Construction Engineering and Management, IUG

A Thesis Submitted in Partial Fulfillment of Requirements for Master's Degree in Construction Project Management, Civil Engineering

September 2015 AD - 1436 HJ

إقـــــــزار

أنا الموقع أدناه مقدم الرسالة التي تحمل العنوان:

An investigation into Building Information Modeling (BIM) application in Architecture, Engineering and Construction (AEC) industry in Gaza strip

البحث في تطبيق تكنولوجيا نمذجت معلوماث البناء )BIM( في صناعت التصميم وتشييد البناء في قطاع غزة

أقر بأن ما اشتممت عميو ىذه الرسالة إنما ىي نتاج جيدي الخاص، باستثناء ما تمت اإلشارة إليو حيثما ورد، وان ىذه الرسالة ككل، أو أي جزء منيا لم يقدم من قبل لنيل درجة أو لقب عممي أو بحثي لدى أية مؤسسة تعميمية أو بحثية أخرى.

DECLARATION

The work provided in this thesis, unless otherwise referenced, is the researcher's own work, and has not been submitted elsewhere for any other degree or qualification.

اسم الباحثة: Researcher's name

لينـا أحمــد عطــا أبـو حمـرة Lina Ahmed Ata AbuHamra

E-mail: [email protected]

التوقيع: :Signature

التاريخ: Date: 2/9/2015 2/9/2015

Citing the thesis

To cite this thesis:

AbuHamra, Lina Ahmed (2015). An investigation into Building Information Modeling (BIM) application in Architecture, Engineering and Construction (AEC) industry in Gaza strip. MSc Thesis , Construction Project Management, Civil Engineering, The Islamic University of Gaza (IUG), Gaza, Gaza strip, Palestine. Or: AbuHamra, L. A. (2015). An investigation into Building Information Modeling (BIM) application in Architecture, Engineering and Construction (AEC) industry in Gaza strip. MSc Thesis, Construction Project Management, Civil Engineering, The Islamic University of Gaza (IUG), Gaza, Gaza strip, Palestine.

To link to this thesis: http://library.iugaza.edu.ps/thesis/116796.pdf

قال تعاىل: } يَْرفَع ا ّ هَلل ا ّ َّلي َن آ َمنهوا منْ ه ُْك َو ا ّ َّلي َن ُآوتهوا الْ ع ْ َْل َد َر َجات{

سورة اجملادةل : 11

صدق هللا العظمي

“All things are difficult before they are easy”

Thomas Fuller (1608 -1661)

Dedication

Firstly, this research is lovingly dedicated to my beloved Father Engineer/ Ahmed Ata AbuHamra and my beloved Mother Mrs. Rasmia Ali Qatrawi, who have been my constant source of inspiration. They have given me the guidance and discipline to tackle any difficulty in this life with enthusiasm and determination. Without their prayers, love, encouragement and support, this work would not have been made possible. Their constant love has sustained me throughout my life. And without a doubt, I dedicate this thesis to my beloved sisters, brothers, best real friends in Gaza strip in Palestine and other places in the world, as well the entire special people who have supported me throughout the process of carrying out this work. Their love and encouragement have had a significant impact on giving me the power to complete this work. I also dedicate my work to myself because I have kept trying to learn new things as well as I have been keen on fidelity and accuracy in achieving my thesis.

Lina Ahmed Ata AbuHamra

Acknowledgements

First of all, I am grateful to ALLAH the Almighty for all blessings in this life and for giving me power and ability that were necessary to achieve this goal. All thanks and praise are due to ALLAH ―Alhamdulillah.‖ I would like to express my great appreciation to Prof. Dr. Adnan Ali Enshassi, Distinguished Professor of Construction Engineering and Management and my research supervisor, for his patient guidance, enthusiastic encouragement and useful critiques of this research work. I am proud to be one of his students and to have the opportunity to be under his supervision. I would also like to express my sincere gratitude to Dr. Husameddin Mohammed Dawoud, Assistant Professor at the College of Applied Engineering and Urban Planning of The University of Palestine, Gaza. His valuable and constructive advice and assistance during the planning and development of the methodology of this research work, as well as his continuous encouragement to me, are priceless. I thank him for his willingness to dedicate to me much of his time so generously. The advice was given to me by Dr. Khalid AbdelRaouf Al-Hallaq, Assistant Professor of Civil Engineering/ Construction Management at The Islamic University of Gaza, have been of great help in the elimination of confusion at the beginning of the research in some fundamental things that identified the orientation of the study. His willingness to support and to facilitate many issues to me is appreciated. I take this opportunity to express the most sincere gratitude to Dr. Javed Intekhab, PhD in Phytochemistry, lecturer in the Department of Chemistry, Swami Vivekananda P.G College, India, for providing me with all the necessary references which needed access to the present research. I place on record, my sincere thanks to him for having encouraged me and for his honest and valuable advice according to his extensive experience. I wish to send my great thanks to Dr. Davide Polimeno, MPhil in Classical Archaeology, External Assistant of the Apulian Direction of Antiquities (Italy) and EXARC member (EU-Netherlands). I am extremely thankful and indebted to him for sharing expertise, and valuable guidance as well as for encouraging me. I would also like to express my particular thanks to both of Syed Muzammil Ali, MS in Electrical Engineering, and Tayyab Zafar, MS in Mechatronics Engineering, from Pakistan, for providing me with many of the necessary references useful to this research.

Special thanks should be given to the Department of Architectural Engineering at The Islamic University of Gaza, in particular for each of them: Prof. Nader J. El-Namara, Dr. Suhair M. Ammar, Dr. Omar S. Asfour, and Dr. Sanaa Y. Saleh, for their welcoming and help in the arbitration of the questionnaire. In the same context, special thanks to Haroun Mousa Bhar, MSc in Statistics, for his help in the statistical arbitration of the questionnaire.

I‘m particularly grateful for the assistance was given by Malek M. Abuwarda, MSc in Structural Engineering, Technical Instructor in GTC-UNRWA in Gaza, by sharing his valuable knowledge about Building Information Modeling (BIM) and Revit. I am also grateful to all those who participated in response to the questionnaire and all organizations that cooperated with me. I want to thank Abdul-Rahman Ayyash, MSc in Civil Engineering, for his help in understanding factor analysis test. My sincere thanks also extended to all my friends and colleagues for their support and encouragement to me. Last but not the least; there are no words to describe how I‘m so grateful to my beloved Father Engineer/ Ahmed Ata AbuHamra and my beloved Mother Mrs. Rasmia Ali Qatrawi for the endless encouragement, support and attention throughout all my studies at university, and especially while writing this research. As well, my profound thanks must be expressed to my beloved sisters and brothers for everything.

Thank you, Lina Ahmed Ata AbuHamra

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Abstract

Purpose: Building Information Modeling (BIM) has recently attained widespread attention in the Architecture, Engineering, and Construction (AEC) industry. BIM has been suggested by several professionals and researchers as the universal remedy to addressing the inefficiencies in the AEC industry. In numerous cases of different countries, potential benefits and competitive advantages have been reported. However, in spite of the benefits and potentials of BIM technologies, it is not applied in the AEC industry in Gaza strip in Palestine just like many other regions of the world. Therefore, the purpose of this research was to develop a clear understanding about BIM for identifying the different factors that provide useful information to consider adopting BIM technology by the practitioners in the AEC industry in Gaza strip. This purpose has been done by achieving five primary objectives by assessing the awareness level of BIM by the professionals in the AEC industry in Gaza strip, identifying BIM functions and BIM benefits that would convince the professionals for adopting BIM in the AEC industry in Gaza strip, determining barriers to BIM adoption, and by studying some hypotheses to help to reach to successful BIM-based workflow implementation.

Design/methodology/approach: A quantitative survey was used in the research. Three main steps were used to reach to the final amendment of the questionnaire: (1) Face validity by presenting the questionnaire to 12 experts in the fields of the AEC industry and Statistics (from Gaza city as well as outside Palestine), (2) pre-testing the questionnaire in two phases with 12 people who represented the target group, which involved the professionals (Architects, Civil Engineers, Mechanical Engineers, Electrical Engineers, and any other professional with related specialization) in the AEC industry in Gaza strip in Palestine, and (3) a Pilot study was conducted by distributing 40 copies of the questionnaire to respondents from the target group and analyzing them for testing the statistical validity and reliability. After piloting, the questionnaire was adopted and was distributed to the whole sample (convenience sample) from the target group. 275 copies of the questionnaire were distributed, and 270 copies of the questionnaire were received from the respondents with a response rate = 97.8%. To draw meaningful results, the collected data have been analyzed by using the quantitative data analysis techniques (which include the Relative important index, Factor analysis, Pearson correlation analysis, and others) through the Statistical Package for Social Science (SPSS) IBM version 22.

Findings: The study results indicated that the awareness level of BIM by the professionals in the AEC industry in Gaza strip is very low. Findings indicated that BIM functions are significantly needed and important for the professionals in the AEC industry in Gaza strip as well as BIM benefits are significantly valuable for them. BIM function that got the top ranking according to the overall respondents is Interoperability and translation of information. In addition to that, factor analysis has clustered BIM functions into three components. The major factor is Data management and utilization in planning; operation and maintenance. Regarding BIM benefits, the BIM benefit that got the top ranking according to the overall respondents is: Enhance design team collaboration (Architectural, Structural, Mechanical, and Electrical Engineers). Results obtained from factor analysis have clustered BIM benefits in four components, and the major factor is Controlled whole-life costs and environmental data. On the other hand, the study findings demonstrated that BIM barriers are greatly affecting the adoption of iv

BIM in the AEC industry in Gaza strip. The top barrier to BIM adoption in the AEC industry in Gaza strip from the point view of the respondents is the Lack of the awareness of BIM by stakeholders. Lack of BIM interest was the major factor of BIM barriers among four factors according to the factor analysis. Finally, Pearson correlation analysis asserted that there is a negative relationship between the BIM barriers and between each of the awareness level of BIM and the importance of BIM functions, as well as the value of BIM benefits. Pearson correlation analysis also asserted that there is a positive relationship between the awareness level of BIM and between both of the importance of BIM functions, and the value of BIM benefits.

Theoretical and practical implications of the research: More specific and practical studies are needed to understand thoroughly all topics that related to BIM. Meanwhile the awareness level and interest of BIM in Gaza strip in Palestine need to be increased through the education and the training by the academic institutions and universities, as well as any bodies that train Architects and Engineers. The AEC organizations must be patient with the BIM learning process and must act positively toward the necessary change for the successful BIM adoption. Governmental agencies should also take progressive steps to apply BIM in the AEC industry by generating a simplified implementation roadmap for the organizations to be followed gradually with clear legal benchmarks.

Originality/ value: This study will add to the current body of knowledge about BIM all over the world. It is the first study that contributes significantly to consider BIM in Gaza strip in Palestine and investigates into BIM application in the AEC firms to remedy all of their severe problems. This study can provide a documentation of reference for BIM situation in Gaza strip. It could be used as a comparative guide for the future development and broadening understanding to increase knowledge of BIM and create a creative working environment.

Keywords: Architectural Engineering and Construction (AEC) industry, Building information modeling (BIM), Organization culture, Awareness level of BIM, BIM functions, BIM benefits, BIM barriers, Gaza strip, Palestine, Factor analysis test

ممخص البحث

الغرض: حققت نمذجة معمومات المباني )BIM( في اآلونة األخيرة اىتماما ً واسع النطاق في صناعة التصميم وتشييد البناء )AEC(، حيث تم اقتراح BIM من قبل العديد من المينيين والباحثين كعالج شامل لمتغمب عمى أوجو القصور في صناعة AEC. باإلضافة إلى أنو تم رصد العديد من اإلمكانيات و الفوائد القيمة لتكنولولجيا BIM في العديد من المناطق المختمفة في العالم. ولكن وبالرغم من ذلك، إال أنو لم يتم تطبيق ىذه التكنولوجيا في قطاع غزة في فمسطين، تماما ً كما ىو الحال في العديد من المناطق األخرى في العالم. وبناء عمى ذلك، كان الغرض من ىذا البحث: بمورة مفيوم واضح عن تكنولوجيا BIM لمتعرف عمى العوامل المختمفة التي توفر معمومات مفيدة لمنظر في اعتماده لتمبية المطالب الحالية لصناعة التصميم وتشييد البناء. وقد تم ذلك من خالل تحقيق عدة أىداف رئيسية من خالل تقييم مستوى المعرفة بتكنولوجيا BIM من قبل المينيين العاممين في صناعة AEC في قطاع غزة، باإلضافة لتحديد أىم الوظائف التي يقوم بيا BIM، وفوائده األكثر قيمة والتي من شأنيا أن تقنع المينيين العتماده وتطبيقو. كما تم تحديد العوائق التي تحول دون اعتماد BIM لمتغمب عمييا. ا ًوأخير، تم دراسة بعض الفرضيات لممساعدة في الوصول إلى اعتماد BIM بنجاح.

منيجية البحث: تم اختيار البحث الكمي وذلك بإستخدام اإلستبانة التي تم تصميميا باإلستناد عمى الدراسات السابقة. وقد تم إستخدام ثالث خطوات رئيسية لموصول إلى الشكل األخير من اإلستبانة، حيث كانت كالتالي: )1( اختبار الصالحية من خالل تقديم اإلستبانة إلى 12 ا ًخبير في مجال صناعة التصميم وتشييد البناء ومجال اإلحصاء )من مدينة غزة وكذلك من خارج فمسطين(. )2( اختبار اإلستبانة عمى مرحمتين مع 12 شخص ممن يمثمون الفئة المستيدفة، والتي تشمل المينيين في صناعة AEC في قطاع غزة في فمسطين وىم: )الميندسون المعماريون، ميندسو المدني، والكيرباء، والميكانيك، باإلضافة لمميندسين من أصحاب التخصصات األخرى ذات الصمة(. )3( وقد أجريت دراسة تجريبية عن طريق توزيع وتحميل 40 نسخة من اإلستبانة لمفئة المستيدفة إلجراء اختبار الصالحية اإلحصائي باإلضافة الختبار الثبات. وبعد نجاح الدراسة التجريبية، تم إعتماد اإلستبانة وتوزيعيا عمى العينة كاممة )العينة المالئمة( من الفئة المستيدفة. وقد تم جمع 270 إستبانة كعدد إجمالي من أصل 275 استبانة، لتكون بذلك نسبة اإلستجابة = 97.8 %. وأ ا ًخير، تم تحميل البيانات كمياً إلستنباط نتائج ذات مغزى وذلك بإستخدام برنامج SPSS )إصدار IBM 22(.

النتائج: أشارت نتائج الدراسة إلى أن مستوى المعرفة بتكنولوجيا BIM منخفض جدا ً من قبل المينيين في صناعة AEC في قطاع غزة. في حين أشارت النتائج إلى األىمية والحاجة الكبيرة لوظائف BIM، والقيمة الكبيرة لمفوائد الناتجة من تطبيق BIM. وقد تبين أن وظيفة BIM األكثر أىمية وفقا لممستجيبين، ىي: قابمية التشغيل البيني ونقل المعمومات بين المستخدمين بشكل سمس. باإلضافة إلى أنو تم تجميع وظائف BIM إلى ثالثة عوامل باستخدام إختبار التحميل العاممي بيدف تقميص وتجميع البنود/ المتغيرات. وكان العامل الرئيسي في وظائف BIM ىو: إدارة البيانات واستخداميا في التخطيط ، والتشغيل، والصيانة. أما بالنسبة لفوائد BIM، فكانت الفائدة األكثر قيمة من وجية نظر المستجيبين ىي: تعزيز التعاون بين أعضاء فريق التصميم. وقد تم إستخراج أربعة عوامل رئيسية لفوائد BIM بإستخدام التحميل العاممي، وكان العامل الرئيسي ىو: التحكم في تكاليف المبنى خالل دورة حياتو والتحكم في البيانات البيئية الخاصة بالمبنى. من ناحية أخرى، أظيرت نتائج الدراسة، وجود حواجز تعرقل بشكل كبير تطبيق

BIM. وكان العائق الرئيسي لتطبيق BIM ىو: عدم المعرفة بتكنولوجيا BIM من قبل الجيات المعنية. كما تم إستخراج أربعة عوامل رئيسية لعوائق تطبيق BIM بإستخدام التحميل العاممي، وقد كان العامل الرئيسي ىو: عدم وجود إىتمام بتكنولوجيا BIM. ا ،ًوأخير ومن خالل تحميل االرتباط بيرسون، تبين أن ىناك عالقة سمبية بين حواجز تطبيق BIM، وبين كال من مستوى المعرفة بتكنولوجيا BIM، وأىمية وظائفو، وكذلك قيمة فوائده. باإلضافة إلى وجود عالقة إيجابية بين مستوى المعرفة بتكنولوجيا BIM، وبين كال ً من أىمية وظائف BIM، وقيمة فوائده.

اآلثار النظرية والعممية لمبحث: توجد حاجة ماسة لممزيد من البحوث المستقبمية لمعمل عمى زيادة الفيم لجميع المواضيع المتعمقة بتكنولوجيا BIM، بحيث تكون محددة بشكل أكبر، باإلضافة إلجراء البحوث التطبيقية في مجال ال BIM. من ناحية أخرى، توجد ضرورة ممحة لزيادة االىتمام والمعرفة بتكنولوجيا BIM في قطاع غزة في فمسطين من خالل التعميم والتدريب من قبل المؤسسات األكاديمية والجامعات، فضال ً عن الييئات التي تقوم بتدريب الميندسين. كذلك، يجب عمى المؤسسات والشركات العاممة في مجال AEC أن تتصرف بشكل إيجابي نحو التغيير الالزم لنجاح اعتماد BIM. كما يجب عمى الجيات الحكومية دعم تطبيق BIM من خالل اتخاذ خطوات تدريجية وفعالة كعمل خارطة طريق لتطبيق BIM بشكل تدريجي، مع ضرورة توفير المعايير القانونية الالزمة لذلك وبشكل واضح.

قيمة البحث: يعد ىذا البحث إضافة لمدراسات الموجودة عن تكنولوجيا BIM حول العالم. كما تعد ىذه الدراسة ىي األولى من نوعيا التي ستساىم بشكل كبير لمنظر في تكنولوجيا BIM في قطاع غزة في فمسطين، والتحقيق في تطبيق BIM في الشركات والمؤسسات في صناعة AEC في قطاع غزة لمعالجة جميع المشاكل الصعبة التي تواجييا أثناء العمل. عالوة عمى ذلك، يمكن إستخدام ىذه الدراسة كقاعدة أساسية لمبحوث المستقبمية بيدف توسيع المدارك لزيادة المعرفة بتكنولوجيا BIM من أجل إيجاد بيئة أكثر إبداعا ً ا ًوتطور في العمل اليندسي في مجال التصميم والبناء.

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Table of contents Citing the thesis ...... IV Dedication ...... i Acknowledgements ...... ii Abstract ...... iv

vi ...... ممخص البحث

Table of contents ...... viii List of tables ...... xii List of figures ...... xvi List of abbreviations ...... xvii Chapter 1: Introduction ...... 2 1.1 Background...... 2 1.2 Problem statement and research justification ...... 3 1.3 Research aim, objectives, questions, and hypotheses...... 4 1.4 Delimitations of the study ...... 6 1.5 Research design ...... 7 1.6 Contribution to knowledge ...... 7 1.7 Structure of the thesis ...... 8 Chapter 2: Literature review ...... 10 2.1 Understanding of BIM concept ...... 10 2.1.1 BIM: Definition and characteristics ...... 10 2.1.2 Types of BIM ...... 13 2.1.3 The awareness level of BIM ...... 13 2.1.4 How is BIM used? ...... 14 2.2 Impact of BIM in the AEC/ FM industry ...... 18 2.2.1 Possible benefits of BIM adoption in the AEC/ FM industry ...... 19 2.2.2 Benefits of BIM during design, construction, facilities and operations, and maintenance of a building project ...... 21 2.2.2.1 BIM benefits related to the design phase of a project ...... 22 2.2.2.2 BIM benefits during the construction phase ...... 24 2.2.2.3 BIM benefits during facilities, operations and maintenance of a building project ...... 26 2.3 Slow adoption of BIM in construction industry ...... 29

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2.3.1 Barriers and challenges to implementing BIM in construction industry ...... 30 2.3.2 Identified BIM implementation obstacles and their interdependencies ...... 33 2.3.2.1 Barriers linked to the BIM product ...... 34 2.3.2.2 Barriers linked to the BIM process ...... 35 2.3.2.3 Barriers linked to the people using BIM ...... 36 2.4 Summary...... 40 Chapter 3: Research methodology ...... 42 3.1 Research aim and objectives ...... 42 3.2 Research plan/ strategy ...... 42 3.3 Research location...... 42 3.4 Target population, sampling of the questionnaire, and data collection ...... 42 3.5 Questionnaire design and development ...... 43 3.6 Face validity ...... 44 3.7 Pre-testing the questionnaire ...... 46 3.8 Pilot study ...... 48 3.8.1 Statistical validity of the questionnaire ...... 48 3.8.2 Reliability test ...... 49 3.9 Final amendment to the questionnaire ...... 51 3.10 Quantitative data analysis ...... 60 3.11 Measurements ...... 60 3.11.1 Cross-tabulation analysis ...... 60 3.11.2 Calculating of Relative Importance Index (RII) of Factors ...... 61 3.11.3 Factor analysis ...... 61 3.11.3.1 Type of factor analysis ...... 61 3.11.3.2 Methods of factoring ...... 62 3.11.3.3 The distribution of data ...... 62 3.11.3.4 Validity of sample size ...... 62 3.11.3.5 Validity of correlation matrix (correlations between variables) ...... 62 3.11.3.6 Kaiser-Meyer-Olkin (KMO) and Bartlett's Test as a measure of appropriateness of factor analysis...... 62 3.11.3.7 Determining the number of factors ...... 63 3.11.3.8 Mathematical validity of factor analysis ...... 63 3.11.4 Normal distribution ...... 63 3.11.5 Homogeneity of variances (Homoscedasticity) ...... 64

3.11.6 Parametric tests ...... 64 3.11.6.1 Pearson's correlation coefficient ...... 64 3.11.6.2 Independent Samples t-test ...... 65 3.11.6.3 One-way Analysis of Variance (One-way ANOVA)/ (F-test) ...... 65 3.11.6.4 Scheffé's method (Multiple-Comparison procedure) ...... 65 3.12 Summary...... 65 Chapter 4: Results and discussion ...... 72 4.1 Respondents‘ profiles ...... 72 4.2 The way of implementing work by respondents ...... 73 4.3 The awareness level of BIM ...... 75 4.4 The importance of BIM functions ...... 78 4.4.1 RII of BIM functions ...... 78 4.4.2 Factor analysis results of BIM functions ...... 82 4.4.2.1 Appropriateness of factor analysis ...... 82 4.4.2.2 The extracted factors ...... 89 4.5 The value of BIM benefits ...... 93 4.5.1 RII of BIM benefits ...... 93 4.5.2 Factor analysis results of BIM benefits ...... 98 4.5.2.1 Appropriateness of factor analysis ...... 98 4.5.2.2 The extracted factors ...... 107 4.6 The strength of BIM barriers ...... 113 4.6.1 RII of BIM barriers ...... 113 4.6.2 Factor analysis results of BIM barriers ...... 117 4.6.2.1 Appropriateness of factor analysis ...... 117 4.6.2.2 The extracted factors ...... 126 4.7 Test of research hypotheses ...... 132 4.7.1 The correlation between the awareness level of BIM and BIM barriers ..... 133 4.7.2 The correlation between the importance of BIM functions and BIM barriers ...... 134 4.7.3 The correlation between the value of BIM benefits and BIM barriers ...... 135 4.7.4 The correlation between the awareness level of BIM by the professionals and the importance of BIM functions ...... 136 4.7.5 The correlation between the awareness level of BIM by the professionals and the value of BIM benefits ...... 137

4.7.6 Hypothesis related to respondents‘ profiles (respondents analysis) ...... 138 4.7.6.1 An analysis taking into account the gender ...... 138 4.7.6.2 An analysis taking into account the educational qualification ...... 139 4.7.6.3 An analysis taking into account the study place ...... 140 4.7.6.4 An analysis taking into account the specialization ...... 141 4.7.6.5 An analysis taking into account the nature of the workplace ...... 143 4.7.6.6 An analysis taking into account the location of the workplace ...... 145 4.7.6.7 An analysis taking into account the current field/ the present job...... 147 4.7.6.8 An analysis taking into account the years of the experience ...... 148 Chapter 5: Conclusions and recommendations ...... 152 5.1 Summary of the research ...... 152 5.2 Conclusions of the research objectives, questions, and hypotheses ...... 152 5.2.1 Outcomes related to objective one ...... 152 5.2.2 Outcomes related to objective two ...... 153 5.2.3 Outcomes related to objective three ...... 153 5.2.4 Outcomes related to objective four ...... 154 5.2.5 Outcomes related to objective five ...... 154 5.3 Recommendations ...... 161 5.3.1 Education and training to increase BIM awareness and interest ...... 161 5.3.2 Change organizational culture ...... 162 5.3.3 Provide appropriate governmental support ...... 163 5.4 Research benefits to knowledge and the AEC industry ...... 163 5.5 Limitations and future studies ...... 164 References...... 166 Appendix A: Questionnaire (English) ...... 177 Appendix B: Questionnaire (Arabic) ...... 184 Appendix C: Correlation coefficient ...... 192

List of tables

Table (2.1): BIM features ...... 12 Table (2.2): Examples of BIM functions; (Source: Baldwin, 2012) ...... 16 Table (2.3): Summary of BIM functions ...... 17 Table (2.4): Benefits of BIM during preconstruction; design; construction; and post construction of a building project; (Eastman et al., 2008; 2011) ...... 21 Table (2.5): Summary of BIM benefits ...... 26 Table (2.6): Summary of BIM barriers ...... 37 Table (3.1): The used quantifiers for the rating scale (the five-point Likert scale) in each of the second, third, fourth and fifth fields of the questionnaire ...... 44 Table (3.2): Results of the face validity ...... 44 Table (3.3): Results of pre-testing the questionnaire ...... 47 Table (3.4): Structure validity of the questionnaire ...... 49 Table (3.5): Split-Half Coefficient method ...... 50 Table (3.6): Cronbach‘s Coefficient Alpha for reliability (Cα) ...... 50 Table (3.7): A summary illustrates how items were obtained for each field in the questionnaire ...... 52 Table (3.8): List of the items of BIM functions for the final questionnaire ...... 53 Table (3.9): List of the items of BIM benefits for the final questionnaire ...... 54 Table (3.10): List of the items of BIM barriers for the final questionnaire ...... 56 Table (3.11): Skewness and Kurtosis results ...... 64 Table (3.12): The summary of the methodology ...... 66 Table (4.1): The respondent‘s profile ...... 72 Table (4.2): The awareness level of BIM by the professionals in the AEC industry ...... 75 Table (4.3): The importance of BIM functions ...... 79 Table: (4.4): Correlations between items/ variables of BIM functions ...... 84 Table: (4.5) KMO and Bartlett's test for items/ variables of BIM functions ...... 84 Table: (4.6) Communalities of BIM functions ...... 85 Table (4.7): Total Variance Explained of BIM functions ...... 86 Table (4.8): Results of factor analysis for BIM functions ...... 89 Table (4.9): The value of BIM benefits ...... 94 Table: (4.10a): Correlations between items/ variables of BIM benefits...... 100

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Table: (4.10b): Correlations between items/ variables of BIM benefits ...... 101 Table: (4.11) KMO and Bartlett's test for items of BIM benefits ...... 101 Table: (4.12) Communalities of BIM benefits ...... 102 Table (4.13): Total variance Explained of BIM benefits...... 104 Table (4.14): Results of factor analysis for BIM benefits ...... 106 Table (4.15): The strength of BIM barriers ...... 113 Table: (4.16): Correlations between items/ variables of BIM barriers ...... 120 Table: (4.17) KMO and Bartlett's test for items/ variables of BIM barriers ...... 120 Table: (4.18) Communalities of BIM barriers ...... 121 Table (4.19): Total variance Explained of BIM barriers ...... 123 Table (4.20): Results of factor analysis for BIM barriers...... 125 Table (4.21): The correlation coefficient between the awareness level of BIM by the professionals and BIM barriers in the AEC industry in Gaza strip ...... 134 Table (4.22): The correlation coefficient between the importance of BIM functions and BIM barriers in the AEC industry in Gaza strip ...... 135 Table (4.23): The correlation coefficient between the value of BIM benefits and BIM barriers in the AEC industry in Gaza strip ...... 135 Table (4.24): The correlation coefficient between the awareness level of BIM by the professionals in the AEC industry in Gaza strip and the importance of BIM functions ...... 136 Table (4.25): The correlation coefficient between the awareness level of BIM by the professionals in the AEC industry in Gaza strip and the value of BIM benefits ...... 137 Table (4.26): Results of Independent samples t-test regarding the gender of the respondents ...... 138 Table (4.27): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the educational qualification of the respondents ...... 139 Table (4.28): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the study place of the respondents ...... 141 Table (4.29): Results of Scheffe test for multiple comparisons due to the study place of the respondents for the field of ―The importance of BIM functions‖ ...... 141 Table (4.30): Results of Scheffe test for multiple comparisons due to the study place of the respondents for all the fields of ―the investigation into BIM application in the AEC industry in Gaza strip‖ ...... 141

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Table (4.31): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the specialization of the respondents ...... 142 Table (4.32): Results of Scheffe test for multiple comparisons due to the specialization of the respondents for the field of ―The awareness level of BIM by the professionals‖ ...... 143 Table (4.33): Results of Scheffe test for multiple comparisons due to the specialization of the respondents for all fields of ―The investigation into BIM application in the AEC industry in Gaza strip‖ ...... 143 Table (4.34): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the nature of the workplace for the respondents ...... 144 Table (4.35): Results of Scheffe test for multiple comparisons due to the nature of the workplace of the respondents for the field of ―The awareness level of BIM by the professionals‖ ...... 145 Table (4.36): Results of Scheffe test for multiple comparisons due to the nature of the workplace of the respondents for the field of ―The importance of BIM functions‖ .....145 Table (4.37): Results of Scheffe test for multiple comparisons due to the nature of the workplace of the respondents for all fields of ―The investigation into BIM application in the AEC industry in Gaza strip‖ ...... 145 Table (4.38): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the location of the workplace of the respondents ...... 146 Table (4.39): Results of Scheffe test for multiple comparisons due to the location of the workplace of the respondents for the field of ―The awareness level of BIM by the professionals‖ ...... 147 Table (4.40): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the current field/ present job of the respondents ...... 147 Table (4.41): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the years of experience of the respondents ...... 149 Table (4.42): Results of Scheffe test for multiple comparisons due to the years of experience of the respondents for the field of ―The awareness level of BIM by the professionals‖ ...... 150 Table (4.43): Results of Scheffe test for multiple comparisons due to the years of experience of the respondents for the field of ―The importance of BIM functions‖ .....150 Table (4.44): Results of Scheffe test for multiple comparisons due to the years of experience of the respondents for the field of ―The value of BIM benefits‖ ...... 150

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Table (4.45): Results of Scheffe test for multiple comparisons due to the study place of the respondents for all fields of ―The investigation into BIM application in the AEC industry in Gaza strip‖ ...... 150 Table (5.1): summary of the findings of the study ...... 156 Table (C1): The correlation coefficient between each paragraph/ item in the field and the whole field (The first field is the awareness level of BIM by the professionals) ....193 Table (C2): The correlation coefficient between each paragraph in the field and the whole field (The second field is the importance of BIM functions) ...... 193 Table (C3): The correlation coefficient between each paragraph in the field and the whole field (The third field is the value of BIM benefits)...... 194 Table (C4): The correlation coefficient between each paragraph in the field and the whole field (The fourth field is the strength of BIM barriers) ...... 195

List of figures

Figure (1.1): Hypotheses model (Source: The researcher, 2015) ...... 6 Figure (4.1): Percentage of implementation the work by using 3D programs ...... 74 Figure (4.2): The used software tool by respondents to carry out projects ...... 75 Figure (4.3): RII of statements (A1 to A9) used to assess the awareness level of BIM ..76 Figure (4.4): RII of BIM functions (F1 to F16) ...... 80 Figure (4.5): The three components (factors) of BIM functions ...... 86 Figure (4.6): Scree plot for factors of BIM functions...... 87 Figure (4.7): RII of BIM benefits (BE1 to BE 26) ...... 96 Figure (4.8): The four components (factors) of BIM benefits ...... 103 Figure (4.9): Scree plot for factors of BIM benefits ...... 105 Figure (4.10): RII of BIM barriers (BA 1 to BA 18) ...... 115 Figure (4.11): The four components (factors) of BIM barriers ...... 122 Figure (4.12): Scree plot for factors of BIM barriers ...... 124 Figure (4.13): Hypotheses model (Source: The researcher, 2015) ...... 133

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List of abbreviations

Abbreviation The interpretation of the abbreviation AEC Architecture, Engineering, and Construction MEP Mechanical, Electrical and Plumbing BIM Building Information Model/ Modeling/ Management BIM(M) Building Information Modeling and Management CAD Computer Aided Design D Dimensional 2D Two dimensions: x, y 3D Three-dimensional: x, y, z (the height, length, and width) Four-dimensional; 3D model connected to a time line (fourth 4D dimension) Five-dimensional; 4D model connected to cost estimations (fifth 5D dimension) Six-dimensional; 6D model which is 5D plus site (sixth 6D dimension) Seven-dimensional; 7D model: BIM for life cycle facility 7D management (seventh dimension) nD A term that covers any other information GIS Geographic Information System CM Construction Management QS Quantity Surveyors RFI Requests For Information ILM Infrastructure Lifecycle Management ICT Information and Communications Technology CBIMKM Construction BIM-based Knowledge Management OSHA (in the US) Occupational Safety and Health Administration USC University of Southern California IT Information Technology FM Facilities Management CSCM Construction Supply Chain Management UK The United Kingdom USA The United States of America US The United States UAE The United Arab Emirates SPSS Statistical Package for the Social Sciences Cα Cronbach‘s coefficient alpha RII Relative Importance Index EFA Exploratory Factor Analysis CFA Confirmatory Factor Analysis PCA Principal Component Analysis Pearson product-moment correlation coefficient, or ―Pearson‘s r correlation coefficient‖ N Sample size DF Degree of Freedom

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Chapter 1

Chapter 1: Introduction

This chapter is aimed to give an introductory overview of the study that has been made. The problem statement was presented according to the challenges faced by the Architecture, Engineering, and Construction (AEC) industry in Gaza strip in Palestine and also the study was justified. This chapter also included aim, objectives, key research questions, hypotheses, delimitations of the study, research design, and research contribution to knowledge as well as the outline of the thesis was included in this chapter.

1.1 Background

Participants in the building process are constantly challenged to deliver successful projects despite tight budgets, limited manpower, accelerated schedules, as well as problems that regarding to the issue of waste, which is happening due to the fragmented nature of the Architecture, Engineering, and Construction (AEC) industry (RCS, 2014; Man and Machine, 2014).

The AEC industry has long sought to adopt techniques to decrease project cost, increase productivity and quality, reduce project delivery time, and eliminate waste (Azhar et al., 2008b). One of these techniques is Building Information Modeling (BIM). Azhar et al. (2008a) said that BIM has recently attained widespread attention in the AEC industry. Traditionally, Architectural design, Structural analysis, and construction management are three separate steps with distinct objectives in building engineering activities. With the prevalence of information technologies in the building industry, the combination of design and construction activities can be achieved through the integration of BIM and four-dimensional (4D) technology (Zhenzhong et al., 2008).

BIM is an inevitable development from 3D CAD (Malleson, 2013). BIM represents the development and the use of the computer-generated n-dimensional (n-D) model to simulate the design, construction, and operation of that facility. It is the process and practice of virtual design and construction throughout its lifecycle (AGC, 2005; Lorch, 2012).

Hergunsel (2011) said that BIM is becoming a better-known established collaboration process in the construction industry. The construction industry engagement with BIM has primarily been as a common platform for information exchange between a multitude of professionals, suppliers, and constructors. It is a platform to share knowledge and communicate between project participants. This enhances and accelerates the dialogue between various team members (Lorch, 2012).

Due to the different perceptions, background and experiences of researchers and professionals in the AEC industry, they can define BIM in different ways (Khosrowshahi and Arayici, 2012). For example, Gu and London (2010) said that BIM is an information technology (IT) enabled approach that involves applying and maintaining an integral digital representation of all building information for different phases of the project lifecycle in the form of a data repository. On the other hand, Eastman et al. (2008) emphasized that BIM is not only a tool, but also a process that allows project team members to have an unprecedented ability to collaborate over the 2

course of a project, from early design to occupancy. Stebbins (2009) agreed that BIM is a process rather than a piece of software. He clearly identified BIM as a business and management decision. BIM implementation is strongly related to managerial aspects of professional practices for different working styles and cultures (cited in Ahmad et al., 2012).

BIM has a broad range of application cross the design; construction; and operation process (Baldwin, 2012). BIM is important to develop the design process by managing the changes in the design. It is efficient in checking and updating all the views (plans, sections, and elevations) when any changes occur (CRC construction innovation, 2007). BIM promises exponential improvements in construction quality and efficiency (Ashcraft, 2008). In general, BIM is transforming the way Architects, Engineers, contractors, and other building professionals work in the industry today (Mandhar and Mandhar, 2013). The key benefit of BIM is its accurate geometrical representation of the parts of a building in an integrated data environment (CRC Construction Innovation, 2007). The use of BIM can increase the value of a building, shorten the project duration, provide reliable cost estimates, produce market-ready facilities, and optimize facility management and maintenance (Eastman et al., 2011).

On the other hand, the realization of the benefits of BIM is contingent upon a proper implementation of BIM at an organizational level and its integration at the industry level (Khosrowshahi and Arayici, 2012). Previous studies showed that there are several problems when implementing BIM in the very fragmented AEC industry and this is connected with many different barriers hindering effective adoption of BIM (Lindblad, 2013; Mandhar and Mandhar, 2013). In general, the barriers for BIM adoption in the AEC industry may be knowledge barriers, technical barriers, process barriers, managerial barriers, legal barriers, cultural barriers, as well as barriers to education and training (Fischer and Kunz, 2004; Becerik-Gerber et al., 2011; Both and Kindsvater, 2012; Khosrowshahi and Arayici, 2012; Löf and Kojadinovic, 2012).

1.2 Problem statement and research justification

The AEC industry is the most important industry in Gaza strip in Palestine due to the urgent need for reconstruction after the frequent wars suffered by Gaza strip, especially the recent war in the summer of 2014. In the meanwhile, the AEC industry, in turn, suffers from many of complex problems even in the case that political outstanding issues have been resolved. These problems make the achievement of the construction and reconstruction processes more difficult.

For example, construction projects in Gaza strip suffer from many complex issues due to the fragmented nature of the AEC industry and a lack of knowledge sharing as well as a lack of communication between different professionals and stakeholders. These problems can be observed between members of design teams, or even between consultants and contractors. In addition, the rising costs of construction projects remain the greatest problem the construction industry is facing now in Gaza strip. There are also other factors that affect directly and negatively the AEC industry such as delay, waste, lack of interest in the maintenance of buildings, and other issues that influence the quality of the construction projects. Accordingly, there is a need to know how to overcome these problems.

On the other hand, BIM has recently attained widespread attention in the AEC industry, and its use is growing in this industry. The use of BIM goes beyond the planning and design phase of the project. It is also important during the construction phase and for post-construction phases and facility management (Azhar et al., 2008a; Eastman et al., 2008; Eastman et al., 2011; Hardin, 2009). It promises exponential improvements in construction quality and efficiency (Ashcraft, 2008). BIM is the collaboration process in the AEC industry, where it is a platform to share knowledge and to communicate between a multitude of professionals, suppliers, and constructors. This collaboration enhances and accelerates the dialogue between various team members (Hergunsel, 2011; Lorch, 2012). Thus, BIM can be the information backbone of the whole AEC industry and thus increase the value of the workflow processes. BIM controls the accuracy of project estimates in terms of time and cost (Nassar, 2010). By implementing BIM: risk is reduced, design is maintained, quality is controlled, the collaboration between stakeholders is improved, and higher analytic tools are more accessible (CRC for Construction Innovation, 2007). A growing number of case studies over the world have shown the benefits of BIM to users who have used a building model to apply BIM technology. In spite of that, BIM has not been adopted by the AEC firms in Gaza strip just like many other regions of the world. This prompts the need for research to identify how the AEC firms in Gaza strip can adopt and implement BIM into their practices and projects to have the ability to solve all the challenging problems in the AEC industry. This can be achieved by a better understanding of BIM concept from the literature review. Additionally, and through a field survey, it can be obtained by assessing the awareness level of BIM by the professionals in the AEC industry in Gaza strip and by identifying BIM functions and BIM benefits that would convince the professionals for adopting BIM in the AEC industry in Gaza strip. This study is significant to investigate BIM barriers that face BIM adoption in the AEC industry in Gaza strip.

1.3 Research aim, objectives, questions, and hypotheses

The aim of the research is to develop a clear understanding about BIM for identifying the different factors that provide useful information to consider adopting BIM technology in projects by practitioners in the AEC industry in Gaza strip. In achieving this aim, five primary objectives have been outlined as follows:

Research objectives

1. To assess the awareness level of BIM by the professionals in the AEC industry in Gaza strip. 2. To identify the top BIM functions that would convince the professionals for adopting BIM in the AEC industry in Gaza strip. 3. To identify the top BIM benefits that would convince the professionals for adopting BIM in the AEC industry in Gaza strip. 4. To investigate and rank the top BIM barriers which face the implementation of BIM in the AEC industry in Gaza strip. 5. To study some hypotheses that might help to find solutions to adopting BIM in the AEC industry in Gaza strip.

Key research questions

RQ 1: What is the level of the awareness of BIM by the professionals in the AEC industry in Gaza strip?

RQ 2: Are the functions of BIM important from the viewpoint of the professionals (according to the need for these functions) in the AEC industry in Gaza strip? RQ 3: Are the benefits of BIM valuable from the standpoint of the professionals (according to the need for these functions) in the AEC industry in Gaza strip? RQ 4: Are BIM barriers affecting the adoption of BIM in the AEC industry in Gaza strip? RQ 5: What is the effect of the awareness level of BIM by the professionals on the reduction of BIM barriers in the AEC industry in Gaza strip? RQ 6: What is the effect of the importance of BIM functions on the reduction of BIM barriers in the AEC industry in Gaza strip? RQ 7: What is the effect of the value of BIM benefits on the reduction of BIM barriers in the AEC industry in Gaza strip? RQ 8: What is the effect of the awareness level of BIM by the professionals on increasing the importance of BIM functions in the AEC industry in Gaza strip? RQ 9: What is the effect of the awareness level of BIM by the professionals on increasing the value of BIM benefits in the AEC industry in Gaza strip? RQ 10: Are there differences in the answers of the respondents depending on the demographic data of the respondents? Research hypotheses

According to Figure (1.1), the study contains five hypotheses:

H1: There is an inverse relationship, statistically significant at α ≤ 0.05, between the awareness level of BIM by the professionals and BIM barriers in the AEC industry in Gaza strip.

H2: There is an inverse relationship, statistically significant at α ≤ 0.05, between the importance of BIM functions and BIM barriers in the AEC industry in Gaza strip. H3: There is an inverse relationship, statistically significant at α ≤ 0.05, between the value of BIM benefits and BIM barriers in the AEC industry in Gaza strip. H4: There is a positive relationship, statistically significant at α ≤ 0.05, between the awareness level of BIM by the professionals and the value of BIM benefits in the AEC industry in Gaza strip. H5: There is a positive relationship, statistically significant at α ≤ 0.05, between the awareness level of BIM by the professionals and the importance of BIM functions in the AEC industry in Gaza strip.

H6: There are statistically significant differences attributed to the demographic data of the respondents and the way of their work at the level of α ≤ 0.05 between the averages of their views on the subject of the application of BIM in the AEC industry in Gaza strip.

H4 The awareness level H5 of BIM by the professionals

The The value of importance of HI BIM BIM benefits functions

H2 H3 BIM barriers

Figure (1.1): Hypotheses model (Source: The researcher, 2015)

1.4 Delimitations of the study

The study covers the following central aspects:

 Knowledge: the study focuses on BIM adoption in the AEC industry in Gaza strip in Palestine. It aimed only to develop a clear understanding about BIM for identifying fundamental factors (the awareness level of BIM, the importance of BIM functions, the value of BIM benefits, and the BIM barriers) which help to consider adopting BIM technology in projects by the practitioners in the AEC industry. According to that, an intensive literature review was conducted to review the previous studies made in this field and dealt with these factors.

 Approach and instrument: the research approach was a quantitative survey research to measure objectives (Descriptive survey and Analytical survey). The research technique was shaped as a questionnaire. The questionnaire aimed first to meet the research objectives, to cover the central questions of the study, and to collect all the necessary data that can support the results and discussion, as well as help in putting recommendations.

 Geographical: the study covers only the AEC industry in Gaza strip in Palestine. Gaza strip consists of five governorates: the Northern Governorate, Gaza Governorate, the Middle Governorate, KhanYounis Governorate and Rafah Governorate.

 Population and Sample: research population includes professionals in the AEC industry (Architects, Civil Engineers, Mechanical Engineers, Electrical Engineers, and any other professional with related specialization). 270 out of 275 copies of the questionnaire had been returned from the respondents. Respondents were selected because of their convenient accessibility and proximity to the researcher. The sample size was chosen to provide adequate information on reliability and a certain degree of validity.

 Time: The questionnaire survey (distribution and collection) was conducted in 2015 (January). It was terminated in a period not exceeding two weeks, to remedy the delay that occurred during the preparation of the research. This delay was due to the difficult circumstances during and after the recent war in the summer of 2014.

1.5 Research design

To fulfill research objectives the following tasks were done:  It was initiated to identify the problem, define the problem, establish aim, objectives, hypotheses and key research questions, and develop research plan/strategy by deciding on the research approach and deciding on the research technique.  An intensive literature review was conducted to review the previous studies made in this field. It was performed by reading and note-taking from different sources.  Based on the extensive literature reviews, a questionnaire was designed.  Face validity was conducted by experts in the fields of the AEC industry and Statistics to see whether the questionnaire in this study appears to be valid or not.  Pre-testing the questionnaire was done in two phases to make sure that the questionnaire is going to deliver the right data and to ensure the quality of the collected data. Each phase of the pre-testing has been tested with six professionals in the AEC industry in Gaza strip.  A pilot study was conducted by distributing 40 copies of the questionnaire to respondents from the target group to measure statistical validity and reliability of the questionnaire.  After the pilot study, the questionnaire was adopted and was distributed to the whole sample.  The collected data have been analyzed quantitatively by Statistical Package for Social Science (SPSS) IBM version (22).  Findings were concluded, and appropriate graphical representations and tables were obtained to understand and analyze results.  Recommendations were suggested through the conclusion of the research.

1.6 Contribution to knowledge

The research will add to the existing knowledge about BIM technology all over the world. It is the first study that contributes significantly to consider BIM in Gaza strip in Palestine and investigates into BIM application in the AEC firms to remedy all of their severe problems. Additionally, this comprehensive study can provide a documentation of reference for BIM situation in Palestine, especially in Gaza strip. It could be used as a 7

comparative guide for future development and broadening understanding to increase knowledge of BIM and create a creative working environment.

1.7 Structure of the thesis

The research is divided into five chapters to create a good flow for the information. The outline of the thesis is as the following:

Chapter 1: Introduction

This chapter explains the background of the research. It provides the introduction to guide the reader into the research topic. The problem statement and justification of the study, research aim, objectives, questions, hypotheses, research delimitations, research design, research limitations, and research contribution to knowledge as well as the outline of the thesis are included in this chapter.

Chapter 2: Literature review

This chapter discusses BIM with a particular focus on the concept, BIM characteristics, BIM types, the awareness level and the usage. Besides, the possible benefits of BIM adoption in the AEC industry in design, construction, operations and maintenance of an asset. Finally, this chapter showed the different barriers and challenges to implementing BIM in the AEC industry.

Chapter 3: Research methodology

This chapter presents the detailed research design and the method. The chapter also explains the used technique in the analysis and issues related to data collection.

Chapter 4: Results and discussions

The findings are shown and discussed in chapter four. After results were analyzed, they are presented, discussed and linked with the previous studies in this chapter.

Chapter 5: Conclusion and recommendations

According to the final results, recommendations and conclusion of the research are discussed in chapter five.

References

Appendices

Chapter 2

Chapter 2: Literature review

The literature review is aimed to establish a theoretical understanding of the concept of the Building Information Modeling (BIM) and the barriers limiting its adoption. It has been used in two stages, first to assure the researcher understanding of the prior knowledge in the subject, and secondly to be used in comparison with the empirical data. The areas of interest for literature review are: BIM as a concept (definitions, the awareness level of BIM, and BIM functions), benefits of BIM, and barriers to BIM adoption. The sources have mainly been refereed academic research journals, refereed conferences, dissertation/ theses, reports/ occasional paper/ white papers, government publications, and books.

2.1 Understanding of BIM concept

BIM has been in use internationally for several years, and its use continues to grow. It is one of the most promising developments in the Architecture, Engineering, and Construction (AEC) industry and it has the potential to become the information backbone of a whole new AEC industry (Eastman et al., 2011; Cheng and Ma, 2013; Stanley and Thurnell, 2014). BIM is continuously developing as a concept because the boundaries of its capabilities continue to expand as technological advances are made (Joannides et al., 2012). BIM is now considered the ultimate in project delivery within the AEC industry (Azhar et al., 2008a). It is motivating an extraordinary shift in the way the construction industry functions. This fundamental change involves using digital modeling software to more effectively design, build and manage projects (Nassar, 2010).

2.1.1 BIM: Definition and characteristics

First of all, it is important to note that the acronym BIM can be used to refer to: a (1) product (building information model, meaning a structured dataset describing a building for simulation, automation, and presentation); (2) a building process or activity (building information modeling, meaning the act of creating a building information model such as thinking, creating, scheduling and organization); and (3) a system (building information management, meaning the business structures of work and communication that increase quality and efficiency such as sharing, preservation, querying the model, organization and maintaining) (NBIMS-US, 2007; Ahmad et al., 2012; State of Ohio, 2010).

RIBA (2012) pointed out that BIM should be the abbreviation for ‗building information management‘ and the term BIM(M) is alluding to ‗building information modeling and management.‘ On the other hand, it must be known that there is no exact definition of BIM; rather there are many ways of interpreting what BIM is. Khosrowshahi and Arayici (2012) agreed with Eastman et al. (2011) and Hardin (2009) that BIM is defined by various experts and organizations differently due to their perceptions, background, and experiences. They defined it based on the specific way they work with BIM (Abbasnejad and Moud, 2013).

BIM can be defined as the development and the use of a computer software model to simulate the construction and operation of a facility. The resulting building information 10

model is a digital representation of physical and functional characteristics of a facility, from which views appropriate to various users‘ needs. It serves as a shared knowledge resource for information about a facility forming a reliable basis for decisions, as well as supports collaboration between different stakeholders at different phases of the life cycle (AGC, 2005; Smith, 2007; GSA, 2007; State of Ohio, 2010; NBIMS-US, 2012). Gu and London (2010) had the same idea, where they said that BIM is an information technology (IT) enabled approach that involves applying and maintaining an integral digital representation of all building information for different phases of the project lifecycle in the form of a data repository.

Dzambazova et al. (2009) defined BIM in a different way, which is the management of information throughout the entire life cycle of a design process, from early conceptual design through construction administration, and even into facilities. BIM, for some, is merely a form of computable three-dimensional (3D) modeling (Ellis, 2006). Eastman in the BIM Handbook, viewed BIM as more of human activity, i.e., modeling, instead of seeing it as an object-oriented approach or being a particular software (Eastman et al., 2011).

Smith et al. (2004) viewed BIM as an integrative process driven by 3D computable digitized images and linked to Internet-based building cost information services. Howard and Bjork (2008) emphasized on that by saying that BIM is the ability to transfer information digitally throughout the construction process. Laiserin (2007) participated in the same point of view, where Laiserin (2007) (cited in Schade et al., 2011) defined BIM as a process to support communication (sharing data), collaboration (acting on shared data), simulation (using data for prediction) and optimization (using feedback to improve design, documentation and delivery).

From another point of view, Azhar (2011) agreed with Yan and Damin (2008) and defined BIM as a new powerful technology, which has all the functions of 3D computer-aided design (CAD) and constructs digitally an accurate virtual model of a building. BIM has also been identified by the Causeway (2011) as a key component for achieving the desired step change by transforming the information process right through the life cycle of the built environment.

BIM can be defined with a more inclusive definition. For example, BIM can be defined as the process of using information technology for sharing, modeling, evaluation, collaboration, and management of a virtually building model within a building life cycle (Ahmad et al., 2012). Hardin (2009) agreed with Smith and Tardiff (2009) and said that BIM is a revolutionary CAD technology, and building process that has transformed the way buildings are designed, analyzed, constructed, and managed. BIM model ties all the components of a building together as objects embedded with information that tracks its manufacture, cost, delivery, installation methods, labor costs, and maintenance (Smith and Tardiff, 2009).

Building Smart (2010) defined BIM as a set of information that is structured in a way that the data can be shared. BIM is a digital model of a building in which information about a project is stored. It can be 3D; four-dimensional (4D) (integrating time); or even five-dimensional (5D) (including cost); and right up to (nD) (a term that covers any other information). Eastman et al. (2011) viewed BIM as a technology that constructs digitally one or more accurate virtual models of a building to support design through its

phases, allowing better analysis and control than manual processes. These computer generated models contain precise geometry and data needed to support the construction, fabrication, and procurement activities through which the building is realized. In other words, BIM, whether building information modeling or building information management, is a technology that has improved the way structures are designed and built. BIM, Therefore, for the purpose of this research, BIM can be defined through a combination of multi-definitions, where it views as a managed process of using information technology for collection, exploitation, and sharing of information on a project. At its core is a computer-generated model that contains all the textual, graphical and tabular data about the design, construction and operation of the facility. It is used for modeling; simulation the construction; and evaluation. It supports collaboration; operation of a facility; and management of a virtually building model within a building life cycle (AGC, 2005; Smith, 2007; GSA, 2007; State of Ohio, 2010; NBIMS-US, 2012; Ahmad et al., 2012). Features of BIM

Ahmad et al., (2012) identified seven keywords from 15 different definitions of BIM. These keywords appeared at least three times in all the 15 different definitions of BIM. The keywords were as follows: (a) Information; (b) Management; (c) Modeling; (d) Process; (e) Technology; (f) Analysis; and (g) Collaboration. The keywords: "Information"; "Modeling"; and "Process" had appeared more than any other feature of BIM from the seven keywords.

Table (2.1) was tabulated by identifying the same previous seven keywords of Ahmad et al. (2012), in addition to an eighth feature which is: "Simulation," which has appeared in some BIM definitions as presented above. The total number of the definitions (that have been shown above) is 16. The keywords appeared at least three times in all the last 16 different definitions of BIM.

Table (2.1): BIM features

BIM features

Reference

Process

Analysis

Modeling

Simulation

Information Technology

Management Collaboration NBIMS-US (2007) √ √ √ √ √ √ State of Ohio (2010) √ √ √ √ √ √ AGC (2005) √ √ √ Smith (2007) √ √ √ GSA (2007) √ √ √ State of Ohio (2010) √ √ √ NBIMS-US (2012) √ √ √

Gu and London (2010) √ √ √

Dzambazova et al. (2008) √

Ellis (2006) √ Smith et al. (2004) √ √ √ Howard and Bjork (2008) √ √ Laiserin (2007) (cited in Schade et al., 2011) √ √ √ Azhar (2011) √ √ √

Table (2.1): BIM features

BIM features

Reference

Process

Analysis

Modeling

Simulation

Information Technology

Management Collaboration Yan and Damin (2008) √ √ √ Causeway (2011) √ √ √ Ahmad et al. (2012) √ √ √ √ √ √ √ Hardin (2009) √ √ √ √ √ Smith and Tardiff (2009) √ √ √ √ √ Building Smart (2010) √ √ √ √

Eastman et al. (2011) √ √ √ √ √ √ √ Weygant (2011) √ √ √ √ √ √

2.1.2 Types of BIM

Many new terms, concepts and BIM applications have been developed such as 4D; 5D; six-dimensional (6D); and seven-dimensional (7D). The (D) in the term of 3D BIM means ―dimensional‖ and it has many different purposes for the construction industry. Wang (2011) explained BIM types as the following:

. 3D: three-dimensional means the height, length, and width. . 4D: 3D plus time for construction planning and project scheduling. . 5D: 4D plus cost estimation. . 6D: 5D plus site. This would require the integration of geographic information system (GIS) and BIM. With the integration of GIS, all the items in the site model would carry the exact location and elevation information (X, Y, Z) as they are in the real construction world. . 7D: BIM for life-cycle facility management.

Recent advances in BIM have disseminated the utilization of multidimensional nD CAD information in the construction industry (Eastman et al., 2008; Jung and Joo, 2011). In addition to the parametric properties of 3D BIM, the technology also has 4D and 5D capabilities. Recent advancements in software have allowed contractors to add the parameters of cost and scheduling to models to facilitate value engineering studies; estimating and quantity take-offs; and even simulate project phasing (Holness, 2006).

2.1.3 The awareness level of BIM

There is a pressing demand for improved knowledge and understanding of BIM across the AEC industry, according to many studies related to BIM. Lack of knowledge regarding BIM has led to a slow uptake of this technology and ineffective management of adoption (Mitchell and Lambert, 2013; NBS, 2013).

In general, many studies, such as Arayici et al. (2009); Khosrowshahi and Arayici (2012); Elmualim and Gilder (2013); and Aibinu and Venkatesh (2014), concluded that there is a lack of the awareness of BIM and its benefits in the field of construction industry. They also found that there is a lack of the awareness of the business value of BIM from a financial perspective. More precisely, there is a large lack of understanding

of BIM (the core concepts of BIM) and its practical applications throughout the life of projects. There is also a lack of technical skills that professionals need to have for using the BIM software as well as a lack of knowledge of how to implement the BIM software to be helpful in construction processes.

In Hong Kong, Tse et al. (2005) revealed by research that BIM benefits were often misunderstood or not known. Gu et al., (2008) and NBS (2012) said that BIM is quite misunderstood across the board. Only 54% of the architectural practices are currently aware of BIM (NBS, 2013). In the South Australian, Newton and Chileshe (2012) found through their study that a significant proportion of respondents have little or no understanding of the concept of BIM, and the usage was found to be very low. The same finding was shown by Mitchell and Lambert (2013), where they said that people in Australia suffer from a lack of knowledge about BIM and its distinctive capabilities in the field of construction industry. Löf and Kojadinovic (2012) said that there is a lack of guidelines on how to use and align BIM in the production phase of construction projects in Sweden. Kassem et al. (2012) found through their study in the UK that there is an overall lack of knowledge and understanding of what BIM is. Thurairajah and Goucher (2013) study in the UK agreed with Kassem et al. (2012), but they found too that cost consultants in the UK are aware of BIM.

On the contrary, there was an exception in a study conducted in Ireland by Crowley (2013). It was directly relating to BIM awareness and use by quantity surveyors (QS) profession. The outcomes of the questionnaire found that 73% of the sample (105 responses) were only aware of BIM without using it; 24% were aware of BIM and using it in performing their job, and there was only 3% who were not aware of BIM.

2.1.4 How is BIM used?

At its most basic level, BIM provides three-dimensional visualization to owners. It also used as a marketing tool for potential clients and designers can employ this technology to demonstrate design ideas (Azhar et al., 2008a). Weygant (2011) viewed BIM as a tool that is used for model analysis, clash detection, product selection, and whole project conceptualization. Eastman et al. (2008) described the different uses of BIM in construction as the followings:

A. 3D model 1. Model walkthroughs for both designers and contractors to identify and resolve problems with the help of the model before walking on-site. 2. Clash detection; BIM enabled potential problems to be identified early in the design phase and resolved before construction begins. 3. Project visualization provides a very useful and successful marketing tool by making a simple schedule simulation of the building, which can show the owner what the building will look like as construction progresses. 4. Virtual mock-up models; on large projects, BIM modeling enables virtual mock-ups to be made for the owner for better understanding and making decisions. 5. Prefabrication can be utilized greater with BIM. As a result, more construction work can be performed offsite, cost efficiently, in controlled factory conditions and then efficiently installed.

B. 4D time 1. Construction planning and management; BIM tools can be used to enhance the planning and monitoring of health and safety precautions needed on-site as the project progresses. 2. Schedule visualization; by watching the schedule visualization, project members will be able to make decisions based upon multiple sources of accurate real-time information.

C. 5D cost 1. Quantity take-offs; BIM model includes information that allows a contractor to accurately and rapidly generate an array of essential estimating information, such as materials; quantities and costs; size and area estimates. As changes are made, estimating information automatically adjusts, allowing greater contractor productivity. 2. Real-time cost estimating; In a BIM model, cost data can be added to each object enabling the model to automatically calculate a rough estimate of material costs. This enables designers to conduct value engineering.

D. 6D facilities management (FM) 1. Lifecycle management; BIM model that created by the designer and updated throughout the construction phase, will have the capacity to become an ―as built‖ model, which also can be delivered to the owner. 2. Data Capture; sensors can feedback and record data relevant to the operation phase of a building, enabling BIM to be used to model and evaluate energy efficiency, monitor a building's life cycle costs and optimize its cost efficiency.

Likewise, Ashcraft (2008) presented how BIM is being used as follows: (1) single data entry, multiple uses; (2) design accuracy; (3) consistent design bases (4) 3D modeling; (5) conflict identification and resolution; (6) take-offs and estimating; (7) shop and fabrication drawing; (8) visualization of alternative solutions and options; (9) energy optimization; (10) constructability reviews and 4D simulations; (11) control fabrication costs and errors; (12) facilities management; and (13) functional simulations.

Becerik-Gerber et al. (2011) assessed the current status of BIM implementation in facility management (FM), potential applications, and the level of interest in the utilization of BIM through face-to-face interviews that conducted with the support of the FM group at the University of Southern California (USC) as well as an online survey. Becerik-Gerber et al. (2011) recognized the application areas of FM that can be implemented by BIM and can be beneficial as follow: (1) locating building component; (2) facilitating real-time data access; (3) visualization and marketing; (4) checking maintainability, where these maintainability studies can address the following areas: accessibility, sustainability of materials, and preventive maintenance; (5) creating and updating digital assets; (6) space management; (7) planning and feasibility studies for non-capital construction; (8) emergency management; (9) controlling and monitoring energy; and (10) personnel training and development.

Ku and Taiebat (2011), furthermore, investigated by an online survey among national and regional U.S. construction companies to establish baseline information of the

current level of BIM implementations and capabilities of construction companies. Ku and Taiebat (2011) found that companies utilize BIM in the following domain areas of construction management: (1) constructability and visualization (the most used aspects of BIM in all companies), where constructability tasks included clash detection for trade coordination; (2) site planning; (3) database information management; (4) model-based estimating; (5) cost control; and (6) 4D scheduling.

The Pennsylvania State University BIM execution planning guide defined twenty-five distinct BIM functions. Branching into the specialist areas of BIM, one could argue that there are much more. Building SMART International currently has over one hundred BIM activities defined as individual information delivery manuals. Regardless of how they are defined, BIM functions can be roughly grouped into five categories as shown in Table (2.2) (Baldwin, 2012).

Table (2.2): Examples of BIM functions; (Source: Baldwin, 2012) Category Examples of BIM functions Design existing conditions modeling, spatial programming, model authoring, design coordination Analysis structural analysis, energy analysis, lighting analysis, model auditing, code checking Construction site utilization, construction sequencing 4D, cost estimation 5D, digital fabrication, BIM-to-filed Operation asset and space management, maintenance scheduling, facility expansion Data collaborative platforms, change management, issue reporting and tracking, management managing metadata, linking databases, interoperability and file exchange.

Gray et al. (2013) reported, through an electronic survey, patterns of BIM usage in Australia and internationally (Korea, China, Indonesia, the United Kingdom (UK), Canada, Brazil, India and the United States of America (USA). These patterns included disciplinary users; project life cycle stages; technology integration including software compatibility; and organizational issues such as human resources and interoperability. The list of BIM uses included: (1) design visualization; (2) design assistance and constructability review; (3) site planning and site utilization; (4) scheduling and sequencing (4D); (5) cost estimating (5D); (6) integration of subcontractors and supplier models; (7) systems coordination; (8) layout and fieldwork; (9) prefabrication; and (10) operations and maintenance (including as-built records).

On the other hand, in Korea, Lee et al. (2014) summarized tasks that grounded under the construction industry and can utilize BIM as follows: (1) 3D visualization (Architectural/ Structural/ Mechanical, Electrical and Plumbing (MEP)); (2) clash detection; (3) feasibility studies; (4) model-based quantity take-off and estimation; (5) visualized scheduling 4D management; (6) environmental analysis or LEED certification (energy efficiency/ sunshine/ CO2 emission analysis); (7) creation of shop drawings and schedule management for installation of rebar/steel frame/curtain wall; (8) visualized constructability review (material lifting operation planning/ temporary resources installation); (9) visual and geospatial coordination for construction of atypical shapes; and (10) creation of as-built model for facility management.

Based on the above, it can be said that BIM has a broad range of application: right cross the design; construction; and operation process. It is often impractical for any single BIM user to have expertise in all areas; nevertheless, it is important to be aware of the

areas of application and thus be able to select which BIM functions are most applicable to one‘s own business (Baldwin, 2012). BIM is transforming the way that used by Architects, Engineers, contractors, and other building professionals in the industry today (Mandhar and Mandhar, 2013). Table (2.3) summarized the BIM functions according to items that have been presented above.

Table (2.3): Summary of BIM functions No. BIM Function Authors A. Design 3D modeling Ashcraft (2008); Eastman et al. (2008); 1 Baldwin (2012) 3D model for walkthroughs/ Ashcraft (2008); Eastman et al. (2008); 2 visualization for designers Becerik-Gerber et al. (2011); Ku and Taiebat (Architecture/ Structure/ MEP) (2011); Gray et al. (2013); Lee et al. (2014) 3 Functional simulations Ashcraft (2008) Virtual mock-up models on large Eastman et al. (2008) 4 projects Spatial programming/ Visual and Baldwin ( 2012); Lee et al. (2014) 5 geospatial coordination for construction of atypical shapes 6 Creating and updating digital assets Becerik-Gerber et al. (2011); Baldwin (2012) 7 Design assistance Gray et al. (2013) 8 Consistent design bases Ashcraft (2008) Feasibility studies/ feasibility studies for Becerik-Gerber et al. (2011); Lee et al. (2014) 9 non-capital construction B. Analysis 10 Structural analysis Baldwin ( 2012) 11 Lighting analysis Baldwin ( 2012); Lee et al. (2014) Environmental analysis or LEED Baldwin ( 2012); Lee et al. (2014) 12 certification (energy efficiency/ sunshine/ CO2 emission analysis) 13 Model auditing Baldwin ( 2012) 14 Code checking Baldwin ( 2012) C. Construction 3D model walkthroughs/ visualization Eastman et al. (2008) 15 for contractors Visualized constructability reviews Ashcraft (2008); Eastman et al. (2008); Ku 16 (material lifting operation planning/ and Taiebat (2011); Gray et al. (2013); Lee et temporary resources installation) al. (2014) 17 Prefabrication Eastman et al. (2008); Gray et al. (2013) 4D scheduling and sequencing (4D Eastman et al. (2008); Ku and Taiebat (2011); 18 simulations) Baldwin ( 2012); Gray et al. (2013); Lee et al. (2014) Cost estimation 5D Eastman et al. (2008); Baldwin ( 2012); Gray 19 et al. (2013) Site planning and site utilization/ Ku and Taiebat (2011); Baldwin ( 2012); Gray 20 Layout and fieldwork et al. (2013) Planning and monitoring of health and Eastman et al. (2008) 21 safety precautions needed on-site 22 Control fabrication costs and errors Ashcraft (2008); Ku and Taiebat (2011)

Table (2.3): Summary of BIM functions No. BIM Function Authors Model-based quantity take-offs Ashcraft (2008); Eastman et al. (2008); Ku estimating information such as and Taiebat (2011); Lee et al. (2014) 23 materials; quantities and costs; size and area estimates Clash detection/ conflict identification Ashcraft (2008); Ku and Taiebat (2011); Lee 24 and resolution et al. (2014) 25 Shop and fabrication drawing Ashcraft (2008); Lee et al. (2014) Integration of subcontractors and Gray et al. (2013) 26 supplier models D. Operation Creation of as-built model for facility/ Ashcraft (2008); Eastman et al. (2008); Lee et 27 lifecycle management al. (2014) 28 Locating building component Becerik-Gerber et al. (2011) 29 Marketing tool Becerik-Gerber et al. (2011) 30 Asset and space management Becerik-Gerber et al. (2011); Baldwin (2012) 31 Facility expansion Baldwin ( 2012) 32 Emergency management Becerik-Gerber et al. (2011) Checking maintainability (accessibility, Becerik-Gerber et al. (2011); Baldwin (2012); sustainability of materials, and Gray et al. (2013) 33 preventive maintenance)/ Maintenance scheduling Controlling and monitoring energy Ashcraft (2008); Eastman et al. (2008); 34 efficiency Becerik-Gerber et al. (2011) Monitor a building's life cycle costs and Eastman et al. (2008) 35 optimize its cost efficiency 36 Coordination of systems Gray et al. (2013) 37 Personnel training and development Becerik-Gerber et al. (2011) E. Data Management 38 Single data entry multiple uses Ashcraft (2008) 39 Data capture; issue reporting and Eastman et al. (2008); Baldwin ( 2012) tracking 40 Database information management Ku and Taiebat (2011); Baldwin ( 2012) 41 Managing metadata Baldwin ( 2012) 42 Interoperability and file exchange Baldwin ( 2012); Gray et al. (2013) 43 Facilitating real-time data access Becerik-Gerber et al. (2011) 44 Collaborative platforms Baldwin ( 2012) 45 Change Management CRC construction innovation (2007); Baldwin (2012)

2.2 Impact of BIM in the AEC/ FM industry

BIM reflects the current heightened transformation within the AEC industry and the FM sector, offering a host of benefits from increased efficiency, accuracy, speed, coordination, consistency, energy analysis, project cost reduction etc., to various stakeholders from owners to Architects, Engineers, contractors and other built environment professionals (Mandhar and Mandhar, 2013). BIM has far reaching benefits in the AEC/FM industry in supporting and improving business practices compared to traditional practices that are paper-based or two-dimensional (2D) CAD (Eastman et al., 2011). BIM is becoming more and more necessary to manage complex communication and information sharing processes in collaborative building projects. BIM serves all the stakeholders, (e.g.: designer, contractor, owner and facility manager), 18

in designing, constructing, forecasting and budgeting (Weygant, 2011). A growing number of design, engineering, and construction firms have made attempts to adopt BIM to enhance their services and products (Sebastian and Berlo, 2010; Aibinu and Venkatesh, 2013).

The adoption of BIM by the development community indicates an acceptance of its use and acknowledgment of its potential to improve the integration between procurement decisions and actual operational issues (Lorch, 2012). BIM comprises collaboration frameworks and technologies for integrating process and object-oriented information throughout the life cycle of the building in a multi-dimensional model (Sebastian and Berlo, 2010). Utilization of BIM requires collaboration among the contracting parties such as owners, Architects, Engineers, contractors, and facilities managers (Eastman et al., 2011). The use of BIM can increase the value of a building, shorten the project duration, provide reliable cost estimates, produce market-ready facilities, and optimize facility management and maintenance (Eastman et al., 2011). Sarno (2012) explored in greater detail how various activities, grouped under the term ‗project lifecycle management‘ can be consistently linked to BIM. By integrating BIM with construction project management and infrastructure lifecycle management (ILM) solutions, project stakeholders can gain new efficiencies across the entire project lifecycle. In addition to that, BIM model helps owners to achieve more control and more savings through the use of BIM in project design and construction (Eastman et al., 2011). For the AEC industry, BIM has been one of the most promising developments of our times as it allows for the creation of an accurate virtual model containing precise geometry and other relevant information aiding in modeling the entire lifecycle of a building (Eastman et al., 2011). BIMs contain a rich information model (geometric, topology and semantic details) related to the life cycle of a facility, and enable enhanced communication, coordination, analysis, and quality control (McGraw-Hill Construction, 2008). The color of BIM is green, where using it properly will cut project time and thereby energy use, as well as cost. BIM will reduce the waste of materials during construction and building management and eventually assist in sustainable demolition. Energy modeling can also minimize energy use over a building‘s life (Kolpakov, 2012). BIM models allow for a previously unimaginable array of collaborative activities; integrated inter-disciplinary design review, multi-model coordination and clash detection, and real-time integration with other specialist disciplines for cost estimation, construction management, etc. (Karlshøj, 2012).

2.2.1 Possible benefits of BIM adoption in the AEC/ FM industry

BIM benefits have been the subject of several research studies. The key benefit of BIM is its accurate geometrical representation of the parts of a building in an integrated data environment (CRC Construction Innovation, 2007). Barlish and Sullivan (2012) provided a framework calculation model to determine the value of BIM. The developed model is applied via three case studies within a large industrial setting where similar projects are evaluated, some implementing BIM and some with traditional, non-BIM approaches. Cost or investment metrics were considered along with benefit or return metrics. The return metrics were: requests for information (RFIs); change orders; and duration improvements. The investment metrics were: design and construction costs.

The findings indicated that there is a high potential for BIM benefits to be realized. Actual returns and investments will vary with each project.

From their point of view, Azhar et al. (2008a) and Azhar et al. (2008b) represented benefits of BIM as follows: 1. Faster and more effective processes: information is more easily shared; can be value-added and reused. 2. Better design: building proposals can be rigorously analyzed; simulations can be performed quickly and performance benchmarked; enabling improved and innovative solutions. 3. Controlled whole-life costs and environmental data: environmental performance is more predictable; lifecycle costs are better understood. 4. Better production quality: documentation output is flexible and exploits automation. 5. Automated assembly: digital product data can be exploited in downstream processes and be used for manufacturing/assembling of structural systems. 6. Better customer service: proposals are better understood through accurate visualization. 7. Lifecycle data: requirements, design, construction and operational information can be used in facilities management.

Allen Consulting Group (2010) has highlighted the potential benefits to be gained from the adoption of BIM technology. These included the following: (a) improved information sharing; (b) enhanced productivity through time and cost savings; (c) improved quality; (d) increased sustainability; (e) support decision making; and (f) labor market improvements.

Fast and simple material quantity take-offs represent an efficient method of checks and balances and often reduce bidding time (Holness, 2006). The BIM users‘ perception concerning the benefits of BIM features to Quantity Surveyors (QS), (also referred to as cost consultants or cost Engineers), was investigated in Australia by Aibinu and Venkatesh (2013). Data collected from a web-based survey of 180 QS firms with 40 responses and two in-depth interviews. Findings from the study showed that: (1) time savings is the most important perceived benefit nominated by 80% of the respondents. It reduces labor intensive quantity take-off and increases the ability to identify and advise the design team on elements exceeding the cost target. Other benefits listed are (2) increasing visualization (nominated by 40% of respondents), and (3) increasing productivity (nominated by 20% of the respondents).

Likewise, and based on structured interviews with the quantity surveyors in Auckland, Stanley and Thurnell (2014) found that 5D BIM provides advantages over traditional forms of quantity surveying by increasing efficiency, improving visualization of construction details, and earlier risk identification. More precisely, Stanley and Thurnell (2014) pointed out that benefits of 5D BIM for quantity surveying can sum up in: (1) increasing visualization; (2) enhancing collaboration on projects as people need to work together to make the models effective; (3) improving project quality and BIM data quality; (4) making project conceptualization easier; (5) increasing analysis capability; (6) improving efficiency of take-offs during budget estimate stage; (7) improving efficiency of cost planning during detailed cost plan stage; (8) improving risk

identification to be available in earlier stage; (9) increasing ability to resolve requests for information (RFIs) in real time; and (10) improving estimating and project options.

Khosrowshahi and Arayici (2012), in a questionnaire survey amongst the major contractors in the UK and interviews with high profile organizations in Finland geared toward establishing issues can be overcome by BIM implementation, recognized the following eight benefits: (1) reduce error, rework and waste for better sustainability for design and construction; (2) improve risk management; (3) removal of waste from process; (4) improve lean construction and design; (5) improve the whole lifecycle asset management, better facility management/asset management; (6) ability to better deal with client made changes to the design and the lifecycle implications of these; (7) gaining supply-chain support in producing documentation and supply-chain skill set; and (8) construction management appreciation of the use of technology.

Newton and Chileshe (2012) conducted a study to achieve two objectives which are related to BIM awareness and benefits among the stakeholders of the South Australian construction industry. A field study was conducted with a randomly selected sample of twenty-nine construction organizations. Ten of BIM benefits were used, and survey response data were collected using structured questionnaires. About the awareness and usage, the findings indicated that a significant proportion of respondents have little or no understanding of the concept of BIM and the usage was found to be very low. The benefits summed up in (a) improved constructability; (b) improved visualization; (c) improved productivity; and (d) reduced clashes as the highly ranked benefits associated with BIM adoption.

2.2.2 Benefits of BIM during design, construction, facilities and operations, and maintenance of a building project

This section of exploring the previous studies, which related to BIM, looks at the various benefits of using BIM and shows how much the various stakeholders can gain from going beyond the traditional 2D CAD approach throughout the different stages of construction (preconstruction, design, fabrication and construction, and post construction as operation and maintenance). Eastman, in the BIM Handbook, described BIM as an innovative way to preconstruction; design; construction; and post construction of a building project in comparison to the traditional way of drawing (Eastman et al., 2008; 2011). Table (2.4) summarized BIM benefits according to Eastman et al. (2008; 2011).

Table (2.4): Benefits of BIM during preconstruction; design; construction; and post construction of a building project; (Eastman et al., 2008; 2011) BIM benefits A. Preconstruction benefits to owner 1. The concept, feasibility, and design benefits 2. Increased building performance and quality 3. Improved collaboration using integrated project delivery B. Design benefits 1. Earlier and more accurate visualizations of design 2. Automatic low-level corrections when changes are made to design 3. Generation of accurate and consistent 2D drawings at any stage of the design 4. The earlier collaboration of multiple design disciplines 5. Easy verification of consistency to the design intent

Table (2.4): Benefits of BIM during preconstruction; design; construction; and post construction of a building project; (Eastman et al., 2008; 2011) BIM benefits 6. Extraction of cost estimates during the design stage 7. Improvement of energy efficiency and sustainability C. Construction and fabrication benefits 1. Use of design model as a basis for fabricated components 2. Quick reaction to design changes 3. Discovery of design errors and omissions before construction 4. Synchronization of design and construction planning 5. Better implementation of lean construction techniques 6. Synchronization of procurement with design and construction D. Post construction benefits 1. Improved commissioning and handover of facility information 2. Better management and operation of facilities 3. Integration with facility operation and management systems

2.2.2.1 BIM benefits related to the design phase of a project

The construction industry is widely being criticized as a fragmented industry. There are mounting calls for the industry to change and to use technologies that enable to integrate processes of design, construction, and across the supply chain. According to that, a questionnaire survey conducted by Elmualim and Gilder (2013) to ascertain the change in the construction industry concerning design management, innovation, and the application of BIM as cutting edge pathways for collaboration. The questionnaire survey was distributed and answered by respondents in the UK with other respondents representing Europe, USA, India, Ghana, China, Russia, South Africa, Australia, Canada, Malaysia and United Arab Emirates (UAE). The respondents to the survey were from an array of designations across the construction industry such as construction managers, designers, Engineers, design coordinators, design managers, Architects, Architectural Technologists, and Surveyors. As a result, there was a general agreement by most respondents that the design team was responsible for design management in their organization and BIM technologies provide a new paradigm shift in the way buildings are designed, constructed, and maintained. This paradigm shift calls for rethinking the curriculum for educating building professionals, collectively.

With BIM, efficiencies through the design process are becoming clearer. The biggest single gain would seem to be simple coordination of components using clash detection software combined with a virtual build, which means mistakes are identified before work commences on site. BIM will also demand increased attention to the selection of components at the earliest stage (Lorimer, 2011). The client can get a better scope and nature of the design and construction with BIM visualization (Ahmad et al., 2012). Traditionally, quantity take-offs and cost estimating occur late in the design stages. The use of BIM enables these estimates to occur early on and to be continuously updated as changes are made to the model (Ashcraft, 2008). The different stakeholders can find benefits from using BIM. The model developed using BIM helps owners visualize the spatial organization of the building as well as understand the sequence of construction activities and project duration (Eastman et al., 2011). Architects benefit from BIM‘s capability of creating 3D renderings, graphically accurate models, and sets of construction documents. The use of BIM prevents costly delays due to inaccurate drawings. The Architects can use the as-built models if they 22

need to work on the renovation, addition, or alteration of a building. BIM is also beneficial to the design and installation of MEP services on any construction project systems as well as their coordination with other building systems. The adoption of BIM can also help Civil Engineers to quickly analyze and compare several design alternatives (Holness, 2006). Decisions early in the design process have a significant impact on the life cycle performance of a building and with the rising cost of energy and growing environmental concerns; the demand for sustainable buildings with minimal environmental impact is increasing (Schade et al., 2011; Azhar and Brown, 2009). According to that, Schade et al. (2011) proposed a decision-making framework using a performance-based design process in the early design phase. It is developed to support decision-makers to take informed decisions regarding the life cycle performance of a building. The benefits of this BIM-based design include that such information as building geometry, structure, material, installation and functional use is stored in the BIM model. This BIM-based design reduces time and cost for analysis of energy performance for the building. Upon to energy savings, Park et al. (2012) in Korea sought to build a BIM-based system that can assess the energy performance of buildings. In recent years there is a global trend towards sustainable development in the AEC industry (Cheng and Ma, 2013). The crossover between sustainability and BIM is significant. Both seek to reduce waste, optimize building performance, and promote lean construction and integrate practices. Consequently, there is a tremendous advantage in the integration of green and BIM processes, however, as both domains are broad (covering design to operation); complex (engaging virtually every discipline in the construction process); and continually developing, this is no easy undertaking (Kolpakov, 2012). The combination of sustainable design strategies and BIM technology has the potential to change the traditional design practices and to produce a high-performance facility design (Azhar and Brown, 2009). One such effort on the Columbia campus of the University of South Carolina resulted in approximately $900,000 savings over the next ten years at current energy costs (Gleeson, 2008) (cited in Azhar and Brown, 2009).

Krygiel et al. (2008) indicated that BIM could aid in the following aspects of sustainable design: (1) building orientation (to select the best building orientation that results in minimum energy costs); (2) building massing (to analyze building form and optimize the building envelope); (3) daylighting analysis, water harvesting (to reduce water needs in a building); (4) energy modeling (to reduce energy needs and analyze renewable energy options such as solar energy); and (5) sustainable materials (to reduce material needs and to use recycled materials).

In the same context, Azhar and Brown (2009), through his study, sought to achieve many objectives. One of them was to determine the current state and benefits of BIM- based sustainability analyses. Necessary data were collected via a (1) questionnaire survey, which was distributed via a web-based service; (2) a case study; and (3) semi- structured interviews. Azhar and Brown (2009) found that the most common analyses were found to be: (1) energy analysis; (2) daylighting; (3) solar analysis; (4) building orientation analysis; (5) massing analysis; and (6) site analysis.

On the other hand, one of the most important features of the BIM for designers is the possibility of integration with GIS. Abukhater (2013) summarized benefits of this integration as follows: (1) manage end-to-end planning and design workflows; (2) generate, visualize and evaluate planning alternatives in the context of the real world; and (3) perform what-if analysis integrating 2D and 3D data. In his paper, Irizarry et al. (2013) presented an integrated BIM-GIS system for visualizing the supply chain process and the actual status of materials through the supply chain (manifesting the flow of materials, availability of resources, and ―map‖ of the respective supply chains visually). BIM has the capability to accurately provide a detailed takeoff in an early phase of the procurement process, and GIS supports the wide range of spatial analysis that used in the logistics perspective (warehousing and transportation) of the construction supply chain management (CSCM).

2.2.2.2 BIM benefits during the construction phase

Although much focus has been given to designer‘s use of BIM, contractors are also using BIM to support various construction management (CM) functions (Nepal et al., 2012). Ahmad et al. (2012) said that BIM is used more (higher percentage of use) on the construction compare to the design phase; perhaps BIM is effective in achieving quality and efficiency in construction management. Farnsworth et al. (2014) emphasized that BIM has become an integral part of commercial construction processes in recent years. Through a survey over the phone with participants for asking them a series of questions about BIM use within their companies, Farnsworth et al. (2014) explored the advantages and effects of using BIM within commercial construction by each of the different employee levels. The top advantages of using BIM were as follows: (1) improve communication; (2) more accurate scheduling; (3) improve coordination; (4) improve visualization; (5) clash detection; (6) more accurate cost estimation; and (7) performing quantity takeoffs accurately.

Regarding the effects of using BIM, companies reported a positive impact on profitability, time of construction, and marketing. According to a survey conducted by McGraw-Hill Construction in 2009, BIM enables a transparent, legitimate, and collaborative process by differentiating competitors, decreasing project duration and cost, and increasing productivity and return on investment. Seventy-three percent of users felt that BIM had a positive impact on their companies‘ productivity. The more experienced the user, the more valuable the BIM process because the company can efficiently utilize all of the benefits of BIM (McGraw-Hill Construction, 2009). Add to that, Weygant (2011); Succar (2009); Hardin (2009); Eastman et al. (2008, 2011); agreed that 4D and 5D modeling help clients and contractors in making informed decisions, by estimation, coordination and scheduling the construction process.

Holness (2006), furthermore, explained that the use of clash detection through BIM helps to resolve conflicts early in the design stage, that is, before construction starts. As a result, change orders due to design errors are virtually avoided. A schedule of construction activities can be accurately prepared and visualized using BIM. As the model developed using BIM is up-to-date and limits errors due to miscommunication between Architects, Engineers, and constructors, cost estimation is also more accurate. Nassar (2010) examined the effect that BIM can have on the accuracy of project estimates in terms of time and cost. An analytical approach was taken to quantify the potential increase in accuracy. The results proved that BIM would increase the precision

and accuracy of the quantity aspect of the estimate and it may very well also impact the precision and accuracy of the productivity aspect.

The construction industry engagement with BIM has primarily been in the use as a common platform for information exchange between a multitude of professionals, suppliers, and constructors. This engagement typically involves a shared model for a proposed design with inputs from various team members. This BIM model enhances and accelerates the dialogue between various team members (Lorch, 2012). Lin (2014), in his paper, addressed the application of knowledge management in the construction phase of construction projects and prepossessed a construction BIM-based knowledge management (CBIMKM) system for general contractors. The CBIMKM is applied in selected case studies of a construction building project in Taiwan to demonstrate the effectiveness of sharing knowledge in the 3D environment. By applying the BIM approach, all participants in a project can share and reuse explicit and tacit knowledge through the 3D CAD-based knowledge map.

According to a report conducted in 2009 by McGraw-Hill Construction, 80% of contractors in the UK believed that sustainable waste management would become an important practice by 2014; an increase of 19% compared to five years ago (McGraw- Hill Research and Analytics, 2009). Cheng and Ma (2013) developed a waste estimation system leveraging the BIM technology. This system can not only serve as a waste estimation tool before demolition or renovation but also serve as a tool to calculate waste disposal charging fee and pickup truck requirements.

Furthermore, the growing implementation of BIM in the AEC/FM industry is changing the way that safety can be approached. Significant time and economic resources are lost when workers are injured on the job sites (Zhang et al., 2013). Zhang and Hu (2011), in their study, proposed a new approach for conflict and safety analysis during construction through the integration of construction simulation, 4D construction management, and safety analysis. It presented by a 4D structural information model, which combines the advantages of 4D technology and BIM and it provides an accurate representation of construction procedure, as well as any changing of the construction plan. Moreover, all construction activities are involved in the proposed information model, therefore supporting 4D dynamic structural safety analysis.

Later, Qi et al. (2013) conducted research to explore how BIM technology can be used to enhance construction worker safety. They were developed using the BIM server and Solibri model checker software platforms respectively. This research contributed to the body of knowledge by developing these application tools which can be used to automatically check for fall hazards in building information models and in providing design alternatives to users. They can be used by Architects/Engineers during the design process or by constructors before commencing construction work. In addition to that, Zhang et al. (2013) outlined a framework for a rule-based checking system for safety planning and simulation by integrating BIM and safety. It was developed based on occupational safety and health administration (OSHA)'s fall protection rules and other construction best practices in safety and health. The automated safety-rule model checker showed the very good capability of practical applications in building modeling and planning of work tasks related to fall protection.

2.2.2.3 BIM benefits during facilities, operations and maintenance of a building project

BIM is also used in managing existing facilities, by fully modeling and linking the structure to the virtual model. By this way, energy consumption and operational faults can be detected from the model for management purposes. The Sydney-Opera House is currently managed using a BIM model for FM (Ahmad et al., 2012). BIM holds promise for creating value for owners and facilities management organizations, where the information collected through a BIM process and stored in a BIM compliant database could be beneficial for a variety of FM practices. There is a growing interest in the use of BIM in FM for coordinated, consistent, and computable building information/ knowledge management from design to construction to maintenance and operation stages of a building‘s life cycle (Becerik-Gerber et al., 2011). BIFM (2012) reported some views of some of the experts in the field of construction about the benefits of BIM for FM. They all agreed that having the building information through BIM model to do moves and changes is something that would be very useful to a facilities manager. It would make the maintenance strategy easier, improve collaboration, and save time and costs.

The advantages of BIM in the construction industry include support for graphic elements and a data management environment. BIM not only provides information related to quantity, cost, schedule, and material inventory to aid prompt decision- making, but also allows data analysis that takes into consideration the specific structure and environment (Choi, 2010; Lee et al., 2009; Lee et al., 2007; Smart Market Report, 2012) (cited in Lee et al., 2014). BIM applications are being rapidly embraced by the construction industry to reduce cost, time, and enhance quality as well as environmental sustainability (Ku and Taiebat, 2011). BIM results in a faster and more cost-effective project delivery process, and higher quality buildings that perform at reduced costs (Eastman et al., 2011). Table (2.5) summarized the BIM benefits according to items that have been presented above.

Table (2.5): Summary of BIM benefits No. BIM Benefit Authors A. BIM benefits related to the design phase of a project 1 Concept becomes clearer, and project Eastman et al. (2008, 2011); Stanley and conceptualization becomes easier to owner Thurnell (2014) 2 Earlier and more accurate visualizations of Azhar et al. (2008a); Azhar et al. (2008b); a design to the owner for better Eastman et al. (2008, 2011); Ahmad et al. understanding of proposals (2012); Newton and Chileshe (2012); Stanley and Thurnell (2014) 3 Support decision making regarding the Allen Consulting Group (2010) design 4 Improve feasibility studies Eastman et al. (2008, 2011) 5 Improve simulations (performed quickly ) Azhar et al. (2008a); Azhar et al. (2008b) 6 Improve design quality and verify Eastman et al. (2008, 2011); Holness consistency to the design intent easily, (2006) which prevents expensive delays 7 Improve the design and installation of Holness (2006) MEP services on any construction project systems as well as their coordination with other building systems

Table (2.5): Summary of BIM benefits No. BIM Benefit Authors 8 Increase analysis capability for building Azhar et al. (2008a); Azhar et al. (2008b); proposals Stanley and Thurnell (2014) 9 Improve lean design Khosrowshahi and Arayici (2012) 10 Improve sustainability: (reduce waste; use Eastman et al. (2008, 2011); Krygiel et al. recycled materials; optimize building (2008); (Gleeson, 2008) (cited in Azhar, performance and quality; promote lean 2009); Khosrowshahi and Arayici (2012); construction and integrated practices) Park et al. (2012); Kolpakov (2012) 11 Improve energy efficiency and Eastman et al. (2008, 2011); Krygiel et al. sustainability analysis such as: energy (2008); Azhar and Brown (2009); Allen analysis; day lighting; solar analysis; Consulting Group (2010) building orientation analysis; massing analysis (to analyze building form and optimize the building envelope); water harvesting; and site analysis 12 Reduce time and cost for analysis of Gleeson (2008) (cited in Azhar and energy performance for the building due to Brown, 2009); Schade et al. (2011) the information of the building that stored in BIM models such as building geometry, structure, material, installation and functional use 13 Improve the performance of the Architect Azhar et al. (2008a); Azhar et al. (2008b); and Civil Engineer; enabling improved and Allen Consulting Group (2010); Lorimer innovative solutions and use the as-built (2011); Holness (2006) models for renovation, addition, or alteration of a building 14 Integration between BIM and GIS for Abukhater (2013); Irizarry et al. (2013) managing end-to-end planning and design workflows; visualizing and evaluating planning alternatives in the context of the real world; performing what-if analysis integrating 2D and 3D data; and support the wide range of spatial analysis 15 Improve earlier collaboration of multiple Eastman et al. (2008, 2011) design disciplines using integrated project delivery 16 Save design time and costs Barlish and Sullivan (2012); Aibinu and Venkatesh (2013) 17 Improve identifying mistakes before work Eastman et al. (2008, 2011); Lorimer commences on site, where corrections can (2011) be set automatically when changes are made to design and coordinate components simply using clash detection software with a virtual build 18 Increase attention to the selection of the Lorimer (2011) construction components at the earliest stage 19 Earlier quantity takeoffs and cost Ashcraft (2008); Eastman et al. (2008, estimating during the design stages with 2011) continuously updating as changes are made to the model

Table (2.5): Summary of BIM benefits No. BIM Benefit Authors B. BIM benefits during the construction and fabrication phase 20 Improve understanding the sequence of Eastman et al. (2011) construction activities and project duration 21 Improve visualization of construction Aibinu and Venkatesh (2013); Farnsworth details et al. (2014) 22 Improve synchronization of design and Eastman et al. (2008, 2011) construction planning 23 Improve synchronization of procurement Eastman et al. (2008, 2011) with design and construction 24 Improve supply-chain process Khosrowshahi and Arayici (2012) 25 Improve constructability Newton and Chileshe (2012) 26 Improve prefabricated components Eastman et al. (2008, 2011) 27 Improve risk identification (risk Eastman et al. (2008, 2011); Khosrowshahi management) to be available in earlier and Arayici (2012); Stanley and Thurnell stage before construction (2014) 28 Improve safety Zhang et al. (2013) 29 Improve quality and efficiency in Ahmad et al. (2012); Khosrowshahi and construction management Arayici (2012) 30 Improve project quality and BIM digital Azhar et al. (2008a); Azhar et al. (2008b); data quality Stanley and Thurnell (2014) 31 Increase the ability to resolve requests for Barlish and Sullivan (2012); Stanley and information (RFIs) in real time Thurnell (2014) 32 Improve the ability of contractors to make Hardin (2009); Succar (2009); Eastman et informed decisions, by estimation, al. (2008, 2011); Weygant (2011) coordination and scheduling the construction process 33 Reduce project duration and cost of McGraw-Hill Construction (2009); construction Eastman et al. (2011); Barlish and Sullivan (2012); Barlish and Sullivan (2012) 34 Enhance productivity through time and McGraw-Hill Construction (2009); Allen cost savings Consulting Group (2010); Nassar (2010); Newton and Chileshe (2012); Aibinu and Venkatesh (2013) 35 More accurate scheduling Holness (2006); Farnsworth et al. (2014) 36 More accurate cost estimation Holness (2006); Farnsworth et al. (2014); Stanley and Thurnell (2014) 37 Better implementation of lean construction Eastman et al. (2008, 2011); Khosrowshahi techniques and Arayici (2012) 38 Reduce error, rework, and waste for better Khosrowshahi and Arayici (2012) sustainability for construction 39 Improve calculation of waste disposal Khosrowshahi and Arayici (2012); before demolition or renovation Kolpakov (2012); Cheng and Ma (2013) 40 Improve communication (information Lin (2012); Lorch (2012); Farnsworth et al. exchange among stakeholders) (2014) 41 Improve coordination and enhance McGraw-Hill Construction (2009); Lorch collaboration on projects as people need to (2012); Farnsworth et al. (2014); Stanley work together with transparency and and Thurnell (2014) legitimacy to make effective models 42 Improve labor market Allen Consulting Group (2010); Aibinu and Venkatesh (2013) 43 Improve efficiency of quantity take-offs Nassar (2010); Farnsworth et al. (2014); during budget estimate stage Stanley and Thurnell (2014) 28

Table (2.5): Summary of BIM benefits No. BIM Benefit Authors 44 Quick reaction to design changes (change Eastman et al. (2008, 2011); Barlish and orders improvement) Sullivan (2012) 45 Clash detection (reduce clashes) Holness (2006); Newton and Chileshe (2012); Farnsworth et al. (2014) C. BIM benefits during facilities, operations, and maintenance of a building project 46 Improve the control of the whole-life CRC Construction Innovation (2007); environmental data and make an accurate Azhar et al. (2008a); Azhar et al. (2008b) geometrical representation of the parts of a building in an integrated data environment 47 Information/ knowledge of a building's life Azhar et al. (2008a); Azhar et al. (2008b); cycle (Design; Construction; Maintenance Eastman et al. (2008, 2011); Allen and Operation) can be shared more easily Consulting Group (2010); Becerik-Gerber et al. (2011) 48 Improve collaboration BIFM (2012) 49 Improve the quality of the whole life cycle Azhar et al. (2008a); Azhar et al. (2008b); asset/ FM by fully modeling and linking Eastman et al. (2008, 2011); Becerik- the structure to the virtual model Gerber et al. (2011); Ahmad et al.(2012); BIFM (2012); Ku and Taiebat (2011); Khosrowshahi and Arayici (2012); 50 Reduce time and cost of FM operations Eastman et al. (2011); Ku and Taiebat (2011); BIFM (2012) 51 Support decision-makers in taking prompt Schade et al. (2011); Lee et al. (2007); Lee informed decisions regarding the life cycle et al. (2009); Choi (2010); Smart Market performance of a building, where BIM Report (2012) (cited in Lee et al., 2014) provides information related to quantity, cost, schedule, and material inventory 52 Enhance environmental sustainability Ku and Taiebat (2011) 53 Make the maintenance strategy of building Becerik-Gerber et al. (2011); BIFM (2012) easier 54 Improve the control of the whole-life costs CRC Construction Innovation (2007); Azhar et al. (2008a); Azhar et al. (2008b) 55 Improve emergency management Becerik-Gerber et al. (2011)

2.3 Slow adoption of BIM in construction industry

BIM adoption is much slower than anticipated (Fischer and Kunz, 2004). Even though the potential benefits are well documented (both in terms of improved productivity, together with many other potential benefits), but the adoption of the new technology of BIM is still slow in the AEC industry in different countries (Bernstein and Pittman, 2004; Azhar et al., 2008b; Gu and London, 2010). For example, the implementation of the BIM method in Germany is still at very early stages. In comparison to the USA and the Nordic European countries, the German AEC sector still does not internalize the potentials of BIM method and technology (Both & Kindsvater, 2012). Furthermore, Sebastian (2011) found, through his research, that the implementation of BIM in hospital building projects in Netherlands is still limited due to certain commercial and legal barriers, as well as the fact that integrated collaboration has not yet been embedded in the real estate strategies of healthcare institutions.

For BIM to be adopted successfully to improve productivity; there is a need to change the traditional work processes (Kiviniemi, 2013) (cited in Lindblad, 2013). For all actors at all phases of construction, there are several issues that need to be addressed or 29

to be fixed to gain a smooth implementation. Thus BIM benefits can be gained (Gökstorp, 2012). Due to the fragmented nature of the AEC industry, changes cannot be adopted by a single actor. It must affect all involved actors (Kiviniemi, 2013) (cited in Lindblad, 2013).

2.3.1 Barriers and challenges to implementing BIM in construction industry

There are several problems when implementing BIM in the very fragmented AEC industry and this is connected with many different barriers hindering effective adoption of BIM (Lindblad, 2013; Mandhar and Mandhar, 2013). Some of these barriers are quite simple to be removed, while others could be considered impossible to even mitigate (Gökstorp, 2012). Many studies were conducted to identify these barriers of BIM adoption in the construction industry in different countries. The results of some studies will be presented below.

Yan and Damian (2008) said, according to the results of a questionnaire, that the barriers to implementing BIM in the UK and the USA are as the following: (1) people refuse to learn and think current design technology is enough for them to design the projects; (2) people think that BIM is unsuitable for the projects; (3) about 40% of respondents from the USA and about 20% respondents from the UK believe that BIM wastes time and human resources, and their companies have to allocate lots of time and human resources to the training process; in addition to (4) the cost of copyright and training. Howard and Björk (2008) sent emails in 2006 asking questions related to BIM for Architects, Engineers, contractors and IT specialists in Denmark, Hong Kong, Holland, Norway, Sweden, the UK and the USA. Howard and Björk (2008) found many obstacles to implementing BIM in the respondents‘ answers. The barriers were as follows: (1) the need for education; (2) the need of sharing information; (3) the lack of standards; and (4) the absence of legal issues to implement BIM.

Likewise, Arayici et al. (2009) investigated, through a survey in the UK and by interviews carried out in Finland, the primary barriers to implementing BIM in many UK construction companies. The barriers are listed below according to their weighted ranks from the respondents as follows: (1) firms are not familiar enough with BIM use; (2) reluctance to initiate new workflows or train staff; (3) firms do not have enough opportunity for BIM implementation; (4) benefits from BIM implementation do not outweigh the costs to implement it; (5) benefits are not tangible enough to warrant its use; and (6) BIM does not offer enough of a financial gain to warrant its use. In his master‘s thesis, Keegan (2010) identified several observed barriers to the utilization of BIM in this regard; namely: (1) the lack of knowledge about BIM by the owner; (2) the lack of the knowledge of the software; and (3) the cost of implementing and updating the system. Becerik-Gerber et al. (2011), furthermore, reported two main groups of challenges to implementing BIM in FM: (i) technology and process challenges; and (ii) organizational challenges. Becerik-Gerber et al. (2011) detailed each group as follows: (i) the technology and process challenges: (1) unclear roles and responsibilities for loading data into the model or databases and maintaining the model; (2) the lack of effective collaboration between project stakeholders for modeling and model utilization; and (3) difficulty in software vendors‘ involvement, including fragmentation among different vendors, competition, and lack of common interests.

(ii) The organizational challenges: (1) cultural barriers toward adopting new technology; (2) organization-wide resistance regarding the need for investment in infrastructure, training, and new software tools; (3) undefined fee structures for additional scope; (4) the lack of sufficient legal framework for integrating owners‘ view in design and construction; and (5) the lack of real-world cases have been implemented by BIM and proof of positive return on investment.

Later, through the online survey within national and regional U.S. construction companies; (Ku and Taiebat, 2011) asked questions about the barriers to BIM implementation. The answers were categorized as follows:

 Factors were concerned with internal company resource aspects: 1. Lack of skilled personnel and the learning curve of new tools. 2. The investment cost of BIM in terms of time and resources.

 Factors related to sharing BIM with external stakeholders: 1. The difficulty of sharing BIM with external teams/ reluctance of others (e.g., Architects, Engineers, owners, and subcontractors). 2. Lack of collaborative work processes with the external team and modeling standards. 3. Interoperability issues between software programs. 4. The lack of legal and contractual agreements.

Lack of expertise and experience plus cost and time constraints were the two most mentioned obstacles to BIM implementation (Ku and Taiebat, 2011). In the same context, Lahdou and Zetterman (2011) have highlighted the challenges for BIM adoption in the construction project process in Sweden. For their master‘s thesis, data were collected via semi-structured interviews. In total, twelve separate interviews were conducted, of which six were with project managers and six with BIM experts. According to the interviewees, the challenges were as follows: (1) personal opinions towards BIM; (2) the lack of cohesion among stakeholders in the industry; (3) the difficulty of finding stakeholders who have the required competence to participate in BIM projects, where the Swedish construction industry generally is on a beginner level concerning the implementation of BIM; (4) the difficulties in the implementation of BIM software; (5) the legal status regarding the combined building information model which does not have any legal validity; (6) the lack of knowledge in the way of choosing an appropriate level of detail for the building information model to ensure that money and time are not wasted on compilation of unnecessary information.

In another master‘s thesis, Kjartansdóttir (2011) executed a survey among organizations and firms within the Icelandic AEC sector. The research work indicated that regulations in Iceland lacked to support the implementation of BIM. The adoption rate of BIM was 40%. The results also indicated that BIM was not being used by contractors, which indicates a low level of BIM maturity. According to the survey results, reasons for not applying BIM in Iceland were collected as follows: (1) BIM lacks features or flexibility to create building model/drawing; (2) clients are not requiring BIM; (3) BIM is too expensive; (4) other project team members are not requiring BIM; (5) the existing CAD system fulfills the need to design and draft; (6) BIM does not reduce time used on drafting compared with current drawing approach; (7) no need to produce BIM; and (8) the lack of training in BIM software.

Khosrowshahi and Arayici (2012) identified the most significant reasons to failure to implement BIM in the UK, and Finland as the following: (1) firms are not familiar enough with BIM use; (2) reluctance to initiate new workflows or train staff; (3) benefits from BIM implementation do not outweigh the costs to implement it; (4) advantages of BIM are not tangible enough to warrant its use; (5) BIM does not offer enough of a financial gain to warrant its use; (6) lack of the capital to invest in having started with hardware and software; (7) BIM is too risky from a liability standpoint to warrant its use; (8) resistance to culture change; and (9) no demand for BIM use. Moreover, Khosrowshahi and Arayici (2012) investigated challenges that faced some of the respondents during their experience in tries to implement BIM. The challenges are listed below based on their weighted ranks from the respondents as follows: (1) training staff on new process and workflow; (2) training staff on new software and technology; (3) effectively implementing the new process and workflow; (4) establishing the new process, workflow and client expectations; (5) understanding BIM enough to implement it; (6) realizing the value from a financial perspective; (7) understanding and mitigating liability; (8) purchasing software and technology; and (9) liability for common data for subcontractors.

Later, Kassem et al. (2012) investigated the barriers to adopting BIM and 4D through a web-based questionnaire. It was submitted to a selected sample of 52 consultants and 46 contractors within the UK civil and building industry. The most of the barriers were non-technical such as (1) the inefficiency in the evaluation of the business value of BIM and 4D; (2) the shortage of experience within the workforce; and (3) the lack of awareness by the stakeholders.

Choi (2010); Lee et al. (2009); Lee et al. (2007); Smart Market Report (2012) (cited in Lee et al., 2014) reported that the application of BIM in the construction industry has been slow in Korea due to the following obstacles: (1) unclear and invalid benefits of BIM in ongoing practices; (2) the lack of supporting education and training to use of BIM; (3) the lack of supporting resources (software, hardware) to use BIM tools; (4) the lack of effective collaboration between project stakeholders for modeling and model utilization; (5) unclear roles and responsibilities for loading data into a model or databases and maintaining the model; and (6) the lack of sufficient legal framework for integrating owners‘ view in design and construction.

Through their study, Elmualim and Gilder (2013) sought to achieve many objectives. One of the objectives was to determine the various challenges that are facing the construction industry in the installation of BIM in the UK, Europe, USA, India, Ghana, China, Russia, South Africa, Australia, Canada, Malaysia, and UAE. Findings from the study showed that: 20.4% of the respondents stated that they lack the capital to invest in getting started with the hardware and software; whereas about 2% stated that BIM is too risky from a liability standpoint to warrant its use. There were some other prominent responses such as 15.3% stated that the benefits of BIM do not outweigh the cost to implement it; while another 15.3% stated that the benefits are not tangible enough to warrant its use. About 8.2% of the respondents also said that they were reluctant to initiate new workflows or to train its staff. However, almost 37.8% did not know themselves as to why they had not implemented BIM as yet.

Likewise, Thurairajah and Goucher (2013) conducted research to identify the challenges and usability of BIM for cost consultants, and its likely impact during cost estimation in the UK. Data collected through a questionnaire survey and expert interviews. The respondents were approximately 20% of cost consultants and 40% of general construction professionals that having previously used BIM. The results showed a low level of BIM experience amongst the respondents. They mentioned several obstacles to BIM implementing as the following: (1) overall lack of knowledge and understanding of what BIM is; (2) a high training requirement associated with BIM implementation to gain the full advantages from it; and (3) the need for detailed understanding of cost consultants‘ challenges during the implementation of 5D BIM in construction projects.

Crowley (2013) conducted a questionnaire survey to ascertain the current position of the QS profession in Ireland directly relating to BIM use and awareness. When asked on a scale of ―very important‖ to ―not important‖ in relation to the potential barriers to BIM, the following responses were received (majority response very important): (1) lack of training/ education; (2) BIM use by Irish designers; (3) lack of client demand; (4) lack of government lead/ direction; and (5) lack of standards.

Furthermore, Aibinu and Venkatesh (2013) have investigated the progress towards BIM of QS firms in Australia. They said that the overall level of BIM adoption by QS is low in Australia. Broadly speaking, it appeared that the barriers to the adoption of BIM by Australia QS are: (1) the cost of implementation; (2) the lack of awareness of the benefits from cost-benefit analysis perspective; (3) the lack of demand by clients; (4) the lack of trust in the integrity of BIM; (5) the lack of a standard for a description of BIM objects and coding systems; (6) the lack of information on business process changes and how to change those processes; (7) the contract/ legal issues and uncertainties; (8) skills shortage; (9) transformation and adaptation issues; and (10) the technology change and ability of firms to adapt to the change from cultural perspective and financial perspective.

A similar study was conducted in Auckland in New Zealand by Stanley and Thurnell (2014) to identify the obstacles to implementing 5D BIM by doing structured interviews with eight QS. The results were as the following: (1) the lack of software compatibility; (2) prohibitive set-up costs; (3) the lack of protocols for coding objects within building information models; (4) the absence of an electronic standard for coding BIM software; and (5) the lack of integrated models, which are an essential prerequisite for full interoperability, and hence collaborative working in the industry.

2.3.2 Identified BIM implementation obstacles and their interdependencies

Some researchers tried to classify the barriers to adopting BIM in the construction industry into groups and link them together to facilitate understanding of the issue of these obstacles. For example, Fischer and Kunz (2004) reported two main groups of obstacles, which are: (i) the technical constraints; and (ii) the managerial barriers. Arayici et al. (2005) said that some of BIM barriers can be grouped into the following four categories: (1) the legal issues; (2) the cultural issues; (3) the technological issues; and (4) the fragmented nature of the AEC industry. Likewise, Becerik-Gerber et al. (2011) reported two main groups of challenges to implementing BIM in FM as follows: (i) the technology and process challenges; and (ii) the organizational challenges. Furthermore, Both and Kindsvater (2012) grouped the BIM barriers into the following

four categories: (1) the technological issues; (2) normative issues; (3) general issues; and (4) the education and training.

From another point of view, Löf and Kojadinovic (2012) clustered the obstacles in three areas, which are internally related to each other. There are also dependencies between each area. The three areas are as the following: (i) Area (1) 1. The gap between design and construction process regarding BIM usage. 2. Lack of guidelines of how BIM should be implemented in the production phase. 3. Not suitable support or training for onsite personnel to use BIM in the projects.

(ii) Area (2) 1. Lack of knowledge by the production managers in using BIM. 2. Lack of incentives to use BIM in their projects if added values are not understood.

(iii) Area (3) 1. Interoperability issues/ BIM technology not ―ready packed‖ for production phase needs. 2. Lack of demands from production on information needs. 3. Lack of incorporation of construction knowledge in the detailed design Gu et al., (2008) categorized relevant barriers to adopting BIM in the AEC industry. These categories are regarding: (1) product; (2) process; and (3) people.

2.3.2.1 Barriers linked to the BIM product

1. Interoperability

When moving to adopt BIM, new requirements need to be introduced to ensure effective interoperability and information exchange. Simply, BIM cannot run on old machines designed for AutoCAD (BD white paper, 2012). According to that, software incompatibility is the largest obstacle to interoperability. Costs are another obstacle to interoperability, with the largest expenditures coming from training and time spent on translation when switching to programs allowing interoperability (McGraw-Hill Construction, 2007). Confirmation on that, Broquetas (2010) said that the existence of certain software issues that seem not to be allowing the use of BIM with all its potential is a big challenge to adopt BIM. Accordingly, the most discussed issue when it comes to the technological aspect is the interoperability between the different programs (Bernstein and Pittman, 2004; RAIC, 2007; Both and Kindsvater, 2012; Wong and Fan, 2013). BIM software vendors have developed proprietary interfaces between design and analysis tools to facilitate interoperability, but their interfaces for each tool are different, also often resulting in the need for multiple models (Sanguinetti et al. 2012).

2. Different views on BIM

The lack of a single treatise that instructs on the application of the new 3D collaborative technology was a significant obstacle to adopting BIM in the construction industry

(AGC, 2005; Azhar et al., 2008b). BIM is quite misunderstood across the board (Gu et al., 2008; NBS, 2012). Only 54% of the architectural practices are currently aware of BIM suggesting that a lot of work needs to be done in bringing about a wider awareness of BIM (NBS, 2013).

3. Poor match with the user’s needs

Tse et al. (2005) revealed by research that a large part of the Architects in Hong Kong did not find the tools in BIM that satisfy their needs, others just stated that BIM is ―not easy to use.‖ People in Australia displayed a degree of hesitancy in implementing BIM on a project because of the lack of knowledge about BIM and its distinctive capabilities in the field of the construction industry (Mitchell and Lambert, 2013).

2.3.2.2 Barriers linked to the BIM process

1. Changing work processes

The construction industry is known for its conflicts regarding change and mistakes, which often go all the way to court. This fact fosters a culture that is heavily influenced by traditions where people like to do things according to the way they have worked before (Arayici et al., 2005). On the contrary, the adoption of BIM requires changing the traditional work practice (Davidson, 2009; Arayici et al., 2009; Gu and London, 2010). According to research by Bernstein and Pittman (2004), the data of the design should be computable; in addition to the need for well-developed practical strategies for the purposeful exchange and integration of the meaningful information among the BIM model components. Collaboration from all different stakeholders is needed for BIM to be successful; to insert, extract, update or modify information in the BIM model at the various stages of the facilities life-cycle (Sebastian, 2011). 2. Risks and challenges with the use of a single model

People in Australia expressed liability concerns when implementing BIM such as: who bears the risk; who controls the design; and who owns the BIM model (Mitchell and Lambert, 2013). The responsibility issues are due to that several stakeholders (i.e. owners, designers, and constructors) can adjust the model and that means revealing unfinished work, which gives uncertainties from the actors regarding the accuracy of the BIM model and how should the developmental and operational costs are distributed (Thomson and Miner, 2006; Azhar et al., 2008b; Gu and London, 2010). Fischer and Kunz (2004) emphasized on that by saying that the responsibility in BIM is for updating the model and ensuring that it is accurate.

3. Legal issues

When implementing BIM, one of the first issues needed to be addressed is the ownership of the model. The project owner, who pays for the design, might feel that he is entitled to own the model, but other project team members might have provided property information, and such information needs to be protected as well (Thomson and Miner, 2006). The perceived legal risks of moving from a 2D to a 3D industry and absence of standard BIM contract documents are another major stumbling block for many companies to move aggressively into BIM (Perlberg, 2009; Becerik-Gerber et al., 2010). The issue of that there are no BIM contracts is preventing people from adopting 35

and utilizing BIM with security in the construction industry (Weygant, 2011; Eastman et al., 2008; Mitchell and Lambert, 2013). 4. Transactional business process evolution

The designers, developers, contractors, and construction managers all tend to focus on their area and protect their interests in the building process, which leads to the presence of a fragmented industry (Johnson and Laepple, 2003). Different roles in the building supply chain are connected with certain obligations, risks, and rewards. These three business issues must be addressed and defined in parallel before BIM can be widely adopted by the AEC industry (Bernstein and Pittman, 2004; Gu and London, 2010).

5. Lack of demand and disinterest

Tse et al. (2005) said that one major reason for why Architects are not changing towards BIM is the lack of demand from clients and other project team members. Mitchell and Lambert (2013) said that no many asking for BIM projects in the construction industry in Australia. Because of the insufficient number of case studies showing the potential financial benefit of BIM, the AEC industry is not very interested in investing towards the change in technology (Yan and Damian, 2008).

6. Initial costs

The AEC industry consists of many small companies which have trouble to afford the high initial investment to purchase the needed software that is required to offer BIM services (Kaner et al., 2008). When respondents of QS in Australia were asked to list the barriers to the use of BIM features, the results showed that the cost of implementation was the most frequently cited (Aibinu and Venkatesh, 2013). There are several examples of the high costs that are needed to implement BIM, such as: (1) software licensing; (2) the costs to improve server capacity to suit having such a high IT requirements; (3) ongoing maintenance fee; (4) the cost of the proper creation of a building model; and (5) the costs of training (Keegan, 2010; Aibinu and Venkatesh, 2013).

2.3.2.3 Barriers linked to the people using BIM

1. The new role of BIM model manager

Adoption of BIM will affect the roles and relationships of the participating actors, as well as their work processes (Gu and London, 2010). One new role in construction project was presented by Sebastian (2011) for BIM adoption is the model manager. Grys and Westhorpe (2012) said that BIM processes should be defined and monitored by the BIM manager considering the project life-cycle, for example: (a) design creation and coordination; (b) quantity take-off; (c) cost estimation; (d) scheduling and progress monitoring; (e) change management; (f) operation and maintenance; and (g) asset management.

2. Training of individuals

When adopting BIM, it is vital that the individuals are sufficiently trained in the use of the new technology for them to be able to contribute to the changing work environment 36

(Arayici et al., 2007; Gu et al., 2008). Yan and Damian (2008) revealed that most companies in their study who did not use BIM are believed that the training would be too costly in regard to time and human resource. Many companies have not had sufficient time to consider and evaluate BIM because they had to focus on their existing projects (McGraw-Hill Construction, 2009). Löf and Kojadinovic (2012) emphasized that the time needed for training to work efficiently with BIM is one of the main challenges to adopting BIM. Kaner et al., (2008); Keegan (2010); and Aibinu and Venkatesh (2013) agreed that the high initial costs needed for training of the individuals to be able to deal with BIM are very high, and this is the primary challenge to adopt BIM in the AEC industry. Table (2.6) summarized BIM barriers according to items that have been presented above.

Table (2.6): Summary of BIM barriers No. BIM Barrier Authors A. Barriers linked to the BIM product Lack of supporting resources (software, Lee et al. (2007); Lee et al. (2009); Choi 1 hardware) to use BIM tools (2010); Smart Market Report (2012) (cited in Lee et al., 2014) Lack of interoperability due to the Bernstein and Pittman (2004); McGraw-Hill software incompatibility between the Construction (2007); Gu et al. (2008); Raic different programs for design and (2010); Ku and Taiebat (2011); BD white 2 analysis and hence the lack of integrated paper (2012); Both and Kindsvater (2012); Löf models and collaborative working and Kojadinovic (2012); Sanguinetti et al. (2012); Wong and Fan (2013); Stanley and Thurnell (2014) Lack of awareness by designers, Kassem et al. (2012); Löf and Kojadinovic Engineers, and other stakeholders about (2012); Mitchell and Lambert (2013); NBS 3 BIM and its distinctive capabilities in (2013); Thurairajah and Goucher (2013) the field of construction industry Different views on BIM, where BIM is Gu et al. (2008); Yan and Damian (2008); quite misunderstood across the board, Lahdou and Zetterman (2011); NBS (2012) 4 and people think that BIM is unsuitable for projects Designers/ Engineers think that the Yan and Damian (2008); Kjartansdóttir (2011) 5 current CAD system fulfills the need to design and draft for any project Designers/ Engineers see that BIM does Kjartansdóttir (2011) not reduce time used on drafting 6 compared with current drawing approach Lack of guidelines of how to implement AGC (2005); Azhar et al. (2008b); 7 BIM in production phase Khosrowshahi and Arayici (2012); Löf and Kojadinovic (2012); Crowley (2013) Normative issues; lack of standards for Howard and Björk (2008); Both and description of BIM objects and systems Kindsvater (2012); Crowley (2013); Aibinu 8 and Venkatesh (2014); Stanley and Thurnell (2014) Lack of protocols for coding objects Stanley and Thurnell (2014) 9 within BIM models 10 Benefits of BIM are not tangible enough Arayici et al. (2009); Khosrowshahi and in ongoing practices to warrant its use/ Arayici (2012); Löf and Kojadinovic (2012); Lack of incentives to use BIM in Elmualim and Gilder (2013); Lee et al.(2007); projects Lee et al. (2009); Choi (2010);

Table (2.6): Summary of BIM barriers No. BIM Barrier Authors Smart Market Report (2012) (cited in Lee et al., 2014) Lack of trust in the integrity of BIM; Gu et al. (2008); Kjartansdóttir (2011); Aibinu some organizations see that BIM is poor and Venkatesh (2014) 11 in matching with the user‘s needs and lacking features or flexibility to make a building model/drawing Lack of knowledge of the software, Keegan (2010); Lahdou and Zetterman (2011); 12 which leads to the existence of Kassem et al. (2012) difficulties in applying BIM software B. Barriers linked to the BIM process The fragmented nature of the AEC Arayici et al. (2005); Löf and Kojadinovic industry and its conflicts due to the gap (2012); Lindblad (2013); Mandhar and 13 between design and construction Mandhar (2013) process Resistance to culture change toward (Davidson (2009); Arayici et al. (2005); Gu et adopting new technology/ people refuse al., (2008); Yan and Damian (2008); Arayici et 14 to learn new technology, but the al. (2009); Becerik-Gerber et al. (2011); Gu adoption of BIM requires changing the and London (2010); Khosrowshahi and traditional work processes Arayici (2012) Reluctance to initiate a new workflow Arayici et al. (2009); Khosrowshahi and due to the lack of the ability of firms to Arayici (2012); Elmualim and Gilder (2013); 15 adapt it effectively Thurairajah and Goucher (2013); Aibinu and Venkatesh (2014) Data of the design should be Bernstein and Pittman (2004); Howard and computerized; in addition to the need Björk (2008) 16 for well-developed and practical strategies for sharing the meaningful information The difficulty of sharing BIM with Ku and Taiebat, 2011 external teams and reluctance of others 17 (e.g., Architect, Engineer, owners, and subcontractors) Lack of effective collaboration between Becerik-Gerber et al. (2011); Ku and Taiebat project stakeholders for modeling and (2011); Lahdou and Zetterman (2011); 18 BIM model utilization Sebastian (2011); Lee et al. (2007); Lee et al. (2009); Choi (2010); Smart Market Report (2012) (cited in Lee et al., 2014) The difficulty of finding the Lahdou and Zetterman (2011) 19 stakeholders that have the required competence to participate in BIM Lack of knowledge about how to choose Lahdou and Zetterman (2011) an appropriate level of detail for the 20 BIM model to ensure that money and time are not wasted on compilation of unnecessary information BIM is too risky regarding the Thomson and Miner (2006); Azhar et al. responsibility where several (2008b); Gu et al. (2008); Becerik-Gerber et stakeholders can adjust the model and al. (2011); Gu and London (2010); 21 that means revealing unfinished work Khosrowshahi and Arayici (2012); Elmualim and Gilder (2013); Mitchell and Lambert (2013); Aibinu and Venkatesh (2014); Lee et

Table (2.6): Summary of BIM barriers No. BIM Barrier Authors al. (2007); Lee et al. (2009); Choi (2010); Smart Market Report (2012) (cited in Lee et al., 2014) Lack of knowledge regarding the Khosrowshahi and Arayici (2012) 22 liability for common data for subcontractors Lack of legal and contractual Becerik-Gerber et al. (2010); Arayici et al. agreements that preserve the rights (2005); Eastman et al.(2008); Gu et al. (2008); when adopting BIM in the construction Howard and Björk (2008); Perlberg (2009); Ku 23 industry and Taiebat (2011); Lahdou and Zetterman (2011); Weygant (2011); Mitchell and Lambert (2013); Aibinu and Venkatesh (2014) Lack of sufficient legal framework for Becerik-Gerber et al. (2011); Lee et al. (2007); 24 integrating owners‘ view in the design Lee et al. (2009); Choi (2010); Smart Market and construction when adopting BIM Report (2012) (cited in Lee et al., 2014) Lack of government Kjartansdóttir (2011); Crowley (2013) 25 regulations/directions to fully support implementation of BIM Lack of information on business process Johnson and Laepple (2003); changes and how to change those Bernstein and Pittman (2004); Gu et al. processes among the stakeholders (2008); Gu and London, (2010); Löf and 26 (obligations, risks, and rewards must be Kojadinovic (2012); Aibinu and Venkatesh addressed and defined in parallel before (2014) BIM) Lack of knowledge about BIM by the Keegan (2010) 27 owner Lack of demand and disinterest Tse et al. (2005); Gu et al. (2008); regarding BIM from clients and the Kjartansdóttir (2011); Khosrowshahi and 28 other project team members Arayici (2012); Löf and Kojadinovic (2012); Crowley (2013); Aibinu and Venkatesh (2014) Lack of real-world cases that have Yan and Damian (2008); Becerik-Gerber et al. 29 implemented by using BIM and have (2011) proved positive return of investment Lack of awareness about the business Arayici et al. (2009); Kassem et al. (2012); value of BIM from a financial Khosrowshahi and Arayici (2012); Elmualim 30 perspective and Gilder (2013); Aibinu and Venkatesh (2014) Lack of the ability of small firms to Gu et al. (2008); Kaner et al. (2008); Yan and afford the high initial investment to Damian (2008); Arayici et al. (2009); Keegan purchase the needed software and (2010); Becerik-Gerber et al. (2011); 31 hardware that are required to offer BIM Khosrowshahi and Arayici (2012); Elmualim services and Gilder; Aibinu and Venkatesh (2014); Stanley and Thurnell (2014) C. Barriers linked to the people using BIM Adoption of BIM will affect the roles Fischer and Kunz (2004); Gu et al. (2008); and relationships of the participating (Gu and London, 2010) 32 actors such as the need to the new role of the "BIM model manager" Companies have no enough time to McGraw-Hill Construction (2009); Löf and consider and evaluate BIM because of Kojadinovic (2012) 33 focusing on the existing projects

Table (2.6): Summary of BIM barriers No. BIM Barrier Authors Lack of skilled personnel and the need Gu et al. (2008); Howard and Björk (2008); for the education and the training for the Kjartansdóttir (2011); Ku and Taiebat (2011); staff to use BIM effectively Both and Kindsvater (2012); Khosrowshahi and Arayici (2012); Crowley (2013); 34 Thurairajah and Goucher (2013); Aibinu and Venkatesh (2014); Lee et al. (2007); Lee et al. (2009); Choi (2010); Smart Market Report (2012) (cited in Lee et al., 2014) Reluctance to train the staff due to Kaner et al., (2008); Yan and Damian (2008); insufficient time and human resources Arayici et al. (2009); Becerik-Gerber et al. 35 as well as the high costs of training (2011); Keegan (2010); Khosrowshahi and Arayici (2012); Elmualim and Gilder (2013); Aibinu and Venkatesh (2014) Lack of suitable support or training for Löf and Kojadinovic (2012) 36 onsite personnel to use BIM in the projects

2.4 Summary

Many researchers have been conducted studies to explain the concept of BIM, so the definition and characteristics of BIM as well as the types of BIM were reviewed in this study. Researchers have defined BIM in different ways due to their different perceptions, background, and experiences. All definitions were reviewed.

BIM has many important functions that can be applied in the whole process of construction (from the beginning of the design phase, during the building phase, as well as during the operation phase). Most of these functions were reviewed. BIM benefits which resulting from these functions were reviewed too. Finally, it was necessary to review barriers to adopting BIM in the AEC industry.

According to the previous studies and for the purpose of this research, BIM can be defined through a combination of multi-definitions, where it views as a managed process of using information technology for collection, exploitation, and sharing of information on a project. At its core is a computer-generated model that contains all the textual, graphical and tabular data about the design, construction, and operation of the facility. It is used for modeling; simulation the construction; and evaluation. It supports collaboration; operation of a facility; and management of a virtually building model within a building life cycle (AGC, 2005; Smith, 2007; GSA, 2007; State of Ohio, 2010; NBIMS-US, 2012; Ahmad et al., 2012). In general, BIM promises exponential improvements in construction quality and efficiency (Ashcraft, 2008). Finally, it was necessary to review barriers to adopting BIM in the AEC industry.

Chapter 3

Chapter 3: Research methodology

This chapter discusses the methodology which was used in this research. The research methodology was chosen to satisfy the research aim and objectives which help to accomplish this research study. This chapter included information about the research plan/ strategy, population, sample size, data collection technique, questionnaire design and development, face validity of the questionnaire, pre-test the questionnaire, pilot study, final content of the questionnaire, and analytical methods of data.

3.1 Research aim and objectives

This research was designed to develop a clear understanding about BIM for identifying the different factors which provide useful information to consider adopting BIM technology in projects by the practitioners in the Architecture, Engineering, and Construction (AEC) industry in Gaza strip in Palestine. In achieving this aim, five main objectives have been outlined which includes:

The research strategy is the general plan for how and what data should be collected and how the results should be analyzed. The chosen research plan will influence the type and the quality of the collected data (Ghauri and Grønhaug, 2010). To investigate the research questions and hypotheses about adopting BIM technology by the practitioners in the AEC industry in Gaza strip, a quantitative survey approach has been adopted. The research technique was chosen as a questionnaire research to measure objectives.

3.3 Research location

The research was carried out in Gaza strip in Palestine, which consists of five governorates: the Northern Governorate, Gaza Governorate, the Middle Governorate, KhanYounis Governorate, and Rafah Governorate.

3.4 Target population, sampling of the questionnaire, and data collection

The questionnaire survey was conducted in 2015 (January). Research population includes professionals (Architects, Civil Engineers, Mechanical Engineers, Electrical Engineers, and any other professional with related specialization) in the AEC industry in Gaza strip in Palestine as a target group. A convenience sample was chosen as the

type of the sample. Convenience sampling is a type of nonprobability sampling in which respondents are sampled simply because they are ―convenient‖ sources of data for researchers (Lavrakas, 2008). In other words, they were selected because of their convenient accessibility and proximity to the researcher (Dillman et al., 2000). The sample size was chosen to provide adequate information on reliability and a certain degree of validity. 275 copies of the questionnaire were distributed. Each respondent took about 6 to 8 minutes to fill out the questionnaire. 270 copies of the questionnaire were returned from the respondents and completed for quantitative analysis. The totals of 270 questionnaires were satisfactorily completed, making the total response rate (270/ 275)*100 = 97.8%. Personal delivery for the whole sample helped to increase the rate of response, and thus the representation of the sample.

3.5 Questionnaire design and development

A self-administered questionnaire was used for data collection. Three fundamental stages were taken for constructing the questionnaire:

1. Identifying the first thought questions. 2. Formulating the final questionnaire. 3. The wording of questions. Identification of items for the study and preparation of questionnaire was a crucial step for the success of the research. A significant amount of work has already been done on items of BIM functions, benefits, and barriers and there is a well-documented and peer- reviewed set of those available items in the literature review in the previous chapter.

According to the review of literature related to BIM in the AEC industry, a well- designed questionnaire was developed for the study. The questionnaire consisted of close-ended (multiple choice) questions. Close-ended questions are more difficult to design than open-ended questions, but they come up with much more efficient data collection, processing and analysis (Bourque and Fielder, 2003). Bourque and Fielder (2003) said that ―surveyors should avoid using open-ended questions in the mail and other self-administered questionnaires.‖ The questionnaire divided into five parts as follows:

 Part one, which is related to the respondent‘s demographic data and the way of work performance.  Part two: to assess the awareness level of BIM by the professionals in the AEC industry in Gaza strip.  Part three: to investigate the importance of BIM functions in the AEC industry in Gaza strip.  Part four: to investigate the value of BIM benefits in the AEC industry in Gaza strip.  Part five: to investigate the BIM barriers in the AEC industry in Gaza strip. And of course, the questionnaire was provided with a covering letter explaining the aim of the research, the security of the information to encourage a high response, and the way of responding. The variety of the questions aimed first to meet the research objectives, to cover the main questions of the study, and to collect all the necessary data that can support the results and discussion, as well as the recommendations in the research. 43

After answering the first part that related to the respondent‘s demographic data and the way of work performance, respondents were asked to rate each item in each of the second, third, fourth, and fifth fields on a rating scale (five-point Likert scale) that required a ranking (1–5), where 1 represented ―the lowest scale‖ and 5 represented ―the highest scale‖, as the case might be. The rating scale (the five-point Likert scale) was chosen to format the questions of the questionnaire with some common sets of response categories called quantifiers (they reflect the intensity of the particular judgment involved) (Naoum, 2007). Those quantifiers were used to facilitate understanding as shown in Table (3.1).

Table (3.1): The used quantifiers for the rating scale (the five-point Likert scale) in each of the second, third, fourth and fifth fields of the questionnaire

The awareness level of Somewhat Much BIM by professionals Never Little Very much

The importance of BIM Of little Moderately Very Unimportant Important functions importance important important Extremely Low Moderately Highly Extremely The value of BIM low beneficial beneficial beneficial high benefits beneficial beneficial Average The strength of BIM Very weak Weak Strong Very strong strength barriers

Scale 1 2 3 4 5

The first draft of the questionnaire was revised through three main stages, which are: the face validity, pre-testing the questionnaire, and the pilot study. With each stage, the questionnaire was revised and refined more and more. Regarding details of each stage, it will be discussed in the following parts.

3.6 Face validity

Face validity was important to see whether the questionnaire appears to be valid or not. It was a ―common-sense‖ assessment by the experts in the fields of the AEC industry and Statistics (Salkind, 2010). The questionnaire was presented to 12 experts (from Gaza city as well as outside Palestine) by hand delivery and by the email at different periods for assessment the validity of the questionnaire. Many useful and important modifications have been made for the questionnaire. Those modifications have been explained in Table (3.2).

Table (3.2): Results of the face validity Name Country Specialization Outcome Expert Palestine MSc of  Corrected the formulation of the questions A (Gaza) Statistics (regarding Statistics) in the part #1 of the questionnaire which was about the respondent demographic data and the way of work performance. Expert Palestine Distinguished  Some of the items in the different fields of the B (Gaza) Prof. of questionnaire were deleted because it were not Construction related to the AEC industry in Gaza strip, or it Engineering and was not clear or ambiguous such as: Management 44

Table (3.2): Results of the face validity Name Country Specialization Outcome  Model auditing (BIM functions)  Collaborative platforms (BIM functions)  Improve labor market (BIM benefits)  Adoption of BIM will affect the roles and relationships of the participating actors such as the need to the new role of the "BIM model manager" (BIM barriers)  Some of the items were modified.  Added an item, which was:  Improve safety design (BIM benefits).  Some of the items needed for further explanation.  Some items were merged.  Advised to clarify any attached shortcuts. Expert Palestine PhD in the  Helped in designing the questions for C (Gaza) College of measuring objective #1, which was about Applied assessing the awareness level of BIM by the Engineering & professionals in the AEC industry in Gaza strip. Urban Planning  Some items, in the field of BIM barriers in the questionnaire, were designed, which are:  Lack of interest in Gaza strip to pursue the condition of the building over the life after completion of implementation  Lack of education or training on the use of BIM, whether in the university or any governmental or private training centers Expert Italy MPhil in  Audited the English language of the first draft D Classical of the questionnaire and modified some words. Archaeology  Proposed the words of the rating scale (the five- point Likert scale) for each field. Expert India PhD in  Audited the cover letter of the questionnaire E Chemistry and the general structure of the questionnaire. Expert Palestine PhD in  Had advised shortcutting the questionnaire. F (Gaza) Sustainable  Some of the items in the field of BIM functions Architecture & were deleted because they did not relate to the Housing AEC industry in Gaza strip and they were ambiguous such as:  Spatial programming/ Visual and geospatial coordination for construction of atypical shapes  Virtual mock-up models on large projects  Design assistance  Locating building component  Single data entry multiple  Facilitating real-time data access Expert Palestine PhD in  Had advised shortcutting the questionnaire. G (Gaza) Renewable  Some of the items in the field of BIM barriers Energy & were deleted because they contained difficult Architectural technical expressions, which were not suitable Design for professionals who are non-users of BIM, such as:  Lack of interoperability due to the software 45

Table (3.2): Results of the face validity Name Country Specialization Outcome incompatibility between the different programs for design and analysis and hence the lack of integrated models and collaborative working  Normative issues; lack of standards for description of BIM objects and systems  Designers/ Engineers see that BIM does not reduce time used on drafting compared with current drawing approach  Lack of trust in the integrity of BIM; some organizations see that BIM is poor in matching with the user’s needs and lacking features or flexibility to make a building model/ drawing  Lack of knowledge about how to choose an appropriate level of detail for the BIM model to ensure that money and time are not wasted on compilation of unnecessary information Expert Turkey PhD student in  Reviewed the English language of the H Urban Planning questionnaire and checked the Arabic translation for the questionnaire. Expert Palestine PhD in Housing  Audited the Arabic language of the I (Gaza) questionnaire. Expert Palestine Professor of  Proposed a statistical modification for the J (Gaza) Statistics questions that related to objective #1 which was about assessing the awareness level of BIM by professionals in the AEC industry in Gaza strip.  Corrected the statistical formulation of the hypotheses. Expert Palestine MSc in  Helped to design the questions for the second K (Gaza) Statistics part: “The awareness level of BIM by professionals.‖ Expert Palestine PhD in  Proposed to develop the format of the questions L (Gaza) Architectural of the ―Part 1: The respondent demographic Design and data and the way of work performance.‖ Construction  Modified question #8 ―Current field-present Technology job‖ in ―Part 1: The respondent demographic data and the way of work performance‖ and the options of this question.  Deleted two questions were designed for the field of ―Part 2: The awareness level of BIM professionals in the AEC in Gaza strip.‖

3.7 Pre-testing the questionnaire

Pre-testing the questionnaire was done to make sure that the questionnaire is going to deliver the right data and to ensure the quality of the collected data. In other words, pre- testing the questionnaire was an important and necessary step for finding out if the survey has any logic problems, if the questions are too hard to be understood, if the wording of the questions is ambiguous, or if it has any response bias, etc. (Lavrakas,

2008). The pre-testing was conducted in two phases with twelve professionals of the AEC industry in Gaza strip (each phase has been tested with six professionals).

The first phase of the pre-testing resulted with some amendments to the wording of some words in the questions, and further explanation was added to some items to facilitate the understanding of the question. The questionnaire was modified based on the results of the first phase of the pre-testing. After that, the second phase was conducted with the other six professionals, and it was sufficient to ensure the success of the questionnaire, where there were no any queries from any professional and everything was clear. According to that, questions have become clear to be answered in a way that helps to achieve the target of the study and to start the phase of the pilot study. For further details, review Table (3.3).

Table (3.3): Results of pre-testing the questionnaire Name Specialization Outcome A1 MSc in Urban  Modified an item in the field of BIM barriers (in Planning English language) to facilitate understanding:  Part 5: BA13: it was as ―Lack of real-world cases that have implemented by using BIM and have proved a positive return on investment.‖ It was in need for further explanation because it was ambiguous and not understood, so it became as follow: ―Lack of real cases in Gaza strip or other nearby areas in the region that have been implemented by using BIM and have proved a positive return on investment.‖ B1 MSc in  Modified some items in the field of BIM functions Construction (in English language) to be as the following: Management  Part 3: F11: Future expansion/ extension in facility and infrastructure  Part 3: F14: Issue Reporting and Data

archiving via a 3D model of the building C1 MSc student in  Modified an item in the field of BIM benefits (in Construction English language), where it was in need for more

Pretest 1 Pretest Management explanation as follows:  Part 4: BE 7: “Improve the selection of construction components carefully in line with the quality and costs (such as types of doors and windows, coverage type of the exterior walls, etc.).” D1 BSc in  Modified the formulation of the central question in Architecture part3, part4, and part 5 to facilitate understanding. E1 BSc in Civil  Modified the wording (in Arabic language) of some Engineering items in the different fields of the questionnaire (see Appendix B):  Part 3: F 4, F 7, F 10, F 15 (BIM functions)  Part 4: BE 1 (BIM benefits) F1 PhD in  Modified the wording (in Arabic language) of some Architectural questions and items of the different fields of the Design and questionnaire, where they were in need for more Construction explanation (see Appendix B): Technology  Part 1: Q4, Q8 (Respondent demographic data)

Table (3.3): Results of pre-testing the questionnaire Name Specialization Outcome  Part 2: A 8 (The awareness level of BIM)  Part 4: BE 1, BE 5 (BIM benefits)  Part5: BA 2, BA 3, BA 4, BA 15, BA 1 (BIM barriers) A2 BSc in Civil Everything was clear Engineering B2 BSc in Everything was clear Architecture C2 BSc in Everything was clear

Architecture

2 D2 BSc in Everything was clear Architecture E2 MSc student in Everything was clear Pretest Pretest Construction Management F2 PhD in Everything was clear Architectural Design and Construction Technology

3.8 Pilot study

After the success of the second phase of the pretesting of the questionnaire, a trial run on the questionnaire was done before circulating it to the whole sample to get valuable responses and to detect areas of possible shortcomings (Thomas, 2004). Bell (1996) described the pilot study as: ―getting the bugs out of the instrument (questionnaire) so that subjects in the primary study will experience no difficulties in completing it and so that the researcher can carry out a preliminary analysis to see whether the wording and format of questions will present any difficulties when the main data are analyzed‖ (cited in Naoum, 2007).

To do a pilot study, the researcher needs to test all the survey steps from start to finish with a reasonably large sample. The size of the pilot sample depends on how big the actual sample is. A sample of around 30-50 people is usually enough to identify any significant bugs in the system (Thomas, 2004; Weiers, 2011). According to that, 40 copies of the questionnaire were distributed conveniently to respondents from the target group (the professionals in the AEC industry in Gaza strip). All the copies were collected, coded, and analyzed through Statistical Package for the Social Sciences IBM (SPSS) version 22. The tests that conducted were as follows: 1. The statistical validity of the questionnaire/ criterion-related validity. 2. Reliability of the questionnaire by Half Split method and the Cronbach‘s Coefficient Alpha method. 3.8.1 Statistical validity of the questionnaire

In quantitative research, validity is the extent to which a study using particular tool measures what it sets out to measure. To ensure the validity of the questionnaire, two statistical tests should be applied. The first test is the criterion-related/ internal validity test (Pearson test) which measures the correlation coefficient between each item in the

field and the whole field. The second test is the structure validity test (Pearson test) that used to test the validity of the questionnaire structure by testing the validity of each field and the validity of the whole questionnaire. It measures the correlation coefficient between one field and all the fields of the questionnaire that have the same level of similar scale (Weiers, 2011; Garson, 2013).

Internal validity test

Internal consistency of the questionnaire was measured by the scouting sample (the sample of the pilot study), which consisted of 40 questionnaires. It was done by measuring the correlation coefficients (Pearson test) between each item in one field and the whole field (Weiers, 2011; Garson, 2013). Tables in Appendix C from 1 to 4 show the correlation coefficient P-value for each item in each field. The test applied on the parts (2: Assessing the awareness level of BIM by the professionals in the AEC industry in Gaza strip, 3: Investigating the importance of BIM functions in the AEC industry in Gaza strip, 4: Investigating the value of BIM benefits in the AEC industry in Gaza strip, and 5: Investigating the BIM barriers in the AEC industry in Gaza strip) of the questionnaire. As shown in the Tables C1, C2, C3, and C4, the P-values are less than 0.05, so the correlation coefficients of each field are significant at α = 0.05. Thus, it can be said that the items of each field are consistent and valid to measure what they were set out to measure.

Structure validity test

Structure validity is the second statistical test that used to test the validity of the questionnaire structure by testing the validity of each field and the validity of the whole questionnaire. It measures the correlation coefficient between one field and all of the other fields of the questionnaire that have the same level of the rating scale (five-point Likert scale) (Weiers, 2011; Garson, 2013). As shown in Table (3.4), the significance values (P-values) are less than 0.05, which indicates that the correlation coefficients of all the fields are significant at α = 0.05. Thus, it can be said that the fields are valid to measure what they were set out to measure to achieve the main aim of the study.

Table (3.4): Structure validity of the questionnaire Pearson Fields correlation P-value coefficient The awareness level of BIM by the professionals 0.421 0.01 The importance of BIM functions 0.477 0.00 The value of BIM benefits 0.420 0.01 The strength of BIM barriers 0.380 0.02

3.8.2 Reliability test

Reliability is the degree of consistency or dependability with which an instrument (questionnaire for this study) measures what it is designed to measure. The test is doing by repeating the questionnaire to the same sample of the target group in a different time and comparing the scores that obtained for the first time and for the second time by computing a reliability coefficient. For the most purposes, it considered satisfactory if the reliability coefficient is above 0.7. A period of two weeks to a month is recommended for distributing the questionnaires for the second time (Field, 2009; 49

Weiers, 2011; Garson, 2013). Due to the complicated conditions, it was too difficult to ask the same sample to respond to the same questionnaire twice within a short period. Thus, to overcome the distribution of the questionnaire twice to measure the reliability, Half Split method, and Cronbach‘s alpha coefficient test were used through the SPSS software to achieve that.

Half Split Method

This method depends on finding Pearson correlation coefficient between the Means of the questions with the odd rank and the questions with the even rank of each field of the questionnaire. Then, correcting the Pearson correlation coefficients can be done by using Spearman-Brown correlation coefficient of correction. The corrected correlation coefficient (consistency coefficient) is computed according to the following equation: Consistency coefficient = 2r/(r +1), where r is the Pearson correlation coefficient. The normal range of corrected correlation coefficient 2r/(r +1) is between 0.0 and + 1.0 (Weiers, 2011; Garson, 2013).

As shown in Table (3.5), all the corrected correlation coefficients values are between 0.82 and 0.88 and the general reliability for all items equals 0.86. The significance values are less than 0.05, which indicates that the corrected correlation coefficients are significant at α= 0.05. Thus, it can be said that the studied fields were reliable according to the Half Split method.

Table (3.5): Split-Half Coefficient method Spearman- person- Sig. No. Fields Brown correlation (2-tailed) Coefficient 1 The awareness level of BIM by 0.75 0.86 0.00* the professionals 2 The importance of BIM functions 0.69 0.82 0.00* 3 The value of BIM benefits 0.79 0.88 0.00* 4 The strength of BIM barriers 0.77 0.87 0.00* All items 0.76 0.86 0.00*

Cronbach’s Coefficient Alpha (Cα)

This method is used to measure the reliability of the questionnaire between each field and the Mean of the whole fields of the questionnaire. The normal range of Cronbach‘s coefficient alpha (Cα) value is between 0.0 and +1.0, and the higher value reflects a higher degree of internal consistency (Field, 2009; Weiers, 2011; Garson, 2013). As shown in Table (3.6), the Cronbach‘s coefficient alpha (Cα) was calculated for four fields. The results were in the range from 0.84 and 0.92 and the general reliability for all items equals 0.87. This range is considered high, where it is above 0.7. Thus, the result ensures the reliability of the questionnaire.

Table (3.6): Cronbach’s Coefficient Alpha for reliability (Cα) Cronbach's Alpha No. Fields (Cα) 1 The awareness level of BIM by professionals 0.89 2 The importance of BIM functions 0.84

Table (3.6): Cronbach’s Coefficient Alpha for reliability (Cα) Cronbach's Alpha No. Fields (Cα) 3 The value of BIM benefits 0.92 4 The strength of BIM barriers 0.89 All items 0.87

As shown above, results of the statistical validity of the questionnaire (the internal and the structure of the questionnaire) as well as the results of reliability tests (Half Split method and the Cronbach‘s coefficient Alpha method) showed the success of the tests and thus the success of the questionnaire (valid and reliable). Thereby, the questionnaire was adopted, and the 40 successful copies of the pilot study were included in the whole sample. 3.9 Final amendment to the questionnaire

After piloting, the questionnaire was adopted and distributed to the whole sample. Each field was straightforward and short to improve response rates (Dillman et al., 2000). And as mentioned above, the questionnaire was provided with a covering letter explaining the aim of the research, the security of the information to encourage a high response, and the way of responding. The original questionnaire was developed in the English language. English language questionnaire is attached to (Appendix A). Based on the belief of the researcher that the questionnaire would be more effective and easier to be understood for all respondents if it is in Arabic (native language) and thus get more realistic results, the questionnaire (after final adoption) was translated in the Arabic language, which is attached to (Appendix B).

Regarding the final content of the questionnaire, as mentioned above in (3.2 Research design), the researcher summarized a set of items that related to BIM functions, BIM benefits, and barriers to adopting BIM that were reviewed in the previous chapter (Literature review) in three tables (2.3), (2.5), (2.6), where the researcher has compiled and summarized 45 items of BIM functions, 55 items of BIM benefits, and 36 items of BIM barriers. According to the research objectives, those items were used in the questionnaire design in three parts (part 3, part 4, and part 5). While all items of part 2 were designed by the researcher as well as questions of part 1. As it turns out by explaining each step of the process of the questionnaire design and development and according to the results of each step, some of those items have been selected, other items have been modified, while others have been merged, as well as some items have been added. Table (3.7) shows how items were obtained for each field in the questionnaire. All changes in those items can also be followed through the following three Tables: (3.8), (3.9), and (3.10). Based on that, the final questionnaire contains:

 Part one: is related to the respondent’s demographic data and the way of work performance (consists of 11 questions; Q1 to Q11).  Part two: to assess the awareness level of BIM by the professionals in the AEC industry in Gaza strip (consists of 9 items; A1 to A9).  Part three: to investigate the importance of BIM functions in the AEC industry in Gaza strip (consists of 16 items; F1 to F16).

 Part four: to investigate the value of BIM benefits in the AEC industry in Gaza strip (consists of 26 items; BE 1 to BE 26).  Part five: to investigate the BIM barriers in the AEC industry in Gaza strip (consists of 18 items; BA 1 to BA 18).

Table (3.7): A summary illustrates how items were obtained for each field in the

questionnaire

tems

tems tems

tems

I I

eview

tems

I R

Field

From

Merged and and Merged

Added Added

Deleted Deleted Merged

Selected Selected

Modified Modified

odified odified

Final used used Final

iterature iterature

The The

The The The

The The

The The The The The awareness level of - - 9 - - - - 9 BIM by the professionals The importance of BIM - 45 - 22 1 13 2 16 functions The value of BIM benefits 55 - 1 10 2 18 5 26 The BIM barriers 36 1 2 10 1 11 3 18

Table (3.8): List of the items of BIM functions for the final questionnaire The way that No. BIM function Source was done to get the item Three-dimensional (3D) modeling and visualization Ashcraft (2008); Eastman et al. (2008); Baldwin (2012); F1 Becerik-Gerber et al. (2011); Ku and Taiebat (2011); Gray et Merged al. (2013); Lee et al. (2014) Functional simulations to choose the best solution (such as Ashcraft (2008); Eastman et al. (2008); Baldwin (2012); Lee et Modified and F2 Lighting, energy, and any other sustainability information) al. (2014) Merged Change Management (any modification to the building design CRC construction innovation (2007); Baldwin (2012) F3 will automatically replicate in each view such as floor plans, Modified sections, and elevation) Visualized constructability reviews/ Building simulation (a Ashcraft (2008); Eastman et al. (2008); Ku and Taiebat F4 3D structural model as well as a 3D model of Mechanical, (2011); Gray et al. (2013); Lee et al. (2014) Modified Electrical, and Plumbing (MEP) services) Four-dimensional (4D) visualized scheduling and construction Eastman et al. (2008); Ku and Taiebat (2011); Baldwin (2012); F5 Modified sequencing Gray et al. (2013); Lee et al. (2014) F6 Model-based cost estimation (Five-dimensional (5D)) Eastman et al. (2008); Baldwin ( 2012); Gray et al. (2013) Modified F7 Model-based site planning and site utilization Ku and Taiebat (2011); Baldwin ( 2012); Gray et al. (2013) Modified F8 Safety planning and monitoring on-site Eastman et al. (2008) Modified Model-based quantity take-offs of materials and labor Ashcraft (2008); Eastman et al. (2008); Ku and Taiebat (2011); F9 Modified Lee et al. (2014) Creation of as-built model that contains all the necessary data Ashcraft (2008); Eastman et al. (2008); Lee et al. (2014) F10 to manage and operate the building (facility management) Modified F11 Future expansion/ extension in facility and infrastructure Baldwin ( 2012) Modified Maintenance scheduling via as-built model Becerik-Gerber et al. (2011); Baldwin (2012); Gray et al. F12 Modified (2013) Energy optimization of the building Ashcraft (2008); Eastman et al. (2008); Becerik-Gerber et al. F13 Modified (2011) Issue Reporting and Data archiving via a 3D model of the Eastman et al. (2008); Ku and Taiebat (2011); Baldwin (2012) Merged and F14 building Modified

Table (3.8): List of the items of BIM functions for the final questionnaire The way that No. BIM function Source was done to get the item Managing metadata (provide information about an individual Baldwin ( 2012) F15 Modified item's content) via a 3D model of the building Interoperability and translation of information (among the Baldwin ( 2012); Gray et al. (2013) F16 Modified professionals) within the same system/ program

Table (3.9): List of the items of BIM benefits for the final questionnaire The way that No. BIM benefit Source was done to get the item Improve realization of the idea of a design by the owner via a Eastman et al. (2008, 2011); Stanley and Thurnell (2014) BE 1 Modified 3D model of the building Support design decision-making by comparing different design Azhar et al. (2008a); Azhar et al. (2008b); Eastman et al. (2008, BE 2 alternatives on a 3D model 2011); Allen Consulting Group (2010); Ahmad et al. (2012); Merged Newton and Chileshe (2012); Stanley and Thurnell (2014) Enhance design team collaboration (Architectural, Structural, Eastman et al. (2008, 2011) BE 3 Modified Mechanical, and Electrical Engineers) Improve design quality (reducing errors/ redesign and Holness (2006); Eastman et al. (2008, 2011) BE 4 Modified managing design changes) Azhar et al. (2008a); Azhar et al. (2008b); Eastman et al. (2008, 2011); (Gleeson, 2008) (cited in Azhar Improve sustainable design and lean design and Brown, 2009); Azhar and Brown (2009); Krygiel et al. Merged and BE 5 (2008); Allen Consulting Group (2010); Schade et al. (2011); Modified Khosrowshahi and Arayici (2012); Kolpakov (2012); Park et al. (2012); Stanley and Thurnell (2014) BE 6 Improve safety design Added

Table (3.9): List of the items of BIM benefits for the final questionnaire The way that No. BIM benefit Source was done to get the item Improve the selection of the construction components carefully Holness (2006); Eastman et al. (2008, 2011); Lorimer (2011); Merged and BE 7 in line with the quality and costs (such as types of doors and Barlish and Sullivan (2012); Aibinu and Venkatesh (2013) Modified windows, coverage type of the exterior walls, etc.) Improve understanding the sequence of the construction Eastman et al. (2011); Newton and Chileshe (2012); Aibinu and BE 8 Merged activities Venkatesh (2013); Farnsworth et al. (2014) Enhance work coordination with subcontractors and suppliers Eastman et al. (2008, 2011); Hardin (2009); McGraw-Hill (supply chain) Construction (2009); Succar (2009); Weygant (2011); Ahmad et Merged and BE 9 al. (2012); Khosrowshahi and Arayici (2012); Lorch (2012); Modified Farnsworth et al. (2014); Stanley and Thurnell (2014) Increase the quality of prefabricated (digitally fabricated) Eastman et al. (2008, 2011); Gray et al. (2013) BE 10 Modified components and reduce its costs Improve safety planning and monitoring on-site/ reduce risks Eastman et al. (2008, 2011); Khosrowshahi and Arayici (2012); Merged and BE 11 Zhang et al. (2013); Stanley and Thurnell (2014) Modified BE 12 Increase the accuracy of scheduling and planning Holness (2006); Farnsworth et al. (2014) Modified Increase the accuracy of cost estimation Holness (2006); Nassar (2010); Farnsworth et al. (2014); BE 13 Modified Stanley and Thurnell (2014) BE 14 Improve communication between project parties Lin (2012) ; Lorch (2012); Farnsworth et al. (2014) Modified Reduce change/ variation orders in the construction stage Eastman et al. (2008, 2011); Lorimer (2011); Barlish and BE 15 Modified Sullivan (2012) Reduce clashes among the stakeholders (clash detection) Holness (2006); Newton and Chileshe (2012); Farnsworth et al. BE 16 Modified (2014) Reduce the overall project duration and cost McGraw-Hill Construction (2009); Eastman et al. (2011); BE 17 Modified Barlish and Sullivan (2012); Barlish and Sullivan (2012) Improve the implementation of lean construction techniques to Eastman et al. (2008, 2011); Kjartansdóttir (2011); get sustainable solutions for reducing waste of materials during Khosrowshahi and Arayici (2012); Kolpakov (2012); Cheng Merged and BE 18 construction and demolition and Ma (2013) Modified

Table (3.9): List of the items of BIM benefits for the final questionnaire The way that No. BIM benefit Source was done to get the item Ease of information retrieval for the entire life of the building Azhar et al. (2008a); Azhar et al. (2008b); Eastman et al. (2008, BE 19 through as-built 3D model 2011); Allen Consulting Group (2010); Becerik-Gerber et al. Modified (2010); BIFM (2012) Improve the management and the operation of the building to Schade et al. (2011); Lee et al. (2007); Lee et al. (2009); Choi BE 20 maintain its sustainability by supporting decision-making on (2010); Smart Market Report (2012) (cited in Lee et al., 2014) Modified matters relating to the building Increase coordination between the different operating systems Gray et al. (2013) Modified BE 21 of the building (such as security and alarm system, lighting, air conditioning, etc.) Enhance energy efficiency and sustainability of the building Ku and Taiebat (2011) BE 22 Modified

Improve maintenance planning (preventive and curative)/ Becerik-Gerber et al. (2011); BIFM (2012) BE 23 Modified maintenance strategy of the facility Control the whole-life costs of the asset effectively CRC Construction Innovation (2007); Azhar et al. (2008a); BE 24 Azhar et al. (2008b); Eastman et al. (2011); Ku and Taiebat Modified (2011); BIFM (2012) BE 25 Increase profits by marketing for the facility via a 3D model Becerik-Gerber et al. (2011) Modified Improve emergency management (put plans for avoiding Becerik-Gerber et al. (2011) BE 26 Modified hazards and cope with disasters such as fire, earthquakes, etc.)

Table (3.10): List of the items of BIM barriers for the final questionnaire The way that No. BIM barrier Source was done to get the item Necessary high costs to buy BIM software and costs of the Lee et al. (2007); Lee et al. (2009); Choi (2010); Smart Market necessary hardware updates Report (2012) (cited in Lee et al., 2014); Aibinu and Venkatesh BA 1 Modified (2013)

Table (3.10): List of the items of BIM barriers for the final questionnaire The way that No. BIM barrier Source was done to get the item Lack of the awareness of BIM by stakeholders Kassem et al. (2012); Löf and Kojadinovic (2012); Mitchell and Modified BA 2 Lambert (2013); NBS (2013); Thurairajah and Goucher (2013) Lack of knowledge of how to apply BIM software AGC (2005); Azhar et al. (2008b); Keegan (2010); Lahdou and BA 3 Zetterman (2011); Kassem et al. (2012); Khosrowshahi and Modified Arayici (2012); Löf and Kojadinovic (2012); Crowley (2013) Professionals think that the current CAD system and other Yan and Damian (2008); Kjartansdóttir (2011) BA 4 conventional programs satisfy the need of designing and Modified performing the work and complete the project efficiently Lack of the awareness of the benefits that BIM can bring to Arayici et al. (2009); Kassem et al. (2012); Khosrowshahi and Engineering offices, companies, and projects Arayici (2012); Löf and Kojadinovic (2012); Elmualim and Modified and BA 5 Gilder (2013); Lee et al.(2007); Lee et al. (2009); Choi (2010); Merged Smart Market Report (2012) (cited in Lee et al., 2014); Aibinu and Venkatesh (2014) Lack of effective collaboration among project stakeholders to Arayici et al. (2005); Becerik-Gerber et al. (2011); Ku and exchange necessary information for BIM application, due to the Taiebat (2011); Lahdou and Zetterman (2011); Sebastian (2011); Modified and BA 6 fragmented nature of the AEC industry in Gaza strip Löf and Kojadinovic (2012); Lindblad (2013); Lee et al. (2007); Merged Lee et al. (2009); Choi (2010); Smart Market Report (2012) (cited in Lee et al., 2014); Mandhar and Mandhar (2013) Resistance by companies and institutions for any change can (Davidson (2009); Arayici et al. (2005); Gu et al., (2008); Yan occur in the workflow system and the refusal of adopting a new and Damian (2008); Arayici et al. (2009); Becerik-Gerber et al. BA 7 Modified technology (2011); Gu and London (2010); Khosrowshahi and Arayici (2012) Lack of the financial ability for the small firms to start a new Arayici et al. (2009); Khosrowshahi and Arayici (2012); BA 8 workflow that is necessary for the adoption of BIM effectively Elmualim and Gilder (2013); Thurairajah and Goucher (2013); Modified Aibinu and Venkatesh (2014) Companies prefer focusing on projects (under working/ McGraw-Hill Construction (2009); Löf and Kojadinovic (2012) construction) rather than considering, evaluating, and BA 9 Modified implementing BIM

Table (3.10): List of the items of BIM barriers for the final questionnaire The way that No. BIM barrier Source was done to get the item Difficulty of finding project stakeholders with the required Lahdou and Zetterman (2011) BA 10 Selected competence to participate in applying BIM Lack of the governmental regulations for full support the Becerik-Gerber et al. (n.d.); Arayici et al. (2005); Eastman et implementation of BIM al.(2008); Gu et al. (2008); Howard and Björk (2008); Perlberg (2009); Becerik-Gerber et al. (2011); Kjartansdóttir (2011); Ku and Taiebat (2011); Lahdou and Zetterman (2011); Weygant BA 11 Merged (2011); Khosrowshahi and Arayici (2012); Crowley (2013); Lee et al. (2007); Lee et al. (2009); Choi (2010); Smart Market Report (2012) (cited in Lee et al., 2014) Mitchell and Lambert (2013); Aibinu and Venkatesh (2014) Lack of demand and disinterest from clients regarding with Tse et al. (2005); Gu et al. (2008); Keegan (2010); using BIM technology in design and construction of the project Kjartansdóttir (2011); Khosrowshahi and Arayici (2012); Löf Modified and BA 12 and Kojadinovic (2012); Crowley (2013); Aibinu and Venkatesh Merged (2014) Lack of the real cases in Gaza strip or other nearby areas in the Yan and Damian (2008); Becerik-Gerber et al. (2011) BA 13 region that have been implemented by using BIM and have Modified proved positive return of investment Lack of interest in Gaza strip to pursue the condition of the BA 14 Added building over the life after completion of implementation stage Lack of Architects/ Engineers skilled in the use of BIM Gu et al. (2008); Howard and Björk (2008); Kjartansdóttir programs (2011); Ku and Taiebat (2011); Both and Kindsvater (2012); Khosrowshahi and Arayici (2012); Crowley (2013); Lee et al. BA 15 (2007); Lee et al. (2009); Choi (2010); Smart Market Report Modified (2012) (cited in Lee et al., 2014); Thurairajah and Goucher (2013); Aibinu and Venkatesh (2014)

Lack of the education or training on the use of BIM, whether in BA 16 Added the university or any governmental or private training centers

Table (3.10): List of the items of BIM barriers for the final questionnaire The way that No. BIM barrier Source was done to get the item The unwillingness of Architects/ Engineers to learn new Davidson (2009); Arayici et al. (2005); Gu et al. (2008); Yan applications because of their educational culture and their bias and Damian (2008); Arayici et al. (2009); Becerik-Gerber et al. BA 17 Modified toward the programs they are dealing with (2011); Gu and London (2010); Khosrowshahi and Arayici (2012) Reluctance to train Architects/ Engineers due to the costly Kaner et al., (2008); Yan and Damian (2008); Arayici et al. training requirements in terms of time and money (2009); Becerik-Gerber et al. (2011); Keegan (2010); BA 18 Modified Khosrowshahi and Arayici (2012); Elmualim and Gilder (2013); Aibinu and Venkatesh (2014)

3.10 Quantitative data analysis

A quantitative method was adopted in the current research, where quantitative methods of data analysis can be of great value to the researcher who is attempting to draw meaningful results from a large body of qualitative data. The main beneficial aspect is that quantitative analytical approach provides the Means to separate out the large number of confounding factors that often obscure the main qualitative findings (Field, 2009; Salkind, 2010, Abeyasekera, 2013). Statistical methods play a prominent role in most research that dependent on quantitative analysis of data through converting the ordinal data to numeric data by using the rating scale (the five-point Likert scale) as it mentioned before. This way helps to conclude better results and to link them and comparing with the results of previous research to show the contrast and the extent of progress. Statistical analysis also helps the researcher to identify the degree of accuracy of data and information of the study. It allows reporting of summary results in numerical terms to be given with a specified degree of confidence (Field, 2009; Treiman, 2009; Salkind, 2010).

3.11 Measurements

Analysis of the data was undertaken using IBM SPSS Statistics (Statistical Package for the Social Sciences) Version 22(IBM). The following quantitative measures were used for the data analysis:

A. Descriptive Statistics (Naoum, 2007; Salkind, 2010): 1. Frequencies and Percentile. 2. Measures of central tendency (the Mean) 3. Measurement of dispersion based on the Mean (Standard Deviation) 4. Relative Important Index (RII) 5. Factor analysis 6. Normal distribution 7. Homogeneity of variances (Homoscedasticity)

B. The Inferential Statistics (bivariate)/ test of hypotheses (Naoum, 2007; Salkind, 2010): 1. Cross-tabulation analysis 2. Pearson product-moment correlation coefficient/ Pearson's correlation coefficient )a parametric test) 3. The sample independent t-test to find out whether there is a significant difference in the Mean between two groups )a parametric test( 4. One-way Analysis of Variance (ANOVA) test )a parametric test( 5. Scheffé's method for multiple comparisons The tabulation, bar chart, pie chart, and graph are the tools which have been used to present the results. 3.11.1 Cross-tabulation analysis

In Statistics, a cross tabulation (crosstab) is a type of table in a matrix format that displays the (multivariate) frequency distribution of the variables. They are heavily used in survey research, business intelligence, Engineering and scientific research. They provide a basic picture of the interrelation between two variables and can help find 60

interactions between them. In other words, the cross tabulation is a tool that allows a researcher to compare the relationship between two variables.

3.11.2 Calculating of Relative Importance Index (RII) of Factors

The relative importance index method (RII) was used to determine the ranks of items/ variables as perceived by the respondents in each of part 2, part 3, part 4, and part 5. The relative importance index was computed as (Sambasivan and Soon, 2007; Field, 2009): 푅퐼퐼=Σ푊/ (퐴*푁) Where:

W = the weighting given to each factor by the respondents (ranging from 1 to 5) A = the highest weight (i.e. 5 in this case) N = the total number of respondents

The RII value had a range of 0 to 1 (0 not inclusive), the higher the value of RII, the more impact of the attribute. However, RII doesn't reflect the relationship between the various items.

As such analysis does not provide any meaningful outcomes regarding understanding the clustering effects of the similar items and the predictive capacity, further analysis is required using advanced statistical methods. Factor analysis was used to reduce the items and investigating the clustering effects.

3.11.3 Factor analysis

Factor analysis is a generic term for a family of statistical techniques concerned with the reduction of a set of observable variables regarding a small number of latent factors. It has been developed primarily for analyzing relationships among some measurable entities (such as survey items or test scores). The underlying assumption of factor analysis is that there exist some unobserved latent variables (or ―factors‖) that account for the correlations among observed variables. In other words, the latent factors determine the values of the observed variables (Doloi, 2008; Doloi, 2009; Hardy and Bryman, 2004; Larose, 2006; Liu and Salvendy, 2008; Field, 2009). The main applications of factor analytic techniques are:

(1) To reduce the number of variables; and (2) To detect structure in the relationships between variables, that is to classify variables.

3.11.3.1 Type of factor analysis

 Exploratory factor analysis (EFA), which is used to identify complex interrelationships among items and group items that are part of unified concepts. The researcher makes no ―priori‖ assumptions about relationships among factors.  Confirmatory factor analysis (CFA), which is a more complex approach that tests the hypothesis that the items are associated with specific factors.

3.11.3.2 Methods of factoring

There are several methods for unearthing factors in data (Field, 2009):  Principal component analysis (PCA): is a widely used method for factor extraction, which is the first phase of EFA. Factor weights are computed to extract the maximum possible variance, with successive factoring continuing until there is no further meaningful variance left. The factor model must then be rotated for analysis  Canonical factor analysis (also called Rao's canonical factoring)  Image factoring  Alpha factoring  Factor regression model

Principal Component Analysis (PCA) is the preferred method, and thus, it has been selected for factoring in this research to examine the underlying structure or the structure of interrelationships among the variables.

3.11.3.3 The distribution of data

The assumption of normality is the essential requirement to generalize the results of factor analysis test beyond the sample collected (Field, 2009; Zaiontz, 2014).

3.11.3.4 Validity of sample size

The reliability of factor analysis is dependent on sample size. PCA can be conducted on a sample that has fewer than 100 respondents, but more than 50 respondents. The standard rule is to suggest that sample size contains at least 10–15 respondents per item/ variable. In other words, sample size should be at least ten times the number of items/ variables and some even recommend twenty times (Field, 2009; Zaiontz, 2014).

3.11.3.5 Validity of correlation matrix (correlations between variables)

It is simply a rectangular array of numbers which gives the correlation coefficients between a single item/ variable and every other item/ variable in the investigation. The correlation coefficient between a variable and itself is always 1; hence the principal diagonal of the correlation matrix contains 1s. The correlation coefficients above and below the principal diagonal are the same. PCA requires that there be some correlations greater than 0.30 between the items/ variables included in the analysis (Field, 2009; Zaiontz, 2014).

3.11.3.6 Kaiser-Meyer-Olkin (KMO) and Bartlett's Test as a measure of appropriateness of factor analysis

The value of KMO can be calculated for individual and multiple items/ variables and represents the ratio of squared correlation between items/ variables to the squared partial correlation between items/ variables. It varies from 0 to 1. Interpretive adjectives for the Kaiser Meyer Olkin Measure of Sampling Adequacy are: in the 0.90 as marvelous, in the 0.80's as meritorious, in the 0.70's as middling, in the 0.60's as mediocre, in the 0.50's as miserable, and below 0.50 as unacceptable. A value close to 1 indicates that pattern of correlation is relatively compact, and hence factor analysis should give clear

and reliable results (Kaiser, 1974; Field, 2009; Zaiontz, 2014). Bartlett's test of sphericity tests the hypothesis that the correlation matrix is an identity matrix; i.e. all diagonal elements are 1 and all off-diagonal elements are 0, implying that all of the items/ variables are uncorrelated. If the significant value for this test is less than alpha level; researcher must reject the null hypothesis that the correlation matrix is an identity matrix (Field, 2009; Zaiontz, 2014).

3.11.3.7 Determining the number of factors

Determining the optimal number of factors to extract is not a straightforward task since the decision is ultimately subjective. There are several criteria for the number of factors to be extracted. The ―eigenvalues greater than one‖ rule has been most commonly used due to its simple nature and availability in various computer packages. The eigenvalue (variance) criterion stated that each component explained at least one item's/ variable's worth of the variability, and therefore only components with eigenvalues greater than one should be retained (Larose, 2006; Field, 2009).

After extraction of factors, table of ―communalities (common variances)‖ should be examined to know how much of the variance in each of the original items/ variables is explained by the extracted factors. If the communality for a variable is less than 50%, it is a candidate for exclusion from the analysis because the factor solution contains less than half of the variance in the original item/ variable, and the explanatory power of that variable might be better represented by the individual item/ variable (Field, 2009; Zaiontz, 2014). Components are then rotated via varimax rotation approach to assist in the process of interpretation and to discover the best distribution of the better loading components regarding the meaning of the components. This does not change the underlying solution or the relationships among the items/ variables. Rather, it presents the pattern of loadings in a manner that is easier to interpret factors/ components (Factor loading: the regression coefficient of an item/ a variable for the linear model that describes a latent variable or factor in factor analysis). On another hand, the pattern of factor loadings should be examined to identify variables that have a complex structure (complex structure occurs when one item/ variable has high loadings or correlations (0.50 or greater) on more than one factor/ component). If an item/ a variable has a complex structure, it should be removed from the analysis (Reinard, 2006; Field, 2009; Zaiontz, 2014).

3.11.3.8 Mathematical validity of factor analysis

Once factors have been extracted, it is necessary to cross check if factor analysis measured what was intended to be measured by using Cronbach's alpha test (Cα). An alpha of 0.60 or higher is the minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009; Weiers, 2011; Garson, 2013).

3.11.4 Normal distribution

Normal distribution approximates many natural phenomena so well. It has been developed into a standard of reference for many probability problems (Field, 2009). Parametric statistical tests often assume the data has a normal distribution, because when the data is not normal, it produces unqualified results. Normality was assessed by 63

applying the Central Limit Theorem. The Central Limit Theorem states that when samples are large (above about 30), the sampling distribution will take the shape of a normal distribution regardless of the shape of the population from which the sample was drawn (Field, 2009; Levine et al., 2009). According to that, the collected data of the research follows the normal distribution, where the sample size is N=270, and so parametric tests must be used. Besides The Central Limit Theorem, normality was assessed by conducting Skewness and Kurtosis tests (Hair et al., 2013). The acceptable range for normality is Skewness and Kurtosis lying between -1 to 1 (Hair et al., 2013). As shown in Table (3.11), Skewness and Kurtosis values were located in the acceptable range in the current data set. Due to the large size of the sample (N=270), Skewness and Kurtosis are decreased and data considered normal. This result supports The Central Limit Theorem.

Table (3.11): Skewness and Kurtosis results Std. Error of Std. Error of Fields Skewness Kurtosis Skewness Kurtosis The awareness level of BIM by the 0.77 0.15 0.16 0.30 professionals The importance of BIM functions -0.53 0.15 -0.19 0.30 The value of BIM benefits -0.62 0.15 0.04 0.30 The strength of BIM barriers -0.71 0.15 1.08 0.30 All fields -0.51 0.15 -0.04 0.30 Sample size (N) = 270, Missing= 0

3.11.5 Homogeneity of variances (Homoscedasticity)

Equal variances across samples are called Homogeneity of variance. Some statistical tests, for example, the analysis of variance, assume that variances are equal across groups or samples. The assumption of Homoscedasticity (Homogeneity of variance) simplifies mathematical and computational treatment. Levene's test (Levene 1960) is used to verify the assumption that k samples have equal variances (Field, 2009).

3.11.6 Parametric tests

A parametric test is one that requires data from one of the large catalogue of distributions that statisticians have described and for data to be parametric certain assumptions must be true. The assumptions of parametric tests are as follows: Normally distributed data, Homogeneity of variance, Interval data, and Independence (Field, 2009; Weiers, 2011).

3.11.6.1 Pearson's correlation coefficient

Correlation refers to any of a broad class of statistical relationships involving dependence. The most familiar measure of dependence between two quantities (two sets of data or two variables) is the Pearson product-moment correlation coefficient, or ―Pearson's correlation coefficient,‖ commonly called just ―the correlation coefficient.‖ It shows the linear relationship between two sets of data. Two letters are used to represent the Pearson correlation: Greek letter rho (ρ) for a population and the letter (r) for a sample (Filed, 2009; Treiman, 2009). The Pearson's correlation coefficient measures the strength and the direction of the relationship between two quantitative variables. It is used to measure the strength of a linear association between two

variables, where the value r = 1 means a perfect positive correlation and the value r = -1 means a perfect negative correlation. The sign of (r) denotes the nature of the relationship, while the value of (r) denotes the strength of relationship (Filed, 2009; Treiman, 2009).

Requirements to apply the test  Scale of measurement should be interval or ratio  Variables should be approximately normally distributed  The association should be linear  There should be no outliers in the data

3.11.6.2 Independent Samples t-test

The t-test is a parametric test which helps the researcher to compare whether two groups have different average (Mean) values (for example, whether men and women have different average heights). According to the data gathered, the critical value of t = 1.97, where the degree of freedom (df) = [N-2] = [270-2] = 268 (N is the sample size) at significance (probability) level (α) = 0.05 (Field, 2009; Weiers, 2011).

3.11.6.3 One-way Analysis of Variance (One-way ANOVA)/ (F-test)

One-way Analysis of Variance (abbreviated one-way ANOVA) provides a parametric statistical test of whether or not the Means of several groups are equal (by using the F- ratio), and therefore generalizes the t-test to more than two groups. Critical value of F: at degree of freedom (df) = [(K-1), (N-K)] at significance (probability) level (α) = 0.05 (Field, 2009; Weiers, 2011).

3.11.6.4 Scheffé's method (Multiple-Comparison procedure)

In Statistics, Scheffé's method, named after the American statistician Henry Scheffé, is a method for adjusting significance levels in a linear regression analysis to account for multiple comparisons. It is particularly useful in ANOVA (a special case of regression analysis), and in constructing simultaneous confidence bands for regressions involving basis functions (Field, 2009; Weiers, 2011).

3.12 Summary

This chapter described the detailed adopted methodology of the research. It included the primary design for the research, details of research location, target population, sample size, and response rate. The questionnaire design was detailed including the types of questions, question format, the sequence of questions, and the covering letter. Face validity, pre-testing the questionnaire, and a pilot study were three main steps that were used to reach to the final amendment of the questionnaire. They all have been illustrated through this chapter. Quantitative data analysis techniques, which include the Relative important index, Factor analysis, Pearson correlation analysis, and others, were adopted to be applied by the instruments of SPSS. For testing the research validity, reliability, and adequacy of methods used in analysis, different statistical tests were used and explained in details. The following Table (3.12) summarized the method chart.

Table (3.12): The summary of the methodology Methodology Purpose Outcome Proposal  Identify the problem  Research problem  Define the problem Non-application of Building Information Modeling (BIM) in the Architecture,  Establish aim, objectives, Engineering, and Construction (AEC) industry in Gaza strip in Palestine. hypothesis, and key research questions  Research Aim  Develop research plan/ strategy To develop a clear understanding about BIM for identifying the different factors which (outline methodology) provide useful information to consider adopting BIM technology in projects by the  Deciding on the research practitioners in the AEC industry in Gaza strip in Palestine. approach  Deciding on the research  Research Objectives technique 1. To assess the awareness level of BIM by the professionals in the AEC industry in Gaza strip. 2. To identify top BIM functions that would convince the professionals for adopting BIM in the AEC industry in Gaza strip. 3. To identify top BIM benefits that would convince the professionals for adopting BIM in the AEC industry in Gaza strip. 4. To investigate and rank top BIM barriers that face the BIM adoption in the AEC industry in Gaza strip. 5. To study some hypotheses that might help to find solutions to adopting BIM in the AEC industry in Gaza strip.

 Research plan/ strategy  The research approach was quantitative survey research to measure objectives (descriptive survey and analytical survey).  The research technique was a questionnaire. Literature Review  Collecting existing knowledge on  The following factors have been compiled and summarized from the previous studies: 45 the subject, reading and note-taking factors of BIM functions, 55 factors of BIM benefits, and 36 factors of BIM barriers. from different sources such as  Refereed academic research  They factors were reviewed in Chapter (2) in three Tables (2.3), (2.5), (2.6). Some of journals those items have been modified; other items have been merged; or have been deleted  Refereed Conferences through the process of questionnaire development as well as some items have been added.

Table (3.12): The summary of the methodology Methodology Purpose Outcome  Dissertations/ Theses  Reports/ occasional papers/ white papers  Government publications  Books Questionnaire  Questionnaires have been widely  Types of questions design used for descriptive and analytical Closed-ended (multiple choice) questions and ranking the importance of factors surveys to find out facts, opinions and views on what is happening,  Question format who, where, how many or how Rating scale (five-point Likert scale). The rating scale (five-point Likert scale) was much (Naoum, 2007). chosen to format the questions of the questionnaire with some common sets of response categories called quantifiers (they reflect the intensity of the particular judgment  Identify: involved). Those quantifiers were used to facilitate understanding (see Table 3.1).  types of questions,  question format,  The sequence of questions  the sequence of questions, and The content of the questionnaire verified the objectives in this research as follows:  the covering letter . Part one, which is related to the respondent‘s demographic data and the way of work performance. . Part two: to assess the awareness level of BIM by the professionals in the AEC industry in Gaza strip. . Part three: to investigate the importance of BIM functions in the AEC industry in Gaza strip. . Part four: to investigate the value of BIM benefits in the AEC industry in Gaza strip. . Part five: to investigate the BIM barriers in the AEC industry in Gaza strip.

 The covering letter The questionnaire was provided with a covering letter explaining the aim of the research, the security of the information to encourage a high response, and the way of responding.

Table (3.12): The summary of the methodology Methodology Purpose Outcome Face validity  See whether the measurement  The questionnaire was presented to twelve experts (from Gaza and outside Palestine) procedure (the questionnaire) in the by hand and by email at different periods. study appears to be valid or not. It  Many useful and important modifications have been made for the questionnaire. is a "common-sense" assessment Those modifications have been explained in Table (3.2). by the experts in the fields of the AEC industry and Statistics. Pre-testing the  To make sure that the questionnaire  The pre-testing was conducted in two phases, and each phase has been tested with six questionnaire is going to deliver the right data people. and to ensure the quality of the  The first phase of the pre-testing resulted with some amendments to the wording of collected data. some words in the questions and adding further explanation to some factors to facilitate the understanding of the questionnaire.  To find out if the survey has any  The second phase was sufficient to ensure the success of the questionnaire, where logic problems, if the questions are there were not any queries, and everything was clear. too hard to understand, if the  For further details, review Table (3.3). wording of the questions is ambiguous, or if it has any response bias, etc. Pilot study  A trial run on the questionnaire  40 copies of the questionnaire were distributed to respondents from the target group before circulating it to the whole (The professionals in the AEC industry in Gaza strip). sample to get valuable responses  All the copies were collected and analyzed through Statistical Package for the Social and to detect areas of possible Sciences IBM (SPSS) version 22. shortcomings.  The tests that have conducted were as follows:  Often a sample of 30-50 responses 1. The statistical validity of the questionnaire/ criterion-related validity (the internal is obtained, coded, and analyzed. and the structure validity).  Questions that are not providing 2. The reliability of the questionnaire by Half Split method and the Cronbach‘s useful data are discarded, and the Coefficient Alpha method. final revisions of the questionnaire  The results showed the success of the tests, and thus the success of the questionnaire. are made.  The questionnaire was adopted and was distributed to the whole sample.  The 40 successful copies were included in the whole sample.

Table (3.12): The summary of the methodology Methodology Purpose Outcome Sampling the  Identify the population from which  The type of the sample questionnaire and the sample is to be drawn, where A convenience sample was chosen as the type of the sample, where convenience sampling data collection the term ―sample‖ means a is a non-probability sampling technique. specimen or part of a whole (population) which is drawn to  The population show what the rest is like The population included the professionals (Architects, Civil Engineers, Mechanical Engineers, Electrical Engineers, and any other professional with a related specialization) in the AEC industry in Gaza strip.

 Size sample 275 copies of the questionnaire were distributed, and 270 copies of the questionnaire were received from the respondents. Thus, the whole sample was 270 (the successful sample of the pilot study was included, which equals 40).

 Response rate (270/ 275)*100 = 97.8 % Analysis and  Analyze the results of the collected  Analysis instrument Presentation of data to determine the direction of IBM (SPSS) version 22 the Results the study  Choose the analysis instrument  Method of analysis  Identify the method of the analysis Quantitative analysis of data by converting the ordinal data to scale data.  Present the results  The quantitative measures/ analysis A. Descriptive Statistics: 1. Frequencies and Percentile (results can be presented in the form of tabulation, a bar chart, a pie chart or a graph). 2. Measures of central tendency (The Mean) 3. Measurement of dispersion based on the Mean (Standard Deviation) 4. Relative Important Index (RII) 5. Factor analysis 6. Normal distribution

Table (3.12): The summary of the methodology Methodology Purpose Outcome 7. Homogeneity of variances (Homoscedasticity)

B. The Inferential Statistics (bivariate)/ test of hypotheses: 1. Cross-tabulation analysis 2. Pearson product-moment correlation coefficient/ Pearson's correlation coefficient (a parametric test) 3. Independent samples t-test to find out whether there is a significant difference in the Mean between two groups (a parametric test) 4. One-way Analysis of Variance (One-way ANOVA)/ (F-test) (a parametric test) 5. Scheffé's method for multiple comparisons

The tabulation, bar chart, pie chart, and graph are the tools which have been used to present the results.

Chapter 4

Chapter 4: Results and discussion

This chapter included analysis and discussion of the results that have been collected from field surveys. A total of 270 completed copies had been returned, representing a valid response rate of 97.8%. Data were analyzed quantitatively using IBM (SPSS) version 22 including Descriptive and Inferential statistical tools. This chapter included the respondents‘ profiles and the way of implementing their work, quantitative analysis of the questionnaire, and finally the summary framework of the results.

4.1 Respondents’ profiles

The target respondents of the questionnaire survey were the professionals (Architects, Civil Engineers, Mechanical Engineers, Electrical Engineers, and other Engineers who work in design and construction) in the Architectural, Engineering, and Construction (AEC) industry in Gaza strip. This section analyzed the demographic data of the 270 respondents.

Among the respondents, a large majority had ―less than 5 years‖ of working experience in the AEC industry, with 35.2%. The experience for the rest of the respondents was "from 5 to less than 10 years", and "10 years and more‖ with 32.6% and 32.2%, respectively. With respect to the respondents' specialization, there were 129 Civil Engineers (47.8%), 83 Architects (30.7%), 41 Electrical Engineers (15.2%), 14 Mechanical Engineers (5.2%) and 3 from other specializations (1.1%) including: Electromechanical Engineer, Environmental Engineer, and Geographic Information System (GIS) Engineer.

Respondents for this study had a good understanding of consulting and construction works in the AEC industry, and could thus provide reliable answers to the questionnaire. In terms of the nature of their workplace, a majority of the respondents were working as consultants with 30%, 24.4% were working as contractors, 19.3% of them were working in the governmental sector, 15.6% of them were working in the NGOs, and 10.7% were working in other places such as the Engineers Association. Table (4.1) presents the characteristics of the respondents as follows:

Table (4.1): The respondent’s profile

General information about Categories Frequency Percentage respondents

Male 222 82.2% Gender Female 48 17.8% Educational Bachelor's 195 72.2% qualification Master's 71 26.3% Ph.D. 4 1.5% Study place Gaza strip 196 72.6% Outside Palestine 65 24.1% West Bank 9 3.3%

Table (4.1): The respondent’s profile

General information about Categories Frequency Percentage respondents

Civil 129 47.8% Architect 83 30.7% Electrical 41 15.2% Mechanical 14 5.2% Other Specialization (Electromechanical Engineer, 3 1.1% Environmental Engineer, and GIS Engineer) Consultant 81 30% Contractor 66 24.4% Nature of the Governmental 52 19.3% Workplace NGOs 42 15.6% Other (the Engineers 29 10.7% Association) Gaza 204 75.6% Rafah 23 8.5% Location of North 21 7.8% workplace KhanYounis 14 5.2% Middle 8 3% Designer 73 27% Supervisor 64 23.7% Current field - Site Engineer 54 20% present job Other (office 46 17% Engineer) Projects Manager 33 12.2% Less than 5 years 95 35.2% Years of From 5 to less than 88 32.6% experience 10 years 10 years and more 87 32.2%

4.2 The way of implementing work by respondents

The way of implementing work by the respondents has been assessed through two questions, one of them was about the use of the three-dimensional (3D) programs in implementing the work, and the other question was about the software tools that used in implementing the work in the AEC industry. Results were shown in the Figures (4.1) and (4.2) respectively.

Percentage of implementation the work by using three-dimensional (3D) programs

Figure (4.1) shows that 65.6% of the respondents are using 3D programs in implementing of their works by ―less than 25%‖, while 18.9% of the respondents are using 3D programs ―from 25% to less than 50%‖, 9.3% of the respondents are using 3D programs ―from 50% to less than 70%‖, and 6.3% of the respondents are using 3D programs by ―70% and more‖ in performing their works. As shown from the results, the

use of the 3D programs in implementing works by the professionals in Gaza strip in the AEC industry is little. 3D programs are usually used only by Architects for both the exterior design and the interior design of the building according to the request of the owner.

From 50% to 70% and more less than 70% (6%) (9%)

From 25% to less than 50% (19%) Less than 25% (66%)

Figure (4.1): Percentage of implementation the work by using 3D programs

The used software tool by the respondents to carry out projects

Figure (4.2) illustrates that the more commonly programs used by the respondents to conduct projects in the AEC industry are ―Excel‖ and ―AutoCAD (2D),‖ where 23.9% of the respondents use ―Excel,‖ and 23.8% use ―AutoCAD (2D).‖ ―Excel‖ is the most used program in achieving the Engineering works in Gaza strip, which is often used in the calculation of quantities and financial matters. In addition to the adoption of ―AutoCAD (2D)‖ software in Engineering drawings and design by all the Engineers of various specializations, and this result confirms the result in the previous question as it shows a lack of the use of the (3D) programs.

―MS Project‖ is also an important software tool to carry out projects in the AEC industry. It is used for planning the schedule. It was found that 18.4% of the respondents use ―MS Project.‖ On the other hand, 9.5% of the respondents use other programs such as ―Primavera and Robot.‖ There are also some programs are being used for design but with small percentages, where 6.1% of the respondents use ―AutoCAD (3D),‖ 3.7% of the respondents use ―Revit,‖ 3.3% of the respondents use ―3D Max‖, and finally 2.3% of the respondents are using ―ArchiCAD.‖

ArchiCAD 2.3%

3D Max 3.3%

Revit 3.7%

AutoCAD (3D) 6.1%

Sketch up 9%

Other programs such as Primavera and Robot 9.5%

MS Project 18.4%

AutoCAD (2D) 23.8%

Excel 23.9%

0% 5% 10% 15% 20% 25% 30%

Figure (4.2): The used software tool by respondents to carry out projects

4.3 The awareness level of BIM

There was a field contains nine statements to assess the level of the awareness of BIM by the professionals in the AEC industry in Gaza strip. These statements were subjected to the views of the respondents, and the outcomes of the analysis were shown in Table (4.2). The Descriptive statistics, i.e. Means, Standard Deviations (SD), t-value (two- tailed), probabilities (P-value), Relative Importance Indices (RII), and finally ranks were established and presented in Table (4.2) as follows:

Table (4.2): The awareness level of BIM by the professionals in the AEC industry

tailed)

No. The awareness statement -

value

value value

Rank

(Sig.)

Mean

RII(%)

P (two

I think that BIM technology is important A8 2.60 1.37 52 -4.81 0.00* 1 for the AEC industry in Gaza strip. I think that BIM technology has a A9 positive impact on the sustainable 2.59 1.32 51.70 -5.16 0.00* 2 environment. I know that Revit and ArchiCAD A6 programs are BIM technology 1.86 1.11 37.10 -16.99 0.00* 3 techniques. I have a good idea about the concept of A3 1.85 0.98 36.96 -19.30 0.00* 4 BIM technology. I have a high rate of information A4 regarding the use of BIM technology in 1.75 0.93 34.96 -22.11 0.00* 6 Engineering project management. I have read some research and studies A1 1.75 0.94 35.04 -21.79 0.00* 5 about BIM. I have an idea about how to use BIM A5 1.51 0.88 30.26 -27.74 0.00* 7 technology programs. 75

Table (4.2): The awareness level of BIM by the professionals in the AEC industry

tailed)

No. The awareness statement -

value

value value

Rank

(Sig.)

Mean

RII(%)

P (two Some of my college courses at University A2 1.31 0.70 26.30 -39.80 0.00* 8 talked about BIM. A7 I use BIM technology in my job. 1.23 0.66 24.59 -44.34 0.00* 9 All statements 1.83 0.76 36.57 -25.50 0.00* Critical value of t: at degree of freedom (df) = [N-1] = [270-1] = 269 and significance (Probability) level 0.05 equals “1.97”

A8 60 52 A7 50 51.70 A9 40 30 24.59 20 A2 A6 26.30 10 37.10 0

30.26 36.96 A5 A3 34.96 35.04 A4 A1

Figure (4.3): RII of statements (A1 to A9) used to assess the awareness level of BIM

The numerical scores obtained from the questionnaire responses provided an indication of the awareness level of BIM by the professionals in the AEC industry in Gaza strip. To further investigate the collected data, RII is used to rank the used statements (A1 to A9) to assess the awareness level of BIM by the professionals according to the scores by the respondents. Table (4.2) provides RIIs and ranks of the statements, respectively. It worth mentioning that ranking of the statements was based on the highest Mean, RII, and the lowest SD. If some statements have similar Means and RIIs, as in the case of A1 and A4, the ranking will depend on the lowest SD. For example; although A1 and A4 have the same Mean and RIIs, A4 is ranked higher than the A1 because it has a lower SD. Statements were categorized with ratings from 24.59 % to 52% (Figure 4.3). The findings indicated that “I think that BIM technology is important for the AEC industry in Gaza strip” (A8) with (RII =52 %; P-value = 0.00*) got the highest rank according to the overall respondents. This result is consistent with the result of researchers who found that BIM has recently obtained widespread attention in the AEC industry (Azhar et al., 2008a).

“I think that BIM technology has a positive impact on the sustainable environment” (A9) with (RII = 51.70%; P-value = 0.00*) got the second rank. It supports the first result. Since respondents have a sense of the importance of BIM in the AEC industry, this sense must be reflected on thoughts about BIM benefits for sustainability improvement. The crossover between sustainability and BIM is significant (Kolpakov, 2012).

“Some of my college courses at University talked about BIM” (A2) was ranked as the 8th position with (RII of 26.30%; P-value = 0.00*). Regarding this statement, there were some interesting results which found when cross-tabulations were done between this statement and question #3 about the study place in the profile data. Findings show that the study place affects the degree of the knowledge of BIM. As found, an enormous percentage of the total respondents who studied in Gaza strip (80%) had never taken courses about BIM in their universities. 77% of the total respondents who had studied in the West Bank had the same answer. The lowest ratio was for the respondents who studied outside Palestine with 75% of the total of them whose had never taken courses about BIM in their universities. Based on this result, it can be observed the absence of interest of educating BIM through courses in universities. Thus, the lack of the awareness of BIM is logical and expected result.

Lastly, and “I use BIM technology in my job" (A7) was ranked in the 9th position as the least statement of the field of “the awareness level of BIM by the professionals in the AEC industry in Gaza strip” with (RII = 24.59%; P-value = 0.00*) according to the all respondents. It is a meaningful and realistic result about the current situation in the AEC industry in Gaza strip. According to the respondents, BIM is used individually and with the level of negligible, but not on companies‘ level. In addition to that, BIM does not be applied professionally, and thus the professionals do not get the full benefits of BIM, where they are only using some advantages of BIM software (such as the advantages of Revit program) in the design phase.

The overall results for the field of “the awareness level of BIM by professionals in the AEC industry in Gaza strip” show that the Mean for all statements equals 1.83. The total RII equals 36.57% and for evaluating this result, it was important to calculate the neutral value of RII and compare the total RII with the neutral value of RII. Based on that, the average of the five-point scale that was used for rating the items has an average of (3). Consequently, the neutral value of RII is (3/5)*100 = 60%, where (5) refers to the rating scale that was used and (3) refers to the average of that rating scale as mentioned before. Based on all of that, and as shown, the total RII 36.57% is less than the neutral value of RII 60%. In addition, ―critical value‖ of t (tabulated t), at degree of freedom (df) ―[N (the whole sample) -1] = [270-1] = 269‖ and at ―significance level = 0.05‖, equals 1.97, while the value of t-test equals 25.50. As shown, the value of t-test (25.50) is greater than the critical value of t (1.97). The total P-value of all items also equals 0.00*, which is less than the significance level 0.05. Based on the previous results, the awareness level of BIM by the professionals in the AEC industry in Gaza strip is too low. These results also agree with the results obtained by Keegan (2010) through information from the interviews and the meetings that conducted in the United Kingdom (UK), where he confirmed that general knowledge of BIM and its benefits was little, and only 42% of the respondents were familiar with it. Thurairajah and Goucher (2013) also claimed that there is an overall lack of the

knowledge and the understanding of what BIM is in the UK despite there are some destinations have adopted BIM in their work. Newton and Chileshe (2012) conducted a field study in the South Australian construction industry about the awareness and usage of BIM. The findings indicated that a significant proportion of the respondents have little or no understanding of the concept of BIM and the usage was found to be very low. The same result was shown by Mitchell and Lambert (2013), where they said that people in Australia suffer from a lack of the knowledge about BIM and its distinctive capabilities in the field of the construction industry. In addition to the presence of other studies and reports that support this result, where Gu et al., (2008) and NBS (2012) said that BIM is entirely misunderstood across the board. Only 54% of the Architectural practices are currently aware of BIM (NBS, 2013). In general, many studies, such as Arayici et al. (2009); Kassem et al. (2012); Khosrowshahi and Arayici (2012); Löf and Kojadinovic (2012); Elmualim and Gilder (2013); and Aibinu and Venkatesh (2014), concluded that there are a lack of the awareness of BIM and its benefits in the field of the construction industry as well as the business value of BIM from a financial perspective.

On the contrary, there was an exception in a study conducted in Ireland by Crowley (2013). It was directly relating to the awareness and the use of BIM by the Quantity Surveyors (QS) profession. The outcomes of the questionnaire found that 73% of the sample (105 responses) were only aware of BIM without using it; 24% were aware of BIM and using it in performing their job, while, there was only 3% who not aware of BIM.

4.4 The importance of BIM functions

There was a field contains 16 items of BIM functions, and this list of the 16 items was taken from the literature review and adapted by modifying or merging according to the results of the face validity and the pretesting of the questionnaire as shown in Chapter 3. These items were subjected to the views of the respondents and were analyzed. The Descriptive Statistics, i.e. Means, Standard Deviations (SD), t-value (two-tailed), probabilities (P-value), Relative Importance Indices (RII), and finally ranks were established and presented in Table (4.3).

4.4.1 RII of BIM functions

RII was calculated to weight each function of BIM (from F1 to F16) according to the numerical scores obtained from the questionnaire responses by the professionals in the AEC industry in Gaza strip and the results have been ranked from the highest degree (the most important BIM function) to the least degree (the lowest important BIM function). Table (4.3) provides RIIs and ranks of the items of BIM functions, respectively. The numbers in the ―rank‖ column represent the sequential ranking. It worth mentioning that ranking of BIM functions was based on the highest Mean, RII, and the lowest SD. If some items have similar Means and RIIs, as in the case of (F2 and F1); and (F12 and F13), the ranking will depend on the lowest SD. More precisely, although F2 and F1 have the same Mean and RIIs, F2 is ranked higher than the F1 because it has a lower SD. The same thing was done for F12 and F13, where F12 has taken the higher rank than F13. Items were categorized with ratings from 77.19 % to 68.44 % (Figure 4.4).

Table (4.3): The importance of BIM functions

tailed)

No. BIM function -

value

value value

Rank

(Sig.)

Mean

RII(%)

P (two Interoperability and translation of F16 information (among the professionals) 3.86 1.01 77.19 14.02 0.00* 1 within the same system/ program Change Management (any modification to the building design will automatically F3 3.81 0.90 76.22 14.83 0.00* 2 replicate in each view such as floor plans, sections, and elevation) Functional simulations to choose the best F2 solution (such as Lighting, energy, and any 3.74 0.91 74.89 13.48 0.00* 3 other sustainability information) Three-dimensional (3D) modeling and F1 3.74 0.93 74.89 13.13 0.00* 4 visualization F8 Safety planning and monitoring on-site 3.73 1.03 74.59 11.68 0.00* 5 Visualized constructability reviews/ Building simulation (a 3D structural F4 model as well as a 3D model of 3.67 0.97 73.33 11.32 0.00* 6 Mechanical, Electrical, and Plumbing (MEP) services) Model-based site planning and site F7 3.66 1.04 73.19 10.46 0.00* 7 utilization F11 Future expansion/ extension in facility and 3.62 0.94 72.44 10.93 0.00* 8 infrastructure Managing metadata (provide information F15 about an individual item's content) via a 3.59 0.92 71.85 10.55 0.00* 9 3D model of the building F12 Maintenance scheduling via as-built model 3.57 0.98 71.48 9.63 0.00* 10 F13 Energy optimization of the building 3.57 1.04 71.48 8.97 0.00* 11 Creation of as-built model that contains all F11 the necessary data to manage and operate 3.56 0.88 71.26 10.46 0.00* 12 the building (facility management) Four-dimensional (4D) visualized F5 3.54 1.00 70.81 8.85 0.00* 13 scheduling and construction sequencing Model-based cost estimation (Five- F6 3.53 0.99 70.64 8.82 0.00* 14 dimensional (5D)) Issue Reporting and Data archiving via a F14 3.48 0.97 69.67 8.19 0.00* 15 3D model of the building Model-based quantity take-offs of F9 3.42 0.98 68.44 7.06 0.00* 16 materials and labor All functions 3.63 0.70 72.64 14.92 0.00* Critical value of t: at degree of freedom (df) = [N-1] = [270-1] = 269 and significance (Probability) level 0.05 equals “1.97”

F16 F9 78 77.19 F3 76 76.22 F14 74 F2 68.44 72 74.89 F6 69.67 70 F1 74.89 70.64 68 66 F5 70.81 64 74.59 F8

71.26 73.33 F10 F4 71.48 73.19 71.48 F13 71.85 72.44 F7 F12 F11 F15 Figure (4.4): RII of BIM functions (F1 to F16)

The findings indicated that “Interoperability and translation of information (among the professionals) within the same system/ program” (F16) is the most important function that would convince non-users of BIM for adopting BIM in the AEC industry in Gaza strip. It has been ranked as the first position with (RII =77.19%) and (P-value = 0.00*) according to the overall respondents. This result is in line with the studies of Baldwin (2012) and Gray et al. (2013). It is also consistent with which has been talked about by Bernstein and Pittman (2004), RAIC (2007), Both and Kindsvater (2012) and Wong and Fan (2013). They said that insurance of effective interoperability and information exchange between the different programs is the most important thing and necessary when thinking about the adoption of BIM. It is facilitating accurate information mobility among all the parties as well as the collaborative working in the AEC industry.

“Change Management (any modification to the building design will automatically replicate in each view such as floor plans, sections, and elevation)” (F3) was ranked as the second most important function of BIM with (RII = 76.22%; P-value = 0.00*). It contributes to the improvement of design phase by checking and updating the design. It updates the building design according to any modification, where it will automatically replicate in each view such as floor plans, sections, and elevation. This result is consistent with which has been reported by CRC construction innovation (2007) and Baldwin (2012). They emphasized that the “design change management” through BIM is important for saving time, reducing rework, preserving design intent, and accelerating project delivery. With BIM, the overall impact of change can be assessed. BIM plans and manages change. Consequently, BIM lowers risk associated with change.

“Functional simulations to choose the best solution (such as Lighting, energy, and any other sustainability information)” (F2) was ranked as the third position with (RII of 74.89%; SD = 0.91; P-value = 0.00*). This function of BIM would be critical for the AEC industry in Gaza strip. The simulations of each of lighting, energy, and any other sustainability information would affect the strength and the quality of the design, and

hence the operation of the building positively. The result is agreed with which was written about the sustainable design and its great impact on the overall quality of the work. According to that, Architects, Engineers, and even owners need for additional types of simulations for assessing the appropriate take-offs when considering the use of day lighting and the mitigation of glare and solar heat gain, as compared with the project cost and the overall project requirements. BIM technologies provide stakeholders with the required tools for ensuring doing this effectively (Ashcraft, 2008; Eastman et al., 2008; Baldwin, 2012; Lee et al., 2014). “Three-dimensional (3D) modeling and visualization” (F1) was ranked as the fourth position with (RII of 74.89%; SD = 0.93; P-value = 0.00*). It is indicating the importance of this function. This function is useful for all parties in all phases of the AEC industry. The function of “3D modeling and visualization” is important for both designers and contractors to identify and resolve problems with the help of the model before working on-site. This function of BIM enabled potential problems to be identified early in the design phase and resolved before construction begins. “3D modeling and visualization” is also important for owners of projects for better understanding and making decisions. This function can be used as very useful and successful marketing tool for the building. Choosing this function as an important function for the AEC industry in Gaza strip is an acceptable outcome, where this function can affect the AEC industry positively in Gaza strip according to the above results, and hence encouraging the adoption of BIM. This result is consistent with those reported by Becerik-Gerber et al. (2011), Ku and Taiebat (2011), Gray et al. (2013) and Lee et al. (2014), whose research studies determined this function as the most important function of BIM for the construction companies in Southern California, the U.S., Australia, and Korea, respectively. In addition to that, this outcome corroborates the findings of the studies of Ashcraft (2008), Eastman et al. (2008) and Baldwin (2012).

Finally, ―Model-based quantity take-offs of materials and labor” (F9) was ranked as the lowest function in the 15th position with (RII = 68.44%; P-value = 0.00*) as per perceptions of all the respondents. This result means that the respondents do not know the importance of this function for the AEC industry in Gaza strip. On the contrary of the result of the analysis, for each of Ashcraft (2008); Ku and Taiebat (2011); Lee et al. (2014) have proved in their studies the importance of the function of the quantity take- offs of materials and labor through BIM model. It is significantly reducing the time required in the traditional approach as well as lessen the cost of this process. Fast and simple material quantity take-offs represent an efficient method of checks and balances and often reduce bidding time (Holness, 2006). Aibinu and Venkatesh (2013) investigated how much BIM is essential for Quantity Surveyors (QS) in Australia. Findings from the study showed that “Model-based quantity take-offs of materials and labor” leads to time savings, where it reduces labor intensive quantity take-off and increases the ability to identify and advise the design team on elements exceeding the cost target. It is also growing productivity. BIM improves the efficiency of the quantity take-offs during the budget estimating stage (Eastman et al., 2008). BIM model ensures speed, simplicity, and accuracy of quantity take-offs.

The top four functions of BIM, which were rated by the respondents, are logical and acceptable to be the essential functions of BIM that would convince the professionals to adopt it in the AEC industry in Gaza strip. Regarding results for all items of the part of BIM functions, it is shown that the Mean for all those items equals 3.63, and the total RII equals 72.64%, which is greater than 60% (the neutral value of RII (3/5)*100 = 81

60%). The value of t-test equals 14.92, which is higher than the critical value of t that equals 1.97. As well as the total P-value of all items equals 0.00* and it is less than the significance level of 0.05. Based on all the previous results, BIM functions are significantly necessary for the professionals in the AEC industry in Gaza strip.

4.4.2 Factor analysis results of BIM functions

RII analysis did not provide any meaningful outcomes regarding understanding the clustering effect of the similar items/ variables, and thus further analysis was required using advanced statistical methods such as factor analysis. The use of factor analysis is purely exploratory. Factor analysis was used to examine the pattern of intercorrelations between the 16 items/ variables of the field of BIM functions in an attempt to reduce the number of them. It also used to group items/ variables with similar characteristics together. In other words, it identified subsets of items/ variables that correlate highly with each other, which called factors or components. Factor analysis was conducted for this study using the Principal Component Analysis (PCA).

4.4.2.1 Appropriateness of factor analysis

The data was first assessed for its suitability to the factor analysis application. There were many stages of that assessment:

The distribution of data

The assumption of normality is the essential requirement to generalize the results of factor analysis test beyond the sample collected (Field, 2009; Zaiontz, 2014). As shown in Chapter 3, the received data of the research follows the normal distribution. The result has been satisfied with this requirement.

Validity of sample size

The reliability of factor analysis is dependent on sample size. Factor analysis/ PCA can be conducted on a sample that has fewer than 100 respondents, but more than 50 respondents. The sample size for this study was 270. Further, the standard rule is to suggest that sample size contains at least 10–15 respondents per item/ variable. In other words, sample size should be at least ten times the number of items/ variables and some even recommend 20 times (Field, 2009; Zaiontz, 2014). Fortunately, for this field of BIM functions, the condition was verified. This field contains 16 items/ variables, and the sample size was 270. With 270 respondents and 16 items/ variables (BIM functions), the ratio of respondents to items/ variables are 17: 1, which exceeds the requirement for the ratio of respondents to items/ variables.

Validity of Correlation matrix (Correlations between items/ variables)

Table (4.4) illustrates the correlation matrix for the 16 items/ variables of BIM functions. It is simply a rectangular array of numbers which gives the correlation coefficients between a single item/ variable and every other item/ variable in the investigation (Field, 2009; Zaiontz, 2014). As shown in Table (4.4), the correlation coefficient between an item/ a variable and itself is always 1; hence the principal diagonal of the correlation matrix contains 1s. The correlation coefficients above and

below the principal diagonal are the same. PCA requires that there be some correlations greater than 0.30 between the items/ variables included in the analysis. For this set of items/ variables, that most of the correlations in the matrix are strong and greater than 0.30. Correlations have been satisfied with this requirement.

Kaiser-Meyer-Olkin (KMO) and Bartlett's test

The Kaiser-Meyer-Olkin (KMO) sampling adequacy test and Bartlett's test of Sphericity were carried out. The results of these tests are reported in Table (4.5). The value of the KMO measure of sampling adequacy was 0.92 (close to 1) and was considered acceptable and marvelous because it exceeds the minimum requirement of 0.50 and it is above 0.90 (‗superb‘ according to Kaiser, 1974; Field, 2009; Zaiontz, 2014). Moreover, the Bartlett test of sphericity was another indication of the strength of the relationship among items/ variables. The Bartlett test of sphericity was 2707.30, and the associated significance level was 0.00. The probability value (Sig.) associated with the Bartlett test is less than 0.01, which satisfies the PCA requirement. This result indicated that the correlation matrix was not an identity matrix and all of the items/ variables are correlated (Field, 2009; Zaiontz, 2014). According to the results of these two tests, the sample data of BIM functions were appropriated for factor analysis.

Measures of reliability for the whole items/variables

Cronbach's alpha test was performed on the items/ variables in the field of BIM functions. The value of Cronbach‘s alpha (Cα) could be anywhere in the range of 0 to 1, where a higher value denotes the greater internal consistency and vice versa. An alpha of 0.60 or higher is the minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009; Weiers, 2011; Garson, 2013). As shown in Table (4.5), the value of the calculated Cα for all items/ variables in the field of BIM functions is 0.94 which is considered to be marvelous.

Table: (4.4): Correlations between items/ variables of BIM functions F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 F14 F15 F16

F1 1

F2 0.72** 1

F3 0.62** 0.69** 1

F4 0.52** 0.57** 0.62** 1

F5 0.48** 0.46** 0.47** 0.56** 1

F6 0.43** 0.46** 0.48** 0.51** 0.74** 1

F7 0.49** 0.51** 0.47** 0.46** 0.54** 0.54** 1

F8 0.53** 0.45** 0.56** 0.45** 0.47** 0.48** 0.74** 1

F9 0.38** 0.39** 0.35** 0.42** 0.49** 0.56** 0.37** 0.33** 1

F10 0.48** 0.52** 0.43** 0.44** 0.52** 0.54** 0.56** 0.50** 0.60** 1

F11 0.46** 0.48** 0.51** 0.45** 0.46** 0.41** 0.50** 0.53** 0.39** 0.66** 1

F12 0.46** 0.44** 0.48** 0.43** 0.46** 0.47** 0.54** 0.56** 0.33** 0.56** 0.63** 1

F13 0.50** 0.48** 0.50** 0.38** 0.39** 0.39** 0.54** 0.60** 0.28** 0.48** 0.63** 0.66** 1

F14 0.40** 0.41** 0.39** 0.44** 0.54** 0.55** 0.50** 0.48** 0.42** 0.42** 0.43** 0.56** 0.48** 1

F15 0.40** 0.44** 0.47** 0.44** 0.47** 0.47** 0.53** 0.60** 0.36** 0.48** 0.53** 0.59** 0.58** 0.66** 1

F16 0.48** 0.47** 0.49** 0.44** 0.43** 0.37** 0.51** 0.50** 0.38** 0.47** 0.49** 0.51** 0.48** 0.49** 0.62** 1 **. Correlation is significant at the 0.01 level (1-tailed). *. Correlation is significant at the 0.05 level (1-tailed).

Table: (4.5) KMO and Bartlett's test for items/ variables of BIM functions KMO and Bartlett's test Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.92 Approx. Chi-Square 2707.30 Bartlett's Test of Sphericity df 120 Sig. 0.00 Cronbach's Alpha (Cα) 0.94

Communalities (common variance)

Table: (4.6) Communalities of BIM functions

No. BIM function

Initial Extraction F1 Three-dimensional (3D) modeling and visualization 1 0.73 Functional simulations to choose the best solution (such as Lighting, F2 1 0.78 energy, and any other sustainability information) Change Management (any modification to the building design will F3 automatically replicate in each view such as floor plans, sections, and 1 0.75 elevation) Visualized constructability reviews/ Building simulation (a 3D F4 structural model as well as a 3D model of Mechanical, Electrical, and 1 0.63 Plumbing (MEP) services) Four-dimensional (4D) visualized scheduling and construction F5 1 0.71 sequencing F6 Model-based cost estimation (Five-dimensional (5D)) 1 0.76 F7 Model-based site planning and site utilization 1 0.60 F8 Safety planning and monitoring on-site 1 0.65 F9 Model-based quantity take-offs of materials and labor 1 0.66 Creation of as-built model that contains all the necessary data to manage F10 1 0.59 and operate the building (facility management) F11 Future expansion/ extension in facility and infrastructure 1 0.60 F12 Maintenance scheduling via as-built model 1 0.69 F13 Energy optimization of the building 1 0.71 F14 Issue Reporting and Data archiving via a 3D model of the building 1 0.62 Managing metadata (provide information about an individual item's F15 1 0.69 content) via a 3D model of the building Interoperability and translation of information (among the professionals) F16 1 0.53 within the same system/ program

Total Variance Explained

By using the output from iteration 1, there were three eigenvalues greater than 1 (Figure 4.5). The eigenvalue criterion stated that each component explained at least one item's/ variable's worth of the variability, and therefore only components with eigenvalues greater than one should be retained (Larose, 2006; Field, 2009). The latent root criterion for some factors to be derived would indicate that there were three components (factors) to be extracted for these items/ variables. Results were tabulated in Table (4.7). The three components solution explained a sum of the variance with component 1 85

contributing 52.60%; component 2 contributing 7.41%; and component 3 contributing 6.77%. All the remaining factors are not significant.

Factor 1: Data management and utilization in planning, operation, and maintenance "eigenvalue = 8.42"

Factor 2: Visualized design and The importance of analysis BIM functions "eigenvalue = 1.19"

Factor 3: Construction and operation "eigenvalue = 1.08"

Figure (4.5): The three components (factors) of BIM functions

The three components were then rotated via varimax (orthogonal) rotation approach. This approach does not change the underlying solution or the relationships among the items/ variables. Rather, it presents the pattern of loadings in a manner that is easier to interpret factors (components) (Reinard, 2006; Field, 2009; Zaiontz, 2014). The rotated solution revealed that the three components solution explained a sum of the variance with component 1 contributing 28.21%; component 2 contributing 19.36%; and component 3 contributing 19.20%. These three components (factors) explained 66.77% of total variance for the varimax rotation.

Table (4.7): Total Variance Explained of BIM functions Extraction Sums of Rotation Sums of Initial Eigenvalues

Squared Loadings Squared Loadings

Total Total Total

Component

Cumulative % Cumulative % Cumulative % Cumulative

%of Variance %of Variance %of Variance 1 8.42 52.60 52.60 8.42 52.60 52.60 4.51 28.21 28.21 2 1.19 7.41 60.01 1.19 7.41 60.01 3.10 19.36 47.57 3 1.08 6.77 66.77 1.08 6.77 66.77 3.07 19.20 66.77 4 0.81 5.04 71.82

5 0.69 4.29 76.11

6 0.60 3.72 79.83

Table (4.7): Total Variance Explained of BIM functions Extraction Sums of Rotation Sums of Initial Eigenvalues

Squared Loadings Squared Loadings

Total Total Total

Component

Cumulative % Cumulative % Cumulative % Cumulative

%of Variance %of Variance %of Variance 7 0.51 3.20 83.03

8 0.43 2.70 85.73

9 0.39 2.44 88.16

10 0.36 2.24 90.40

11 0.34 2.12 92.52

12 0.31 1.92 94.44

13 0.28 1.75 96.19

14 0.22 1.39 97.59

15 0.21 1.33 98.91

16 0.17 1.09 100

Scree Plot

The scree plot below in Figure (4.6) is a graph of the eigenvalues against all the factors. This graph can also be used to decide on some factors that can be derived. The point of interest is where the curve starts to flatten. It can be seen that the curve begins to flatten between factors 3 and 4. Note also that factor 4 has an eigenvalue of less than 1, so only three factors have been retained to be extracted.

Figure (4.6): Scree plot for factors of BIM functions

Rotated Component (Factor) Matrix

Table (4.8) shows the factor loadings after rotation of 15 items/ variables (from the original 16 items/ variables) on the three factors extracted and rotated. The pattern of factor loadings should be examined to identify items/ variables that have complex structures (Complex structure occurs when one item/ variable has high loadings or correlations (0.50 or greater) onto more than one factor/ component). If an item/ a variable has a complex structure, it should be removed from the analysis (Reinard, 2006; Field, 2009; Zaiontz, 2014). According to that, it was necessary to remove the item/ variable “Issue Reporting and data archiving via a 3D model of the building” (F14) because it demonstrated a complex structure. It was loading onto two components (component 1 and component 3) at the same time with a factor loading of 0.60 onto component 1 and a factor loading of 0.51 onto component 3. As shown in Table (4.8), the factor loading for each remaining item/ variable is above 0.50 and all items/ variables had simple structures. The items/ variables are listed in order of the size of their factor loadings.

Naming the Factors

Once an interpretable pattern of loadings is made, the factors or components should be named according to their substantive content or core. The factors should have conceptually distinct names and content. Items/ Variables with higher loadings on a factor should play more important role in naming the factor. The three components (factors) were named as the following: Factor 1: ―Data management and utilization in planning, operation, and maintenance.‖ Factor 2: ―Visualized design and analysis.‖ Factor 3: ―Construction and operation.‖

Measures of reliability for each factor (component)

Once factors have been extracted and rotated, it was necessary to cross checking if the items/ variables in each factor formed collectively explain the same measure within target dimensions (Doloi, 2009). If items/ variables indeed form the identified factor (component), it is understood that they should reasonably correlate with one another, but not the perfect correlation though. Cronbach's alpha (Cα) test was conducted for each component (factor) as follows:

Factor 1 ―Data management and utilization in planning, operation, and maintenance‖ with items/ variables: F13, F12, F15, F8, F11, F7, and F16. Factor 2 ―Visualized design and analysis‖ with items/ variables: F2, F3, F1, and F4. Factor 3 ―Construction and operation‖ with items/ variables: F6, F9, F5, and F10.

The higher value of Cα denotes the greater internal consistency and vice versa. An alpha of 0.60 or higher is the minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009; Weiers, 2011; Garson, 2013). According to the results which were tabulated in Table (4.8), Cα for factor 1 is 0.90; Cα for factor 2 is 0.86; and Cα for factor 3 is 0.84. They are considered to be excellent.

Table (4.8): Results of factor analysis for BIM functions

No. Factors/ Components of BIM function

Factor

explained

variance Cronbach's

Alpha (Cα) Alpha

Eigenvalues

Component/ Factor One: Data management and utilization in planning, operation, and maintenance F13 Energy optimization of the building 0.78 F12 Maintenance scheduling via as-built model 0.76 F15 Managing metadata (provide information about an 0.76 individual item's content) via a 3D model of the building F8 Safety planning and monitoring on-site 0.69 8.42 52.60 0.90 F11 Future expansion/ extension in facility and 0.66 infrastructure F7 Model-based site planning and site utilization 0.61 F16 Interoperability and translation of information (among 0.61 the professionals) within the same system/ program Component/ Factor Two: Visualized design and analysis F2 Functional simulations to choose the best solution 0.80 (such as Lighting, energy, and any other sustainability information) F3 Change Management (any modification to the building 0.77 design will automatically replicate in each view such as floor plans, sections, and elevation) 1.19 7.41 0.86 F1 Three-dimensional (3D) modeling and visualization 0.77 F4 Visualized constructability reviews/ Building 0.62 simulation (a 3D structural model as well as a 3D model of Mechanical, Electrical, and Plumbing (MEP) services) Component/ Factor Three: Construction and operation F6 Model-based cost estimation (Five-dimensional (5D)) 0.79 F9 Model-based quantity take-offs of materials and labor 0.78 F5 Four-dimensional (4D) visualized scheduling and 0.74 construction sequencing 1.08 6.74 0.84 F10 Creation of as-built model that contains all the 0.53 necessary data to manage and operate the building (facility management)

4.4.2.2 The extracted factors

The next section will interpret and discuss each of the extracted components (factors) as follows:

Factor 1: Data management and utilization in planning, operation, and maintenance The first factor named Data management and utilization in the planning, operation, and maintenance explains 52.60 % of the total variance and contains seven items/ variables. The majority of items/ variables had relatively high factor loadings (≥ 0.61). The seven items/ variables are as follows:

1. Energy optimization of the building (F13), with a factor loading = 0.78. 2. Maintenance scheduling via as-built model (F12), with a factor loading = 0.76. 3. Managing metadata (provide information about an individual item's content) via a 3D model of the building (F15), with a factor loading = 0.76. 4. Safety planning and monitoring on-site (F8), with a factor loading = 0.69. 5. Future expansion/ extension in facility and infrastructure (F11), with a factor loading = 0.66. 6. Model-based site planning and site utilization (F7), with a factor loading = 0.61. 7. Interoperability and translation of information (among professionals) within the same system/ program (F16), with a factor loading = 0.61.

The name of this factor has been chosen according to the correlations between these seven items/ variables. Data management is the process of controlling the information generated during a project. Throughout the lifecycle of a project or asset (from design, construction, and handover to operations) the number of assets that need to be documented, exchanged, and referenced is enormous. Finding the right solution that can help to improve secure collaboration and control among all stakeholders, while increasing compliance, mitigating risk, and integrating with core processes can be a challenge (Eastman et al., 2011; Baldwin, 2012). And with BIM, data management solutions have proved great ability for maintaining data consistency and context as well as supporting more efficient processes across the project lifecycle (Choi, 2010; Lee et al., 2009; Lee et al., 2007; Smart Market Report, 2012) (cited in Lee et al., 2014). As shown from results, the item/ variable with the highest loading onto this first factor (component) is ―Energy optimization of the building‖ (F13), and the item/ variable with the lowest loading onto this first factor (component) is ―Interoperability and translation of information (among professionals) within the same system/ program‖ (F16).

―Energy optimization of the building‖ (F13) is the highest item/ variable of factor 1 of BIM functions with a factor loading of 0.78. It is an important function of BIM, where the demand for sustainable buildings with minimal environmental impact and efficient energy use is increasing. Energy modeling can minimize energy use over a building‘s life (Kolpakov, 2012). From a cost perspective, designing a building for efficient energy usage is more expensive in the early design and construction phases, but it reduces building costs over the entire lifecycle. BIM model monitors building's life cycle costs and optimizes cost efficiency. BIM model incorporates a large part of what facilities management (FM) would require to operate and maintain the building from the energy usage perspective. Sensors can feedback and record data relevant to the operation phase of a building, enabling BIM to be used to model, evaluate, control, and monitor energy efficiency (Ashcraft, 2008; Eastman et al., 2008; Becerik-Gerber et al., 2011; Ku and Taiebat, 2011). Upon to energy savings, Park et al. (2012) in Korea sought to build a BIM-based system that can assess the energy performance of buildings. It is strongly required to enhance the energy efficiency through an intelligent operation and/ or management of Heating, Ventilation, and Air Conditioning (HVAC) system by dealing with the BIM-based energy performance analysis.

“Interoperability and translation of information (among the professionals) within the same system/ program” (F16) is the lowest item/ variable of factor 1 of BIM functions with a factor loading of 0.61. This function of BIM can facilitate the collaborative working in the AEC industry. This function was mentioned in the literature review as an important function of BIM according to the studies of Baldwin (2012) and Gray et al.

(2013). ―Interoperability and translation of information” is an important thing when adopting BIM in work, where it facilitates accurate information mobility among all parties in the AEC industry.

Factor 2: Visualized design and analysis The second factor named Visualized design and analysis explains 7.41% of the total variance and contains four items/ variables. The majority of items/ variables had relatively high factor loadings (≥ 0.62). The four items/ variables are as follows:

1. Functional simulations to choose the best solution (such as Lighting, energy, and any other sustainability information) (F2), with a factor loading = 0.80. 2. Change Management (any modification to the building design will automatically replicate in each view such as floor plans, sections, and elevation) (F3), with a factor loading = 0.77. 3. Three-dimensional (3D) modeling and visualization (F1), with a factor loading = 0.77. 4. Visualized constructability reviews/ Building simulation (a 3D structural model as well as a 3D model of Mechanical, Electrical, and Plumbing (MEP) services) (F4), with a factor loading = 0.62.

The name of this factor has been chosen according to the correlations between these four items/ variables. In design phase and through BIM, collaboration takes place among all design consultants from the beginning of a project so every aspect of the design can be coordinated whether it is Architectural, Structural, Engineering, etc. Because the model is linked to a database, any change to one design is reflected throughout the model; thus, eliminating oversights and saving time changing design models and drawings. BIM can also be employed on projects of any size and portions of projects. The 3D depiction/ visualization helps the owner and the entire team in visualizing the project which makes design decisions easier. It is easier to do complex design in BIM because Architects/ Engineers can document the complexity better in the drawings. Errors/ clashes in the design among the disciplines can be spotted and resolved easily (Ashcraft, 2008; Eastman et al., 2008; Becerik-Gerber et al., 2011; Ku and Taiebat, 2011; Baldwin, 2012; Gray et al., 2013; Lee et al., 2014). BIM can also be used for improving analysis, where BIM model is used for determining the most effective Engineering method based on design specifications. Development of information is the basis for what will be passed on to the owner and/ or operator for use in the building's systems (i.e. energy analysis, structural analysis, emergency evacuation planning, etc.). These analysis tools and performance simulations can significantly improve the design of the facility and its energy consumption during its lifecycle in the future (Baldwin, 2012; Lee et al., 2014). As shown from results, the item/ variable with the highest loading onto this first factor (component) is ―Functional simulations to choose the best solution (such as Lighting, energy, and any other sustainability information)‖ (F2), and the item/ variable with the lowest loading onto this first factor (component) is ―Visualized constructability reviews/ Building simulation (a 3D structural model as well as a 3D model of Mechanical, Electrical, and Plumbing (MEP) services)‖ (F4).

“Functional simulations to choose the best solution (such as lighting, energy, and any other sustainability information)” (F2) is the highest item/ variable of factor 2 of BIM functions with a factor loading of 0.80. It is an important BIM function, where

extending BIM to analysis can help in identifying ways to reduce resource consumption, increase on-site renewable opportunities, increase investor confidence, improve employee morale, and meet requirements for sustainable design and energy efficiency. As passed in the previous studies, Ashcraft (2008), Eastman et al. (2008), Baldwin (2012), and Lee et al. (2014) pointed to the importance of this function. Simulations of lighting, energy, and any other sustainability information would affect the strength and the quality of the design and hence the operation of the building effectively.

“Visualized constructability reviews/ Building simulation (a 3D structural model as well as a 3D model of Mechanical, Electrical and Plumbing (MEP) services)” (F4) is the lowest item/ variable of factor 2 of BIM functions with a factor loading of 0.62. This function of BIM can assist in completing building at the optimal level through a practical understanding of the design and hence choosing the best method for the construction. In other words, understanding the significance of quality design and completing a project efficiently leads to the use of BIM to manage the coordination of MEP/ Architectural design on renovation and new construction projects. This function of BIM can effectively integrate the construction knowledge into the conceptual planning, design, construction, and field operations of a project to achieve the overall project objectives in the best possible time and accuracy at the most cost-effective levels (Ashcraft, 2008; Eastman et al., 2008; Ku and Taiebat, 2011; Gray et al., 2013; Lee et al., 2014).

Factor 3: Construction and operation The third factor named Construction and operation explains 6.77 % of the total variance and contains four items/ variables. The majority of items/ variables had relatively high factor loadings (≥ 0.53). The four items/ variables are as follows:

1. Model-based cost estimation (Five-dimensional (5D)) (F6), with a factor loading = 0.79. 2. Model-based quantity take-offs of materials and labor (F9), with a factor loading = 0.78. 3. Four-dimensional (4D) visualized scheduling and construction sequencing (F5), with a factor loading = 0.74. 4. Creation of as-built model that contains all the necessary data to manage and operate the building (facility management) (F10), with a factor loading = 0.53. The name of this factor has been chosen according to the correlations between these four items/ variables. Moving beyond design, BIM models can facilitate materials purchasing, the bidding process, and the construction stage of the project. Linking the contractor‘s model to the design model can allow the stakeholders to pre-build the project before the actual construction and provide information for better staging and scheduling. On the other hand; BIM supports the collaboration, the operation of a facility, and the management of a virtually building model within a building life cycle (AGC, 2005; Smith, 2007; GSA, 2007; State of Ohio, 2010; NBIMS-US, 2012; Ahmad et al., 2012). BIM is the future of the construction and the long-term facility management, where BIM controls time and operation and maintenance costs. It optimizes facility management and maintenance strategy (Ashcraft, 2008; Eastman et al., 2008; Becerik-Gerber et al., 2011; Ku and Taiebat, 2011; Baldwin, 2012; Gray et al., 2013; Lee et al., 2014). As shown from results, the item/ variable with the highest loading onto this first factor (component) is ―Model-based cost estimation (5D)‖ (F6),

and the item/ variable with the lowest loading onto this first factor (component) is ―Creation of as-built model that contains all the necessary data to manage and operate the building (facility management)‖ (F10). “Model-based cost estimation (5D)” (F6) is the highest item/ variable of factor 3 of BIM functions with a factor loading of 0.79. It is a very important function of BIM for the professionals in the AEC industry. This function was mentioned in the literature review as an important function of BIM according to the studies of Eastman et al. (2008), Baldwin (2012), and Gray et al. (2013). Nassar (2010) examined the effect that BIM can have on the accuracy of project estimates in terms of time and cost. Results proved that BIM would increase the precision and the accuracy of the quantity aspect of the estimate. Cost estimating, 5D in BIM supports the entire lifecycle of a facility from the cradle to the grave. By using a building information model instead of the drawings; the takeoffs, the counts, and the measurements can be generated directly from the underlying model. Therefore the information is always consistent with the design. And when a change is made in the design (a smaller window size, for example), the change automatically ripples to the all construction related documentations and schedules, as well as all the takeoffs, the counts, and the measurements that are used by the estimator. Cost estimating, 5D via BIM can save time, cost, and reduces the potential for human error.

“Creation of as-built model that contains all the necessary data to manage and operate the building (facility management)” (F10) is the lowest item/ variable of factor 3 of BIM functions with a factor loading of 0.53. This function was mentioned in the literature review as an important function of BIM according to the studies of Ashcraft (2008), Eastman et al. (2008), and Lee et al. (2014). BIM model that created by designers and updated throughout the construction phase, can have the capacity to become an “as built” model, which can also be delivered to the owner or facility manager. It serves as a shared knowledge resource for information about a facility forming a reliable basis for decisions regarding the operation and the maintenance of the building.

4.5 The value of BIM benefits

There was a field contains 26 items of BIM benefits, and this list of the 26 items was taken from the literature review and adapted by modifying or merging according to the results of face validity and pretesting of the questionnaire as shown in Chapter 3. These items were subjected to the views of respondents and were analyzed. The Descriptive Statistics, i.e. Means, Standard Deviations (SD), t-value (two-tailed), probabilities (P- value), Relative Importance Indices (RII), and finally ranks were established and presented in Table (4.9).

4.5.1 RII of BIM benefits

RII was calculated to weight each benefit of BIM (from BE 1 to BE 26) according to the numerical scores obtained from the questionnaire responses by the professionals in the AEC industry in Gaza strip and results have been ranked from the highest degree (the most valuable benefit of BIM) to the least degree (the lowest valuable benefit of BIM). Table (4.9) provides RIIs and ranks of BIM benefits, respectively. The numbers in the ―rank‖ column represent the sequential ranking. It worth mentioning that ranking of BIM benefits was based on the highest Mean, RII, and the lowest SD. If some items 93

have similar Means and RIIs, as in the case of (BE 2 and BE 1); (BE 13 and BE 8); (BE 21 and BE 25); (BE 24 and BE 14); (BE 11 and BE 22); (BE 10 and BE 20); and (BE 9 and BE 17) ranking will depend on the lowest SD. For example, although BE 2 and BE 1 have the same Mean and RIIs, BE 2 is ranked higher than the BE 1 because it has lower SD. The same thing was done for BE 13 and BE 8, where BE 13 has taken the higher rank than BE 8. Items were categorized with ratings from 77.70 % to 68.62% (Figure 4.7).

Table (4.9): The value of BIM benefits

tailed)

No. BIM benefit -

value

Rank

(Sig.)

Mean

RII(%)

P (two Enhance design team collaboration BE 3 (Architectural, Structural, Mechanical, 3.89 0.93 77.70 15.61 0.00* 1 and Electrical Engineers) Improve design quality (reducing errors/ BE 4 3.87 0.93 77.48 15.48 0.00* 2 redesign and managing design changes) Improve sustainable design and lean BE 5 3.73 0.94 74.52 12.64 0.00* 3 design Support design decision-making by BE 2 comparing different design alternatives 3.72 0.83 74.44 14.18 0.00* 4 on a 3D model Improve realization of the idea of a BE 1 design by the owner via a 3D model of 3.72 0.95 74.44 12.46 0.00* 5 the building BE 6 Improve safety design 3.70 0.99 74.07 11.66 0.00* 6 Ease of information retrieval for the BE 19 entire life of the building through as- 3.65 0.98 72.96 10.88 0.00* 7 built 3D model Improve the selection of the construction components carefully in line with the BE 7 quality and costs (such as types of doors 3.63 0.98 72.52 10.48 0.00* 8 and windows, coverage type of the exterior walls, etc.) Improve emergency management (put plans for avoiding hazards and cope BE 26 3.62 1.05 72.37 9.73 0.00* 9 with disasters such as fire, earthquakes, etc.) Increase the accuracy of scheduling and BE 12 3.61 0.92 72.22 10.95 0.00* 10 planning BE 13 Increase the accuracy of cost estimation 3.60 0.88 72.04 11.12 0.00* 11 Improve understanding the sequence of BE 8 3.60 0.90 72.04 10.99 0.00* 12 the construction activities Increase coordination between the different operating systems of the BE 21 3.58 0.92 71.56 10.32 0.00* 13 building (such as security and alarm system, lighting, air conditioning, etc.) Increase profits by marketing for the BE 25 3.58 1.03 71.56 9.21 0.00* 14 facility via a 3D model

Table (4.9): The value of BIM benefits

tailed)

No. BIM benefit -

value

Rank

(Sig.)

Mean

RII(%)

P (two Improve the implementation of lean construction techniques to get BE18 sustainable solutions for reducing waste 3.57 0.95 71.41 9.92 0.00* 15 of materials during construction and demolition BE 24 Control the whole-life costs of the asset 3.56 0.93 71.33 10.02 0.00* 16 effectively BE 14 Improve communication between project 3.56 0.96 71.33 9.73 0.00* 17 parties Improve maintenance planning BE 23 (preventive and curative)/ maintenance 3.55 0.96 70.96 9.40 0.00* 18 strategy of the facility Improve safety planning and monitoring BE 11 3.54 0.91 70.81 9.76 0.00* 19 on-site/ reduce risks Enhance energy efficiency and BE 22 3.54 0.94 70.81 9.40 0.00* 20 sustainability of the building Reduce change/ variation orders in the BE 15 3.53 0.96 70.60 9.02 0.00* 21 construction stage Reduce clashes among the stakeholders BE 16 3.51 1.05 70.19 7.96 0.00* 22 (clash detection) Increase the quality of prefabricated BE 11 (digitally fabricated) components and 3.50 0.86 70 9.54 0.00* 23 reduce its costs Improve the management and the operation of the building to maintain its BE 21 sustainability by supporting decision- 3.50 0.95 70 8.64 0.00* 24 making on matters relating to the building Enhance work coordination with BE 9 subcontractors and suppliers (supply 3.43 0.96 68.62 7.35 0.00* 25 chain) Reduce the overall project duration and BE 17 3.43 1.06 68.62 6.68 0.00* 26 cost All benefits 3.60 0.67 72.10 14.82 0.00* Critical value of t: at degree of freedom (df) = [N-1] = [270-1] = 269 and significance (Probability) level 0.05 equals “1.97”

BE 3 BE 17 78 77.7 BE 4 BE 9 77.48 BE 5 76 74.52 BE 20 BE 2 74 74.44 68.62 BE 10 BE 1 68.62 72 74.44 70 70 BE 16 70 BE 6 68 74.07 70.19 BE 15 66 BE 19 70.6 72.96 64 BE 22 70.81 72.52 BE 7 70.81 72.37 BE 11 70.96 BE 26 72.22 71.33 BE 23 72.04 BE 12 71.33 72.04 71.41 71.56 BE 14 71.56 BE 13 BE 24 BE 8 BE 18 BE 21 BE 25

Figure (4.7): RII of BIM benefits (BE1 to BE 26)

The findings indicated that “Enhance design team collaboration (Architectural, Structural, Mechanical, and Electrical Engineers)” (BE 3) is the most valuable BIM benefit that would convince the professionals for adopting BIM in the AEC industry in Gaza strip. It has been ranked as the first position with (RII = 77.70%) and (P-value = 0.00*) according to the overall respondents. This result is consistent with which has been talked about by Eastman et al. (2008, 2011). They said that BIM is an enabling platform that provides the opportunity to facilitate collaboration and information sharing in design and construction. For example, changes to the Architectural model will generate changes to the Structural model, and vice versa.

“Improve design quality (reducing errors/ redesign and managing design changes)” (BE 4) was ranked as the second most valuable BIM benefit with (RII = 77.48%; P- value = 0.00*). Successful implementation of BIM would result in a better quality design. BIM provides a much more robust design environment, which is fully integrated between all of the design disciplines, saving time and money in both the design and construction phases of the project. BIM eliminates the need to translate or transfer information, thereby, reducing errors, redesign, time and cost while increasing accuracy and quality. In other words, this benefit of BIM ensures verifying consistency to the design intent easily, which prevents costly delays and eliminates conflicts (Holness, 2006; Eastman et al., 2008; Eastman et al., 2011).

“Improve sustainable design and lean design” (BE 5) was ranked as the third position with (RII of 74.52%; P-value = 0.00*). This benefit of BIM would be precious for the AEC industry in Gaza strip. The color of BIM is green, where BIM enables Architects to create an accurate virtual or prototype of a sustainable building project before the actual construction commences. As such, the most effective decisions related to the sustainable design of a building can be made in the early design and preconstruction stages (Azhar et al., 2008a; Azhar et al., 2008b; Krygiel et al., 2008; Azhar and Brown, 2009; Allen Consulting Group, 2010; Schade et al., 2011; and Kolpakov, 2012). The combination of sustainable design strategies and BIM technology has the potential to change the traditional design practices and to produce a high-performance facility design. On the other hand, lean design and BIM theme focuses on developing solutions to support the generation of better value to clients and users of the built environment through improved processes with the use of the supporting BIM technologies. Its core is in extending design thinking into strategies and methods to support innovation and improve the efficiency of the design and construction industry (Eastman et al., 2008, Eastman et al., 2011; Khosrowshahi and Arayici, 2012). This result is consistent with those reported by Azhar and Brown (2009); Khosrowshahi and Arayici (2012); Park et al. (2012); and Stanley and Thurnell (2014), whose research studies determined this benefit as most valuable benefit of BIM for the AEC companies in the United States, the United Kingdom, Korea, and New Zealand, respectively.

“Enhance work coordination with subcontractors and suppliers (supply chain)” (BE 9) was ranked in the 25th position with (RII of 68.62%; SD = 0.96; P-value = 0.00*). It is very low rank. On the contrary of the result of the analysis, studies of Eastman et al. (2008, 2011); Hardin (2009); McGraw-Hill Construction (2009); Succar (2009); Weygant (2011); Ahmad et al. (2012); Khosrowshahi and Arayici (2012); Lorch (2012); Farnsworth et al. (2014); and Stanley and Thurnell (2014) emphasized on the value of adopting BIM to the supply chain in the construction industry. BIM is a collaborative approach that improves communication means between client, design professionals, contractors, suppliers, and subcontractors. Subcontractors can adopt BIM and stop suffering from additional expenses for having to use various models. The adoption of BIM can quickly clarify the complexity of some components. Coordinating the assembly of materials on-site can save cost, increase productivity, improve quality, save time, and minimize risks. In his paper, Irizarry et al. (2013) presented an integrated BIM-GIS system for visualizing the supply chain process and the actual status of materials through the supply chain (manifesting the flow of materials, availability of resources, and ―map‖ of the respective supply chains visually). BIM is interconnected with all the parties, and once a change occurred, it is automatically changed and communicated with the whole group of model users. Consultants, contractors, suppliers, and subcontractors all benefit from sharing project information through BIM model.

Finally, ―Reduce the overall project duration and cost” (BE 17) was ranked as the lowest valuable BIM benefit in the 26th position with (RII of 68.62%; SD = 1.06; P- value = 0.00*) as per perceptions of all the respondents. On the contrary of the result of the analysis, McGraw-Hill Construction (2009); Eastman et al. (2011); Barlish and Sullivan (2012); and Barlish and Sullivan (2012) said that BIM has risen as a very effective tool, which has been proven to lower costs and time considerably. BIM helps for reducing time and cost for data input, where the BIM model stores all the information relating to the building‘s design and all other related information about the project, including scheduling and cost, and allowing the same information to be used in

multiple documents and places, without having to recreate or re-input that information. Further, BIM improves productivity within the Architectural and Engineering team as well as reduces design rework and construction changes; and increases communication among the individual specialists through the BIM model, and thus eliminating conflicts and delays.

The top three benefits of BIM, which were rated by the respondents, are logical and acceptable to be the most valuable benefits of BIM that would convince the professionals for adopting it in the AEC industry in Gaza strip. Regarding results for all items of the part of BIM benefits, they show that the Mean for all those items equals 3.60, and the total RII equals 72.10%, which is greater than 60% (the neutral value of RII (3/5)*100 = 60%). The value of t-test equals 14.82, which is higher than the critical value of t that equals 1.97. As well as the total P-value of all the items equals 0.00 and it is less than the significance level of 0.05. Based on all previous results, BIM benefits are significantly valuable for the professionals in the AEC industry in Gaza strip.

4.5.2 Factor analysis results of BIM benefits

RII analysis did not provide any meaningful outcomes in terms of understanding the clustering effects of the similar items/ variables and thus further analysis was required using advanced statistical methods such as factor analysis. The use of factor analysis is purely exploratory. Factor analysis was used to examine the pattern of intercorrelations between the 26 items/ variables of the field of BIM benefits in attempt to reduce the number of them. It used also to group items/ variables with similar characteristics together. In other words, it identified subsets of items/ variables that correlate highly with each other, which called factors or components. Factor analysis was conducted for this study using the Principal Component Analysis (PCA).

4.5.2.1 Appropriateness of factor analysis

The data was first assessed for its suitability to the factor analysis application. There were many stages of that assessment:

The distribution of data

The assumption of normality is the essential requirement to generalize the results of factor analysis test beyond the sample collected (Field, 2009; Zaiontz, 2014). As shown in Ch3, the received data of the research follows the normal distribution. The result has been satisfied with this requirement.

Validity of sample size

The reliability of factor analysis is dependent on sample size. Factor analysis/ PCA can be conducted on a sample that has fewer than 100 respondents, but more than 50 respondents. The sample size for this study was 270. On the other hand, the standard rule is to suggest that sample size contains at least 10–15 respondents per item/ variable. In other words, sample size should be at least ten times the number of items/ variables and some even recommend 20 times (Field, 2009; Zaiontz, 2014). Fortunately, for this field of BIM benefits, the condition was verified. This field contains 26 items/ variables, and the sample size was 270. With 270 respondents and 26 items/ variables (BIM

benefits), the ratio of respondents to items/ variables are 10: 1, which is suitable for the requirement for the ratio of respondents to items/ variables.

Validity of Correlation matrix (Correlations between items/ variables)

Tables (4.10a) and (4.10b) show the correlation matrix for the 26 items/ variables of BIM benefits. It is simply a rectangular array of numbers which gives the correlation coefficients between a single item/ variable and every other item/ variable in the investigation (Field, 2009; Zaiontz, 2014). As shown in Tables (4.10a) and (4.10b), the correlation coefficient between an item/ a variable and itself is always 1; hence the principal diagonal of the correlation matrix contains 1s. The correlation coefficients above and below the principal diagonal are the same. PCA requires that there be some correlations greater than 0.30 between the items/ variables included in the analysis. For this set of items/ variables, that most of the correlations in the matrix are strong and greater than 0.30. Correlations have been satisfied with this requirement.

Kaiser-Meyer-Olkin (KMO) and Bartlett's test

The Kaiser-Meyer-Olkin (KMO) sampling adequacy test and Bartlett's test of Sphericity were carried out. The results of these tests are reported in Table (4.11). The value of the KMO measure of sampling adequacy was 0.95 (close to 1) and was considered acceptable and marvelous because it exceeds the minimum requirement of 0.50 and it is above 0.90 (‗superb‘ according to Kaiser, 1974; Field, 2009; Zaiontz, 2014). Moreover, the Bartlett test of sphericity was another indication of the strength of the relationship among items/ variables. The Bartlett test of sphericity was 4754.45, and the associated significance level was 0.00. The probability value (Sig.) associated with the Bartlett test is less than 0.01, which satisfies the PCA requirement. This result indicated that the correlation matrix was not an identity matrix and all of the items/ variables are correlated (Field, 2009; Zaiontz, 2014). According to the results of these two tests, the sample data of (BIM benefits) were appropriated for factor analysis.

Measures of reliability for the whole items/ variables

Cronbach's alpha test was performed on the items/ variables in the field of (BIM benefits). The value of Cronbach‘s alpha (Cα) could be anywhere in the range of 0 to 1, where a higher value denotes the greater internal consistency and vice versa. An alpha of 0.60 or higher is the minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009; Weiers, 2011; Garson, 2013). As shown in Table (4.11), the value of the calculated Cα for all items/ variables in the field of (BIM benefits) is 0.96 which is considered to be marvelous.

Table: (4.10a): Correlations between items/ variables of BIM benefits BE 1 BE 2 BE 3 BE 4 BE 5 BE 6 BE 7 BE 8 BE 9 BE 10 BE 11 BE 12 BE 13

BE 1 1

BE 2 0.72** 1

BE 3 0.56** 0.62** 1

BE 4 0.51** 0.60** 0.70** 1

BE 5 0.45** 0.51** 0.61** 0.67** 1

BE 6 0.41** 0.42** 0.54** 0.53** 0.60** 1

BE 7 0.47** 0.48** 0.52** 0.50** 0.53** 0.60** 1

BE 8 0.52** 0.48** 0.52** 0.51** 0.44** 0.49** 0.66** 1

BE 9 0.39** 0.38** 0.46** 0.50** 0.46** 0.57** 0.58** 0.63** 1

BE 10 0.40** 0.43** 0.46** 0.50** 0.51** 0.39** 0.43** 0.51** 0.51** 1

BE 11 0.36** 0.38** 0.53** 0.53** 0.56** 0.59** 0.54** 0.47** 0.55** 0.57** 1

BE 12 0.41** 0.43** 0.52** 0.56** 0.57** 0.40** 0.48** 0.53** 0.50** 0.64** 0.61** 1

BE 13 0.32** 0.36** 0.50** 0.48** 0.50** 0.47** 0.51** 0.46** 0.49** 0.45** 0.49** 0.69** 1 BE 14 0.30** 0.39** 0.45** 0.49** 0.54** 0.48** 0.48** 0.42** 0.49** 0.48** 0.51** 0.58** 0.60** BE 15 0.31** 0.44** 0.46** 0.46** 0.51** 0.40** 0.43** 0.45** 0.43** 0.46** 0.42** 0.55** 0.57** BE 16 0.25** 0.32** 0.33** 0.35** 0.40** 0.47** 0.44** 0.40** 0.44** 0.35** 0.52** 0.47** 0.53** BE 17 0.28** 0.36** 0.34** 0.37** 0.38** 0.41** 0.47** 0.45** 0.53** 0.41** 0.48** 0.46** 0.45** BE 18 0.32** 0.35** 0.41** 0.46** 0.53** 0.43** 0.53** 0.51** 0.48** 0.47** 0.51** 0.59** 0.51** BE 19 0.30** 0.44** 0.44** 0.45** 0.48** 0.36** 0.40** 0.40** 0.36** 0.41** 0.35** 0.44** 0.47** BE 20 0.40** 0.44** 0.47** 0.48** 0.49** 0.46** 0.52** 0.47** 0.48** 0.53** 0.53* 0.55** 0.58** BE 21 0.36** 0.44** 0.47** 0.47** 0.46** 0.44** 0.54** 0.48** 0.51** 0.45** 0.48** 0.53** 0.53** BE 22 0.38** 0.46** 0.41** 0.46** 0.54** 0.50** 0.52** 0.44** 0.53** 0.53** 0.55** 0.57** 0.46** BE 23 0.35** 0.36** 0.41** 0.45** 0.50** 0.42** 0.48** 0.43** 0.44** 0.49** 0.49** 0.55** 0.52** BE 24 0.32** 0.38** 0.42** 0.45** 0.42** 0.37** 0.44** 0.46** 0.46** 0.55** 0.51** 0.60** 0.57** BE 25 0.48** 0.52** 0.42** 0.37** 0.37** 0.42** 0.45** 0.44** 0.32** 0.42** 0.35** 0.40** 0.36** BE 26 0.37** 0.38** 0.41** 0.40** 0.46** 0.51** 0.61** 0.53** 0.51** 0.38** 0.53** 0.47** 0.41** **. Correlation is significant at the 0.01 level (1-tailed). *. Correlation is significant at the 0.05 level (1-tailed).

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Table: (4.10b): Correlations between items/ variables of BIM benefits BE 14 BE 15 BE 16 BE 17 BE 18 BE 19 BE 20 BE 21 BE 22 BE 23 BE 24 BE 25 BE 26

BE 14 1

BE 15 0.64** 1

BE 16 0.56** 0.55** 1

BE 17 0.48** 0.57** 0.65** 1

BE 18 0.50** 0.50** 0.52** 0.65** 1

BE 19 0.51** 0.62** 0.40** 0.43** 0.51** 1

BE 20 0.54** 0.58** 0.51** 0.53** 0.55** 0.64** 1

BE 21 0.51** 0.56** 0.50** 0.53** 0.57** 0.58** 0.70** 1

BE 22 0.50** 0.48** 0.49** 0.54** 0.56** 0.48** 0.65** 0.61** 1

BE 23 0.47** 0.49** 0.49** 0.43** 0.49** 0.49** 0.60** 0.56** 0.65** 1

BE 24 0.56** 0.55** 0.53** 0.50** 0.49** 0.50** 0.63** 0.54** 0.62** 0.63** 1

BE 25 0.36** 0.43** 0.44** 0.43** 0.41** 0.42** 0.47** 0.47** 0.50** 0.39** 0.52** 1

BE 26 0.48** 0.50** 0.56** 0.53** 0.56** 0.47** 0.53** 0.59** 0.54** 0.53** 0.53** 0.54** 1 **. Correlation is significant at the 0.01 level (1-tailed). *. Correlation is significant at the 0.05 level (1-tailed).

Table: (4.11) KMO and Bartlett's test for items of BIM benefits KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling 0.95 Adequacy. Bartlett's Test of Approx. Chi-Square 4754.45 Sphericity df 325 Sig. 0.00 Cronbach's Alpha (Cα) 0.96

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Communalities (common variance)

The next part from the output was a Table of communalities. Communalities represent the proportion of the variance in the original items/ variables that is accounted for by the factor solution. The factor solution should explain at least half of each original item's/ variable's variance, so the communality value for each item/ variable should be 0.50 or higher (Field, 2009; Zaiontz, 2014). Table (4.12) shows that all of the communalities for all items/ variables satisfy the minimum requirement of being larger than 0.50, and therefore was not to exclude any of these items/ variables on the basis of low communalities. Thus, all of the 26 items/ variables of this field (BIM benefits) were used in this analysis.

Table: (4.12) Communalities of BIM benefits

No. BIM Benefit

Initial Extraction BE 1 Improve realization of the idea of a design by the owner via a 3D 1 0.75 model of the building BE 2 Support design decision-making by comparing different design 1 0.79 alternatives on a 3D model BE 3 Enhance design team collaboration (Architectural, Structural, 1 0.72 Mechanical, and Electrical Engineers) BE 4 Improve design quality (reducing errors/ redesign and managing 1 0.72 design changes) BE 5 Improve sustainable design and lean design 1 0.66 BE 6 Improve safety design 1 0.65 BE 7 Improve the selection of the construction components carefully in 1 line with the quality and costs (such as types of doors and windows, 0.69 coverage type of the exterior walls, etc.) BE 8 Improve understanding the sequence of the construction activities 1 0.62 BE 9 Enhance work coordination with subcontractors and suppliers 1 0.66 (supply chain) BE 10 Increase the quality of prefabricated (digitally fabricated) 1 0.54 components and reduce its costs BE 11 Improve safety planning and monitoring on-site/ reduce risks 1 0.67 BE 12 Increase the accuracy of scheduling and planning 1 0.70 BE 13 Increase the accuracy of cost estimation 1 0.63 BE 14 Improve communication between project parties 1 0.62 BE 15 Reduce change/ variation orders in the construction stage 1 0.63 BE 16 Reduce clashes among the stakeholders (clash detection) 1 0.62 BE 17 Reduce the overall project duration and cost 1 0.65 BE 18 Improve the implementation of lean construction techniques to get sustainable solutions for reducing waste of materials during 1 0.59 construction and demolition BE 19 Ease of information retrieval for the entire life of the building 1 0.64 through as-built 3D model BE 20 Improve the management and the operation of the building to maintain its sustainability by supporting decision-making on matters relating to the building 1 0.69

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Table: (4.12) Communalities of BIM benefits

No. BIM Benefit

Initial Extraction BE 21 Increase coordination between the different operating systems of the building (such as security and alarm system, lighting, air 1 0.63 conditioning, etc.) BE 22 Enhance energy efficiency and sustainability of the building 1 0.61 BE 23 Improve maintenance planning (preventive and curative)/ 1 0.56 maintenance strategy of the facility BE 24 Control the whole-life costs of the asset effectively 1 0.65 BE 25 Increase profits by marketing for the facility via a 3D model 1 0.67 BE 26 Improve emergency management (put plans for avoiding hazards 1 0.69 and cope with disasters such as fire, earthquakes, etc.)

Total Variance Explained

By using the output from iteration 1, there were four eigenvalues greater than 1 (Figure 4.8). The eigenvalue criterion stated that each component explained at least one item's/ variable's worth of the variability, and therefore only components with eigenvalues greater than one should be retained (Larose, 2006; Field, 2009). The latent root criterion for some factors to be derived would indicate that there were four components (factors) to be extracted for these items/ variables. Results were tabulated in Table (4.13). The four components solution explained a sum of the variance with component 1 contributing 50.48%; component 2 contributing 6.50 %; component 3 contributing 4.27% and component 4 contributing 4.22%. All the remaining factors are not significant.

Factor 1: Controlled whole-life costs and environmental data "eigenvalue = 13.13"

Factor 2: More effective processes "eigenvalue = 1.69" Value of BIM benefits Factor 3: Design and quality improvement "eigenvalue = 1.11"

Factor 4: Decision-making support/ Better customer service "eigenvalue = 1.10"

Figure (4.8): The four components (factors) of BIM benefits

The four components were then rotated via varimax (orthogonal) rotation approach. This approach does not change the underlying solution or the relationships among the items/variables. Rather, it presents the pattern of loadings in a manner that is easier to

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interpret factors (components) (Reinard, 2006; Field, 2009; Zaiontz, 2014). The rotated solution revealed that the four components solution explained a sum of the variance with component 1 contributing 23.20%; component 2 contributing 15.23 %; component 3 contributing 14.92%; and component 4 contributing 12.12%. These four components (factors) explained 65.47 % of total variance for the varimax rotation.

Table (4.13): Total variance Explained of BIM benefits Extraction Sums of Rotation Sums of Initial Eigenvalues

Squared Loadings Squared Loadings

Total Total Total

Component

Cumulative % Cumulative % Cumulative

%of Variance %of Variance %of Variance 1 13.13 50.48 50.48 13.13 50.48 50.48 6.03 23.19 23.19 2 1.69 6.50 56.98 1.69 6.50 56.98 3.96 15.23 38.42 3 1.11 4.27 61.25 1.11 4.27 61.25 3.88 14.92 53.35 4 1.10 4.22 65.47 1.10 4.22 65.47 3.15 12.12 65.47 5 0.87 3.33 68.80

6 0.75 2.90 71.70

7 0.71 2.75 74.45

8 0.64 2.48 76.93

9 0.55 2.12 79.05

10 0.54 2.06 81.10

11 0.48 1.86 82.96

12 0.46 1.75 84.71

13 0.43 1.65 86.36

14 0.39 1.50 87.87

15 0.36 1.39 89.25

16 0.34 1.31 90.56

17 0.33 1.25 91.81

18 0.29 1.13 92.94

19 0.29 1.10 94.05

20 0.27 1.05 95.09

21 0.25 0.96 96.06

22 0.23 0.88 96.94

23 0.22 0.86 97.80

24 0.20 0.78 98.58

25 0.19 0.75 99.33

26 0.17 0.67 100

Scree Plot

The scree plot below in Figure (4.9) is a graph of the eigenvalues against all the factors. This graph can also be used to decide on some factors that can be derived. The point of

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interest is where the curve starts to flatten. It can be seen that the curve begins to flatten between factors 4 and 5. Note also that factor 5 has an eigenvalue of less than 1, so only four factors have been retained to be extracted.

Figure (4.9): Scree plot for factors of BIM benefits

Rotated Component (Factor) Matrix

Table (4.14) shows the factor loadings after rotation of 19 items/ variables (from the original 26 items/ variables) on the four factors extracted and rotated. The pattern of factor loadings should be examined to identify items/ variables that have complex structures (Complex structure occurs when one item/ variable has high loadings or correlations (0.50 or greater) on more than one factor/ component). If an item/ a variable has a complex structure, it should be removed from the analysis (Reinard, 2006; Field, 2009; Zaiontz, 2014). According to that, it was necessary to remove seven items/ variables because they demonstrated complex structures. Each item/ variable of the removed items/ variables was loaded onto two components at the same time with factor loadings exceed of 0.5. Items/ Variables that have been removed are BE 16, BE 17, BE 26, BE 11, BE 3, BE 13, and BE 25. As shown in Table (4.14), the factor loading for each remaining item/ variable is above 0.5 and all items/ variables had simple structures. The items/ variables are listed in order of the size of their factor loadings.

Naming the Factors

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factor should play more important role in naming the factor. The four components (factors) were named as the following:

Factor 1: ―Controlled whole-life costs and environmental data.‖ Factor 2: ―More effective processes.‖ Factor 3: ―Design and quality improvement.‖ Factor 4: ―Decision making support/ Better customer service.‖

Measures of reliability for each factor

Once factors have been extracted and rotated, it was necessary to cross checking if the items/variables in each factor formed collectively explain the same measure within target dimensions (Doloi, 2009). If items/ variables truly form the identified factor (component), it is understood that they should reasonably correlate with one another, but not the perfect correlation though. Cronbach's alpha (Cα) test was conducted for each component (factor) as follows:

Factor 1 “Controlled whole-life costs and environmental data” with items/ variables: BE 20, BE 24, BE 19, BE15, BE 21, BE 23, BE 22, BE 14, and BE 18. Factor 2 “More effective processes” with items/ variables: BE 9, BE 7, BE 6, and BE 8. Factor 3 “Design and quality improvement” with items/ variables: BE 4, BE 5, BE 12, and BE 10. Factor 4 ―Decision-making support/ Better customer service‖ with items/ variables: BE 2, and BE 1.

The higher value of Cα denotes the greater internal consistency and vice versa. An alpha of 0.60 or higher is the minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009; Weiers, 2011; Garson, 2013). According to the results which were tabulated in Table (4.14), Cα for factor 1 is 0.92; Cα for factor 2 is 0.85; Cα for factor 3 is 0.84; and Cα for factor 4 is 0.83. They are considered to be excellent.

Table (4.14): Results of factor analysis for BIM benefits

No. BIM benefit factors (Components)

Factor

explained

variance

Alpha (Cα) Alpha

Cronbach's Cronbach's

Eigenvalues

Component/ Factor One: Controlled whole-life costs and environmental data BE 20 Improve the management and the operation of 0.70 the building to maintain its sustainability by supporting decision-making on matters relating to the building BE 24 Control the whole-life costs of the asset 0.70

effectively 13.13 50.48 0.92 BE 19 Ease of information retrieval for the entire life of 0.70

the building through as-built 3D model BE 15 Reduce change/ variation orders in the 0.69 construction stage

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Table (4.14): Results of factor analysis for BIM benefits

No. BIM benefit factors (Components)

Factor

explained

variance

Alpha (Cα) Alpha

Cronbach's Cronbach's

Eigenvalues

BE 21 Increase coordination between the different 0.65 operating systems of the building (such as security and alarm system, lighting, air conditioning, etc.) BE 23 Improve maintenance planning (preventive and 0.60 curative)/ maintenance strategy of the facility BE22 Enhance energy efficiency and sustainability of 0.59 the building BE14 Improve communication between project parties 0.55 BE18 Improve the implementation of lean construction 0.55 techniques to get sustainable solutions for reducing waste of materials during construction and demolition Component/ Factor Two: More effective processes BE 9 Enhance work coordination with subcontractors 0.66 and suppliers (supply chain) BE 7 Improve the selection of the construction 0.66 components carefully in line with the quality and costs (such as types of doors and windows, 1.69 6.50 0.85 coverage type of the exterior walls, etc.) BE 6 Improve safety design 0.63 BE 8 Improve understanding the sequence of the 0.57 construction activities Component/ Factor Three: Design and quality improvement BE 4 Improve design quality (reducing errors/ redesign 0.64 and managing design changes)

BE 5 Improve sustainable design and lean design 0.64 1.11 4.27 0.84 BE 12 Increase the accuracy of scheduling and planning 0.62

BE 10 Increase the quality of prefabricated (digitally 0.54 fabricated) components and reduce its costs Component/ Factor Four: Decision-making support/ Better customer service BE 2 Support design decision-making by comparing 0.80 different design alternatives on a 3D model 1.10 4.22 0.83 BE 1 Improve realization of the idea of a design by the 0.80 owner via a 3D model of the building

4.5.2.2 The extracted factors

The next section will interpret and discuss each of the extracted components (factors) as follows:

Factor 1: Controlled whole-life costs and environmental data The first factor named Controlled whole-life costs and environmental data explains 50.48% of the total variance and contains nine items/ variables. The majority of items/ variables had relatively high factor loadings (≥ 0.55). The nine items/ variables are as follows:

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1. Improve the management and the operation of the building to maintain its sustainability by supporting decision-making on matters relating to the building (BE 20), with a factor loading = 0.70. 2. Control the whole-life costs of the asset effectively (BE 24), with a factor loading = 0.70. 3. Ease of information retrieval for the entire life of the building through as-built 3D model (BE 19), with a factor loading = 0.70. 4. Reduce change/ variation orders in the construction stage (BE 15), with a factor loading = 0.69. 5. Increase coordination between the different operating systems of the building (such as security and alarm system, lighting, air conditioning, etc.) (BE 21), with a factor loading = 0.65. 6. Improve maintenance planning (preventive and curative)/ maintenance strategy of the facility (BE 23), with a factor loading = 0.60. 7. Enhance energy efficiency and sustainability of the building (BE 22), with a factor loading = 0.59. 8. Improve communication between project parties (BE 14), with a factor loading = 0.55. 9. Improve the implementation of lean construction techniques to get sustainable solutions for reducing waste of materials during construction and demolition (BE18), with a factor loading = 0.55.

The name of this factor has been chosen according to the correlations between these nine items/ variables. Whole-life cost refers to the total cost of the ownership over the life of an asset (cradle to grave costs). The costs include the financial cost which is relatively simple to be calculated and also the environmental and social costs which are harder to be quantified and assigned in numerical values. Typical areas of expenditure in a building project are included in computing the whole-life costs of planning, design, construction, operations, maintenance, rehabilitation, and the cost of finance and replacement or disposal. Lifecycle data of a project (requirements, design, construction and operational information) can be used in facilities management through the BIM model. The BIM model can be used to understand and predict the environmental performance of a building and its lifecycle costs during the management period of the facility. BIM data can be exploited during facilities management, ensuring that procurement decisions depend on the whole-life costs and cultural fit, and not solely on short-term financial criteria (CRC Construction Innovation, 2007; Azhar et al., 2008a; Azhar et al., 2008b; Eastman et al., 2011; Ku and Taiebat, 2011; BIFM, 2012). As shown from results, the item/ variable with the highest loading of this first factor (component) is ―Improve the management and the operation of the building to maintain its sustainability by supporting decision-making on matters relating to the building‖ (BE 20) and the item/ variable with the lowest loading of this first factor (component) is ―Improve the implementation of lean construction techniques to get sustainable solutions for reducing waste of materials during construction and demolition‖ (BE 18).

―Improve the management and the operation of the building to maintain its sustainability by supporting decision-making on matters relating to the building,‖ (BE 20) is the highest item/ variable of factor 1 of BIM benefits with a factor loading of 0.70. Decisions early in the design process have a significant impact on the life cycle performance of a building and with the rising cost of energy and growing environmental concerns; the demand for sustainable buildings with minimal environmental impact is

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increasing (Schade et al., 2011; Azhar and Brown, 2009). On the other hand, there is a tremendous advantage in the integration of green (sustainability) and BIM processes (Kolpakov, 2012). The BIM model can be used as a decision-making framework in the early design phase. It supports decision-makers to take informed decisions regarding the life cycle performance of a building (Schade et al., 2011). This saves time and cost of the management and operation of the building in a green way (Lee et al., 2007; Lee et al., 2009; Choi, 2010; Smart Market Report, 2012) (cited in Lee et al., 2014).

“Improve the implementation of lean construction techniques to get sustainable solutions for reducing waste of materials during construction and demolition” (BE 18) is the lowest item/ variable of factor 1 of BIM benefits with a factor loading of 0.55. This BIM benefit was mentioned in the literature review as a valuable benefit of BIM according to the studies of Kjartansdóttir (2011); Khosrowshahi and Arayici (2012); Kolpakov (2012); and Cheng and Ma (2013). Lean construction techniques are incorporated throughout the BIM workflow. In other words, BIM applications enable the full effect of lean principles. Value maximization and waste reduction (benefits of BIM) are in line with the benefits which lean construction promises. When BIM and lean construction principles are used together, the construction process becomes even more enhanced. The project team becomes more able to tackle complex dynamic and challenging target goals to deliver a project (Eastman et al., 2008; Eastman et al., 2011; Kjartansdóttir, 2011).

Factor 2: More effective processes The second factor named More effective processes explains 6.50% of the total variance and contains four items/ variables. The majority of items/ variables had relatively high factor loadings (≥ 0.57). The four items/ variables are as follows: 1. Enhance work coordination with subcontractors and suppliers (supply chain) (BE 9), with a factor loading = 0.66. 2. Improve the selection of the construction components carefully in line with the quality and costs (such as types of doors and windows, coverage type of the exterior walls, etc.) (BE7), with a factor loading = 0.66. 3. Improve safety design (BE 6), with a factor loading = 0.63. 4. Improve understanding the sequence of the construction activities (BE 8), with a factor loading = 0.57.

The name of this factor has been chosen according to the correlations between these four items/ variables. Throughout the asset life-cycle, BIM helps people save time and money. It enables more effective integrated through-life information management, as well as stronger business continuity. BIM is a coordinated set of processes, supported by technology, which adds value by creating, managing and sharing the properties of an asset throughout its life cycle. BIM models incorporate graphic, physical, commercial, environmental and operational data (Sebastian and Berlo, 2010; Aibinu and Venkatesh, 2013). BIM models allow for a previously incredible array of collaborative activities; integrated inter-disciplinary design review, multi-model coordination and clash detection, real-time integration with other specialist disciplines for cost estimation, and construction management. BIM ensures more controlled conditions for weather, quality, improved supervision of labor and fewer material deliveries. BIM can also increase worker safety through reduced exposure to inclement weather and better of working conditions (Karlshøj, 2012). As shown from results, the item/ variable with the highest loading of this first factor (component) is ―Enhance work coordination with

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subcontractors and suppliers (supply chain)‖ (BE 9) and the item/ variable with the lowest loading of this first factor (component) is ―Improve understanding the sequence of the construction activities‖ (BE 8).

“Enhance work coordination with subcontractors and suppliers (supply chain)” (BE 9) is the highest item/ variable of factor 2 of BIM benefits with a factor loading of 0.66. It is a valuable BIM benefit, where BIM is a collaborative approach that improves communication means among the client, design professionals, contractors, suppliers, and subcontractors. Consultants, contractors, suppliers, and subcontractors all benefit from sharing project information through BIM model. Subcontractors can adopt BIM and stop suffering from the additional expenses for having to use various models. BIM promises significant costs savings for subcontractors and suppliers (Eastman et al., 2008; Eastman et al., 2011; Hardin, 2009; McGraw-Hill Construction, 2009; Succar, 2009; Weygant, 2011; Ahmad et al., 2012; Khosrowshahi and Arayici, 2012; Lorch, 2012; Farnsworth et al., 2014; Stanley and Thurnell, 2014).

“Improve understanding the sequence of the construction activities” (BE 8) is the lowest item/ variable of factor 2 of BIM benefits with a factor loading of 0.57. BIM assists in completing building at the optimal level through a practical understanding of the sequence of the construction activities. 4D BIM modeling provides a powerful visualization and communication tool that gives project teams a better understanding of project milestones and construction plans. 4D simulation can help teams in identifying problems well in advance of construction activities when they are much easier and less costly to resolve. BIM models can be linked with construction activity schedules to explore space and sequencing requirements. Additional information describing equipment locations and materials staging areas can be integrated into the project model to facilitate and support site management decisions, enabling project teams to effectively generate and evaluate layouts for temporary facilities, assembly areas, and material deliveries for all the phases of construction (Eastman et al., 2011; Newton and Chileshe, 2012; Aibinu and Venkatesh, 2013; Farnsworth et al., 2014).

Factor 3: Design and quality improvement The third factor named Design and quality improvement explains 4.27% of the total variance and contains four items/ variables. The majority of items/ variables had relatively high factor loadings (≥ 0.54). The four items/ variables are as follows: 1. Improve design quality (reducing errors/ redesign and managing design changes) (BE 4), with a factor loading = 0.64. 2. Improve sustainable design and lean design (BE 5), with a factor loading = 0.64. 3. Increase the accuracy of scheduling and planning (BE 12), with a factor loading = 0.62. 4. Increase the quality of prefabricated (digitally fabricated) components and reduce its costs (BE 10), with a factor loading = 0.54.

The name of this factor has been chosen according to the correlations between these four items/ variables. Early evaluation of design alternatives using analysis/ simulation tools increases the overall quality of the building. The use of BIM to support digital prototyping has spurred a design revolution allowing for innovations in the Architectural industry. By applying BIM models to buildings, project teams can understand a project digitally before being built. BIM delivers high-quality designs. Making changes or adjustments to a virtual model can be accomplished more quickly,

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more easily and exponentially more cost effectively than waiting until a fully mobilized workforce is involved. BIM allows models to be tested for clashes and conflicts throughout the development of the design. By integrating fabrication level model information, the shop drawing process can be streamlined or eliminated. BIM digital model resolves coordination issues and increases the use of pre-fabricated components, and thus improves quality as well as reduces material and labor waste (Eastman et al., 2008; Eastman et al. 2011; Lorimer, 2011; Elmualim and Gilder, 2013). As shown from results, the item/ variable with the highest loading of this first factor (component) is ―Improve design quality (reducing errors/ redesign and managing design changes)‖ (BE 4), and the item/ variable with the lowest loading of this first factor (component) is ―Increase the quality of prefabricated (digitally fabricated) components and reduce its costs‖ (BE 10). “Improve design quality (reducing errors/ redesign and managing design changes)” (BE 4) is the highest item/ variable of factor 3 of BIM benefits with a factor loading of 0.64. Successful implementation of BIM would result in a better quality design. Architects benefit from BIM‘s capability of creating 3D renderings, graphically accurate models, and sets of construction documents. The use of BIM prevents costly delays due to inaccurate drawings. BIM is also beneficial to the design and installation of MEP services on any construction project systems as well as their coordination with other building systems. The adoption of BIM can also help Civil Engineers in analyzing and comparing several design alternatives quickly. BIM model is linked to a database, and any change to one design is reflected throughout the model; thus, eliminating oversights and changing design models and drawings. BIM facilitates doing complex design and can resolve errors/ clashes in the design among the disciplines easily. BIM ensures verifying consistency to the design intent easily, which prevents costly delays and eliminates conflicts (Holness, 2006; Eastman et al., 2008; Eastman et al., 2011).

“Increase the quality of prefabricated (digitally fabricated) components and reduce its costs” (BE 10) is the lowest item/ variable of factor 3 of BIM benefits with a factor loading of 0.54. Prefabrication is the practice of assembling components of a structure in a factory or other manufacturing site, and transporting complete assemblies or sub- assemblies to the construction site where the structure is to be located. BIM allows for fabrication to occur efficiently offsite of many types of building components. These building components include steel framing, curtain walls, facades, and building envelope designs as well as mechanical and piping assemblies. These precisions of building components reduce waste and condense construction time as well as save costs. The reduction in labor schedules due to the offsite prefabrication diminishes onsite interferences, as well as decreases, lead times; facilitating faster erection and placement of building components on a project. Furthermore, prefabricated (digitally fabricated) components allow for an improved quality via information extracted directly from the BIM project model, reducing errors caused by miscommunication or misinterpretation of the design. The quality of fabricated components generated in controlled settings is superior to those generated onsite. Moreover, the use of digitally fabricated components allows for enhanced coordination amongst Architects, fabricators, and contractors allowing for the theory of the BIM model to be achieved successfully (Eastman et al., 2008; Eastman et al. 2011; Gray et al., 2013).

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Factor 4: Decision-making support/ Better customer service The fourth factor named Decision-making support/ Better customer service explains 4.22% of the total variance and contains two items. The two items/ variables have the same factor loading, which is 0.80. It is a high value. The two items/ variables are as follows: 1. Support design decision-making by comparing different design alternatives on a 3D model (BE 2), with a factor loading = 0.80. 2. Improve realization of the idea of a design by the owner via a 3D model of the building (BE 1), with a factor loading = 0.80.

The name of the factor has been chosen according to the correlations between these two items/ variables on this factor. BIM is used to generate and manage information about a building or piece of infrastructure over its entire lifespan. At every stage of the project lifecycle, from design through to decommissioning, BIM provides information that help owners of the construction projects in making informed choices. It makes the design, construction, operation, and decommissioning process more efficient. Stebbins (2009) agreed that BIM is a process rather than a piece of software. He clearly identified BIM as a business and management decision. BIM implementation is strongly related to managerial aspects of professional practices for different working styles and cultures (cited in Ahmad et al., 2012). More precisely, BIM is a mechanism to share knowledge among design professionals for the purpose of improving decision-making through better project understanding (Schade et al., 2011). The building information models become shared knowledge resources to support decision-making about a facility from the earliest conceptual stages, through design, construction, operational life, and eventually, demolition (Lee et al., 2007; Lee et al., 2009; Choi, 2010; Smart Market Report, 2012) (cited in Lee et al., 2014). As shown from the results, the item/ variable with the higher loading of this first factor (component) is ―Support design decision- making by comparing different design alternatives on a 3D model‖ (BE 2), and the item/ variable with the lower loading of this first factor (component) is ―Improve realization of the idea of a design by the owner via a 3D model of the building‖ (BE 1).

“Support design decision-making by comparing different design alternatives on a 3D model” (BE 2) is the higher item/ variable of factor 4 of BIM benefits with a factor loading of 0.80. Decisions early in the design process have a significant impact on the life cycle performance of a building. The outcome of a construction project can be improved if different design options can rapidly be analyzed to assist the client and design team in making informed decisions in the design process. As the 3D model is created, real-time information associated with the cost database becomes available. This type of information provides the designer with estimated costs for the current design alternative and gives the ability to associate costs with specific design features (Eastman et al., 2008; Thurairajah & Goucher, 2013; Stanley and Thurnell, 2014). The time saved through enhanced information management is also likely to generate productivity and efficiency gains, and also improve design outcomes through better understanding of design alternatives by clients and designers (CRC for Construction Innovation, 2007; Azhar et al., 2008a; Azhar et al., 2008b; Eastman et al., 2008; Eastman et al., 2011; Allen Consulting Group, 2010; Ahmad et al., 2012; Newton and Chileshe, 2012; Stanley and Thurnell, 2014).

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“Improve realization of the idea of a design by the owner via a 3D model of the building” (BE 1) is the lower item/ variable of factor 4 of BIM benefits with a factor loading of 0.80. The different stakeholders can find benefits from using BIM. The model developed using BIM helps owners in visualizing the spatial organization of the building as well as understanding the sequence of construction activities and project duration (Eastman et al., 2011). The owners must be able to manage and evaluate the scope of the design against their requirements at every phase of a project. BIM provides 3D visualization to the owners and thus, project conceptualization is perceived to be made easier with BIM. BIM provides the ability to check each part of the project about each of the projects options (Azhar et al., 2008a; Stanley and Thurnell, 2014).

4.6 The strength of BIM barriers

There was a field contains 18 items of BIM barriers, and this list of the 18 items was taken from the literature review and adapted by modifying or merging according to the results of the face validity and the pretesting of the questionnaire as shown in Chapter 3. These items were subjected to the views of respondents and were analyzed. The Descriptive Statistics, i.e. Means, Standard Deviations (SD), t-value (two-tailed), probabilities (P-value), Relative Importance Indices (RII), and finally ranks were established and presented in Table (4.15).

4.6.1 RII of BIM barriers

RII was calculated to weight each barrier of BIM (from BA 1 to BA 18) according to the numerical scores obtained from the questionnaire responses by the professionals in the AEC industry in Gaza strip and the results have been ranked from the highest degree (The strongest BIM barrier) to the least degree (The most vulnerable BIM barrier). Table (4.15) provides RIIs and ranks of BIM barriers, respectively. The numbers in the ―rank‖ column represent the sequential ranking. It worth mentioning that ranking of BIM barriers was based on the highest Mean, RII, and the lowest SD. If some items/ variables have similar Means and RIIs, as in the case of (BA 4 and BA 13); and (BA 10 and BA 7), the ranking will depend on the lowest SD. More precisely, although BA 4 and BA 13 have the same Mean and RIIs, BA 4 is ranked higher than the BA 13 because it has a lower SD. The same thing was done for BA 10 and BA 7, where BA 10 has taken the higher rank than BA 7. Items/ Variables were categorized with ratings from 77.33 % to 66 % (Figure 4.10).

Table (4.15): The strength of BIM barriers

tailed)

No. BIM barrier -

value value

value

Rank

(Sig.)

Mean

RII(%)

(two

Lack of the awareness of BIM by BA 2 3.87 0.99 77.33 14.34 0.00* 1 stakeholders Lack of knowledge of how to apply BIM BA 3 3.84 0.95 76.80 14.50 0.00* 2 software Lack of the awareness of the benefits that BA 5 BIM can bring to Engineering offices, 3.81 0.98 76.22 13.63 0.00* 3 companies, and projects

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Table (4.15): The strength of BIM barriers

tailed)

No. BIM barrier -

value value

value

Rank

(Sig.)

Mean

RII(%)

(two

Lack of interest in Gaza strip to pursue BA 14 the condition of the building over the life 3.75 1.10 75.04 11.29 0.00* 4 after completion of implementation stage Lack of Architects/ Engineers skilled in BA 15 3.71 1.11 74.15 10.47 0.00* 5 the use of BIM programs Lack of the education or training on the use of BIM, whether in the university or BA 16 3.69 1.02 73.78 11.14 0.00* 6 any governmental or private training centers Lack of demand and disinterest from clients regarding with using BIM BA 12 3.69 1.11 73.78 10.22 0.00* 7 technology in design and construction of the project Lack of the governmental regulations for BA 11 3.68 1.14 73.68 9.82 0.00* 8 full support the implementation of BIM Professionals think that the current CAD system and other conventional programs BA 4 satisfy the need of designing and 3.67 1.01 73.46 10.97 0.00* 9 performing the work and complete the project efficiently Lack of the real cases in Gaza strip or other nearby areas in the region that have BA 13 3.67 1.12 73.46 9.74 0.00* 10 been implemented by using BIM and have proved positive return of investment Lack of effective collaboration among project stakeholders to exchange BA 6 necessary information for BIM 3.57 0.98 71.41 9.57 0.00* 11 application, due to the fragmented nature of the AEC industry in Gaza strip Reluctance to train Architects/ Engineers BA 18 due to the costly training requirements in 3.51 1.08 70.30 7.81 0.00* 12 terms of time and money Lack of the financial ability for the small firms to start a new workflow that is BA 8 3.42 1.17 68.43 5.90 0.00* 13 necessary for the adoption of BIM effectively Companies prefer focusing on projects (under working/ construction) rather than BA 9 3.40 1.07 67.93 6.08 0.00* 14 considering, evaluating, and implementing BIM Difficulty of finding project stakeholders BA 11 with the required competence to 3.36 1.03 67.21 5.75 0.00* 15 participate in applying BIM Resistance by companies and institutions for any change can occur in the workflow BA 7 system and the refusal of adopting a new 3.36 1.08 67.21 5.41 0.00* 16 technology

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Table (4.15): The strength of BIM barriers

tailed)

No. BIM barrier -

value value

value

Rank

(Sig.)

Mean

RII(%)

(two

The unwillingness of Architects/ Engineers to learn new applications BA 17 because of their educational culture and 3.33 1.10 66.54 4.90 0.00* 17 their bias toward the programs they are dealing with Necessary high costs to buy BIM BA 1 software and costs of the necessary 3.30 1.12 66 4.41 0.00* 18 hardware updates All barriers 3.59 0.67 71.80 14.54 0.00* Critical value of t: at degree of freedom (df) = [N-1] = [270-1] = 269 and significance (Probability) level 0.05 equals “1.97”

BA 2 BA 1 80 BA 3 77.33 BA 17 76.80 BA 5 75 66 76.22 BA 7 70 BA 14 66.54 75.04 67.14 65 BA 10 BA 15 67.21 74.15 60 67.93 BA 9 73.78 BA 16 68.43 73.7 BA 8 70.30 BA 12 73.68 71.41 BA 18 73.46 BA 11 73.33 BA 6 BA 4 BA 13

Figure (4.10): RII of BIM barriers (BA 1 to BA 18)

The findings indicated that “Lack of the awareness of BIM by stakeholders” (BA 2) is the strongest barrier to BIM adopting in the AEC industry in Gaza strip. It has been ranked as the first position with (RII = 77.33%) and (P-value = 0.00*) according to the overall respondents. This result indicates that a significant proportion of respondents have little or no understanding of the concept of BIM. This finding is consistent with the result which has been found by Kassem et al. (2012). According to their studies, lack of the awareness of BIM was recognized by the professionals in the construction industry as the primary barrier to BIM and 4D adoption in the UK. This result is also in line with the research of Thurairajah and Goucher (2013), where it has shown that while

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the cost consultants in the UK are aware of BIM, there is an overall lack of knowledge and understanding of what it is. According to the study of Löf and Kojadinovic (2012) in Sweden, the reason for the lack of knowledge of BIM is the lack of guidelines on how to use and align BIM in the production phase of the construction projects. The lack of knowledge regarding BIM has led to a slow uptake of this technology and ineffective management of adoption (Mitchell and Lambert, 2013; NBS, 2013).

“Lack of knowledge of how to apply BIM software” (BA 3) (RII = 76.80 %; P-value = 0.00*) was ranked as the second strongest barrier to BIM adopting in the AEC industry in Gaza strip. Due to the complexity of gathering all the relevant information when working with BIM on a building project some companies have developed, software designed specifically to work in a BIM framework. New BIM software makes massive projects doable (3D Visualization, Quantity Takeoff, Lean Scheduling, Cost Planning and other processes). There are some BIM software applications available in the market. The top three software are as follows: Autodesk® Revit™; Graphisoft® Constructor™; and Bentley® Architecture™ (Azhar et al., 2008b). The result of the analysis is consistent with which has been revealed by research in Hong Kong by Tse et al. (2005). They found that a large part of the Architects stated that BIM is ―not easy to use.‖ This result is also in line with which has been found in Sweden by Lahdou and Zetterman (2011). They found that project managers in the construction projects claimed that the implementation of BIM is not always as easy as software developers suggest. A usual problem is getting different file formats to function properly when creating a combined building information model. In general, there is a knowledge gap regarding BIM software and how to use it efficiently (AGC, 2005; Keegan, 2010; Kassem et al., 2012; Khosrowshahi and Arayici, 2012; Löf and Kojadinovic, 2012; Crowley, 2013).

“Lack of the awareness of the benefits that BIM can bring to Engineering offices, companies and projects” (BA 5) was ranked as the third position with (RII of 76.22 %; P-value = 0.00*). This barrier to BIM adopting would be a very logical choice from the respondents in the AEC industry in Gaza strip, which is because of the knowledge gap regarding BIM. The result is agreed with those reported about barriers to BIM adoption in the UK by Arayici et al. (2009), and Kassem et al. (2012). This outcome also corroborates the findings of the studies of Khosrowshahi and Arayici (2012), Aibinu and Venkatesh (2013), and Elmualim and Gilder (2013). Their research determined the lack of the awareness of the BIM benefits as one of the substantial barriers associated with BIM implementation in the AEC industries in (the UK and Finland), Australia, and (the UK, Europe, the USA, India, Ghana, China, Russia, South Africa, Australia, Canada, Malaysia and the UAE), respectively. People in Australia also displayed a degree of hesitancy in implementing BIM on a project because of the lack of knowledge about BIM and its distinctive capabilities in the field of the construction industry (Mitchell and Lambert, 2013). In Hong Kong, Tse et al. (2005) revealed by research that a large part of the Architects did not find the tools in BIM to satisfy their needs. Thus, BIM benefits are still often misunderstood or not known to those do not use it in their works (Löf and Kojadinovic, 2012).

Finally, ―Necessary high costs to buy BIM software and costs of the necessary hardware updates” (BA 1) was ranked as the lowest barrier to BIM adoption in the 18th position with (RII = 66 %; P-value = 0.00*) as per perceptions of all the respondents. This view has more than one interpretation such as they do not know the real amount of the cost they need to adopt BIM. Some respondents who are working in consulting

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offices also said that the initial costs that must be spent in the beginning would not affect financially on the organization as long as there are significant benefits will be gained from BIM adoption in the long run, and thus costs are not a barrier to adopting BIM. On the contrary of the result of the analysis, when the respondents of QS in Australia were asked to list the barriers to the use of BIM features, the results showed that the cost of implementation was the most frequently cited barrier by the respondents (Aibinu and Venkatesh, 2013). There are several examples of the high costs that are required to implement BIM, such as (1) software licensing; (2) the costs to improve server capacity to suit having such a high IT requirements; (3) ongoing maintenance fee; (4) the cost of the proper creation of a building model; and (5) the costs of the training (Keegan, 2010; Aibinu and Venkatesh, 2013; and (Lee et al., 2007; Lee et al., 2009; Choi, 2010; Smart Market Report, 2012) (cited in Lee et al., 2014)).

The top three barriers to BIM adoption, which were rated by the respondents, are logical and acceptable to be the strongest barriers to BIM adoption in the AEC industry in Gaza strip. Regarding results for all items of the part of BIM barriers, they show that the Mean for all those items equals 3.59 and the total RII equals 71.80 %, which is greater than 60% (the neutral value of RII (3/5)*100 = 60%). The value of t-test equals 14.54, which is higher than the critical value of t that equals 1.97. As well as, the total P-value of all the items equals 0.00, and it is less than the significance level of 0.05. Based on all the previous results, BIM barriers are substantially affecting the adoption of BIM in the AEC industry in Gaza strip.

4.6.2 Factor analysis results of BIM barriers

RII analysis did not provide any meaningful outcomes regarding understanding the clustering effect of the similar items/ variables, and thus further analysis was required using advanced statistical methods such as factor analysis. The use of factor analysis is purely exploratory. Factor analysis was used to examine the pattern of intercorrelations between the 18 items/ variables of the field of BIM barriers in an attempt to reduce the number of them. It also used to group items/ variables with similar characteristics together. In other words, it identified subsets of items/ variables that correlate highly with each other, which called factors or components. Factor analysis was conducted for this study using the Principal Component Analysis (PCA).

4.6.2.1 Appropriateness of factor analysis

The data was first assessed for its suitability to the factor analysis application. There were many stages of that assessment:

The distribution of data

The assumption of normality is the essential requirement to generalize the results of factor analysis test beyond the sample collected (Field, 2009; Zaiontz, 2014). As shown in Ch3, the received data of the research follows the normal distribution. The result has been satisfied with this requirement.

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Validity of sample size

The reliability of factor analysis is dependent on sample size. Factor analysis/ PCA can be conducted on a sample that has fewer than 100 respondents, but more than 50 respondents. The sample size for this study was 270. Further, the standard rule is to suggest that sample size contains at least 10–15 respondents per item/ variable. In other words, sample size should be at least ten times the number of variables and some even recommend 20 times (Field, 2009; Zaiontz, 2014). Fortunately, for this field of BIM barriers, the condition was verified. This field contains 18 barriers, and the sample size was 270. With 270 respondents and 18 items/ variables (BIM barriers), the ratio of respondents to items/ variables are 15: 1, which exceeds the requirement for the ratio of respondents to items/ variables.

Validity of Correlation matrix (Correlations between items/ variables)

Table (4.16) illustrates the correlation matrix for the 18 items/ variables of BIM barriers. It is simply a rectangular array of numbers which gives the correlation coefficients between a single item/ variable and every other item/ variable in the investigation (Field, 2009; Zaiontz, 2014). As shown in Table (4.16), the correlation coefficient between an item/ a variable and itself is always 1; hence the principal diagonal of the correlation matrix contains 1s. The correlation coefficients above and below the principal diagonal are the same. PCA requires that there be some correlations greater than 0.30 between the items/ variables included in the analysis. For this set of items/ variables, that most of the correlations in the matrix are strong and greater than 0.30. Correlations have been satisfied with this requirement.

Kaiser-Meyer-Olkin (KMO) and Bartlett's Test

The Kaiser-Meyer-Olkin (KMO) sampling adequacy test and Bartlett's test of Sphericity were carried out. The results of these tests are reported in Table (4.17). The value of the KMO measure of sampling adequacy was 0.89 (close to 1). It was considered acceptable and meritorious because it exceeds the minimum requirement of 0.50 and it is above 0.80 (according to Kaiser, 1974; Field, 2009; Zaiontz, 2014). Moreover, the Bartlett test of sphericity was another indication of the strength of the relationship among items/ variables. The Bartlett test of sphericity was 2167.89, and the associated significance level was 0.00. The probability value (Sig.) associated with the Bartlett test is less than 0.01, which satisfies the PCA requirement. This result indicated that the correlation matrix was not an identity matrix and all of the items/ variables are correlated (Field, 2009; Zaiontz, 2014). According to the results of these two tests, the sample data of (BIM barriers) were appropriated for factor analysis.

Measures of reliability for the whole items/ variables

Cronbach's alpha test was performed on the items/ variables in the field of (BIM barriers). The value of Cronbach‘s alpha (Cα) could be anywhere in the range of 0 to 1, where a higher value denotes the greater internal consistency and vice versa. An alpha of 0.60 or higher is the minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009; Weiers, 2011; Garson, 2013). As shown in Table (4.17), the value of the calculated Cα for 16 items/ variables of the field of (BIM barriers) is 0.90 which is considered to be marvelous. Cronbach's alpha test was applied only to the 16 items/

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variables (from the original 18 variables) of the field because the remaining two items/ variables were failed according to the Communalities Table and thus were deleted from the analysis as it will be shown below.

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Table: (4.16): Correlations between items/ variables of BIM barriers BA 1 BA 2 BA 3 BA 5 BA 7 BA 8 BA 9 BA 10 BA 11 BA 12 BA 13 BA 14 BA 15 BA 16 BA 17 BA 18

BA 1 1

BA 2 0.50** 1

BA 3 0.39** 0.76** 1

BA 5 0.29** 0.55** 0.56** 1

BA 7 0.23** 0.22** 0.17** 0.28**

BA 8 0.42** 0.28** 0.23** 0.30** 0.50** 1

BA 9 0.28** 0.30** 0.24** 0.32** 0.53** 0.61** 1

BA 10 0.29** 0.30** 0.24** 0.34** 0.45** 0.52** 0.59** 1

BA 11 0.24** 0.42** 0.36** 0.36** 0.24** 0.40** 0.47** 0.60** 1

BA 12 0.22** 0.33** 0.33** 0.38** 0.25** 0.34** 0.34** 0.52** 0.69** 1

BA 13 0.13** 0.31** 0.33** 0.34** 0.28** 0.32** 0.39** 0.45** 0.59** 0.63** 1

BA 14 0.07** 0.29** 0.27** 0.41** 0.29** 0.29** 0.40** 0.37** 0.50** 0.52** 0.63** 1

BA 15 0.15** 0.38** 0.45** 0.40** 0.21** 0.28** 0.40** 0.42** 0.56** 0.57** 0.54** 0.60** 1

BA 16 0.19** 0.41** 0.39** 0.43** 0.20** 0.26** 0.39** 0.42** 0.50** 0.50** 0.47** 0.53** 0.72** 1

BA 17 0.18** 0.26** 0.26** 0.25** 0.27** 0.14** 0.30** 0.29** 0.24** 0.18** 0.27** 0.34** 0.41** 0.45** 1

BA 18 0.27** 0.37** 0.33** 0.35** 0.27** 0.29** 0.35** 0.37** 0.33** 0.27** 0.31** 0.37** 0.41** 0.46** 0.54** 1 **. Correlation is significant at the 0.01 level (1-tailed). *. Correlation is significant at the 0.05 level (1-tailed).

Table: (4.17) KMO and Bartlett's test for items/ variables of BIM barriers KMO and Bartlett's test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.89 Bartlett's Test of Sphericity Approx. Chi-Square 2167.89 df 120 Sig. 0.00* Cronbach's Alpha (Cα) 0.90

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Communalities (common variance)

The next part of the output was a Table of communalities. Communalities represent the proportion of the variance in the original items/ variables that is accounted for by the factor solution. The factor solution should explain at least half of each original item's/ variable's variance, so the communality value for each item/ variable should be 0.50 or higher (Field, 2009; Zaiontz, 2014). On iteration 1 of factor analysis test, the communality for the variable BA 4: “Professionals think that the current CAD system and other conventional programs satisfy the need of designing and performing the work and complete the project efficiently‖ was 0.46; and the communality for the variable BA 6: “Lack of effective collaboration among project stakeholders to exchange necessary information for BIM application, due to the fragmented nature of the AEC industry in Gaza strip‖ was 0.42. Since they were less than 0.50, the variables had to be removed, and the PCA was computed again (new iteration). Table (4.18) shows that all of the communalities for all the remaining items/ variables satisfy the minimum requirement of being larger than 0.50, and therefore was not to exclude any of these items/ variables on the basis of low communalities. Thus, all of the remaining 16 items/ variables (from the original 18 items/ variables) of this field (BIM barriers) were used in this analysis.

Table: (4.18) Communalities of BIM barriers

No. BIM Barrier

Initial Extraction BA 1 Necessary high costs to buy BIM software and costs of the necessary 1 0.61 hardware updates BA 2 Lack of the awareness of BIM by stakeholders 1 0.81 BA 3 Lack of knowledge of how to apply BIM software 1 0.79 BA 5 Lack of the awareness of the benefits that BIM can bring to 1 0.54 Engineering offices, companies, and projects BA 7 Resistance by companies and institutions for any change can occur in 1 0.62 the workflow system and the refusal of adopting a new technology BA 8 Lack of the financial ability for the small firms to start a new 1 0.72 workflow that is necessary for the adoption of BIM effectively BA 9 Companies prefer focusing on projects (under working/ construction) 1 0.70 rather than considering, evaluating, and implementing BIM BA 10 Difficulty of finding project stakeholders with the required 1 0.66 competence to participate in applying BIM BA 11 Lack of the governmental regulations for full support the 1 0.71 implementation of BIM BA 12 Lack of demand and disinterest from clients regarding with using BIM 1 0.74 technology in design and construction of the project BA 13 Lack of the real cases in Gaza strip or other nearby areas in the region that have been implemented by using BIM and have proved positive 1 0.67 return of investment BA 14 Lack of interest in Gaza strip to pursue the condition of the building 1 0.64 over the life after completion of implementation stage BA 15 Lack of Architects/ Engineers skilled in the use of BIM programs 1 0.72 BA 16 Lack of the education or training on the use of BIM, whether in the university or any governmental or private training centers 1 0.68

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Table: (4.18) Communalities of BIM barriers

No. BIM Barrier

Initial Extraction BA 17 The unwillingness of Architects/ Engineers to learn new applications because of their educational culture and their bias toward the programs 1 0.77 they are dealing with BA 18 Reluctance to train Architects/ Engineers due to the costly training 1 0.66 requirements in terms of time and money

Total Variance Explained

By using the output from iteration 2, there were four eigenvalues greater than 1 (Figure 4.11). The eigenvalue criterion stated that each component explained at least one item's/ variable's worth of the variability, and therefore only components with eigenvalues greater than one should be retained (Larose, 2006; Field, 2009). The latent root criterion for some factors to derive would indicate that there were four components (factors) to be extracted for these variables. Results were tabulated in Table (4.19). The four components solution explained a sum of the variance with component 1 contributing 41.70 %; component 2 contributing 9.95 %; component 3 contributing 9.78 %; and component 4 contributing 7.40 %. All the remaining factors are not significant.

Factor 1: Lack of BIM interest "eigenvalue = 6.67"

Factor 2: Organization-wide resistance to change workflows "eigenvalue = 1.59"

BIM barriers Factor 3: Lack of knowledge about BIM and cost of implementing "eigenvalue = 1.57"

Factor 4: Cultural barriers toward adopting new technology and training requirements "eigenvalue = 1.18"

Figure (4.11): The four components (factors) of BIM barriers

The four components were then rotated via varimax (orthogonal) rotation approach. This does not change the underlying solution or the relationships among the items/ variables. Rather, it presents the pattern of loadings in a manner that is easier to interpret factors (components) (Reinard, 2006; Field, 2009; Zaiontz, 2014). The rotated solution revealed that the four components solution explained a sum of the variance

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with component 1 contributing 23.90 %; component 2 contributing 16.59 %; component 3 contributing 16.25 %; and component 4 contributing 12.08 %. These four components (factors) explained 68.83 % of total variance for the varimax rotation.

Table (4.19): Total variance Explained of BIM barriers Extraction Sums of Rotation Sums of Initial Eigenvalues

Squared Loadings Squared Loadings

Total Total Total

Component

Cumulative % Cumulative % Cumulative % Cumulative

%of Variance %of Variance %of Variance

1 6.67 41.70 41.70 6.67 41.70 41.70 3.82 23.90 23.90 2 1.59 9.95 51.65 1.59 9.95 51.65 2.65 16.59 40.50 3 1.56 9.78 61.43 1.56 9.78 61.43 2.60 16.25 56.75 4 1.18 7.40 68.83 1.18 7.40 68.83 1.93 12.08 68.83 5 0.77 4.79 73.62

6 0.58 3.63 77.25

7 0.55 3.46 80.71

8 0.51 3.16 83.87

9 0.47 2.92 86.79

10 0.41 2.58 89.37

11 0.36 2.25 91.62

12 0.32 2.02 93.64

13 0.30 1.90 95.54

14 0.28 1.77 97.31

15 0.24 1.52 98.82

16 0.19 1.18 100

Scree Plot

The scree plot below in Figure (4.12) is a graph of the eigenvalues against all the factors. This graph can also be used to decide on some factors that can be derived. The point of interest is where the curve starts to flatten. It can be seen that the curve begins to flatten between factors 4 and 5. Note also that factor 5 has an eigenvalue of less than 1, so only four factors have been retained to be extracted.

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Figure (4.12): Scree plot for factors of BIM barriers

Rotated Component (Factor) Matrix

Table (4.20) shows the factor loadings after rotation of 16 items/ variables (from the original 18 items/ variables) on the four factors extracted and rotated. The pattern of factor loadings should be examined to identify items/ variables that have complex structures (Complex structure occurs when one item/ variable has high loadings or correlations (0.50 or greater) on more than one factor/ component). If an item/ a variable has a complex structure, it should be removed from the analysis (Reinard, 2006; Field, 2009; Zaiontz, 2014). According to the results of iteration 2, none of the items/ variables demonstrated a complex structure and as shown in Table (4.20), the factor loading for each item/ variable is above 0.5. The items/ variables are listed in the order of the size of their factor loadings.

Naming the Factors

Once an interpretable pattern of loadings is done, the factors or components should be named according to their substantive content or core. The factors should have conceptually distinct names and content. Items/ Variables with higher loadings on a factor should play more important role in naming the factor. The four components (factors) were named as the following: Factor 1: ―Lack of BIM interest.” Factor 2: ―Organization-wide resistance to change workflows.‖ Factor 3: ―Lack of knowledge about BIM and cost of implementing.‖ Factor4: Cultural barriers toward adopting new technology and training requirements.‖

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Measures of reliability for each factor

Once factors have been extracted and rotated, it was necessary to cross checking if the items/ variables in each factor formed collectively explain the same measure within target dimensions (Doloi, 2009). If items/ variables truly form the identified factor (component), it is understood that they should reasonably correlate with one another, but not the perfect correlation though. Cronbach's alpha (Cα) test was conducted for each component (factor) as follows:

Factor 1 ―Lack of BIM interest‖ with items/ variables: BA 12, BA 13, BA 11, BA 14, BA 15, and BA 16. Factor 2 ―Organization-wide resistance to change workflows‖ with items/ variables: BA 8, BA 7, BA 9, and BA 10. Factor 3 ―Lack of knowledge about BIM and cost of implementing‖ with items/ variables: BA 2, BA 3, BA 1, and BA 5. Factor 4: ―Cultural barriers toward adopting new technology and training requirements‖ with items/ variables: BA 17, and BA 18.

The higher value of Cα denotes the greater internal consistency and vice versa. An alpha of 0.60 or higher is the minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009; Weiers, 2011; Garson, 2013). According to the results which were tabulated in Table (4.20), Cα for factor 1 is 0.87; Cα for factor 2 is 0.82; Cα for factor 3 is 0.80 and Cα for factor 4 is 0.69. They are considered to be acceptable.

Table (4.20): Results of factor analysis for BIM barriers

)

% Cα

No. BIM barrier factors (Components)

Factor

explained

variance Cronbach's

Alpha ( Alpha

Eigenvalues

Component/ Factor One : Lack of BIM interest BA 12 Lack of demand and disinterest from clients 0.81 regarding with using BIM technology in design and construction of the project BA 13 Lack of the real cases in Gaza strip or other 0.78 nearby areas in the region that have been implemented by using BIM and have proved positive return of investment BA 11 Lack of the governmental regulations for full 0.74 support the implementation of BIM 6.67 41.70 0.87 BA 14 Lack of interest in Gaza strip to pursue the 0.72 condition of the building over the life after completion of implementation stage BA 15 Lack of Architects/ Engineers skilled in the use 0.72 of BIM programs BA 16 Lack of the education or training on the use of 0.61 BIM, whether in the university or any governmental or private training centers Component/ Factor Two: Organization-wide resistance to change workflows BA 8 Lack of the financial ability for the small firms 0.80 to start a new workflow that is necessary for the adoption of BIM effectively 125

Table (4.20): Results of factor analysis for BIM barriers

)

% Cα

No. BIM barrier factors (Components)

Factor

explained

variance Cronbach's

Alpha ( Alpha

Eigenvalues

BA 7 Resistance by companies and institutions for 0.75 any change can occur in the workflow system and the refusal of adopting a new technology BA 9 Companies prefer focusing on projects (under 0.74 working/ construction) rather than considering, 1.59 9.95 0.82 evaluating, and implementing BIM BA 10 Difficulty of finding project stakeholders with 0.65 the required competence to participate in applying BIM Component/ Factor Three: Lack of knowledge about BIM and cost of implementing BA 2 Lack of the awareness of BIM by stakeholders 0.85 BA 3 Lack of knowledge of how to apply BIM 0.83 software

BA 1 Necessary high costs to buy BIM software and 0.66 1.57 9.78 0.80 costs of the necessary hardware updates

BA 5 Lack of the awareness of the benefits that BIM 0.61 can bring to Engineering offices, companies, and projects Component/ Factor Four: Cultural barriers toward adopting new technology and training requirements BA 17 The unwillingness of Architects/ Engineers to 0.85 learn new applications because of their educational culture and their bias toward the programs they are dealing with 1.18 7.40 0.69 BA 18 Reluctance to train Architects/ Engineers due 0.72 to the costly training requirements in terms of time and money

4.6.2.2 The extracted factors

The next section will interpret and discuss each of the extracted components (factors) as follows:

Factor 1: Lack of BIM interest The first factor named Lack of BIM interest explains 41.70% of the total variance and contains six items/ variables. The majority of items/ variables had relatively high factor loadings (≥ 0.61). The six items/ variables are as follows: 1. Lack of demand and disinterest from clients regarding with using BIM technology in design and construction of the project (BA 12), with a factor loading = 0.81. 2. Lack of the real cases in Gaza strip or other nearby areas in the region that have been implemented by using BIM and have proved positive return of investment (BA 13), with a factor loading = 0.78. 3. Lack of the governmental regulations for full support the implementation of BIM (BA 11), with a factor loading = 0.74.

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4. Lack of interest in Gaza strip to pursue the condition of the building over the life after completion of implementation stage (BA 14), with a factor loading = 0.72. 5. Lack of Architects/ Engineers skilled in the use of BIM programs (BA 15), with a factor loading = 0.72. 6. Lack of the education or training on the use of BIM, whether in the university or any governmental or private training centers (BA 16), with a factor loading = 0.61.

The name of this factor has been chosen according to the correlations between these six items/ variables. Interest is a feeling that causes attention to focus on an object, event, or process. The absence of interest in BIM has a powerful effect on non-adoption it in the AEC industry in Gaza strip. The adoption of BIM has been tightly connected with the interested individuals (Lindblad, 2013). Thus; the primary reason for not using BIM is the fact that clients and other project team members did not request to use BIM. Moreover, if one member of a project team is using BIM while the others continue doing things the old way, there will be a limited benefit (Khosrowshahi and Arayici, 2012; Löf and Kojadinovic, 2012; Crowley, 2013; Aibinu and Venkatesh, 2014). To make the investment worthwhile, someone has to break the stalemate. That someone is often the government. But there is an apparent absence of the government lead and direction to promote the use of BIM and develop the appropriate technical skills amongst firms of the AEC industry in Gaza strip. Studies of Ku and Taiebat (2011); Lahdou and Zetterman (2011); Weygant (2011); Mitchell and Lambert (2013); Aibinu and Venkatesh (2014) pointed out to the Lack of the governmental regulations to fully support the implementation of BIM as a substantial barrier to BIM adoption. The lack of the real cases that have been implemented by using BIM in Gaza strip or other nearby areas in the region is also an important reason for the lack of encouragement to adopt BIM. As shown from the results, the item/ variable with the highest loading of this first factor (component) is ―Lack of demand and disinterest from clients regarding with using BIM technology in design and construction of the project‖ (BA 12), and the item/ variable with the lowest loading of this first factor (component) is “Lack of the education or training on the use of BIM, whether in the university or any governmental or private training centers‖ (BA 16).

―Lack of demand and disinterest from clients regarding with using BIM technology in design and construction of the project‖ (BA 12), the highest item/ variable, with a factor loading of 0.81 can be a high barrier to BIM adoption in the AEC industry in Gaza strip. One of the problems in developing BIM models is the client. The project owner/ client might be not interested in BIM, or not aware of BIM, or not capable of handling BIM models. Clients demand can play a vital role in driving practices to make progress towards BIM. Low client demand is a result of the lack of knowledge of BIM or even uncertainties regarding BIM for certain benefits. Clients are missing out on the benefits of BIM (Tse et al., 2005; Gu et al., 2008; Keegan, 2010; Kjartansdóttir, 2011; Khosrowshahi and Arayici, 2012; Löf and Kojadinovic, 2012; Crowley, 2013; Lindblad, 2013; Aibinu and Venkatesh, 2014). Some respondents stated that they will use BIM if there is a requirement from clients (especially clients of huge projects). The NBS National BIM Report 2013 identified the top five reasons cited by those organizations that haven‘t yet made the move to adopt BIM, and the first barrier was that there is no client demand (NBS, 2013).

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“Lack of the education or training on the use of BIM, whether in the university or any governmental or private training centers” (BA 16), the lowest item/ variable, with a factor loading of 0.61 can play a fundamental role in not adopting BIM in the AEC industry in Gaza strip. There is a lack of BIM integration within the existing education and training services in Gaza strip, while some universities around the world are offering courses for various BIM applications. The Architectural and Engineering education usually reflects the needs of the work market. BIM is not just another CAD; it is the shift from presenting information about the building to representing this information. Crowley (2013) pointed out in his study to the importance of the education and training of BIM for AEC industry.

Factor 2: Organization-wide resistance to change workflows The second factor named Organization-wide resistance to change workflows explains 9.95% of the total variance and contains four items/ variables. The majority of items/ variables had relatively high factor loadings (≥ 0.65). The four items/ variables are as follows: 1. Lack of the financial ability for the small firms to start a new workflow that is necessary for the adoption of BIM effectively (BA 8), with a factor loading = 0.80. 2. Resistance by companies and institutions for any change can occur in the workflow system and the refusal of adopting a new technology (BA 7), with a factor loading = 0.75. 3. Companies prefer focusing on projects (under working/ construction) rather than considering, evaluating, and implementing BIM (BA 9), with a factor loading = 0.74. 4. Difficulty of finding project stakeholders with the required competence to participate in applying BIM (BA 10), with a factor loading = 0.65.

The name of this factor has been chosen according to the correlations between these four items/ variables. Adoption of BIM requires changing the traditional work practice (Davidson, 2009; Arayici et al., 2009; Gu and London, 2010). In contrast, organization- wide resistance regarding the need for investment in infrastructure, training, and new software tools would be a major factor that affects BIM adoption in the AEC industry in Gaza strip. Designers, developers, contractors and construction managers all also tend to focus on their area and protect their interests in the building process, which leads to the presence of a fragmented industry (Johnson and Laepple, 2003). The culture of implementation decides the effectiveness of a new concept. For incorporating BIM, an open-minded culture is required. In the construction industry, where project managers spend most of the time on-site, they have the liberty to work in their way. In the case of BIM, however, these project managers need to adhere to strict guidelines and processes. Therefore, there is resistance to change. Successful BIM adoption is not all about software; it‘s also about organizational change. In other words, for successful BIM adoption, organizations must develop and manage their workflows for different tasks during all phases of the project lifecycle. An organization must look internally to understand their operating systems and identify how BIM can add value to their daily activities (Davidson, 2009; Arayici et al., 2005; Gu et al., 2008; Yan and Damian, 2008; Arayici et al., 2009; Becerik-Gerber et al., 2011; Gu and London, 2010; Khosrowshahi and Arayici, 2012). As shown from the results, the item/ variable with the highest loading of this first factor (component) is ―Lack of the financial ability for the small firms to start a new workflow that is necessary for the adoption of BIM effectively‖ (BA

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8), and the item/ variable with the lowest loading of this first factor (component) is ―Difficulty of finding project stakeholders with the required competence to participate in applying BIM‖ (BA 10).

“Lack of the financial ability for the small firms to start a new workflow that is necessary for the adoption of BIM effectively” (BA 8), the highest item/ variable, with a factor loading of 0.80 is a roadblock in BIM adoption in the AEC industry in Gaza strip. And what proves to be a barrier to BIM adoption is the price of the software and incompatibility with other software. As passed in the previous studies, Arayici et al. (2009); Khosrowshahi and Arayici (2012); Elmualim and Gilder (2013); Thurairajah and Goucher (2013); and Aibinu and Venkatesh (2014) pointed to the strength of this barrier to BIM adoption. Last but not the least, the company that is implementing BIM has to change the work process. For making necessary changes in the process, a cost will be incurred. So, companies (especially, small companies) are more worried about the expenses that follow after the implementation of BIM. But, BIM needs to be seen from the perspective of the value added. The implementation of BIM software can cause a sea change in the way the AEC firm functions, but the long term benefits are irrefutable.

“Difficulty of finding project stakeholders with the required competence to participate in applying BIM” (BA 10), the lowest item/ variable, with a factor loading of 0.65 can be a roadblock in BIM adoption in the AEC industry in Gaza strip. As it turns out previously, the results of objective 1 of the study indicated that the level of knowledge regarding BIM in the AEC industry in Gaza strip is very low; and the lack of cohesion among stakeholders makes it difficult to improve the knowledge level. Firms and disciplines are also working separately and interacting only through the exchange of construction documents. If one member of a project team is using BIM while the others continue doing things the old way, there will be a limited benefit. BIM both enables and requires tighter integration among disciplines and companies. They must work together as one. Lahdou and Zetterman (2011) said that the utilization of BIM goes hand in hand with a new method that allows more partnering like relationships among stakeholders. These collaborative relationships can create more cohesion among stakeholders, thus making it easier to work together towards a common goal of implementing BIM. In other words, collaboration from all different stakeholders needs for BIM to be successful; to insert, extract, update or modify information in the BIM model at the various stages of the facilities life-cycle (Sebastian, 2011). Factor 3: Lack of knowledge about BIM and cost of implementing The third factor named Lack of knowledge about BIM and cost of implementing explains 9.78% of the total variance and contains four items. The majority of items/ variables had relatively high factor loadings (≥ 0.61). The four items/ variables are as follows: 1. Lack of the awareness of BIM by stakeholders (BA 2), with a factor loading = 0.85. 2. Lack of knowledge of how to apply BIM software (BA 3), with a factor loading = 0.83. 3. Necessary high costs to buy BIM software and costs of the necessary hardware updates (BA 1), with a factor loading = 0.66. 4. Lack of the awareness of the benefits that BIM can bring to Engineering offices, companies, and projects (BA 5), with a factor loading = 0.61.

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The name of this factor has been chosen according to the correlations between these four items/ variables. There is a pressing demand for improved awareness and understanding of BIM across the AEC industry, according to many studies related to BIM. Lack of knowledge regarding BIM has led to a slow uptake of this technology and ineffective management of adoption (Mitchell and Lambert, 2013; NBS, 2013). There is a significant lack of understanding of BIM (the core concepts of BIM) and its practical applications throughout the life of projects. There is also a lack of technical skills that professionals need to have for using the BIM software as well as the lack of knowledge of how to implement the BIM software to be helpful in construction processes. According to that, it is clear that there is a significant need for BIM education and training. On the other hand; companies are worried about the costs of implementation of BIM. There are several examples of the high costs that are required to implement BIM, such as (1) software licensing; (2) the costs to improve server capacity to suit having such a high IT requirements; (3) ongoing maintenance fee; (4) the cost of the proper creation of a building model; and (5) the costs of training (Keegan, 2010; Aibinu and Venkatesh, 2013). As shown from the results, the item/ variable with the highest loading of this first factor (component) is ―Lack of the awareness of BIM by stakeholders‖ (BA 2), and the item/ variable with the lowest loading of this first factor (component) is ―Lack of the awareness of the benefits that BIM can bring to Engineering offices, companies, and projects‖ (BA 5).

“Lack of the awareness of BIM by stakeholders” (BA 2), the highest item/ variable, with a factor loading of 0.85 is an adamant barrier to adopting BIM in the AEC industry in Gaza strip. As it turns out previously, the results of objective 1 indicated that the level of knowledge regarding BIM in the AEC industry in Gaza strip is very low. This barrier was mentioned in the literature review as a very high barrier to BIM adoption according to the studies of Kassem et al. (2012), and Löf and Kojadinovic (2012) in the UK and Sweden. Thurairajah and Goucher (2013) also claimed that there is an overall lack of knowledge and understanding of what BIM is in the UK despite there are some destinations have adopted BIM in their work. The same result was shown in Australia by Newton and Chileshe (2012), and Mitchell and Lambert (2013), where they said that people in Australia suffer from a lack of knowledge about BIM and its distinctive capabilities in the field of construction industry.

“Lack of the awareness of the benefits that BIM can bring to Engineering offices, companies, and projects” (BA 5), the lowest item/ variable, with a factor loading of 0.61 can be a roadblock in BIM adoption in the AEC industry in Gaza strip. This barrier was mentioned in the literature review as a strong BIM barrier according to the studies of Arayici et al. (2009), Kassem et al. (2012), Khosrowshahi and Arayici (2012), Aibinu and Venkatesh (2013), and Elmualim and Gilder (2013). The professionals in the AEC industry display a degree of hesitancy in implementing BIM on a project because of the lack of knowledge about BIM and its distinctive capabilities in the field of construction industry, where BIM benefits are still often misunderstood or not known to those not use it in their works (Löf and Kojadinovic, 2012; Mitchell and Lambert, 2013).

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Factor 4: Cultural barriers toward adopting new technology and training requirements

The fourth factor named Cultural barriers toward adopting new technology and training requirements explains 7.40 % of the total variance and contains two items/ variables. The two items/ variables had relatively high factor loadings (≥ 0.72). 1. The unwillingness of Architects/ Engineers to learn new applications because of their educational culture and their bias toward the programs they are dealing with (BA 17), with a factor loading = 0.85. 2. Reluctance to train Architects/ Engineers due to the costly training requirements in terms of time and money (BA 18), with a factor loading = 0.72.

The name of the factor has been chosen according to the correlations between these two items/ variables under this factor. As mentioned before, the culture of implementation decides the effectiveness of a new concept. For incorporating BIM, an open-minded culture is required. In the AEC industry, Architects/ Engineers used to the use of certain programs, and they have the liberty to work in their way. In the case of BIM, however, these Architects/ Engineers need to learn new programs regarding BIM software and adhere to strict guidelines and hence, there is a resistance to change their way of working (Arayici et al., 2005; Yan and Damian, 2008; Arayici et al., 2009; Becerik- Gerber et al., 2011; Gu and London, 2010; Khosrowshahi and Arayici, 2012). On the other hand, most companies are believed that the training for BIM would be too costly and needs much time. Therefore, there is a reluctance to train the Architects and Engineers (Arayici et al., 2009; Becerik-Gerber et al., 2011; Khosrowshahi and Arayici, 2012; Elmualim and Gilder, 2013). As shown from results, the item/ variable with the higher loading of this first factor (component) is ―The unwillingness of Architects/ Engineers to learn new applications because of their educational culture and their bias toward the programs they are dealing with” (BA 17), and the item/ variable with the lower loading of this first factor (component) is “Reluctance to train Architects/ Engineers due to the costly training requirements in terms of time and money” (BA 18).

“The unwillingness of Architects/ Engineers to learn new applications because of their educational culture and their bias toward the programs they are dealing with” (BA 17) is the higher item/ variable of factor 4 with a factor loading of 0.85. When adopting BIM, it is vital that the individuals are sufficiently trained in the use of the new technology for them to be able to contribute to the changing work environment (Aranda-Mena et al., 2007; Gu et al., 2008). The unwillingness to learn BIM may be due to several reasons, including (1) Architects and Engineers think that BIM is a complex and delicate system; (2) Architects and Engineers prefer to keep using the traditional programs and refuse to learn any new programs, especially if they use those traditional programs for a long time; (3) in sometimes, the age of the Architects and Engineers plays a role regarding their acceptance to learn new applications; or (4) maybe they don‘t have enough time to learn new applications. This barrier was mentioned in the literature review as one of the significant barriers to BIM adoption according to the studies of Davidson (2009); Arayici et al. (2005); Gu et al. (2008); Yan and Damian (2008); Arayici et al. (2009); Becerik-Gerber et al. (2011); Gu and London (2010); Khosrowshahi and Arayici (2012).

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“Reluctance to train Architects/ Engineers due to the costly training requirements in terms of time and money” (BA 18) is the lower item/ variable of factor 4 with a factor loading of 0.72. Yan and Damian (2008) revealed that most companies in their study who did not use BIM are believed that the training for BIM would be too costly in terms of time and money. McGraw-Hill Construction (2009) and Löf and Kojadinovic (2012) emphasized that the required time for training to work efficiently with BIM is one of the main challenges to adopting BIM. While, Kaner et al., (2008); Keegan (2010); and Aibinu and Venkatesh (2013) agreed that the required initial costs for training of the individuals to be able to deal with BIM are very high, and this is the primary challenge to adopt BIM in the AEC industry.

4.7 Test of research hypotheses

Some hypotheses have been put to study relations between some variables to support BIM adoption in the AEC industry in Gaza Strip. According to Figure (4.13), five hypotheses were tested through applying the Pearson product-moment correlation coefficient (Pearson's correlation coefficient). The Pearson's correlation coefficient was used to measure the strength and direction of the relationship (linear association/ correlation) between two quantitative variables, where the value (r = 1) means a perfect positive correlation and the value (r = -1) means a perfect negative correlation. Each hypothesis was tested separately. The four variables in Figure (4.13) represent parts of the questionnaire, where the questionnaire was built from the following five parts:

 Part one: is related to the respondent’s demographic data and the way of work performance.  Part two: to assess the awareness level of BIM by professionals in the AEC industry in Gaza strip.  Part three: to investigate the importance of BIM functions in the AEC industry in Gaza strip.  Part four: to investigate the value of BIM benefits in the AEC industry in Gaza strip.  Part five: to investigate the BIM barriers in the AEC industry in Gaza strip.

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H4 The awareness level H5 of BIM by the professionals

The The value of importance of HI BIM functions BIM benefits

H2 H3

BIM barriers

Figure (4.13): Hypotheses model (Source: The researcher, 2015)

4.7.1 The correlation between the awareness level of BIM and BIM barriers

H1: There is an inverse relationship, statistically significant at α ≤ 1.15, between the awareness level of BIM by the professionals and BIM barriers in the AEC industry in Gaza strip.

To test the hypothesis, the Pearson's correlation coefficient was used to measure the strength and the direction of the relationship (linear association/ correlation) between “The awareness level of BIM by the professionals” and “BIM barriers in the AEC industry in Gaza strip.” According to the results of the test that shown in Table (4.21), ―The awareness level of BIM by the professionals‖ is negatively related to ―BIM barriers in the AEC industry in Gaza strip‖, with a Pearson correlation coefficient of (r = -0.79) and the significance value is less than 0.05 (P-value < 0.05), and thus the relationship is statistically significant at α ≤ 0.05 (as indicated by the double asterisk after the coefficient). Consequently, the hypothesis H1 is accepted.

The closer (r) is to +1, the stronger the positive correlation, while the closer (r) is to -1, the stronger the negative correlation. According to that, it can be said that the relationship between ―The awareness level of BIM by the professionals‖ and ―BIM barriers in the AEC industry in Gaza strip‖ is a strong negative relationship because (r = -0.79). This result means, when one variable increases in the value, the second variable decreases in the value. In other words, increasing the awareness level of BIM by the professionals will reduce BIM barriers in the AEC industry in Gaza strip.

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As it turns out previously in this chapter, the results indicated that the level of knowledge regarding BIM by the professionals in the AEC industry in Gaza strip is very low. The results also showed that the lack of knowledge of BIM is a strong BIM barrier in the AEC industry in Gaza strip. The lack of knowledge regarding BIM has led to a slow uptake of this technology and ineffective management of adoption (Mitchell and Lambert, 2013; NBS, 2013).

Table (4.21): The correlation coefficient between the awareness level of BIM by the professionals and BIM barriers in the AEC industry in Gaza strip BIM barriers in the AEC Field Statistic industry in Gaza strip ** The awareness level of Pearson correlation (r) -0.79 P-value BIM by the professionals 0.00 in the AEC industry in Sig. (2-tailed) Gaza strip N 270 **. Correlation is significant at the 0.01 level (2-tailed).

4.7.2 The correlation between the importance of BIM functions and BIM barriers

H2: There is an inverse relationship, statistically significant at α ≤ 1.15, between the importance of BIM functions and BIM barriers in the AEC industry in Gaza strip.

To test the hypothesis, the Pearson's correlation coefficient was used to measure the strength and the direction of the relationship (linear association/ correlation) between ―the importance of BIM functions‖ and ―BIM barriers in the AEC industry in Gaza strip.‖ According to the results of the test that shown in Table (4.22), ―the importance of BIM functions‖ is negatively related to ―BIM barriers in the AEC industry in Gaza strip‖ with a Pearson correlation coefficient of (r = -0.36) and the significance value is less than 0.05 (P-value < 0.05), and thus the relationship is statistically significant at α ≤ 0.05 (as indicated by the double asterisk after the coefficient). Consequently, the hypothesis H2 is accepted.

The closer (r) is to +1, the stronger the positive correlation, while the closer (r) is to -1, the stronger the negative correlation. According to that, it can be said that the relationship between ―the importance of BIM functions‖ and ―BIM barriers in the AEC industry in Gaza strip‖ is an intermediate negative relationship because (r = -0.36). This result means, when one variable increases in the value, the second variable decreases in the value. In other words, when the importance as well the need of BIM functions increases for the professionals in the AEC industry in Gaza strip, this will reduce barriers to BIM adoption in the AEC industry in Gaza strip.

As it turns out previously in this chapter, the results indicated that the BIM functions are significantly important for the professionals in the AEC industry in Gaza strip. BIM has a broad range of the application in the design; construction; and operation process. BIM is transforming the way Architects, Engineers, contractors, and other building professionals work in the industry today (Baldwin, 2012; Mandhar and Mandhar, 2013).

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Table (4.22): The correlation coefficient between the importance of BIM functions and BIM barriers in the AEC industry in Gaza strip BIM barriers Field Statistic in the AEC industry in Gaza strip Pearson correlation (r) -0.36** The importance P-value 0.00 of BIM functions (Sig.) (2-tailed) Sample size (N) 270 **. Correlation is significant at the 0.01 level (2-tailed).

4.7.3 The correlation between the value of BIM benefits and BIM barriers

H3: There is an inverse relationship, statistically significant at α ≤ 1.15, between the value of BIM benefits and BIM barriers in the AEC industry in Gaza strip.

To test the hypothesis, the Pearson's correlation coefficient was used to measure the strength and the direction of the relationship (linear association/ correlation) between ―The value of BIM benefits‖ and ―BIM barriers in the AEC industry in Gaza strip.‖ According to the results of the test that shown in Table (4.23), ―The value of BIM benefits‖ is negatively related to ―BIM barriers in the AEC industry in Gaza strip‖, with a Pearson correlation coefficient of (r = -0.34) and the significance value is less than 0.05 (P-value < 0.05), and thus the relationship is statistically significant at α ≤ 0.05 (as indicated by the double asterisk after the coefficient). Consequently, the hypothesis H3 is accepted.

The closer (r) is to +1, the stronger the positive correlation, while the closer (r) is to -1, the stronger the negative correlation. According to that, it can be said that the relationship between ―the value of BIM benefits‖ and ―BIM barriers in the AEC industry in Gaza strip‖ is an intermediate negative relationship because (r = -0.34). This result means, when one variable increases in the value, the second variable decreases in the value. In other words, when the value of BIM benefits increases for the professionals in the AEC industry in Gaza strip, this will reduce barriers to BIM adoption in the AEC industry in Gaza strip.

As it turns out previously in this chapter, the results indicated that the BIM benefits are significantly valuable for the professionals in the AEC industry in Gaza strip. The use of BIM can increase the value of a building, shorten the project duration, provide reliable cost estimates, produce market-ready facilities, and optimize facility management and maintenance (Eastman et al., 2011; Aibinu and Venkatesh, 2013).

Table (4.23): The correlation coefficient between the value of BIM benefits and BIM barriers in the AEC industry in Gaza strip BIM barriers in the Field Statistic AEC industry in Gaza strip Pearson correlation (r) -0.34** The value of P-value 0.00 BIM benefits (Sig.) (2-tailed) Sample size (N) 270 **. Correlation is significant at the 0.01 level (2-tailed).

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4.7.4 The correlation between the awareness level of BIM by the professionals and the importance of BIM functions

H4: There is a positive relationship, statistically significant at α ≤ 1.15, between the awareness level of BIM by the professionals and the importance of BIM functions in the AEC industry in Gaza strip.

To test the hypothesis, the Pearson's correlation coefficient was used to measure the strength and the direction of the relationship (linear association/ correlation) between ―the awareness level of BIM by the professionals‖ and ―the importance of BIM functions.‖ According to the results of the test that shown in Table (4.24), ―the awareness level of BIM by the professionals‖ is positively related to ―the importance of BIM functions”, with a Pearson correlation coefficient of (r = 0.58) and the significance value is less than 0.05 (P-value < 0.05), and thus the relationship is statistically significant at α ≤ 0.05 (as indicated by the double asterisk after the coefficient). Consequently, the hypothesis H4 is accepted.

In other words, increasing the awareness level of BIM by the professionals will increase the importance of BIM functions for the professionals in the AEC industry in Gaza strip. As it turns out in the previous results in this chapter, there is a large lack of understanding of BIM (the core concepts of BIM) and its practical applications throughout the lifecycle of projects by the professionals in the AEC industry in Gaza strip.

Table (4.24): The correlation coefficient between the awareness level of BIM by the professionals in the AEC industry in Gaza strip and the importance of BIM functions Importance of BIM Field Statistic functions The awareness level of Pearson correlation (r) 0.58** BIM by the professionals P-value 0.00 in the AEC industry in (Sig.) (2-tailed) Gaza strip Sample size (N) 270 **. Correlation is significant at the 0.01 level (2-tailed).

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4.7.5 The correlation between the awareness level of BIM by the professionals and the value of BIM benefits

H5: There is a positive relationship, statistically significant at α ≤ 1.15, between the awareness level of BIM by the professionals and the value of BIM benefits in the AEC industry in Gaza strip.

To test the hypothesis, the Pearson's correlation coefficient was used to measure the strength and the direction of the relationship (linear association/ correlation) between ―the awareness level of BIM by the professionals‖ and ―the value of BIM benefits.‖ According to the results of the test that shown in Table (4.25), ―the awareness level of BIM by the professionals‖ is positively related to ―the value of BIM benefits”, with a Pearson correlation coefficient of r = 0.52 and the significance value is less than 0.05 (P-value < 0.05), and thus the relationship is statistically significant at α ≤ 0.05 (as indicated by the double asterisk after the coefficient). Consequently, the hypothesis H5 is accepted.

The closer (r) is to +1, the stronger the positive correlation, while the closer (r) is to -1, the stronger the negative correlation. According to that, it can be said that the relationship between ―the awareness level of BIM by the professionals‖ and ―the value of BIM benefits‖ is an intermediate positive correlation because (r = 0.52). This result means, when one variable increases in the value, the second variable also increases in the value.

In other words, increasing the awareness level of BIM by the professionals will enhance the value of BIM benefits for the professionals in the AEC industry in Gaza strip. As it turns out in the previous results in this chapter, there is a tremendous lack of knowledge about BIM and its unique capabilities by the professionals in the AEC industry in Gaza strip.

Table (4.25): The correlation coefficient between the awareness level of BIM by the professionals in the AEC industry in Gaza strip and the value of BIM benefits Value of Field Statistic BIM benefits The awareness level Pearson correlation (r) 0.52** of BIM by the P-value 0.00 professionals in the (Sig.) (2-tailed) AEC industry in Gaza 270 Sample size (N) strip **. Correlation is significant at the 0.01 level (2-tailed).

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4.7.6 Hypothesis related to respondents’ profiles (respondents analysis)

H6: There are statistically significant differences attributed to the demographic data of the respondents and the way of their work at the level of α ≤ 1.15 between the averages of their views on the subject of the application of BIM in the AEC industry in Gaza strip.

This hypothesis was to analyze the differences in the opinions of the respondents toward the investigation into BIM application in the AEC industry in Gaza strip due to many things. These things are (1) the gender, (2) the educational qualification, (3) the study place, (4) the specialization, (5) the nature of the workplace, (6) the location of the workplace, (7) the current field/ the present job, and (8) the years of the experience.

Independent samples t-test and One-way Analysis of Variance (ANOVA) test were used to find whether there were statistically significant differences between opinions of respondents or not. Scheffé's method (multiple-comparison procedure) was also used. All used tests are parametric tests based on the normal distribution.

4.7.6.1 An analysis taking into account the gender

Independent samples t-test provides a statistical test of whether the Means of two groups are equal or not. The critical value of t = 1.97, where the degree of freedom (df) = [N-2] = [270-2] = 268 (N is the sample size) at significance (probability) level (α) = 0.05 (Field, 2009; Weiers, 2011). And therefore, Independent samples t-test was used to test the differences among the opinions of the respondents taking into account their gender (male, and female).

As shown in Table (4.26), the P-value for the Levene‘s test is greater than 0.05 in each field and all fields together. Thus, the variances of the two groups (male, and female) are not significantly different (the groups are homogeneous). In addition, according to the results of the Independent samples t-test as shown in Table (4.26), the significance values for each field and all fields together are not significant (P-value > 0.05). The absolute values of t-test for each field and all fields together are also less than the critical value of t (1.97).

Thus, there are no statistically significant differences attributed to the gender of the respondents at the level of α ≤ 0.05 between the Means of their views on the subject of the investigation into BIM application in the AEC industry in Gaza strip.

Table (4.26): Results of Independent samples t-test regarding the gender of the respondents Levene's test for

equality of Mean test

Field variances

value

t P F P-value Male Female (Sig.) (N=222) (N=48) The awareness level of 3.11 0.08 -0.31 0.76 1.82 1.86 BIM by the professionals The importance of BIM 0.04 0.84 -1.04 0.30 3.61 3.73 functions

138

Table (4.26): Results of Independent samples t-test regarding the gender of the respondents Levene's test for

equality of Mean test

Field variances

value

t P F P-value Male Female (Sig.) (N=222) (N=48) The value of BIM benefits 0.03 0.86 -1.35 0.18 3.58 3.72

The strength of BIM barriers 0.28 0.60 -1.10 0.27 3.57 3.69

All fields 0.07 0.80 -1.41 0.16 3.35 3.47 Critical value of t: at degree of freedom (df) = [N-2] = [270-2] = 268 and at significance (Probability) level 0.05 equals “1.97”. *. The Mean difference is significant at the 0.05 level

4.7.6.2 An analysis taking into account the educational qualification

One-way Analysis of Variance (ANOVA)/ (F-test) provides a parametric statistical test of whether the Means of several groups (more than two) are equal or not (by using the F-ratio). The critical value of F at degree of freedom (df) = [(K-1), (N-K)] at the significance (probability) level (α) = 0.05 (Field, 2009; Weiers, 2011). And therefore, One-way ANOVA was used to test the differences among the opinions of the respondents taking into account their educational qualification (Bachelor, Master, or PhD).

According to the results of the test, as shown in Table (4.27), the P-value for the Levene‘s test is greater than 0.05 in each field of the four fields as well as all fields together. Thus, the variances of the groups are not significantly different (the groups are homogeneous). Regarding F-test, the significance values for each field of the four fields as well as all fields together are not significant (P-value > 0.05). The values of F-test in each field of the four fields as well as all fields together are also less than the critical value of F (3.03).

Thus, there are no statistically significant differences attributed to the educational qualification of the respondents at the level of α ≤ 0.05 between the Means of their views on the subject of the investigation into BIM application in the AEC industry in Gaza strip.

Table (4.27): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the educational qualification of the respondents Test of homogeneity of Mean

variances test

Field

value

- -

Levene P- (Sig.) Bachelor Master PhD

Statistic value (N=195) (N=71) (N=4) (Sig.) The awareness level of 2.17 0.12 1.62 0.20 1.78 1.97 1.86 BIM by the professionals The importance of BIM 0.30 0.74 2.32 0.10 3.58 3.78 3.70 functions

139

Table (4.27): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the educational qualification of the respondents Test of homogeneity of Mean

variances test

Field

value

- -

Levene P- (Sig.) Bachelor Master PhD

Statistic value (N=195) (N=71) (N=4) (Sig.) The value of BIM 0.91 0.40 1.27 0.28 3.57 3.69 3.88 benefits The strength of BIM 0.87 0.42 0.41 0.66 3.57 3.64 3.43 barriers All fields 0.76 0.47 1.93 0.15 3.34 3.48 3.46 Critical value of F: at degree of freedom (df) = [(K-1), (N-K)] = [(3-1), (270-2)] = [2,267] and at significance (Probability) level 0.05 equals “3.03”. *. The Mean difference is significant at the 0.05 level.

4.7.6.3 An analysis taking into account the study place

One-way Analysis of Variance (ANOVA)/ (F-test) provides a parametric statistical test of whether the Means of several groups (more than two) are equal or not (by using the F-ratio). The critical value of F at degree of freedom (df) = [(K-1), (N-K)] at the significance (probability) level (α) = 0.05 (Field, 2009; Weiers, 2011). And therefore, One-way ANOVA was used to test the differences among the opinions of the respondents taking into account their study place (Gaza strip, the West Bank, or outside Palestine).

According to the results of the test, as shown in Table (4.28), the P-value for the Levene‘s test is greater than 0.05 in each field of the four fields as well as all fields together. Thus, the variances of the groups are not significantly different (the groups are homogeneous). Regarding F-test, the significance values for the second field (the importance of BIM functions), as well as all fields together, are significant (P-value < 0.05). The values of F-test for the second field and all fields together are also greater than the critical value of F (3.03).

Thus, there are statistically significant differences attributed to the study place of the respondents at the level of α ≤ 0.05 between the Means of their views on the subject of ―the importance of BIM functions‖ as well as the subject of ―the investigation into BIM application in the AEC industry in Gaza strip.‖

And therefore, Scheffe test was used for multiple comparisons between the Means of the opinions of the respondents taking into account their study place (Field, 2009; Weiers, 2011). According to the results of the test as shown in Table (4.29), there is a difference between the averages of the opinions of the respondents who studied ―outside Palestine,‖ and the respondents who studied in ―Gaza strip‖ about the field of ―the importance of BIM functions‖ in favor of the respondents who studied ―outside Palestine.‖ Table (4.30) shows that there is a difference in all fields of the subject of ―the investigation into BIM application in the AEC industry in Gaza strip.‖ The difference here is also between the Means of the opinions of the respondents who studied in

140

―outside Palestine,‖ and the respondents who studied in ―Gaza strip‖ in favor of the respondents who studied in ―outside Palestine.‖

Table (4.28): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the study place of the respondents Test of homogeneity of Mean

variances test Field

- The

value

(Sig.) Gaza Outside

F P

Levene P-value West

strip Palestine statistic (Sig.) Bank (N=196) (N=65) (N=9) The awareness level of 0.81 0.45 2.73 0.07 1.77 2.15 1.97 BIM by the professionals The importance of BIM 1.57 0.21 3.46 0.03 3.57 3.69 3.82 functions The value of BIM benefits 1.67 0.19 2.10 0.12 3.55 3.71 3.74 The strength of BIM 0.34 0.71 0.93 0.39 3.56 3.74 3.67 barriers All fields 0.76 0.47 3.63 0.03 3.32 3.51 3.51 Critical value of F: at degree of freedom (df) = [(K-1), (N-K)] = [(3-1), (270-2)] = [2,267] and at significance (Probability) level 0.05 equals “3.03”. *. The Mean difference is significant at the 0.05 level.

Table (4.29): Results of Scheffe test for multiple comparisons due to the study place of the respondents for the field of “The importance of BIM functions” Outside Mean difference Gaza strip The West Bank Palestine Gaza strip -0.13 -0.26* The West Bank 0.13 -0.13 Outside Palestine 0.26* 0.13

Table (4.30): Results of Scheffe test for multiple comparisons due to the study place of the respondents for all the fields of “the investigation into BIM application in the AEC industry in Gaza strip” Outside Mean difference Gaza strip The West Bank Palestine Gaza strip -0.19 -0.19* The West Bank 0.19 0.00 Outside Palestine 0.19* 0.00

4.7.6.4 An analysis taking into account the specialization

One-way Analysis of Variance (ANOVA)/ (F-test) provides a parametric statistical test of whether the Means of several groups (more than two) are equal or not (by using the F-ratio). The critical value of F at degree of freedom (df) = [(K-1), (N-K)] at significance (probability) level (α) = 0.05 (Field, 2009; Weiers, 2011). And therefore, One-way ANOVA was used to test the differences among the opinions of the respondents taking into account their specialization (Architect, Civil Engineer,

141

Electrical Engineer, Mechanical Engineer, or any other related specialization in the AEC industry).

According to the results of the test, as shown in Table (4.31), the P-value for the Levene‘s test is greater than 0.05 in each field of the four fields as well as all fields together. Thus, the variances of the groups are not significantly different (the groups are homogeneous). Regarding F-test, the significance values for the first field (the awareness level of BIM by the professionals) as well as the fields together are significant (P-value < 0.05). The values of F-test for the first field and all fields together are also greater than the critical value of F (2.41).

Thus, there are statistically significant differences attributed to the study place of the respondents at the level of α ≤ 0.05 between the Means of their views about ―the awareness level of BIM by the professionals‖ as well as the subject of ―the investigation into BIM application in the AEC industry in Gaza strip.‖

And therefore, Scheffe test was used for multiple comparisons between the Means of the opinions of the respondents taking into account their specialization (Field, 2009; Weiers, 2011). According to the results of the test as shown in Table (4.32), there is a difference between the averages of the opinions of the respondents who are ―Civil Engineers,‖ and the respondents who are ―Electrical Engineers‖ about the field of ―the awareness level of BIM by the professionals‖ in favor of the respondents who are ―Civil Engineers.‖

Table (4.33) shows that there is a difference between the averages of the opinions of the respondents about all fields of ―the investigation into BIM application in the AEC industry in Gaza strip.‖ The difference is between the Means of the opinions of the respondents who are ―Architects,‖ and the respondents who are ―Electrical Engineers‖ in favor of the respondents who are ―Architects.‖ There is also a difference between the Means of the opinions of the respondents who are ―Civil Engineers,‖ and the respondents who are ―Electrical Engineers‖ in favor of the respondents who are ―Civil Engineers.‖

Table (4.31): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the specialization of the respondents Test of homogeneity of Mean

variances

test

Field

value

Civil

(Sig.)

Other

(N=3)

Levene Levene

(N=41) (N=14)

statistic

(N= 83) (N=

(N=129)

Architect

Electrical

Mechanical The awareness level of 0.92 0.45 4.01 0.00 1.80 1.97 1.45 1.79 1.85 BIM by the professionals The importance of BIM 3.18 0.10 1.75 0.14 3.62 3.72 3.42 3.46 3.77 functions The value of BIM 1.03 0.39 1.90 0.11 3.64 3.64 3.40 3.54 4.28 benefits The strength of BIM 1.71 0.15 1.30 0.27 3.66 3.62 3.46 3.31 3.61 barriers

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Table (4.31): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the specialization of the respondents Test of homogeneity of Mean

variances

test

Field

value

Civil

(Sig.)

Other

(N=3)

Levene Levene

(N=41) (N=14)

statistic

(N= 83) (N=

(N=129)

Architect

Electrical

Mechanical

All fields 1.83 0.12 2.73 0.03 3.40 3.44 3.17 3.23 3.67 Critical value of F: at degree of freedom (df) = [(K-1), (N-K)] = [(5-1), (270-5)] = [4,265] and at significance (Probability) level 0.05 equals “2.41”. *. The Mean difference is significant at the 0.05 level.

Table (4.32): Results of Scheffe test for multiple comparisons due to the specialization of the respondents for the field of “The awareness level of BIM by the professionals” Mean difference Architect Civil Electrical Mechanical Other Architect -0.17 0.35 0.00 -0.05 Civil 0.17 0.53* 0.18 0.12 Electrical -0.35 -0.53* -0.35 -0.40 Mechanical 0.00 -0.18 0.35 -0.06 Other 0.05 -0.12 0.40 0.06

Table (4.33): Results of Scheffe test for multiple comparisons due to the specialization of the respondents for all fields of “The investigation into BIM application in the AEC industry in Gaza strip” Mean difference Architect Civil Electrical Mechanical Other Architect -0.04 0.23* 0.16 -0.27 Civil 0.04 0.27* 0.20 -0.24 Electrical -0.23* -0.27* -0.07 -0.51 Mechanical -0.16 -0.20 0.07 -0.44 Other -0.16 0.24 0.51 0.44

4.7.6.5 An analysis taking into account the nature of the workplace

One-way Analysis of Variance (ANOVA)/ (F-test) provides a parametric statistical test of whether the Means of several groups (more than two) are equal or not (by using the F-ratio). The critical value of F at degree of freedom (df) = [(K-1), (N-K)] at significance (probability) level (α) = 0.05 (Field, 2009; Weiers, 2011). And therefore, One-way ANOVA was used to test the differences among opinions of respondents taking into account the nature of their workplace (Consultant, NGOs, Contractor, Governmental, or other workplaces).

According to the results of the test, as shown in Table (4.34), the P-value for the Levene‘s test is greater than 0.05 in each field of the four fields as well as all fields together. Thus, the variances of the groups are not significantly different (the groups are homogeneous). Regarding F-test, the significance values for the first field ―the awareness level of BIM by the professionals,‖ the second filed ―the importance of BIM functions,‖ and all fields together are significant (P-value < 0.05). The value of F-test

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for the first field, the second field, and all fields together are also greater than the critical value of F (2.41).

Thus, there are statistically significant differences attributed to the nature of the workplace of the respondents at the level of α ≤ 0.05 between the Means of their views about ―the awareness level of BIM by the professionals,‖ ―the importance of BIM functions,‖ and the subject of ―the investigation into BIM application in the AEC industry in Gaza strip.‖ And therefore, Scheffe test was used for multiple comparisons between the Means of the opinions of the respondents taking into account their specializations (Field, 2009; Weiers, 2011). According to the results of the test as shown in Table (4.35), there is a difference between the averages of the opinions of the respondents who are working for ―NGOs,‖ and the respondents who are working for ―other‖ workplaces (according to Table (4.1) of the respondent‘s demographic data, the ―other‖ workplace was the Engineers Association) about the field of ―the awareness level of BIM by the professionals‖ in favor of the respondents who are working for ―NGOs.‖

According to the results of the test as shown in Table (4.36), there is also a difference between the averages of the opinions of the respondents who are working for ―NGOs,‖ and the respondents who are working for each of contractor, governmental, and other workplaces (Engineers Association) about the field of ―the importance of BIM functions‖ in favor of the respondents who are working for ―NGOs.‖

Table (4.37) shows that there is a difference between the averages of the opinions of the respondents about all fields of ―the investigation into BIM application in the AEC industry in Gaza strip.‖ The difference is between the Means of the opinions of the respondents who are working for ―NGOs,‖ and the respondents who are working for each of the governmental, and other workplaces (Engineers Association) in favor of respondents who are working for ―NGOs.‖

Table (4.34): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the nature of the workplace for the respondents Test of homogeneity Mean

of variances

test

Field

value

(Sig.)

(N=29)

NGOs

Levene Levene

(N=81) (N=42) (N=66) (N=52)

statistic

value

Contractor

Consultant Consultant

Other

Governmental

The awareness level of BIM 0.17 0.95 3.60 0.01 1.90 2.12 1.80 1.71 1.49 by the professionals The importance of BIM 1.35 0.25 2.69 0.03 3.66 3.91 3.60 3.48 3.50 functions The value of BIM benefits 2.04 0.09 2.12 0.08 3.65 3.79 3.62 3.51 3.36 The strength of BIM barriers 0.70 0.59 2.14 0.08 3.64 3.82 3.53 3.50 3.44

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Table (4.34): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the nature of the workplace for the respondents Test of homogeneity Mean

of variances

test

Field

value

(Sig.)

(N=29)

NGOs

Levene Levene

(N=81) (N=42) (N=66) (N=52)

statistic

value

Contractor

Consultant Consultant

Other

Governmental

All fields 2.95 0.20 4.21 0.00 3.42 3.61 3.35 3.26 3.17 Critical value of F: at degree of freedom (df) = [(K-1), (N-K)] = [(5-1), (270-5)] = [4,265] and at significance (Probability) level 0.05 equals “2.41”. *. The Mean difference is significant at the 0.05 level.

Table (4.35): Results of Scheffe test for multiple comparisons due to the nature of the workplace of the respondents for the field of “The awareness level of BIM by the professionals” Mean difference Consultant NGOs Contractor Governmental Other Consultant -0.22 0.09 0.19 0.40 NGOs 0.22 0.31 0.41 0.62* Contractor -0.09 -0.31 0.10 0.31 Governmental -0.19 -0.41 -0.10 0.21 Other -0.40 -0.62* -0.31 -0.21

Table (4.36): Results of Scheffe test for multiple comparisons due to the nature of the workplace of the respondents for the field of “The importance of BIM functions” Mean difference Consultant NGOs Contractor Governmental Other Consultant -0.25 0.06 0.18 0.16 NGOs 0.25 0.31* 0.43* 0.41* Contractor -0.06 -0.31* 0.12 0.10 Governmental -0.18 -0.43* -0.12 -0.02 Other -0.16 -0.41* -0.10 0.02

Table (4.37): Results of Scheffe test for multiple comparisons due to the nature of the workplace of the respondents for all fields of “The investigation into BIM application in the AEC industry in Gaza strip” Mean difference Consultant NGOs Contractor Governmental Other Consultant -0.19 0.07 0.16 0.25 NGOs 0.19 0.25 0.34* 0.44* Contractor -0.07 -0.25 0.09 0.18 Governmental -0.16 -0.34* -0.09 0.09 Other -0.25 -0.44* -0.18 -0.09

4.7.6.6 An analysis taking into account the location of the workplace

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One-way ANOVA was used to test the differences among the opinions of the respondents taking into account the location of their workplace (North, Gaza, Middle, KhanYounis, and Rafah).

According to the results of the test, as shown in Table (4.38), the P-value for the Levene‘s test is greater than 0.05 in each field of the four fields as well as all fields together. Thus, the variances of the groups are not significantly different (the groups are homogeneous). Regarding F-test, the significance value for the first field ―the awareness level of BIM by the professionals‖ is significant (P-value < 0.05). The value of F-test for the first field is also greater than the critical value of F (2.41).

Thus, there are statistically significant differences attributed to the location of the workplace of the respondents at the level of α ≤ 0.05 between the Means of their views about ―the awareness level of BIM by the professionals.‖ And therefore, Scheffe test was used for multiple comparisons between the Means of the opinions of the respondents taking into account their location of the workplace (Field, 2009; Weiers, 2011). According to the results of the test as shown in Table (4.39), there is a difference between the averages of the opinions of the respondents who are working in ―Gaza,‖ and the respondents who are working in ―Rafah‖ about the field of ―the awareness level of BIM by the professionals‖ in favor of the respondents who are working in ―Gaza.‖

Table (4.38): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the location of the workplace of the respondents Test of homogeneity Mean

of variances

test

Field

value

Gaza Gaza

(Sig.)

North

Rafah

(N=8)

Middle Middle

Levene Levene

(N=21) (N=14) (N=23)

statistic

(N=204)

KhanYounis KhanYounis The awareness level of 2.92 0.20 2.64 0.03 1.84 1.89 1.46 1.83 1.41 BIM by the professionals The importance of BIM 0.48 0.75 1.38 0.24 3.74 3.66 3.62 3.54 3.33 functions The value of BIM 0.04 1.00 0.98 0.42 3.73 3.62 3.63 3.53 3.37 benefits The strength of BIM 2.29 0.06 1.73 0.14 3.72 3.57 3.81 3.28 3.79 barriers All fields 0.19 0.94 1.06 0.38 3.48 3.39 3.39 3.25 3.21 Critical value of F: at degree of freedom (df) = [(K-1), (N-K)] = [(5-1), (270-5)] = [4,265] and at significance (Probability) level 0.05 equals “2.41”. *. The Mean difference is significant at the 0.05 level.

146

Table (4.39): Results of Scheffe test for multiple comparisons due to the location of the workplace of the respondents for the field of “The awareness level of BIM by the professionals” Mean difference North Gaza Middle KhanYounis Rafah North -0.05 0.38 0.01 0.42 Gaza 0.05 0.43 0.06 0.48* Middle -0.38 -0.43 -0.37 0.05 KhanYounis -0.01 -0.06 0.37 0.41 Rafah -0.42 -0. 48* -0.05 -0.41

4.7.6.7 An analysis taking into account the current field/ the present job

One-way Analysis of Variance (ANOVA)/ (F-test) provides a parametric statistical test of whether the Means of several groups (more than two) are equal or not (by using the F-ratio). The critical value of F at degree of freedom (df) = [(K-1), (N-K)] at significance (probability) level (α) = 0.05 (Field, 2009; Weiers, 2011). And therefore, One-way ANOVA was used to test the differences among the opinions of the respondents taking into account their current field/ present job (Designer, Supervisor, Site Engineer, Projects Manager, or other related jobs such as office Engineer).

According to the results of the test, as shown in Table (4.40), the P-value for the Levene‘s test is greater than 0.05 in each field of the four fields as well as all fields together. Thus, the variances of the groups are not significantly different (the groups are homogeneous). Regarding F-test, the significance values for each field of the four fields, as well as all fields together, are not significant (P-value > 0.05). The values of F-test in each field of the four fields as well as all fields together are also less than the critical value of F (2.41).

Thus, there are no statistically significant differences attributed to the current field/ present job of the respondents at the level of α ≤ 0.05 between the Means of their views about the subject of ―the investigation into BIM application in the AEC industry in Gaza strip.‖

Table (4.40): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the current field/ present job of the respondents Test of homogeneity Mean

of variances

test

Field

value

Site

anager anager

(Sig.)

Other

ngineer

Levene Levene

(N=73) (N=64) (N=54) (N=33) (N=46)

Statistic

Projects Projects

Designer E

Supervisor The awareness level of BIM by 1.77 0.14 2.20 0.07 1.75 1.99 1.92 1.85 1.60 professionals The importance of 1.63 0.17 2.26 0.06 3.59 3.72 3.61 3.87 3.43 BIM functions The value of BIM 3.63 0.10 0.74 0.57 3.60 3.66 3.59 3.71 3.48 benefits The strength of BIM 0.71 0.58 0.92 0.45 3.67 3.58 3.52 3.70 3.49 barriers

147

Table (4.40): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the current field/ present job of the respondents Test of homogeneity Mean

of variances

test

Field

value

Site

anager anager

(Sig.)

Other

ngineer

Levene Levene

(N=73) (N=64) (N=54) (N=33) (N=46)

Statistic

Projects

Designer E

Supervisor

All fields 2.33 0.06 1.72 0.15 3.37 3.43 3.36 3.50 3.22 Critical value of F: at degree of freedom (df) = [(K-1), (N-K)] = [(5-1), (270-5)] = [4,265] and at significance (Probability) level 0.05 equals “2.41”. *. The Mean difference is significant at the 0.05 level.

4.7.6.8 An analysis taking into account the years of the experience

One-way Analysis of Variance (ANOVA)/ (F-test) provides a parametric statistical test of whether the Means of several groups (more than two) are equal or not (by using the F-ratio). The critical value of F: at degree of freedom (df) = [(K-1), (N-K)] at significance (probability) level (α) = 0.05 (Field, 2009; Weiers, 2011). And therefore, One-way ANOVA was used to test the differences among the opinions of the respondents taking into account their years of experience (Less than 5 years, From 5 to less than 10 years, and 10 years and more).

According to the results of the test, as shown in Table (4.41), the P-value for the Levene‘s test is greater than 0.05 in each field of the four fields as well as all fields together. Thus, the variances of the groups are not significantly different (the groups are homogeneous). Regarding F-test, the significance values for the first field (the awareness level of BIM by the professionals), the second field (the importance of BIM functions), the third field (the value of BIM benefits) and also all fields together are significant (P-value < 0.05). The value of F-test for each of the first field, the second and the third fields as well as all fields together are also greater than the critical value of F (3.03).

Thus, there are statistically significant differences attributed to the years of the experience of the respondents at the level of α ≤ 0.05 between the Means of their views on ―the awareness level of BIM by the professionals‖, ―the importance of BIM functions‖, ―the value of BIM benefits‖, and the subject of ―the investigation into BIM application in the AEC industry in Gaza strip‖. And therefore, Scheffe test was used for multiple comparisons between the Means of the opinions of the respondents taking into account their years of experience (Field, 2009; Weiers, 2011). According to the results of the test as shown in Table (4.42), there is a difference between the averages of the opinions of the respondents who have experience ranging ―From 5 to less than 10 years‘ experience,‖ and the respondents who have ―Less than 5 years‘ experience‖ about the field of ―the awareness level of BIM by the professionals‖ in favor of the respondents who have experience ranging ―From 5 to less than 10 years.‖ There is also a difference between the Means of the opinions of the respondents who have ―10 years‘ experience and more,‖ and the respondents who have

148

―Less than 5 years‘ experience‖ in favor of the respondents who have ―10 years‘ experience and more.‖

Regarding the field of ―the importance of BIM functions, ‖ Table (4.43) shows that there is a difference between the averages of the opinions of the respondents who have ―10 years‘ experience and more,‖ and the respondents who have ―Less than 5 years‘ experience ‖ in favor of the respondents who have ―10 years‘ experience and more.‖

Table (4.44) shows that there is a difference between the averages of the opinions of the respondents who have ―10 years‘ experience and more‖, and the respondents who have ―Less than 5 years‘ experience‖ about the field of ―the value of BIM benefits‖ in favor of the respondents who have ―10 years‘ experience and more.‖

Table (4.45) shows that there is a difference between the averages of the opinions of the respondents about all fields of ―the investigation into BIM application in the AEC industry in Gaza strip.‖ The difference is between the Means of the opinions of the respondents who have ―10 years‘ experience and more,‖ and the respondents who have ―Less than 5 years‘ experience‖ in favor of the respondents who have ―10 years‘ experience and more.‖

Table (4.41): One-way Analysis of Variance (ANOVA)/ (F-test) results regarding the years of experience of the respondents Test of homogeneity of Mean

variances

test

Field From 5 to 10 years

value -

- Less than F

P less than and

5 years

value -

(Sig.) 10 years more

Levene Levene

statistic P

(N=95)

(N=88) (N=87) The awareness level of BIM by the 1.23 0.29 6.62 0.00 1.61 1.99 1.91 professionals The importance of 1.26 0.29 5.95 0.00 3.48 3.60 3.83 BIM functions The value of BIM 4.51 0.10 6.18 0.00 3.45 3.58 3.79 benefits The strength of BIM 0.62 0.54 1.05 0.35 3.51 3.61 3.65 barriers All fields 2.63 0.07 7.16 0.00 3.23 3.39 3.52 Critical value of F: at degree of freedom (df) = [(K-1), (N-K)] = [(3-1), (270-2)] = [2,267] and at significance (Probability) level 0.05 equals “3.03”. *. The Mean difference is significant at the 0.05 level.

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Table (4.42): Results of Scheffe test for multiple comparisons due to the years of experience of the respondents for the field of “The awareness level of BIM by the professionals” From 5 to less 10 years Less than Mean difference than 10 years and more 5 years

Less than 5 years -0.38* -0.30* From 5 to less than 10 years 0.38* 0.08 10 years and more 0.30* -0.08

Table (4.43): Results of Scheffe test for multiple comparisons due to the years of experience of the respondents for the field of “The importance of BIM functions” From 5 to less 10 years Less than Mean difference than 10 years and more 5 years

Less than 5 years -0.12 -0.35* From 5 to less than 10 years 0.12 -0.22 10 years and more 0.35* 0.22

Table (4.44): Results of Scheffe test for multiple comparisons due to the years of experience of the respondents for the field of “The value of BIM benefits” From 5 to less 10 years Less than Mean difference than 10 years and more 5 years

Less than 5 years -0.13 -0.34* From 5 to less than 10 years 0.13 -0.22 10 years and more 0.34* 0.22

Table (4.45): Results of Scheffe test for multiple comparisons due to the study place of the respondents for all fields of “The investigation into BIM application in the AEC industry in Gaza strip” From 5 to less 10 years Less than Mean difference than 10 years and more 5 years

Less than 5 years -0.15 -0.28* From 5 to less than 10 years 0.15 -0.13 10 years and more 0.28* 0.13

Based on the previous findings of the sixth hypothesis (which has been broken down into eight sections), it has appeared that the hypothesis has been rejected in respect of three sections (the gender, the educational qualification, and the current field/ the present job of the respondents). The same hypothesis has been accepted in respect of the rest five sections (the study place, the specialization, the nature of the workplace, the location of the workplace, and the years of experience of the respondents).

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Chapter 5

Chapter 5: Conclusions and recommendations

This chapter summarizes the study and aims to provide recommendations and conclusions for the adoption of Building Information Modeling (BIM) in the Architecture, Engineering, and Construction (AEC) industry in Gaza strip. This chapter also includes research benefits to the knowledge as well the AEC industry and suggests areas of future research after a review of the limitations of this study. By revisiting the research objectives and key findings, an overview discussed to assess the extent to which the research objectives were met.

5.1 Summary of the research

An investigation into the prospects, benefits and barriers to successful BIM-based workflow adoption in the AEC industry in Gaza strip was conducted. An extensive review of the literature was carried out to achieve the aim of the study. The purpose of the research was to develop a clear understanding about BIM for identifying the different factors which provide useful information to consider adopting BIM technology in projects by the practitioners in the AEC industry in Gaza strip. The results of 270 collected questionnaires were analyzed quantitatively and then presented by using an ―interpretive-descriptive‖ method for qualitative data analysis, which contains tabulation, bar chart, pie chart, and graph.

5.2 Conclusions of the research objectives, questions, and hypotheses

In achieving the aim of the research, five primary objectives have been outlined and made through the findings of the analyzed collected questionnaires. These objectives are related to the research questions that were developed to increase one‘s knowledge and familiarity with the subject. The outcomes were found as following:

5.2.1 Outcomes related to objective one

 The objective was: To assess the awareness level of BIM by the professionals in the AEC industry in Gaza strip. This objective is related to the following research question:

. The first research question: What is the level of the awareness of BIM by the professionals in the AEC industry in Gaza strip?

The study findings of RII test indicated that the awareness level of BIM by the professionals in the AEC industry in Gaza strip is very low. Most of the practitioners of the AEC industry have not heard about BIM and did not realize the concept of it. The findings showed that the study place affects the degree of the knowledge of BIM. An enormous percentage of the total respondents who had studied in Gaza strip (80%) had never taken courses about BIM in their universities. 77% of the total respondents who had studied in the West Bank had the same answer. The lowest ratio was for the respondents who had studied outside Palestine with 75% of the total of them whose had never taken courses about BIM in their universities. There is an absence of interest of educating BIM through courses in universities.

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Furthermore, according to the respondents, BIM is used individually in a level of negligible, but not on companies‘ level. It does not be applied professionally, and thus, the professionals do not get the full benefits of BIM, where they are only using some advantages of BIM software such as the advantages of Revit in the design phase.

When the respondents were asked about their way of implementing work in the first part of the questionnaire, results proved that the use of the 3D programs in performing works by the professionals is very little. 3D programs are usually used only by Architects for the purpose of the exterior design of the building or the purpose of the interior design of the building and according to the request of the owner. It was found from results that the more commonly programs used by the respondents to carry out projects in the AEC industry are ―Excel‖ and ―AutoCAD (2D)‖, which confirms the result in the previous question as it shows a lack of the use of the (3D) programs. 5.2.2 Outcomes related to objective two

 The objective was: To identify the top BIM functions that would convince the professionals for adopting BIM in the AEC industry in Gaza strip. This objective is related to the following research question:

. The second research question: Are the functions of BIM important from the viewpoint of professionals (according to the need for these functions) in the AEC industry in Gaza strip?

The study findings of RII test indicated that BIM functions are significantly required and necessary for the professionals in the AEC industry in Gaza strip. Some functions of BIM were more important than others for the professionals. BIM functions that got top ranking according to the overall respondents are as follow: (1) Interoperability and translation of information (F16); (2) Change Management (F3); (3) Functional simulations to choose the best solution (F2); (4) Three-dimensional (3D) modeling and visualization (F1); and (5) Safety planning and monitoring on-site (F8). In addition to that, factor analysis has compiled BIM functions in three components, which are: (1) Data management and utilization in planning; operation, and maintenance; (2) Visualized design and analysis; and (3) Construction and operation.

5.2.3 Outcomes related to objective three

 The objective was: To identify the top BIM benefits that would convince the professionals for adopting BIM in the AEC industry in Gaza strip. This objective is related to the following research question:

. The third research question: Are the benefits of BIM valuable from the standpoint of the professionals (according to the need for these functions) in the AEC industry in Gaza strip?

The study findings of RII test indicated that BIM benefits are significantly valuable for the professionals in the AEC industry in Gaza strip. Some benefits of BIM were more valuable than others for the professionals. BIM benefits that got top ranking according to the overall respondents are as follow: (1) Enhance design team collaboration

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(Architectural, Structural, Mechanical, and Electrical Engineers) (BE 3); (2) Improve design quality (BE 4); and (3) Improve sustainable design and lean design (BE 5).

Factor analysis has also compiled BIM benefits in four components, which are: (1) Controlled whole-life costs and environmental data; (2) More effective processes; (3) Design and quality improvement; and (4) Decision-making support/ Better customer service.

5.2.4 Outcomes related to objective four

 The objective was: To investigate and rank the top BIM barriers which face the adoption of BIM in the AEC industry in Gaza strip. This objective is related to the following research question:

. The fourth research question: Are BIM barriers affecting the adoption of BIM in the AEC industry in Gaza strip?

The study findings of RII test demonstrated that BIM barriers are substantially affecting the adoption of BIM in the AEC industry in Gaza strip. The top barriers to BIM adoption, which got top ranking according to the overall respondents are as follow: (1) Lack of the awareness of BIM by stakeholders (BA 2); (2) Lack of knowledge of how to apply BIM software (BA 3); and (3) Lack of the awareness of the benefits that BIM can bring to Engineering offices, companies, and projects (BA 5).

Factor analysis has also compiled BIM barriers in four components, which are: (1) Lack of BIM interest; (2) Organization-wide resistance to change workflows; (3) Lack of knowledge about BIM and cost of implementing; and (4) Cultural barriers toward adopting new technology and training requirements.

5.2.5 Outcomes related to objective five

 The objective was: To study some hypotheses that might help to find solutions for adopting BIM in the AEC industry in Gaza strip. This objective is related to the following research questions:

. The fifth research question: What is the effect of the awareness level of BIM by the professionals on the reduction of BIM barriers in the AEC industry in Gaza strip? . The sixth research question: What is the effect of the importance of BIM functions on the reduction of BIM barriers in the AEC industry in Gaza strip? . The seventh research question: What is the effect of the value of BIM benefits on the reduction of BIM barriers in the AEC industry in Gaza strip? . The eighth research question: What is the effect of the awareness level of BIM by the professionals on increasing the importance of BIM functions in the AEC industry in Gaza strip? . The ninth research question: What is the effect of the awareness level of BIM by the professionals on increasing the value of BIM benefits in the AEC industry in Gaza strip?

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. The tenth research question: Are there differences in the answers of the respondents depending on the demographic data of the respondents?

To achieve this objective, five hypotheses were tested through applying the Pearson product-moment correlation coefficient (Pearson's correlation coefficient). They all have been accepted. As for the sixth and last hypothesis, it was divided into eight parts. The findings of the hypotheses were as follow:

At first (for H1), Pearson correlation analysis asserted that there is a strong negative relationship between ―the awareness level of BIM by the professionals‖ and ―BIM barriers in the AEC industry in Gaza strip.‖ Thus, the increasing the awareness level of BIM by the professionals will reduce BIM barriers in the AEC industry in Gaza strip.

For (H2 and H3), Pearson correlation analysis proved that there is an intermediate negative relationship between ―the importance of BIM functions‖ and ―BIM barriers in the AEC industry in Gaza strip.‖ The same relationship is also between ―the value of BIM benefits,‖ and ―BIM barriers in the AEC industry in Gaza strip.‖ Accordingly, increasing the importance of BIM functions reduces barriers to BIM adoption in the AEC industry in Gaza strip. The same thing will happen when increasing the value of BIM benefits.

Finally (for H4 and H5), Pearson correlation analysis substantiated that there is an intermediate positive relationship between ―the awareness level of BIM by professionals‖ and both of ―the importance of BIM functions,‖ and ―the value of BIM benefits.‖ Accordingly, increasing the awareness level of BIM by the professionals will increase the importance of BIM functions and the value of BIM benefits for the professionals in the AEC industry in Gaza strip.

The (H6) was about the differences in the opinions of the respondents toward the investigation into BIM application in the AEC industry in Gaza strip due to the gender, the educational qualification, the study place, the specialization, the nature of the workplace, the location of the workplace, the current field/ the present job, and the years of the experience. The outcomes were as follow:

 The Independent samples t-test proved that there are no statistically significant differences attributed to the gender of the respondents at the level of α ≤ 0.05 between the Means of their views on the subject of the application of BIM in the AEC industry in Gaza strip. In the same context, One-way ANOVA confirmed that there are no statistically significant differences associated to each of the educational qualification and the current field/ the present job of the respondents at the level of α ≤ 0.05 between the Means of their views on the same subject. According to that, the hypothesis has been rejected regarding these four parts.  In contrast, One-way ANOVA asserted that there are significant differences attributed to each of the study place, the specialization, the nature of the workplace, the location of the workplace, and the years of the experience of the respondents at the level of α ≤ 0.05 between the Means of their views on the subject of the application of BIM in the AEC industry in Gaza strip. Accordingly, Scheffe test was used for multiple comparisons between the Means of the opinions of the respondents taking into account this information related to them. As a result, the hypothesis has been accepted regarding these five parts.

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Table (5.1) summarized the findings of the study according to the research objectives, the key research questions, and the research hypotheses as represented above.

Table (5.1): summary of the findings of the study Research objectives Key research questions Research hypotheses Findings 1. To assess the RQ1: What is the level of -  The study findings of RII test indicated that the awareness level of the awareness of BIM by the awareness level of BIM by the professionals in the BIM by the professionals in the AEC AEC industry in Gaza strip is very low. Most of the professionals in the industry in Gaza strip? practitioners of the AEC industry have not heard AEC industry in about BIM and did not realize the concept of it. Gaza strip. 2. To identify the top RQ2: Are the functions of -  The study findings of RII test indicated that BIM BIM functions that BIM important from the functions are significantly required and necessary for would convince the viewpoint of the the professionals in the AEC industry in Gaza strip. professionals for professionals (according to  BIM functions that got top ranking according to the adopting BIM in the need for these functions) overall respondents are as follow: the AEC industry in in the AEC industry in Gaza 1) Interoperability and translation of information Gaza strip. strip? (F16); 2) Change Management (F3); 3) Functional simulations to choose the best solution (F2); 4) Three-dimensional (3D) modeling and visualization (F1); and 5) Safety planning and monitoring on-site (F8). In addition to that, factor analysis has compiled BIM functions in three components, which are: 1) Data management and utilization in planning; operation, and maintenance; 2) Visualized design and analysis; and 3) Construction and operation.

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Table (5.1): summary of the findings of the study Research objectives Key research questions Research hypotheses Findings 3. To identify the top RQ3: Are the benefits of -  The study findings of RII test indicated that BIM BIM benefits that BIM valuable from the benefits are significantly valuable for the would convince the standpoint of the professionals in the AEC industry in Gaza strip. Some professionals for professionals (according to benefits of BIM were more valuable than others for adopting BIM in the need for these functions) the professionals. the AEC industry in in the AEC industry in Gaza  BIM benefits that got top ranking according to the Gaza strip. strip? overall respondents are as follow: (1) Enhance design team collaboration (Architectural, Structural, Mechanical, and Electrical Engineers) (BE 3); (2) Improve design quality (BE 4); and (3) Improve sustainable design and lean design (BE 5).  Factor analysis has compiled BIM benefits in four components, which are: 1) Controlled whole-life costs and environmental data; 2) More effective processes; 3) Design and quality improvement; and 4) Decision-making support/ Better customer service. 4. To investigate and RQ4: Are BIM barriers -  The study findings of RII test demonstrated that BIM rank the top BIM affecting the adoption of barriers are substantially affecting the adoption of barriers which face BIM in the AEC industry in BIM in the AEC industry in Gaza strip. the implementation Gaza strip?  The top barriers to BIM adoption, which got top of BIM in the AEC ranking according to the overall respondents are as industry in Gaza follow: strip. 1) Lack of the awareness of BIM by stakeholders (BA 2); 2) Lack of knowledge of how to apply BIM software (BA 3); and

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Table (5.1): summary of the findings of the study Research objectives Key research questions Research hypotheses Findings 3) Lack of the awareness of the benefits that BIM can bring to Engineering offices, companies, and projects (BA 5).  Factor analysis has compiled BIM barriers in four components, which are: 1) Lack of BIM interest; 2) Organization-wide resistance to change workflows; 3) Lack of knowledge about BIM and cost of implementing; and 4) Cultural barriers toward adopting new technology and training requirements. 5. To study some RQ5: What is the effect of H1: There is an inverse  (For H1), Pearson correlation analysis asserted that hypotheses that the awareness level of BIM relationship, statistically there is a strong negative relationship between “the might help to find by the professionals on the significant at α ≤ 0.05, awareness level of BIM by the professionals” and solutions to reduction of BIM barriers in between the awareness level of “BIM barriers in the AEC industry in Gaza strip.” adopting BIM in the AEC industry in Gaza BIM by the professionals and Thus, the increasing the awareness level of BIM by the AEC industry in strip? BIM barriers in the AEC the professionals will reduce BIM barriers in the AEC Gaza strip. industry in Gaza strip. industry in Gaza strip. RQ6: What is the effect of the importance of BIM H2: There is an inverse  (For H2 and H3), Pearson correlation analysis proved functions on the reduction of relationship, statistically that there is an intermediate negative relationship BIM barriers in the AEC significant at α ≤ 0.05, between “the importance of BIM functions” and industry in Gaza strip? between the importance of “BIM barriers in the AEC industry in Gaza strip.” BIM functions and BIM The same relationship is aslo between ―the value of RQ 7: What is the effect of barriers in the AEC industry in BIM benefits,” and “BIM barriers in the AEC the value of BIM benefits on Gaza strip. industry in Gaza strip.” Accordingly, increasing the the reduction of BIM importance of BIM functions reduces barriers to BIM barriers in the AEC industry H3: There is an inverse adoption in the AEC industry in Gaza strip. The same in Gaza strip? relationship, statistically thing will happen when increasing the value of BIM significant at α ≤ 0.05, benefits.

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Table (5.1): summary of the findings of the study Research objectives Key research questions Research hypotheses Findings RQ 8: What is the effect of between the value of BIM  (For H4 and H5), Pearson correlation analysis the awareness level of BIM benefits and BIM barriers in substantiated that there is an intermediate positive by the professionals on the AEC industry in Gaza relationship between “the awareness level of BIM by increasing the importance of strip. professionals” and both of “the importance of BIM BIM functions in the AEC functions,” and “the value of BIM benefits.” industry in Gaza strip? H4: There is a positive Accordingly, increasing the awareness level of BIM relationship, statistically by the professionals will increase the importance of RQ 9: What is the effect of significant at α ≤ 0.05, BIM functions and the value of BIM benefits for the the awareness level of BIM between the awareness level of professionals in the AEC industry in Gaza strip. by the professionals on BIM by the professionals and increasing the value of BIM the value of BIM benefits in  The (H6) was about the differences in the opinions of benefits in the AEC industry the AEC industry in Gaza the respondents toward the investigation into BIM in Gaza strip? strip. application in the AEC industry in Gaza strip due to the gender, the educational qualification, the study RQ 10: Are there differences H5: There is a positive place, the specialization, the nature of the workplace, in the answers of the relationship, statistically the location of the workplace, the current field/ the respondents depending on significant at α ≤ 0.05, present job, and the years of the experience. The the demographic data of the between the awareness level of outcomes were as follow: respondents? BIM by the professionals and the importance of BIM  The Independent samples t-test proved that there functions in the AEC industry are no statistically significant differences in Gaza strip. attributed to the gender of the respondents at the level of α ≤ 0.05 between the Means of their H6: There is a statistically views on the subject of the application of BIM in significant differences the AEC industry in Gaza strip. In the same attributed to the demographic context, One-way ANOVA confirmed that there data of the respondents and the are no statistically significant differences way of their work at the level associated to each of the educational qualification of α ≤ 0.05 between the and the current field/ the present job of the averages of their views on the respondents at the level of α ≤ 0.05 between the subject of the application of Means of their views on the same subject.

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Table (5.1): summary of the findings of the study Research objectives Key research questions Research hypotheses Findings BIM in the AEC industry in According to that, the hypothesis has been Gaza strip. rejected regarding these four parts.

 In contrast, One-way ANOVA asserted that there are significant differences attributed to each of the study place, the specialization, the nature of the workplace, the location of the workplace, and the years of the experience of the respondents at the level of α ≤ 0.05 between the Means of their views on the subject of the application of BIM in the AEC industry in Gaza strip. Accordingly, Scheffe test was used for multiple comparisons between the Means of the opinions of the respondents taking into account this information related to them. As a result, the hypothesis has been accepted regarding these five parts.

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5.3 Recommendations

Based on the achieved objectives of this research as stated earlier, the recommendations below were drawn as a result of the research findings. The recommendations are as follow:

5.3.1 Education and training to increase BIM awareness and interest

The key to any successful change program is the supporting by experts or any bodies that train Architects and Engineers such as the Engineers Association or any specialized training centers during the process of change. Initial vocational training should be done by an expert, a trainer, or even a BIM guru or a training center that specializes in BIM adoption as well as in implementation.

Companies involved in the development of BIM technology provide online courses through its websites. These online courses keen to provide the technical training support and provide the necessary explanation to use BIM efficiently. These websites also keep publishing periodic reports for explaining what's new of BIM technology and show how much it is useful for the AEC industry. It is a guaranteed way to make sure learning use BIM tools properly and correctly. By so doing, the professionals in the AEC industry can derive the maximum benefits from using BIM tools.

Engineers Association has to play a role to identify the concept of BIM, its functions, and benefits, as well as promote the adoption of BIM. It can be done through doing different workshops and by providing technical training courses in applying BIM correctly.

Academic institutions and universities must take the lead to highlight new ways to engage BIM in the AEC industry. The recommended solution is an actively drawing on the educational and research expertise of universities. This approach will not only accelerate the competency and the adoption of BIM but also will align the level and the calibration of the future industry professionals emerging from universities and provide a structure for lifelong development learning around BIM. There are different experiences of universities around the world for the attention of BIM, including:

 Some universities and academies in each of Qatar, the United States, the United Kingdom, Australia, Denmark, Singapore, Hong Kong, China, and others started to offer courses of BIM for students of Bachelor and postgraduate in Architectural and Engineering (BD white paper, 2012; NBIMS-US, 2012; CIC, 2012; China BIM Union, 2013; NBS, 2013; BIM User Day, 2015).

 Qatar University has taken the initiative to facilitate modern and innovative methods in the Gulf construction industry by establishing a knowledge platform about BIM with the government, research, and industry experts. Their major activities are the Qatar BIM User Days, a series of one-day workshops hosted by Qatar University periodically and focused on the four major components of BIM: process, technology, people, and policy. Each day provided expert presentations on one component, allowing in-depth audience discussions and participation. The audience includes (Architectural and Engineering faculties, consultants, contractors, the governmental agencies, NGOs, clients, and any one of the stakeholders in any construction project) (BIM User Day, 2015). 161

 Alumni Association of the Faculty of Architecture of Khartoum University made a week of BIM with Sudan Architecture Forum (SAF) at the beginning of the current year (2015). It was aimed to shed light on the field of BIM and the possibility of its application in Sudan and included some events and workshops. This week activated the relations between the academia and the professional practice in the field of Architecture through the establishment of dialogue, which encouraged the exchange of knowledge, experiences, and ideas. The program hosted a lecturer at the University of Florida, which holds the experience of more than twenty years in the field of BIM. It also applied three training workshops aimed to insert BIM in the professional practice and the development of the construction industry in Sudan (SAF, 2015).

5.3.2 Change organizational culture

Successful BIM adoption is not all about software; it‘s also about the organizational change. For successful BIM adoption, organizations must act positively toward the necessary changing.

 Adopt first, then implement

Be willing to change: one of the first recommended steps towards adopting BIM is to embrace change and learn new methods of doing projects. Firms should decide and pick a date to switch from CAD to BIM and never look back as well as establish a vision that embraces BIM concept. They must ensure that all necessary requirements for BIM adoption are ready. It is imperative that the attitude to change is adopted by all, from top level management, down to the entire members of staff in practice.

 Managing change and transition

Transitioning to BIM workflow is not a process that should be quick and sudden. Implementing BIM approach should be slow and steady to avoid negative impacts to the already existing workflow processes. In other words clearer, the change should be gradual and steady by adopting BIM on a project- by-a project basis (as an example, but not as a limitation). Thus, it would be easier breaking down any psychological, social, and financial barriers to BIM adoption.

 Investment in training

Regarding technology, it is critical to choose the appropriate BIM tools that suit the practice‘s way of work. It is recommended to test out trial versions of vendors and subject them to several functions to evaluate the appropriateness of the tools before making a final decision on which to use. Hardware requirements must also be suitable for new software. Train the right professionals and assign them to tasks, roles, and responsibilities in line with the new BIM workflow implementation and be patient with the learning process. A user cannot suddenly become advanced and proficient; the user requires experience and continuous exposure to the new tools to become an expert.

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5.3.3 Provide appropriate governmental support

The government agencies must take progressive steps to apply BIM in the AEC industry in Gaza strip. For example:

 Generate a clear implementation roadmap/ plan for the implementation of BIM entailing issues that require consideration for the organizations to progress on the BIM maturity ladder.  Identify incrementally and possible steps between major stages.  Provide legal benchmarks for business improvement, where the absence of standard BIM contract documents is preventing people from adopting and utilizing BIM with security in the construction industry (Weygant, 2011; Eastman et al., 2008; Mitchell and Lambert, 2013).

There are different examples of strategies and plans by the governments of various countries over the world, such as:

. The UK government in 2011 published a BIM mandate in the ―Government Construction Strategy‖ stating that ―Fully collaborative 3D BIM will be a minimum requirement‖ by 2016 (BD white paper, 2012; Khosrowshahi and Arayici, 2012).

. Dubai Municipality has decided from the date of the first of January of 2014 to apply BIM in the Architectural as well as Mechanical, Electrical, and Plumbing (MEP) work, where the consulting offices are legally responsible for the application process (Dubai Municipality, 2014). The BIM application will be in stages, where the first stage includes (Dubai Municipality, 2013):

a. The buildings those are higher than 40 floors. b. Buildings area of more than 300, 000 sc. Ft. c. Specialized buildings such as hospitals, universities, and the like. d. All buildings provided through a foreign branch office.

5.4 Research benefits to knowledge and the AEC industry

The novelty of this research lies in highlighting into BIM application in Gaza strip in Palestine. The research has contributed to the AEC industry, simplified as following:

a) The research will add to the existing knowledge on BIM by developing a clear understanding of BIM adoption in Gaza strip in Palestine. b) The study has presented noteworthy findings in the investigation into BIM application in the AEC industry. The research has identified the awareness level of BIM by the professionals in the industry, the most important functions, and the most valuable benefits of BIM for the AEC industry in Gaza strip as well as barriers to the implementation of BIM in the AEC industry. c) The study has established a good platform for future researchers to identify meaningful ways of providing solutions to the identified challenges and facilitate a smoother and more successful transition in the adoption of BIM technologies and innovations in the AEC industry.

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d) Research findings could help the AEC industry to understand the BIM implementation issue. It will assist the companies and the policy makers, especially the government, in identifying the future of BIM adoption and policy in Gaza strip in Palestine. e) The outcomes of this research could also be used for the appropriate education and awareness purposes. It could be integrated into the education programs of the AEC related disciplines. This benefit would improve students' understanding of BIM and BIM implementation.

5.5 Limitations and future studies

Although the research was carefully prepared and has reached its aim, there were some certain limitations.  First of all, because of the geographical limit, this research was conducted only on a population who is living in Gaza strip in Palestine. It was hard to think about a sample from the same population in West Bank. Because of the time limit, it was also hard to think about using e-mail for sending and receiving questionnaires. The involving population of other areas in Palestine would help more to generalize the findings.  Second, the lack of studies related to BIM in Palestine and the surrounding region had limited somehow the discussion of the results.  Finally, the study has taken the concept of BIM comprehensively. It has included all parties who participate in the AEC industry as well as it has studied BIM at all stages of the lifecycle of the facility. The researcher had to do this because this research is the first step in studies about BIM in the area. However, it would be better to allocate the study at a certain stage of the construction project or to be dealt with BIM subject from a perspective of a particular group. Therefore, it is recommended that future researchers should study BIM application in other areas in Palestine. They should also specify more their studies, such as studying the subject of BIM adoption from consultant‘s perspective or contractor‘s perspective. The study can also be conducted about using BIM in a defined phase of the AEC industry such as the Design phase. Furthermore, as a part of any future research, it is suggested to create a BIM model for any construction project that constructed with the traditional way (without BIM). After that, the researcher can study a defined step (such as cost estimation or quantity take-offs of materials) for making a comparison between the results in both cases (before and after BIM).

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Appendices

Appendix A: Questionnaire (English)

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Subject: a Questionnaire Survey about: ―An investigation into Building Information Modeling (BIM) application in Architecture, Engineering and Construction (AEC) industry in Gaza strip”; a Thesis submitted in partial fulfillment of requirements for Master's Degree in Construction Project Management, Civil Engineering

Research aim: to develop a clear understanding about BIM for identifying the different factors that provide useful information to consider adopting BIM technology in projects by the practitioners in the AEC industry in Gaza strip in Palestine.

Target group: Engineers who work in the field of building design, supervision, construction, and maintenance (Architects, Civil Engineers, Mechanical Engineers, Electrical Engineers, and any other professional with related specialization).

The questionnaire consists of five main sections. Filling in the questionnaire does not require prior knowledge about BIM. The required thing from you is the answer and the evaluation of certain points with precision and objectivity according to your perspective and expertise in the field of the Architecture, Engineering and Construction (AEC) industry in the light of the actual reality in Gaza strip. The validity of the questionnaire results entirely depends on your answer accuracy. Thank you in advance for your valuable time and contribution to this research work.

Kind Regards, Lina Ahmed Ata AbuHamra, MSc Candidate in Construction Project Management, Civil Engineering, The Islamic University of Gaza (IUG) (January, 2015)

Part 1: Respondent’s demographic data and the way of implementing their work

 Please tick (√) the appropriate option in the following questions:

Name …………………………………………………………………… (optional)

1. Gender  Male  Female Educational 2. qualification  Bachelor  Master  PhD West 3. Study place Gaza strip  Outside Palestine  Bank  Other 4. Specialization Architect Civil Electrical Mechanical      (…..) Nature of the Other 5. Consultant NGOs Contractor Contractor  workplace     (…..) Location of 6.  North  Gaza  Middle  Khan  Rafah the workplace Younis Current field 7.  Designer  Super -  Site  Project  Other -present job visor Engineer manager (…..) Years of 8.  Less than 5  From 5 to less than 10  10 years and more experience years years

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Percentage of Less than From 25% to less than From 70% and implementati-     25% 50% 50% to more 9. on the work less than by using 3D 70% programs (You can choose more than one answer) Which software tool  AutoCAD  Sketch up  Revit  Excel  MS 10. do you use to (2D) Project carry out projects?  AutoCAD  3D Max  ArchiCAD  Other (………..) (3D)

Part 2: The awareness level of BIM by the professionals in the AEC industry

 To which degree you consistent with the following items? Please tick (√) in

front of the number that reflects your point of view.

Item

Number

. Never . Little . Somewhat . Much . much Very .

1 2 3 4 5 A1 I have read some research and studies about BIM. A2 Some of my college courses at University talked about BIM. A3 I have a good idea about the concept of BIM technology. A4 I have a high rate of information regarding the use of BIM technology in Engineering project management. A5 I have an idea about how to use BIM technology programs. A6 I know that Revit and ArchiCAD programs are BIM technology techniques. A7 I use BIM technology in my job. A8 I think that BIM technology is important for the AEC industry in Gaza strip. A9 I think that BIM technology has a positive impact on the sustainable environment.

Part 3

 How would you rate the following items in terms of their importance and the need for them in the AEC in Gaza strip? Please tick (√) in front of the

number that reflects your point of view.

Item

Number

. Unimportant .

1 Little Of 2. importance Moderately 3. important Important 4. Very 5. Important F1 Three-dimensional (3D) modeling and visualization F2 Functional simulations to choose the best solution (such as Lighting, energy, and any other sustainability information)

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Item

Number

. Unimportant .

1 Little Of 2. importance Moderately 3. important Important 4. Very 5. Important F3 Change Management (any modification to the building design will automatically replicate in each view such as floor plans, sections, and elevation) F4 Visualized constructability reviews/ Building simulation (a 3D structural model as well as a 3D model of Mechanical, Electrical, and Plumbing (MEP) services) F5 Four-dimensional (4D) visualized scheduling and construction sequencing F6 Model-based cost estimation (Five-dimensional (5D)) F7 Model-based site planning and site utilization F8 Safety planning and monitoring on-site F9 Model-based quantity take-offs of materials and labor F10 Creation of as-built model that contains all the necessary data to manage and operate the building (facility management) F11 Future expansion/ extension in facility and infrastructure F12 Maintenance scheduling via as-built model F13 Energy optimization of the building F14 Issue Reporting and Data archiving via a 3D model of the building F15 Managing metadata (provide information about an individual item's content) via a 3D model of the building F16 Interoperability and translation of information (among the professionals) within the same system/ program

Part 4

 How would you rate the following items regarding their benefit in the AEC industry in Gaza strip? Please tick (√) in front of the number that reflects

your point of view.

Items

Number

4.Highly

beneficial beneficial

Beneficial

5.Extremely

3.Moderately

high beneficial high

1.Extremely low 1.Extremely 2. Low beneficial Low 2.

BE 1 Improve realization of the idea of a design by the owner via a 3D model of the building BE 2 Support design decision-making by comparing different design alternatives on a 3D model BE 3 Enhance design team collaboration (Architectural, Structural, Mechanical, and Electrical Engineers) BE 4 Improve design quality (reducing errors/ redesign and managing design changes)

180

Items

Number

4.Highly

beneficial beneficial

Beneficial

5.Extremely

3.Moderately

high beneficial high

1.Extremely low 1.Extremely 2. Low beneficial Low 2.

BE 5 Improve sustainable design and lean design BE 6 Improve safety design BE 7 Improve the selection of the construction components carefully in line with the quality and costs (such as types of doors and windows, coverage type of the exterior walls, etc.) BE 8 Improve understanding the sequence of the construction activities BE 9 Enhance work coordination with subcontractors and suppliers (supply chain) BE 10 Increase the quality of prefabricated (digitally fabricated) components and reduce its costs BE 11 Improve safety planning and monitoring on- site/ reduce risks BE 12 Increase the accuracy of scheduling and planning BE 13 Increase the accuracy of cost estimation BE 14 Improve communication between project parties BE 15 Reduce change/ variation orders in the construction stage BE 16 Reduce clashes among the stakeholders (clash detection) BE 17 Reduce the overall project duration and cost BE 18 Improve the implementation of lean construction techniques to get sustainable solutions for reducing waste of materials during construction and demolition BE 19 Ease of information retrieval for the entire life of the building through as-built 3D model BE 20 Improve the management and the operation of the building to maintain its sustainability by supporting decision-making on matters relating to the building BE 21 Increase coordination between the different operating systems of the building (such as security and alarm system, lighting, air conditioning, etc.) BE 22 Enhance energy efficiency and sustainability of the building BE 23 Improve maintenance planning (preventive and curative)/ maintenance strategy of the facility BE 24 Control the whole-life costs of the asset effectively BE 25 Increase profits by marketing for the facility via a 3D model

181

Items

Number

4.Highly

beneficial beneficial

Beneficial

5.Extremely

3.Moderately

high beneficial high

1.Extremely low 1.Extremely 2. Low beneficial Low 2.

BE 26 Improve emergency management (put plans for avoiding hazards and cope with disasters such as fire, earthquakes, etc.)

Part 5

The greatest feature of BIM is creating a single integrated database through a virtual 3D model of the building where all the design and the construction decisions can be recorded. All project teams can access all contents of the database according to their authority. On the other hand, the application of BIM needs many things to obtain the feature mentioned above, such as:

(New programs are required for BIM application, necessary arrangements in the workplace to adopt this new technology, as well as the need for the cooperation among all parties involved in the project and other requirements). Consequently, and according to your knowledge of the current situation of the AEC industry in Gaza strip:

 How would you rate the following barriers in front of BIM application?

Please tick (√) in front of the number that reflects your point of view.

BIM barrier

Strong

Number

strength

. Very weak Very .

1 Weak 2. Average 3. 3. strong Very 5. BA 1 Necessary high costs to buy BIM software and costs of the necessary hardware updates BA 2 Lack of the awareness of BIM by stakeholders BA 3 Lack of knowledge of how to apply BIM software BA 4 Professionals think that the current CAD system and other conventional programs satisfy the need of designing and performing the work and complete the project efficiently BA 5 Lack of the awareness of the benefits that BIM can bring to Engineering offices, companies, and projects BA 6 Lack of effective collaboration among project stakeholders to exchange necessary information for BIM application, due to the fragmented nature of the AEC industry in Gaza strip BA 7 Resistance by companies and institutions for any change can occur in the workflow system and the refusal of adopting a new technology

182

BIM barrier

Strong

Number

strength

. Very weak Very .

1 Weak 2. Average 3. 3. strong Very 5. BA 8 Lack of the financial ability for the small firms to start a new workflow that is necessary for the adoption of BIM effectively BA 9 Companies prefer focusing on projects (under working/ construction) rather than considering, evaluating, and implementing BIM BA 10 Difficulty of finding project stakeholders with the required competence to participate in applying BIM BA 11 Lack of the governmental regulations for full support the implementation of BIM BA 12 Lack of demand and disinterest from clients regarding with using BIM technology in design and construction of the project BA 13 Lack of the real cases in Gaza strip or other nearby areas in the region that have been implemented by using BIM and have proved positive return of investment BA 14 Lack of interest in Gaza strip to pursue the condition of the building over the life after completion of implementation stage BA 15 Lack of Architects/ Engineers skilled in the use of BIM programs BA 16 Lack of the education or training on the use of BIM, whether in the university or any governmental or private training centers BA 17 The unwillingness of Architects/ Engineers to learn new applications because of their educational culture and their bias toward the programs they are dealing with BA 18 Reluctance to train Architects/ Engineers due to the costly training requirements in terms of time and money

Thank you very much for your valuable time and effort on this survey

183

Appendix B: Questionnaire (Arabic)

184

الموضوع: استبانة حول "البحث في تطبيق تكنولوجيا نمذجة معلومات البناء (BIM) في صناعة التصميم وتشييد البناء في قطاع غزة" استكماال لمتطمبات الحصول عمى درجة الماجستير في إدارة المشاريع اليندسية.

 اليدف الرئيسي من البحث: تطوير فيم واضح حول اعتماد تكنولوجيا BIM وبناء نموذج نظري لتحديد العوامل المختمفة التي توفر معمومات مفيدة لمنظر في اعتماد ىذه التكنولوجيا من قبل الميندسين في المشاريع في صناعة التصميم والتشييد في قطاع غزة في فمسطين.  الفئة المستيدفة: الميندسون الذي يعممون في مجال تصميم المباني، واإلشراف، والتنفيذ، والصيانة )المعماري، والمدني، والكيربائي، والميكانيكي، وأي تخصص ذو عالقة(.  ماىية اإلستبانة: تتكون االستبانة من خمسة أقسام رئيسية، ال تتطمب تعبئة االستبانة معرفة مسبقة عن تكنولوجيا BIM، وانما المطموب ىو التقييم لنقاط معينة بكل دقة وموضوعية وفقا لوجية نظرك، والخبرة في مجال العمل اليندسي الخاص بالتصميم وتشييد البناء في ضوء الواقع الفعمي في قطاع غزة. مدى صحة نتائج االستبانة يعتمد اعتمادا ً كميا ً عمى دقة إجابتك. لكم كل الشكر مقدما عمى المساىمة في ىذا العمل البحثي.

أطيب التحيات،

لينا أحمد عطا أبو حمرة، مهندسة معمارية/ وباحثة للحصول على درجة الماجستير في إدارة المشاريع الهندسية )الهندسة المدنية(، الجامعة اإلسالمية – غزة، قطاع غزة، فلسطين، يناير، 5102

الجزء األول: معمومات خاصة بالميندس الذي يقوم بتعبئة اإلستبانة وطريقة أدائو لمعمل

 يرجى وضع عالمة )√( أمام الخيار المناسب في األسئمة التالية.

اإلسم )اختياري( ...... 1. الجنس  ذكر  أنثى 2. المؤىل العممي  بكالوريوس  ماجستير  دكتوراه 3. بمد الحصول عمى المؤىل  قطاع غزة  الضفة الغربية  الخارج )...... ( العممي 4. التخصص  ميندس  ميندس  ميندس  ميندس  أخرى معماري مدني كيربائي ميكانيكي )...... ( 5. طبيعة مكان  استشارات  مؤسسات  مقاوالت  قطاع  أخرى العمل ىندسية دولية حكومي )...... ( 6. موقع العمل  الشمال  غزة  الوسطى  خانيونس  رفح 7. مجال وظيفتك  مصمم  ميندس  ميندس  مدير مشاريع  أخرى الحالية مشرف موقع )...... (

185

8. سنوات الخبرة  أقل من  5 من 5 إلى أقل من  01 01 سنوات فأكـــــثر سنوات سنــــــوات 9. نسبة أداءك  أقل من  من 55 إلى أقل  من 51 إلى أقل  55% فأكثــــــــــر لعممك باستخدام 25% من 51% من %55 برامج النظام الثالثي األبعاد )3D(؟ 10. البرامج التي )يرجى تحديد جميع البرامج المستخدمة(: تستخدميا في  أوتوكاد  اسكتش أب  ريفيت  إكسل MS  بروجكيت عممك إلنجاز ثنائي األبعاد Revit المشاريع؟ (2D(  أوتوكاد  3D  أرشيكاد  أخرى )...... ( ثالثي ماكس )أركيكاد( األبعاد (3D(

الجزء الثاني: درجة المعرفة بتكنولوجيا نمذجة معمومات البناء )BIM( وتطبيقو في العمل في قطاع غزة

األقل

 إلى أي درجة تتفق مع البنود التالية؟ يرجى وضع عالمة )√( أمام الرقم الذي تراه مناسبا.

4 3 2 1

5 جدا

.إطالقا

الرقم البند

قميمة .بدرجة قميمة

كبيرة بدرجة . بدرجة كبيرة

متوسطة .بدرجة متوسطة

1 قـــرأت قبـــل ذلـــك بعـــض األبحـــاث والدراســـات الخاصـــة بتكنولوجيـــا نمذجـــة معمومات البناء )BIM( 2 تناولــت بعـــض مســاقات دراســـتي فــي الجامعـــة موضــوع تكنولوجيـــا نمذجـــة معمومات البناء)BIM( 3 لدي فكرة جيدة حول مفيوم تكنولوجيا BIM 4 معــــدل معمومــــاتي عــــالي بخصــــوص اســــتخدام تكنولوجيــــا BIM فــــي إدارة المشاريع اليندسية 5 لدي فكرة حول كيفية استخدام وتطبيق برامج تكنولوجيا BIM 6 لـــــــدي عمـــــــم مســـــــبق بـــــــأن برنـــــــامج ريفيـــــــت Revit ، وبرنـــــــامج أرشـــــــيكاد ArchiCAD ىما من برامج تكنولوجيا BIM 7 أستخدم برامج تكنولوجيا BIM في العمل

186

4 3 2 1

5 جدا

.إطالقا

الرقم البند

قميمة .بدرجة قميمة

كبيرة بدرجة . بدرجة كبيرة

متوسطة .بدرجة متوسطة

8 أعتقـــد بـــأن لتكنولوجيـــا BIM أىميـــة لصـــناعة التصـــميم وتشـــييد البنـــاء فـــي قطاع غزة 9 أعتقد أن لتكنولوجيا BIM تأثير إيجابي عمى البيئة المستدامة

الجزء الثالث

 ما تقييمك لمبنود التالية من حيث أىميتيا والحاجة ليا في صناعة التصميم وتشييد البناء في قطاع غزة؟

يرجى وضع عالمة )√( أمام الرقم الذي تراه مناسبا.

4 3 2 1 5

.ميم

الرقم البند

ميم .غير ميم ىام .جدا

األىمية .معتدل األىمية

قميل األىمية . قميل األىمية

1 نمذجة وتصور المبنى بشكل ثالثي األبعاد 2 المحاكاة ألمور معينة تؤثر عمى المبنى المراد إنشاؤه من خالل نموذج إفتراضيثالثي األبعاد ، وذلك بيدف اختيار الحل األفضل. مثل محاكاة اإلضاءة، والطاقة وغيرىا 3 إدارة التغيير في التصميم )في حال حدث تغيير عمى تصميم المبنى، فإن التعديل سيظير تمقائيا في كال من: المساقط، والواجيات، والمقاطع( 4 محاكاة البناء بغرض فيم كيفية البناء والتنفيذ من خالل نموذج افتراضي ثالثي األبعاد )إنشائي، وميكانيكي، وكيربائي( لممبنى المراد تنفيذه 5 عمل جدول زمني مصور لمراحل البناء وذلك بربط الجدول الزمني بنموذج افتراضي ثالثي األبعاد لممبنى

6 تقدير التكاليف لمكّونات المبنى وعممية البناء باالعتماد عمى نموذج افتراضي ثالثي األبعاد 7 تخطيط موقع البناء بشكل سميم وتنظيم وترتيب أماكن المعدات ومواد البناء 8 التخطيط لألمن والسالمة ومراقبة ذلك في موقع البناء 9 حساب الكميات الالزمة من مواد البناء وحساب عدد العمال الالزم إلتمام العمل وذلك باالعتماد عمى نموذج افتراضي ثالثي األبعاد لممبنى 10 استخدام نموذج ثالثي األبعاد لممبنى )مطابق لمواقع( يحتوي عمى كاف ّة البيانات الالزمة بيدف إدارة وتشغيل المبنى

187

4 3 2 1 5

.ميم

الرقم البند

ميم .غير ميم ىام .جدا

األىمية .معتدل األىمية

قميل األىمية . قميل األىمية

11 إدارة التوسع المستقبمي لممنشأة بشكل سميم )عمى سبيل المثال إدارة التمديد في البنية التحتية بشكل مدروس في حالة توسيع المبنى وتطويره ، باإلضافة لغيرىا من المرافق الخاصة بالمبنى( 12 جدولة الصيانة الالزمة لممبنى من خالل توفير جميع البيانات الخاصة بمكونات المبنى 13 ترشيد استيالك الطاقة لممبنى 14 كتابة التقارير وأرشفة البيانات في قاعدة بيانات واحدة متكاممة من خالل نموذج ثالثي األبعاد لممبنى 15 توفير معمومات تفصيمية حول أي بند يخص المبنى في جميع مراحل دورة حياتو 16 نقل البيانات دون فقد أي منيا ما بين الميندسين )المعماري، واإلنشائي، والكيربائي، والميكانيكي( الذين يستخدمون نظام برامج واحد

الجزء الرابع

 ما تقييمك لمبنود التالية من حيث فائدتيا في صناعة التصميم والبناء في قطاع غزة؟ يرجى وضع عالمة

)√( أمام الرقم الذي تراه مناسبا.

4 3 2 1

الرقم البند

كبيرة بدرجة .مفيد بدرجة كبيرة

قميمة بدرجة .مفيد بدرجة قميمة

متوسطة بدرجة .مفيد بدرجة متوسطة

جدا قميمة بدرجة .مفيد جدا كبيرة بدرجة .مفيد بدرجة كبيرة جدا

1 تقوية إدراك المالك لفكرة التصميم من خالل نموذج افتراضي ثالثي األبعاد لممبنى 2 دعم اتخاذ القرار لمميندسين والمالك بشأن خيارات التصميم من خالل المقارنة بين بدائل التصميم المختمفة باالعتماد عمى نموذج افتراضي ثالثي األبعاد لممبنى 3 تعزيز التعاون ما بين أعضاء فريق التصميم )المعماري، واإلنشائي، والميكانيكي، والكيربائي( 4 تحسين جودة التصميم )تقميل األخطاء/ تقميل إعادة التصميم، وادارة التغييرات في التصميم( 5 تحسين التصميم المستدام الذي يقمل من الفواقد ويزيد من قيمة المبنى 6 تحسين التصميم الذي يدعم األمن والسالمة

188

5 4 3 2 1

الرقم البند

كبيرة بدرجة .مفيد بدرجة كبيرة

قميمة بدرجة .مفيد بدرجة قميمة

متوسطة بدرجة .مفيد بدرجة متوسطة

جدا كبيرة بدرجة .مفيد بدرجة كبيرة جدا

جدا قميمة بدرجة .مفيد بدرجة قميمة جدا

7 تحسين اختيار مكونات البناء بعناية بما يتالئم مع الجودة والتكاليف )مثل أنوع األبواب والشبابيك، نوع تكسية الجدران الخارجية، وغيرىا( 8 زيادة القدرة عمى فيم تسمسل أعمال التشييد لممبنى 9 تعزيز تنسيق العمل مع مقاولي الباطن/ والموردين لممواد الالزمة لمبناء

10 زيادة جودة تصميم مكّ ونات المبنى المسبقة الصنع والجاىزة لمتركيب في الموقع وتقميل تكاليفيا 11 تحسين تخطيط األمن والسالمة والمراقبة في الموقع/ الحد من المخاطر في الموقع 12 زيادة دقة الجدولة الزمنية والتخطيط ألعمال تشييد البناء 13 زيادة دق ّة تقدير تكاليف تشييد البناء 14 تحسين االتصال بين األطراف المشاركة في المشروع 15 تقميل أوامر التغيير (Change/ Variation orders) في مرحمة البناء 16 تقميل النزاعات بين األطراف المشاركة في المشروع 17 تقميل المّدة اإلجمالية والتكمفة اإلجمالية لممشروع 18 تحسين استخدام وتطبيق تقنيات البناء التي تضمن الحصول عمى حمول مستدامة لمحد من ىدر المواد أثناء البناء واليدم 19 سيولة استرجاع المعمومات الخاصة بكامل حياة المبنى من خالل نموذج ثالثي األبعاد مطابق لممبنى 20 تحسين إدارة وتشغيل المبنى لمحفاظ عمى استدامتو من خالل دعم اتخاذ القرارات )لممسؤولين عن المبنى( بشأن المسائل المتعمقة بالمبنى 21 زيادة التنسيق بين أنظمة التشغيل المختمفة المستخدمة في المبنى مثل: )النظام األمني واإلنذار، اإلضاءة، التكييف، وغيرىا( 22 تعزيز كفاءة استدامة المبنى 23 تحسين التخطيط لمصيانة )الوقائية، والعالجية( بشكل دائم لممنشأة

24 السيطرة عمى التكاليف الكاممة لممنشأة وادارتيا عمى نحو ف ّع ال 25 زيادة األرباح من خالل التسويق لممبنى باستخدام نموذج ثالثي األبعاد مطابق لو ويحتوي عمى البيانات الالزمة الخاصة بو 26 تحسين إدارة الطوارئ )وضع خطط لتجنب المخاطر والتعامل مع الكوارث مثل الحرائق، والزالزل، وغيرىا(

189

الجزء الخامس

أكثر ما يميز تكنولوجيا نمذجة معمومات البناء )BIM( ىو عمل قاعدة بيانات واحدة متكاممة من خالل نموذج افتراضي ثالثي األبعاد لممبنى يسجل فييا كافة قرارات التصميم واإلنشاء. ويمكن الوصول إلى كل محتوياتيا من كافة فرق العمل في المشروع كل حسب صالحياتو. من جية أخرى، يحتاج تطبيق BIM لمعديد من األمور بيدف الحصول عمى الميزة المذكورة أعاله ، ومن ىذه األمور: )البرامج الجديدة الالزمة لتطبيقو، والترتيبات الالزم إعدادىا داخل مكان العمل لتبني ىذه التكنولوجيا الجديدة، باإلضافة إلى ضرورة التعاون بين كافة األطراف المشاركة في المشروع، وغيرىا من االحتياجات(.

 وبناء عمى ذلك، وبحسب معرفتك لموضع الحالي لصناعة التصميم وتشييد البناء في قطاع غزة:

ما تقييمك لمعوائق التالية أمام تطبيق تكنولوجيا BIM؟ يرجى وضع عالمة )√( أمام الرقم الذي تراه مناسبا.

4 3 2 1

5 .قوي

.ضعيف

الرقم

جدا .قوي جدا

العائق جدا .ضعيف جدا

القوة .متوسط القوة

1 ارتفاع التكاليف الالزمة لشراء برامج BIM، فضال عن تكاليف تحديثات األجيزة الالزمة لتتناسب مع ىذه البرامج 2 عدم المعرفة بتكنولوجيا BIM من قبل أصحاب المصمحة في المشروع 3 عدم المعرفة بكيفية تطبيق برامج BIM 4 االعتقاد بأن البرامج التقميدية المستخدمة حاليا ىي برامج تفي بحاجة الميندسين ألداء العمل وانجاز المشروع بكفاءة، وال توجد حاجة لبرامج جديدة مثل برامج BIM 5 عدم المعرفة بفوائد BIM التي يمكن أن تعود عمى المكاتب اليندسية والشركات والمشاريع

6 عدم وجود تعاون ف ّع ال بين أصحاب المصمحة في المشروع لتبادل المعمومات الالزمة لتطبيق BIM نظرا لمطبيعة المجزأة لصناعة التصميم وتشييد البناء في قطاع غزة 7 مقاومة الشركات والمؤسسات ألي تغيير يمكن أن يطرأ عمى نظام سير العمل فييا، ورفض تبّن ي أي تكنولوجيا جديدة 8 نقص القدرة المالية لمشركات الصغيرة الالزمة لبدء سير العمل الجديد الالزم لتطبيق تكنولوجيا BIM عمى نحو ف ّع ال 9 تفضيل الشركات لمتركيز عمى مشاريع قيد العمل )تحت اإلنشاء( بدال من بذل الوقت لمنظر في أمر BIM وتقييمو وتطبيقو 10 صعوبة العثور عمى أطراف مشاركة في المشروع تكون لدييا الكفاءة المطموبة لممشاركة في تطبيق تكنولوجيا BIM 11 عدم وجود أنظمة حكومية تدعم تطبيق BIM بشكل كامل

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5 4 3 2 1 .قوي

.ضعيف

الرقم

جدا .قوي جدا

العائق جدا .ضعيف جدا

القوة .متوسط القوة

12 عدم طمب المالك استخدام تكنولوجيا BIM في تصميم وتنفيذ المشروع وبالتالي ال يوجد دافع لمتفكير باعتماده في العمل 13 عدم وجود بناء حقيقي في قطاع غزة أو في أماكن مجاورة في المنطقة تم تنفيذه بواسطة تكنولوجيا BIM وأثبت عائدا إيجابيا لالستثمار 14 عدم االىتمام في قطاع غزة بمتابعة حالة المبنى عمى مدى الحياة بعد االنتياء من مرحمة تنفيذه 15 عدم وجود ميندسين متخصصين ذوي خبرة في استخدام برامج BIM 16 عدم التعميم أو التدريب عمى استخدام BIM سواء بالجامعة أو أي مراكز تدريبية حكومية أو خاصة 17 عدم رغبة الميندسين لتعمم تطبيقات جديدة بسبب ثقافتيم التعميمية، وتحيزىم تجاه البرامج المألوفة لدييم 18 التردد في تدريب الميندسين نظرا لمتطمبات التدريب المكمفة من ناحية الوقت والمال

شكرا جزيال عمى وقتك الثمين والجيد المبذول في ىذا االستطالع

191

Appendix C: Correlation coefficient

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Table (C1): The correlation coefficient between each paragraph/ item in the field and the whole

field (The first field is the awareness level of BIM by the professionals)

value

Item -

Pearson Pearson

Number coefficient A1 I have read some research and studies about BIM. 0.83 0.00* A2 Some of my college courses at University talked about BIM. 0.68 0.00* A3 I have a good idea about the concept of BIM technology. 0.89 0.00* A4 I have a high rate of information regarding the use of BIM technology 0.83 0.00* in Engineering project management. A5 I have an idea about how to use BIM technology programs. 0.89 0.00* A6 I know that Revit and ArchiCAD programs are BIM technology 0.81 0.00* techniques. A7 I use BIM technology in my job. 0.69 0.00* A8 I think that BIM technology is important for the AEC industry in Gaza 0.87 0.00* strip. A9 I think that BIM technology has a positive impact on the sustainable 0.89 0.00* environment.

Table (C2): The correlation coefficient between each paragraph in the field and the whole field

(The second field is the importance of BIM functions)

Items

value

Pearson Pearson

Number coefficient

F1 Three-dimensional (3D) modeling and visualization 0.71 0.00* F2 Functional simulations to choose the best solution (such as Lighting, 0.49 0.00* energy, and any other sustainability information) F3 Change Management (any modification to the building design will automatically replicate in each view such as floor plans, sections, and 0.65 0.00* elevation) F4 Visualized constructability reviews/ Building simulation (a 3D structural model as well as a 3D model of Mechanical, Electrical, 0.63 0.00* and Plumbing (MEP) services) F5 Four-dimensional (4D) visualized scheduling and construction 0.73 0.00* sequencing F6 Model-based cost estimation (Five-dimensional (5D)) 0.50 0.00* F7 Model-based site planning and site utilization 0.59 0.00* F8 Safety planning and monitoring on-site 0.65 0.00* F9 Model-based quantity take-offs of materials and labor 0.60 0.00* F10 Creation of as-built model that contains all the necessary data to 0.68 0.00* manage and operate the building (facility management) F11 Future expansion/ extension in facility and infrastructure 0.68 0.00* F12 Maintenance scheduling via as-built model 0.70 0.00* F13 Energy optimization of the building 0.60 0.00* F14 Issue Reporting and Data archiving via a 3D model of the building 0.72 0.00* F15 Managing metadata (provide information about an individual item's 0.82 0.00* content) via a 3D model of the building F16 Interoperability and translation of information (among the 0.71 0.00* professionals) within the same system/ program

193

Table (C3): The correlation coefficient between each paragraph in the field and the whole field

(The third field is the value of BIM benefits)

Items

value

Pearson

Number coefficient Improve realization of the idea of a design by the owner via a 3D BE 1 0.58 0.00* model of the building Support design decision-making by comparing different design BE 2 0.54 0.00* alternatives on a 3D model Enhance design team collaboration (Architectural, Structural, BE 3 0.67 0.00* Mechanical, and Electrical Engineers) Improve design quality (reducing errors/ redesign and managing BE 4 0.52 0.00* design changes) BE 5 Improve sustainable design and lean design 0.76 0.00* BE 6 Improve safety design 0.56 0.00* Improve the selection of the construction components carefully in BE 7 line with the quality and costs (such as types of doors and windows, 0.69 0.00* coverage type of the exterior walls, etc.) BE 8 Improve understanding the sequence of the construction activities 0.68 0.00* BE 9 Enhance work coordination with subcontractors and suppliers 0.62 0.00* (supply chain) BE 10 Increase the quality of prefabricated (digitally fabricated) 0.55 0.00* components and reduce its costs BE 11 Improve safety planning and monitoring on-site/ reduce risks 0.68 0.00* BE 12 Increase the accuracy of scheduling and planning 0.79 0.00* BE 13 Increase the accuracy of cost estimation 0.76 0.00* BE 14 Improve communication between project parties 0.73 0.00* BE 15 Reduce change/ variation orders in the construction stage 0.73 0.00* BE 16 Reduce clashes among the stakeholders (clash detection) 0.78 0.00* BE 17 Reduce the overall project duration and cost 0.72 0.00* BE 18 Improve the implementation of lean construction techniques to get 0.75 0.00* sustainable solutions for reducing waste of materials during construction and demolition BE 19 Ease of information retrieval for the entire life of the building 0.69 0.00* through as-built 3D model BE 20 Improve the management and the operation of the building to 0.75 0.00* maintain its sustainability by supporting decision-making on matters relating to the building BE 21 Increase coordination between the different operating systems of the 0.76 0.00* building (such as security and alarm system, lighting, air conditioning, etc.) BE 22 Enhance energy efficiency and sustainability of the building 0.63 0.00* BE 23 Improve maintenance planning (preventive and curative)/ 0.72 0.00* maintenance strategy of the facility BE 24 Control the whole-life costs of the asset effectively 0.71 0.00* BE 25 Increase profits by marketing for the facility via a 3D model 0.49 0.00* BE 26 Improve emergency management (put plans for avoiding hazards 0.77 0.00* and cope with disasters such as fire, earthquakes, etc.)

194

Table (C4): The correlation coefficient between each paragraph in the field and the whole field

(The fourth field is the strength of BIM barriers)

BIM barrier

value

umber

Pearson coefficient

BA 1 Necessary high costs to buy BIM software and costs of the 0.35 0.03 necessary hardware updates BA 2 Lack of the awareness of BIM by stakeholders 0.57 0.00* BA 3 Lack of knowledge of how to apply BIM software 0.63 0.00* BA 4 Professionals think that the current CAD system and other conventional programs satisfy the need of designing and performing 0.54 0.00* the work and complete the project efficiently BA 5 Lack of the awareness of the benefits that BIM can bring to 0.57 0.00* Engineering offices, companies, and projects BA 6 Lack of effective collaboration among project stakeholders to exchange necessary information for BIM application, due to the 0.50 0.00* fragmented nature of the AEC industry in Gaza strip BA 7 Resistance by companies and institutions for any change can occur in the workflow system and the refusal of adopting a new 0.47 0.00* technology BA 8 Lack of the financial ability for the small firms to start a new 0.45 0.00* workflow that is necessary for the adoption of BIM effectively BA 9 Companies prefer focusing on projects (under working/ construction) rather than considering, evaluating, and implementing 0.52 0.001 BIM BA 10 Difficulty of finding project stakeholders with the required 0.52 0.00* competence to participate in applying BIM BA 11 Lack of the governmental regulations for full support the 0.61 0.00* implementation of BIM BA 12 Lack of demand and disinterest from clients regarding with using 0.48 0.00* BIM technology in design and construction of the project BA 13 Lack of the real cases in Gaza strip or other nearby areas in the region that have been implemented by using BIM and have proved 0.63 0.000 positive return of investment BA 14 Lack of interest in Gaza strip to pursue the condition of the building 0.66 0.00* over the life after completion of implementation stage BA 15 Lack of Architects/ Engineers skilled in the use of BIM programs 0.74 0.00* BA 16 Lack of the education or training on the use of BIM, whether in the 0.76 0.00* university or any governmental or private training centers BA 17 The unwillingness of Architects/ Engineers to learn new applications because of their educational culture and their bias 0.52 0.00* toward the programs they are dealing with BA 18 Reluctance to train Architects/ Engineers due to the costly training 0.47 0.00* requirements in terms of time and money

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All thanks and praise are due to ALLAH “Alhamdulillah”