INTERNATIONAL JOURNAL OF REAL ESTATE STUDIES Published by Centre for Real Estate Studies Website: https://www.utm.my/intrest INTREST 13(1)/201 9, 50-72

APPLYING GROUNDED THEORY METHOD FOR MEASURING EMPLOYMENT OPPORTUNITIES GENERATED BY A SHOPPING CENTRE DEVELOPMENT

Nurul Faiezah Ngadimin1*, Abdul Hamid Mar Iman2, Rohaya Abdul Jalil1 1Faculty of Built Environment and Surveying, Universiti Teknologi 81310 Skudai, , Malaysia 2Faculty of Veterinary Medicine, Universiti Malaysia Kelantan 16100 Pengkalan Chepa, Kelantan, Malaysia

ABSTRACT History:

A shopping centre development project brings about a positive change Received: 29 January 2019 to the community as well as generates a lot of business opportunities Received in revised form: 5 April 2019 which in turn creates more employment and job opportunities for the Accepted: 25 April 2019 locals. However, there is no numerical proof regarding employment Available Online: 30 April 2019 opportunities generated therefrom. In particular, there was neither

assessment nor measurement of employment opportunities generated Keywords: by a shopping centre development being developed. Therefore, this

paper attempts to measure the employment opportunities generated by Grounded theory method, shopping a proposed shopping centre development project by developing centre, employment, employment physical parameters for the measurement on the basis of net-lettable density area (NLA). A grounded theory method (GTM) is adapted since there

is lack of the existing literature on the method or approach of *Corresponding Author assessment. The GTM with an inductive approach as well as deductive [email protected] orientation was employed in measuring employment opportunities

utilizing data generated from the constant comparative method (CCM).

Thus, a CCM-GTM is adopted and six operational shopping centres in

Johor Bahru are selected as a comparable group, called CG6. The data of CG6 were constantly compared for their commonalities and variations, thus the trace out to the emerging pattern are found. This study conceptualized the theory of employment generation and derived the employment density equation from a set of employment quotients (EQ). Besides, this paper presented an ideal figure of retail mix classes existing within a shopping centre together with its percentages distribution placement.

1.0 INTRODUCTION retail and other commercial establishments that are developed and managed as a single property A shopping centre is a place where retail shops (Guy, 1998), thus there are a few components in are located and grouped constituting diverse shopping centre such as department store qualities of products, fast food courts, (anchor store and draw tenant), stand-alone amusement centres, clubs, cinemas, playing stores (small shop or satellite tenant of high areas and relaxation spaces, commercial and street retailers), food court and entertainment retail shops (Terblanche, 1999; Hariyono, 2002). zone (cinema, entertainment, and sports centre). A shopping centre is also viewed as a group of A shopping centre houses a variety of business

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development tenants mix created based on the available floor Employment opportunities generated is one space or let-able space inside and outside the of primarily benefits from the shopping centre building. It generates business and, in turn, development (Ihuah and Benebo, 2014; employment and job opportunities for the locals. Hanachor, 2012; Carrero et al., 2009; Taylor, A survey conducted by Hammerson (2013) 2003); however, there was no numerical proof of shows that the principal benefit received by it. Because of the absence of past studies, there residents resulting from a new shopping centre is was neither assessment nor measurement on the employment; 85% of it is created through employment opportunities generated by a retailers to people living within 20 miles of the shopping centre. Therefore, a grounded theory centre, while 37% of the retail employment method (GTM) is proposed to address this issue. benefits individuals who were previously A GTM is used for several reasons as follows: unemployed and claiming Jobseeker’s Allowance. A shopping centre development has a) The theory exists namely employment strong growth in employment largely in retail density ratio (EDR) or employment space trade and services (REMI Consulting, Inc, factor is too abstract to be tested and 2006), and it provides a variety of employment demonstrably inadequate (Martin and opportunity for the middle and lower-class Turner, 1986; Carson et al., 2001; people (Khaleeque et al., 2004). Therefore, the Suddaby, 2006) for measuring shopping centre is welcomed into the employment opportunities in the context community as an employment generator and the of this study. economic stimulator (Mitchell, 2006; Voyce, b) There is no research has been conducted 2006; and Ryan, 2006). specifically related to the approach or According to Tegner (2009), a single method in measuring employment shopping centre can offer employment for generated by a proposed shopping centre, approximately 2,000 people, while International therefore the GTM is appropriate method Finance Corporation (IFC) (2008) stated that a for analysing the complex social shopping centre typically requires one worker phenomenon (Carson et al., 2001), per 20 sqm (about 215 sqft) of space and, thus, a particularly when there is little known medium-sized, 50,000 sqm shopping centre about the situation under-investigated employs approximately 2,500 full-time retail (Sarantakos, 2005; Martin and Taylor, staff, plus 50-70 workers in management and 1986; Glaser and Strauss, 1967). support functions such as tenant relations, c) The GTM is employed in assessing the administration, marketing, cleaning, security, employment opportunities that are maintenance, gardening, and parking. A survey possibly generated by a proposed new conducted by Malaysian Shopping Malls shopping centre development since it is Association’s (PPK Malaysia) shows that there not possible to make a generalization on are currently 671 malls with the net-lettable area these opportunities without going to the ranging from a minimum of 50,000 square feet ground and making observations on what (sqft.) to 2.2 million square feet (sqft) and they has actually taken place. This study is provide approximately 56,600 direct interpretative (Carson et al., 2001). employments (Eugene, 2018). Employment is d) There is a need for inductive theory generally the most important means of obtaining development to explain the pattern of adequate economic resources which are essential employment distribution; the types of for economic well-being and full participation in employment exist in a shopping centre by today’s society (Waddell and Burton, 2006). its business mixes classification, its Simply, the development of a shopping centre distribution percentages placement and its results in many microeconomic variables density ratio. prospering the local standard of living as well as providing a better quality of life for the Theoretically, in every development process, community. a feasibility study is essential at the early stage of the project’s life cycle before entering into the

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development actual construction works (Huh et al., 2012). A purpose of offering a logically consistent set of feasibility study involves identifying and data collection and analysis procedure aimed at analyzing the strengths and weaknesses of a developing a theory (Martin & Turner, 1986; project and at the same time, determining the Charmaz, 2003; 2006; Evans, 2013). The project’s opportunities and threats within the emphasis in the GTM is theory development construction industry. Therefore, in the context (Strauss & Corbin, 1994). However, Punch of a shopping centre development project, the (1998) argued that GTM is not a theory at all; it benefits in terms of employment opportunities is a method, an approach, and a strategy, hence generated are one of the essential elements that it is best defined as a research strategy whose should be listed in the feasibility study, and thus, purpose is to generate theory from data. the Local Authority can ensure that the project ‘Grounded’ means that the theory is generated development is in line with the needs of a on the basis of ground data; the theory will, community, is feasible and is worth pursuing. therefore, be grounded in the data. ‘Theory’ here The numerical analysis of employment means that the objective of collecting and opportunities possibly generated by the analyzing the data is to conceptually explain a development of a shopping centre helps to new phenomenon of interest. strengthen the evidence for its desirability The GTM allows for the identification of among the local community. Besides, it patterns in data that can help to drive a theory contributes to the improvement of the feasibility that is empirically valid (Glaser and Strauss, analysis report, and indirectly improves the 1967; Martin and Turner, 1986). This is so government’s policy in the planning permission because the theory-building process is so during the development process. intimately tied to the evidence that it is very The analysis of employment opportunities likely that the resulting theory will be consistent demonstrated in this paper is carried out on the with the empirical observation (Fernandez, basis of the planned net-lettable area (NLA) of a 2004). By and large, it can be said that GTM proposed new shopping centre. However, starts with some inductive logics (inductive indirect employment opportunities possibly methodology) with which the theory is created out of the proposed development of this systematically generated from a data collection shopping centre such as kiosks, cleaning, process. security, maintenance, gardening, and parking A few studies have stated that in the GTM, are excluded in the analysis. nothing happens in a vacuum (Glaser, 1978; The paper is organized as follows. Section 2 Glaser and Straus, 1967); everything is discusses the grounded theory in order to integrated; it is an extensive and systematic identify the framework of the study. Section 3 general methodology (independent of research presents the data and methodology. Section 4 paradigm) where actions and concepts can be analyses the outcome of the survey data. Section interrelated with other actions and concepts. 5 briefly discusses the limitation of the study. This can be seen from a researcher’s ‘top-down’ The conclusion of the study is presented in work process - from theory to hypotheses to data Section 6. to add to or to contradict the theory (Creswell and Plano Clark, 2007). Therefore, it can be seen 2.0 THE GROUNDED THEORY that in principle GTM is a deductive method. METHOD (GTM) GTM allows the researcher to develop a theoretical account of the general features of the 2.1 Background topic while simultaneously grounding the account in empirical observation of data. In The GTM, developed by two sociologists, theory, the deduction begins with a general and Barney Glaser and Anselm Strauss in the early ends with a specific one, with arguments based 1960s, is an inductive methodology that allows a on law, rules and other widely accepted researcher to develop a conceptual account on principles are best expressed deductively some phenomena of interest through empirical (Trochim, 2006). observations of the real-world data with a

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

2.2 The GTM in Measuring Employment a common misperception in GTM is that Opportunities researcher enters the field without any knowledge of prior research. Therefore, it is This paper applied GTM with mixed mode- suggested that the study should be aware of the designs, which combines a qualitative and existing literature and the influence that might quantitative data in measuring employment have on their observations (Suddaby, 2006). opportunities generated form a proposed Generally, the employment generated or shopping centre development. Although the created from a single property is measured on GTM tends to rely on qualitative data, the basis of employment density ratio (EDR), quantitative data may add more precision and measured as: clearer understanding of the phenomenon of interest as well as leads to unique insights a) Square feet or square meter of required (Bhattacherjee, 2012). The jointly use of both floor area per person (Hamid, 2006; qualitative and quantitative data pertaining to the Deloitte, 2010). employment generated by a shopping centre b) Average floor space per full-time significantly lead to the development of the equivalent (FTE) member of staff parameter of employment opportunities (Dancer, 2015). measurement. c) Average number of employees per unit of In this paper, a GTM with a systematic floor space provided (Fleming, 2014). design is used. In systematic design, the study starts with the most specific information which This means that EDR is used as a measure of collected and summarized and moves to the building use intensity (BUI) and it is an most abstract characteristics which were able to indicator of how much space each person be found through analyzing the data. However, occupies within the workplace. Therefore, EDR this study starts with the deductive approach, by is applied as a basis for measuring the applying the existing theory of employment employment opportunities generated and then density ratio (EDR) as a basis of measurement. the approach inductively generates theory from Then, a ground survey on several the empirical set of data collection. comparable groups is conducted to collect all the Theoretically, the GTM in this context of study relevant data for measuring the employment adopts inductive as well as deductive orientation opportunity generated by a shopping centre. As in investigating an issue. The application of per LaRossa (2005) and Bowen (2005), it is EDR as a basis is a deductive approach and the important to review prior research before theory generated from the data collection is an entering the field; one needs to know what inductive approach. research exists and how others have treated a Table 1 shows the business components of a particular topic so one can determine what shopping centre. As per Deloitte (2010) and additional research is needed. Prior studies Dancer (2015), the EDR of business components provide a foundation, background, and context in shopping centre vary substantially in terms of of new research; it established a bridge between types of business (Table 2). The term the (proposed) research project and the extant “components in a shopping centre” refers to the knowledge base. According to Suddaby (2006), retail mixes or retail business classification.

Table 1: Retail Mixes Classification

Mustel group (2010) Reikli (2012) ULI & ICSC (2008) Carter & Allen (2012) Comparison: Children’s Wear Clothing and Accessories Family Apparel Apparel Fashion Wear Clothing and Accessories Women’s Apparel Footwear, Luggage & Fashion Shoes Shoes Men’s Apparel Accessories Cosmetics, Health, Bath &Beauty Health – Beauty Drug, Personal Service Jewellery Jewellery, Watches & Accessories Pet and Pet Food Other Retail Card and Gifts Electronics & Appliances Sportswear Hobby, Special Interest Fast Food

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

Multimedia, Books & Music Books, Gifts Gifts, Hobby, Special Interest Home Furnishings Home Furnishings & Accessories Jewelry-Accessories Jewelry Women’s shoes Home Improvements Hypermarket Food Men’s & Boy’s Shoes Food Court and Other Toys, Hobbies,& Pets Food Service, Food Fast Food Food Sporting & Recreational Goods Supermarket Food Specialty Food Convenience: Furniture Home Furnishings Grocery & Specialty Food Home Appliances Home Appliances – Music Pharmacy Showroom Automotive Alcohol & Tobacco Hardware Store Building Materials – Garden Services Home Furnishings Home Furnishings Personal Service, Other Food & Beverage: Services Retail, Financial, Offices Casual & Sit Down Dining/ Entertainment Entertainment, Community Restaurant Entertainment & Leisure

Table 2: Employment Density Guide (Deloitte, 2010; Dancer, 2015)

Use Class Sub-category Sub-sector 2010 Density (sqm.) 2015 Density (sqm.) A1 High Street 19 15 - 20 Retail (NIA) Food store 17 15 - 20 Retail Warehouse 90 90 A2 Finance & Professional Services (NIA) 16 16 A3 Restaurants & Cafes (NIA) 18 15 - 20 D2 Budget 100 Fitness Centres Mid-Market 65 65 Family Cinema (GIA) 90 200* Visitor & Cultural Attractions (GIA) 36 30 – 300 Amusement & Entertainment Centres (GIA) 70 70 *The cinema industry has been going through major restructuring in recent years, such that it has diversified the range of facilities and improved the technology. Much of the cinema ticketing has now moved online, reducing the need for cashiers and ticket sales staff within the cinema itself, replacing them with self-service collection machine. Thus, within the greater range of facilities, employment densities within this market segment tend to be higher.

Generally, the determination of components analyses the percentages distribution placement in a shopping centre is related to the concept of of tenant mixes for the convenience shopping tenant selection. As per Reikli (2012), tenant- centre, which generally quite similar to the selection study practically seeks to answer two regional and community shopping centre. The questions; (1) what components or retail mix distributions percentage space are as follows: should be included in a shopping centre? (2) 27% of food store or food specialties How much space should these components or (hypermarket or supermarket), 16% of fashion retail mix get? In tenant selection, Baker (1999) and accessories, 9% of services, 8% of leisure analyzed the International Council of Shopping and entertainment, 7% of shoes, 7% of health Centre’s data and found that 45% of the floor and beauty, 6% of coffee and restaurant, 6% of space was assigned to fashion-wear retailer sport equipment and fashion, 6% of household, (including women and family wear, and shoe); 5% of kids and toys, and 3% of multimedia and 22.5% to home furnishing; 11.25% to home electronics. According to ICSC Research and appliances, books, sport equipment, personal CoStar Realty Information, Inc., (2017), services and jewel; and 6.1% to food (including convenience shopping centre provides for the fast food and specialty food). In recent year, the sale of personal services and convenience goods appearance of shopping centre shows a great similar to those of a community and regional progress; consequently, the patterns of tenant shopping centre. They are usually anchored by mixes are growing and changing. Mouton (2014) some other type of personal/convenience service

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development such as a supermarket, hypermarket or employment, which will make the results for a department store. However, they are different in particular shopping centre of interest term of size (sqft) and the merchandising; questionable. Therefore, to achieve the objective regional shopping centre offers general of measuring employment opportunities possibly merchandise or fashion-oriented, while the generated by a proposed development of community and convenience shopping centre shopping centre, a ground survey should be offer general merchandise or convenience- conducted employing a constant comparative oriented. method (CCM). CCM is one of the strategies in Bruwer (1997) and Greenspand (1987) the GTM. It entails an iterative process of argued that tenant mix is an art or 'puzzle' concurrent data collection and analysis which performed by a management team of a shopping involves “systematic choice and study of several centre and it is not a static condition. Yuo et al. comparison groups” (Cho & Lee, 2014), and it is (2004) argued that tenant mix always changes important in developing a theory that is over time as do the customer preferences and grounded in the data (Glaser and Strauss, 1967). fashion trends. Consequently, the management A ground survey must be conducted on several team has to adjust the tenant mix constantly to comparable groups within a cluster of keep with the market trends. Nevertheless, the operational shopping centre. best strategy for tenant selection merely sticks to the concept that "a good tenant selection should include a variety of compatible or complementary retail/service providers as well as sufficient public facilities/services, and constantly enhance the quality of shopping centre environment as well as satisfy shopper’s need" (Yuo et al., 2004). Generally, in the early stages of the development of a shopping centre, the developer still has not yet determined the tenant selection, so, there is no information on such data.

Therefore, with the objective in mind and based Figure 1: Step in Measuring Employment Density and Its on the existing literature, the authors have set Variables three research questions, as follow: (Author’s concept)

a) What are the components exist in a Generally, the GTM offers systematic and shopping centre? flexible guidelines for data collection and b) What is the percentage distribution of analysis to construct theories which consist of placement of each retail mix classes from abstract conceptualizations of substantive the total of NLA? problems. In this paper, CCM and the logic of c) What is the employment density of each theoretical sampling are applied to collect only retail mix classes? those data, in those categories, which will provide meaningful comparisons and lead to the The steps for assessing the employment density sought-after theory. Theoretically, CCM is used of a shopping centre development project are to develop concept from the data by coding and depicted in Figure 1. analyzing at the same time (Taylor & Bogdan, Although the employment density figures in 1998). It incorporates four stages, namely Table 1 and Table 2 can be used as a basis for comparing incidents applicable to each category, measuring employment opportunities discussed integrating categories and their properties, in this paper, the real-world situation of delimiting the theory, and finally writing the employment density of a shopping centre is theory (Glaser & Strauss, 1967). Throughout different in each country. Accordingly, we the four stages of the CCM, a researcher might compute various possible densities of continually sorts through data collection,

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

analyzed and code the information, and In conclusion, it can be said that the GTM reinforces theory generation through the process begins with the deductive approach, which is an of theoretical sampling. Bryman and Bell (2007) adoption of the theory of EDR as a basis of highlighted that the most important tools of measurement, and then from the ground data on GTM are constant comparison and theoretical a systematic research, a theory is generated (as sampling together with coding and theoretical per Figure 3). saturation. Figure 2 shows the process of GTM followed in this study.

) What are the components existing in a shopping centre? Research questions a b) What is the percentages distribution of placement of each retail mix classes from the total NLA? c) What is the employment density of each retail mix classes?

Theoretical sensitivity Theory of EDR is applied as a basis. Then the approach inductively generates theory from the empirical set of data collection through ground survey. Deductive approach

Constant comparison A few selected operational shopping centres

Decision to collect secondary data/documentation from Management Team of Theoretical sampling comparable groups (answering research question ‘a’ & ‘b’) and verbal conversation/interview survey on retailers/workers of every comparable group (answering research question ‘c’).

Data collection

Coding

Selective coding Open coding Axial coding All categories unite around one/ more central Themes, sub-categories, Emerging as a category; a systematic discovery of substantive and core categories central category relations between the other categories

Inductive approach Inductive

Saturated categories Sorting, writing/ theorizing, cross referencing with literature

Conceptualize / theorize Parameters of measurement

Figure 2: The Process of GTM (Author’s concept)

Employment quotients (EQ) Theory & employment density (ED) Theory of EDR figures

Retail mix class and its

percentage distribution of INDUCTIVE DEDUCTIVE placement Constant Comparison

Data

Figure 3: Inductive Approach with Deductive Orientation (Author’s concept)

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

2.3 Development of Employment Density general (linear) equation has to be developed as Parameters follows: 푦 = 푎푥 + 푏 The Business Dictionary (2019) defines a parameter as a measurable and constant or where: variable characteristic, dimension, property, or “x” is an independent variable (predictor value selected from a set of data (or population) variable), and “y” is a dependent variable considered to be essential to understand a (criterion variable). “a” and “b” are the situation (or to solve a problem). Yee and coefficients, which are often real numbers. The Bradford (1999) argued that a density parameter coefficient may be considered as parameters of is a building density, which is the square footage EDE. To yield a meaningful equation for non- of building per number of employees. In the zero values of b, the coefficients are required not context of employment density, a parameter to be all zeros. refers to the EDR which is measured in square In the context of this study, “a” refers to the feet or square meter of required floor area per parameter, which is EQ () for retail classes, person. while “b” refers to the autonomous employment From the ground survey of comparable (). “y” is employment density (ED) and “x” is groups, the data of employment density (ED) for net-lettable area for retail mix class (NLAj). every retail mix class of each comparable group Therefore, ED = f(NLAj; ; ), expresses in is obtained and calculated. This comes with Equation 2. what is called employment quotient (EQ). EQ gave a value of fraction or ratio. It is expresses as: EDE =  + NLAj (Equation 2)

EQ = NW/TNA (Equation 1) Theoretically, an autonomous describes

things that function separately and where: independently (Merriam-Webster, 2019), or EQ = employment quotient does not explicitly depend on the independent NW = total number of workers variable. For example, autonomous employment TNA = total net-lettable area of floor space in property real estate refers to the employment by retail mixes class existed on a particular site which not results

from any property development. This type of For example, if TNA = 400 sqft and NW = 4 employment considered automatic and workers, EQ = 0.01. The effect of EQ is such necessary, whether the property being developed that any increase in the total NLA by retail mix or not; such as employment created from a has multiple impacts on the number of workers. business of car parking, stalls and etc. This means, for each square foot of NLA, 0.01 In this study, autonomous employment is the number of worker will indirectly be created. number of employment even if NLA = 0 for all Theoretically, EQ differs by retail mix class. j. It can be anything such as indirect on-site Therefore, the measurement of employment employment or on-site seasonal employment as density of a shopping centre comes with a set of a result of the proposed shopping centre. Thus, EQ based on retail mix class, then; those employment quotients will form an equation of autonomous employment () refers to the employment density. Simply, the employment employment derived from special event density equation (EDE) is derived from a set of entertainment (SEE) held in a shopping centre figures of employment quotients. (such as Hari Raya Aidilfitri, Chinese New The equation above considers a perfect Year, Christmas, Deepavali, etc), for which situation, but in the complex real-world, no one some common area in a shopping centre is let believes that we can capture precisely the out but closed on other days. Those events complexities of economic and business created business opportunities for retailers or behavior. Therefore, in developing EDE, a tenants to promote their products through the floor space provided for SEE utilization.

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

Autonomous employment () in this study 2) Employment quotient (EQ) for SEE. For any came from the measurement of three SEE, the shopping centre management abovementioned elements, as follows: allocates CA that will be rented out and determines the number of tenants (T) to be 1) Auxiliary space is the extra or temporary placed in the CA. Usually; one tenant has an space used by a shopping centre average worker (W) of two people. management for some specialized events as Therefore, EQ for SEE is measured by mentioned before. Auxiliary space dividing the total number of workers for categorized as non-lettable area (NoLA), every tenant with the total square feet area which expressed as follows: of CA, expressed as follow:

NoLA = GFA − NLA EQ for SEE = (T × W)/CA

Most of literatures describe NoLA as a 3) SEE intensity (SEEi). SEEi is the frequency common area; however, NoLA specifically of SEE held in a shopping centre (how many refers to the not commonly lettable area times of SEE per years). This varies from including the common area. The one shopping centre to another and, thus, components of NoLA vary among shopping will need to be ascertained from the centre (for example mezzanine, exhibition management team. space, common area, sidewalks, foyer, etc) (depicted in Figure 4). During the SEE, With all the relevant elements, the measurement some space from NoLA will be let out for of autonomous employment is computes as rent; it usually refers to a concourse area follows: (CA). A concourse is often located where many paths or hallways meet (Wikipedia,  = CA × EQ × SEEi (Equation 3) 2019; Merriam-Webster, 2019). CA is large enough for many people to congregate there where; and is suitable for use as the SEE space. CA  = autonomous employment usually forms some percentage (determined CA = concourse area (% from NoLA) by the management team) of the total EQ = employment quotient for SEE NoLA; intensity (average space allocated for CA = % from NoLA each worker during these event) SEEi = intensity (how many times) of NoLA special event entertainment

Common area Concourse area (CA) Therefore, an employment density equation (EDE) developed in this study is expressed as “Belonging to or shared by two or per Equation 2 above. more individuals or by all members “The wide, open area, open of a group” space or hall where crowds gather” 3.0 DATA AND METHODOLOGY (Wikipedia, 2019) (Wikipedia, 2019; Merriam- Webster, 2019) Based on the famous dictum of Glaser (2002), Common area of shopping centre (Mike, 2014): “all is data”, the GTM utilizes many forms of • Roofs and structure • Mezzanine, data from observations, interviews, and • Entrances and malls Customer • exhibition space, area and facilities • lobbies, documents, all of which could contribute to • Service corridors and stairs • sidewalks or corridors generating a substantive theory. In this study, • Delivery and loading areas • External walkways and CCM-GTM design was employed utilizing pavements data/information from six operational shopping • Car park and roads (a) Use for SEE • Services supporting the above centres (selected as a comparable group) in , called CG6. The selection was Figure 4: General Concept of NoLA based on the occupancy rate - only a shopping

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development centre having an occupancy rate of over 80% in measuring the autonomous employment, was selected. As per Richard Chan, Malaysia namely CA, EQ for SEE, and SEE intensity. Association for Shopping and High-Rise These data also collected from the Complex Management, a shopping centre with documentation provided by the management an occupancy rate of over 80% is considered team of the CG6. From all the CG6, only well-performing (The Star Online, 2017). The three of them are productive in the context selected comparable groups comprised of of SEE, namely Galleria@Kotaraya, Galleria@Kotaraya, Angsana Johor Bahru Mall, Angsana Johor Bahru Mall, and Paradigm Paradigm Mall Johor Bahru, Sutera Mall, Mall Johor Bahru. Table 4 shows the output Perling Mall, and Pelangi Leisure Mall. A of the data obtained from the three ground survey was conducted on those six comparable groups aforementioned. operational shopping centres, and all the data collected to answer the research question The second stage involves determining (Section 2.2, paragraph 9) were constantly employment density (ED) of every component compared for their commonalities and or retail mix classes. A simple structured verbal- variations, then trace out to the emerging pattern conversation or interview was conducted among and theory. Finally, the theory of employment retailers or workers for each retail mix classes in generation was conceptualized. Data collection order to obtain the figure of ED. This simple was carried out in two stages. structured verbal-conversation or interview The first stage dealt with the management conducted by addressing a specific aspect team of each comparable group. It has two namely the number of workers for the following objectives: respondents’ retail business. A dimensional stratified random sampling procedure was used 1) Identifying the components or retail mix for selecting the respondents. In this study, the classes existing in a shopping centre and sample of respondents was arranged according determining the percentages distribution to ‘retail mix classes’ in the CG6; identifying the placement of each retail mix classes from dimensional strata as per Table 5, and then, the total NLA. Data on the retail mix and its applying the random selection procedure to percentages distribution placement from the select the subjects for each of the dimensional total NLA were collected from the stratum. The respondents were randomly chosen documentation provided by the management but carefully selected based on their business team of the CG6. By enlisting the classification to ensure all the retail mix classes components or retail mix classes (Table 1) were included. As many as 660 respondents and from the documentation obtained from representing all retail mix classes were selected the management team, this study came up from the CG6; 117 from Galleria@Kotaraya, with many classifications, making it difficult 165 from Angsana Johor Bahru Mall, 295 from to make a comparison of the results. To Paradigm Mall Johor Bahru, 48 from Perling overcome the problem, we developed a Mall, and 35 from Pelangi Leisure Mall. All the concept of retail mix classes as per Table 3, data collected were then compared constantly resulting in twenty-one components of retail among the CG6 to find a common pattern for mix classes. The retail mix classes and its developing an equation of employment density corresponding percentage of placement for parameters. The ED of every components or each comparable group are shown in Table 3 retail mix classes of each comparable group was and Figure 4. operationalized to calculate the EQ as per 2) Measuring autonomous employment. As Equation 1. The EQ by retail mix classes of each mentioned before, there were three comparable group are shown in Table 6. important elements that must be considered

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

Table 3: Percentages Distribution Placement of Retail Mix Classes of CG6

Angsana Paradigm Pelangi Galleria@ Johor Mall Sutera Perling Retail Mixes Classification Leisure Kotaraya Bahru Johor Mall Mall Mall Mall Bahru Mum & Baby Product 0.00% 0.47% 0.09% 0.00% 0.00% 0.00% Clothing/Fashion wear 7.51% 16.48% 14.39% 20.30% 4.04% 0.06% Shoe ware 1.00% 2.26% 1.31% 2.49% 4.95% 0.00% Pet shop 0.00% 0.00% 0.14% 0.00% 0.00% 0.00% Supermarket 10.97% 29.36% 21.07% 19.96% 26.60% 56.24% Health & Beauty 4.80% 2.93% 3.36% 6.61% 5.90% 1.67% Furniture 0.21% 0.00% 0.93% 0.00% 0.00% 0.82% Sport & Fashion 0.00% 0.76% 1.08% 0.00% 0.00% 0.12% Showroom 0.00% 0.00% 1.65% 0.00% 0.00% 0.00% Book & gift 0.73% 3.78% 4.05% 0.00% 8.11% 0.42% Hardware store/DIY 4.73% 0.00% 0.49% 0.00% 13.77% 3.30% Mobile phone/CD/DVD 0.68% 1.91% 0.97% 1.96% 3.45% 0.39% Home furnishing 0.00% 13.10% 13.34% 3.85% 0.00% 0.00% Jewelry/accessories 1.41% 1.07% 0.97% 0.56% 1.18% 0.00% Services 44.28% 1.18% 0.36% 1.45% 3.85% 0.96% F & B (restaurant, food court) 9.37% 6.39% 10.14% 13.97% 7.15% 2.07% F & B (coffee, bakery, cake) 1.47% 0.56% 1.67% 9.77% 0.00% 0.27% Entertainment 0.00% 11.51% 5.58% 4.84% 0.24% 14.97% Bag/Luggage 0.00% 0.58% 0.30% 0.72% 0.37% 0.10% Optic/Watch 0.00% 1.52% 0.77% 1.27% 2.18% 0.41% Cinema 0.00% 0.00% 4.88% 0.00% 10.40% 0.00% Vacant 12.83% 6.12% 12.46% 12.25% 7.81% 18.21% Others Total 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%

PERCENTAGES DISTRIBUTION PLACEMENT OF RETAIL MIX CLASSES OF CG6

180% Paradigm Mall Johor Bahru 160% Galleria@Kotaraya 140% Perling Mall 120% Pelangi Leisure Mall 100% Sutera Mall

80% Angsana Johor Bahru Mall

60%

40%

20%

0%

Figure 4: Percentages Distribution Placement of Retail Mix Classes of CG6

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

Table 4: CA, ED for SEE, and SEE intensity of CG6

Element Collected Data and Calculation Outcome (Average of output) Comparable Group 1 CA = 6,000 sqft NoLA = 1,031,795 – 401,324.5 = 630,470.5 sqft

GFA NLA % of CA = (6,000/630,470) x 100 = 0.95%

Comparable Group 2 CA = 0.8% x 1,310,950 = 10,488 sqft Concourse Area (CA) % of CA = 1.43% x NoLA GFA % of CA = 0.8%

Comparable Group 3 CA = 9,219 sqft NoLA = 546,530 – 184,383 = 362,147 sqft

GFA NLA % of CA = (9,219/362,147) x 100 = 2.55%

Comparable Group 1 Average number of tenant per SEE = 50 tenant Employment quotient (EQ) Average number of worker per SEE = 50 x 2 = 100 of special event EQ for SEE = 100/6,000 = 0.0167 entertainment (SEE) EQ for SEE = 0.0104 Average worker per tenant Average number of tenant per SEE = 30 tenant = 2 people Average number of worker per SEE = 30 x 2 = 60 EQ for SEE = 60/10,488 = 0.0057

Comparable Group 3 Average number of tenant per SEE = 40 tenant Average number of worker per SEE = 40 x 2 = 80 EQ for SEE = 80/9,219 = 0.0087

Special event entertainment Comparable 1 intensity (SEEi) SEEi = at least 30 times

Comparable 2 SEEi = at least 20 times SEEi = 25

Comparable 3 SEEi = at least 30 times

Therefore, autonomous employment () = 퐂퐀 × 퐄퐐 × 퐒퐄퐄퐢  = 1.43% (NoLA) x 0.0104 x 25 = 0.0037 NoLA

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

Table 5: Sample Size of CG6 Using Stratified Random Sampling Procedure

CG6 Galleria@Kotara Angsana Mall Paradigm Mall Perling Mall Pelangi Leisure ya Johor Bahru Johor Bahru Mall Mall Retail Mix Classes Total Sample Total Sample Total Sample Total Sample Total Sample Mum & Baby Product 0 0 2 2 1 1 0 0 0 0 Clothing/Fashion wear 20 20 59 53 48 48 9 9 1 1 Shoe ware 2 2 10 10 14 14 3 3 0 0 Pet shop 0 0 0 0 1 1 0 0 0 0 Supermarket 0 2 1 1 12 3 1 1 1 1 Health & beauty 8 8 12 12 36 35 8 8 6 6 Furniture 1 1 0 0 1 1 0 0 1 1 Sport & Fashion 0 0 3 3 3 3 0 0 1 1 Showroom 0 0 0 0 1 1 0 0 0 0 Book & gift 1 1 4 4 22 16 1 1 3 3 Hardware store/DIY 2 1 0 0 2 1 1 1 2 2 Mobile phone/CD/DVD 4 4 9 9 24 23 6 6 3 3 Home furnishing 0 0 13 13 18 17 0 0 0 0 Jewel/accessories 7 7 6 6 9 9 3 3 0 0 Services 37 37 9 9 10 8 7 4 6 4 F & B (restaurant, food court) 24 24 34 22 60 48 5 5 3 3 F & B (coffee, bakery, cake) 10 10 3 3 49 46 0 0 3 3 Entertainment 0 0 4 4 7 4 2 2 3 3 Bag/Luggage 0 0 2 2 4 4 1 1 1 1 Optic/Watch 0 0 12 12 12 11 3 3 3 3 Cinema 0 0 1 1 1 1 Vacant 36 24 110 13 12 Total 154 117 207 165 445 295 65 48 49 35 Notes: Due to the complex analysis where more than one category of an independent variable was measured, the sample size was calculated using a sample proportion, which was the ratio of the sample size to the population size (Chua, 2016). Using this concept, the sample size of respondent aforementioned is sufficient, as the value of the sample proportion is more than 5%.

Table 6: Employment Quotient (EQ) of the CG6

Galleria@ Kotaraya Pelangi Johor Bahru Angsana Mall Paradigm Perling Leisure Retail Profile Mall Johor Bahru Mall Mall Mall Mum & Baby Product 0.0036 0.0036 Clothing/ Fashion wear 0.0046 0.0049 0.0030 0.0064 0.0155 Shoe wear 0.0022 0.0036 0.0030 0.0026 Pet shop 0.0033 Supermarket 0.0027 0.0011 0.0021 0.0012 0.0007 Health & Beauty 0.0062 0.0054 0.0051 0.0067 0.0152 Furniture 0.0076 0.0016 0.0021 Sport & Fashion 0.0050 0.0023 0.0110 Showroom 0.0006 Book & gift 0.0030 0.0035 0.0056 0.0012 0.0062 Hardware store/ DIY 0.0013 0.0009 0.0010 0.0018 Mobile phone/ CD/ DVD 0.0101 0.0042 0.0099 0.0052 0.0091 Home furnishing 0.0028 0.0047 Jewellery/ accessories 0.0056 0.0102 0.0040 0.0104 Services 0.0064 0.0080 0.0086 0.0088 0.0063 F & B (restaurant, food court) 0.0097 0.0122 0.0063 0.0108 0.0066 F & B (coffee, bakery, cake) 0.0162 0.0080 0.0091 0.0135 Entertainment 0.0009 0.0010 0.0200 0.0011 Bag/luggage 0.0021 0.0033 0.0065 0.0083 Optic/watch 0.0070 0.0060 0.0071 0.0072 Cinema 0.0005 0.0015

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

In the GTM, reducing the data into sector’s core services to the community in a one- manageable units and coding information are an stop centre). Therefore, the placement of retail integral part of the analysis process (Miles and mix was more for services. Huberman, 1994). The data in this study were Appropriate retail mix placement has been a analyzed using the descriptive statistics which long-term concern for the shopping centre’s comprises graphs, charts, tables and also the management team and researchers. However, calculation of various descriptive measures such there is no hard-and-fast rule for the best as average, variation as well as percentiles strategy for retail mix placement, so the (Larson, 2006). In analyzing data, each management team merely sticks to the interpretation and finding were compared to find fundamental concept, whereby a good retail mix the commonality, variation, then, emerging should include a variety of compatible pattern and theory. Based on the outputs as per retail/service providers, sufficient public Table 4 and Table 6, the analysis proceeded to facilities and services. Nevertheless, the most developing EDE for estimating employment important aspect is the anchor tenant as per opportunities from the case study. Discussion Kyriazis and Cloete (2018). An anchor tenant follows in the next section. will have the most floor space and generates the largest of a shopping centre’s business space. 4.0 RESULT AND DISCUSSION Before analyzing the retail mix placement, there was one important component that should 4.1 Retail Mix Classes be excluded from the analysis, i.e. cinema. It needs a different calculation for determining Table 3 and Figure 4 show the retail mix classes floor space. Generally, the number of halls or of the CG6. Each percentage of placements from screens determines the cinema floor space (Park the total NLA was different among them. and Ham, 2016; website of Independent Cinema However, four of them have quite similar retail Office. There is no specific measurement for mix placement, namely Angsana Johor Bahru determining the number of halls or screens for Mall, Perling Mall, Sutera Mall and Paradigm cinema. It depends on the consideration and Mall Johor Bahru. Retail mix placement of decision of the developer for the said project. Galleria@Kotaraya showed a significant However, the existing information pertaining to difference because of its function, mainly as a the details of cinema in Malaysia (Wikipedia shopping centre, besides functioning as an Website, 2019) (Table 7) can be adopted as a Urban Transformation Centre of Johor (UTC basis of measurement. Johor) (providing government and private

Table 7: Several Cinemas in Johor Bahru (Wikipedia Website, 2019)

Cinema Total Halls Seats Operator City Square 14 2776 mmCineplexes Paradigm Mall 16 2107 AEON Tebrau City 10 1731 TGV Cinema Toppen Shopping Centre 11 1716 TGV Cinema AEON Bukit Indah 9 1614 TGV Cinema KSL City 8 1378 MBO Cinema Plaza Tasek/Tasek Central 3 649 Lotus Five Star Perling Mall 3 582 Blockbuster Cineplex

Table 7 shows the total halls for cinemas in cinema which comprises 16 halls and covering Johor Bahru are in the range of 3 to 16 halls. an area of 64,038 sqft, while, Perling Mall has Results from the ground survey show that the the smallest cinema which comprises only 3 Paradigm Mall Johor Bahru has the largest halls and covering an area of 8,762 sqft.

13:1 (2019) 50-72 | utm.my/intrest | ISSN: 1832-8505 |

Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

Generally, a cinema has an average of 8 unit of TsqftExCIN = Total sqft of NLA without halls (as per Wikipedia website, 2019), thus, this cinema, study assumed a standard number of halls in a R1,2,3… = Percentages retail mix based cinema to be 8 units. The calculation of halls on its classes quotient is expressed as follows: In this study, retail mix placement was Qsh = TSH/TCin (Equation 4) determined by analysing the percentages derived from the CG6. From the analysis, a figure of where, percentage placement for every retail mix in a Qsh = Halls quotient, shopping centre was calculated. Although the TSH = Total unit of halls, percentages placement of retail mix can change TCin = Total floor area of cinema according to any situation and factor, Figure 5 can be used as a basis for determining the Thus, from these data, an analysis was made percentage placement of retail mix. Furthermore, to calculate the quotient of halls giving an this figure seemed to be ideal because it average figure of 0.00029. Accordingly, the total comprised all retail mix classifications with the sqft of floor space for cinema with 8 halls is consideration of market trend. expressed as follows: Figure 5 show that the anchor tenant (supermarket) occupied the largest percentages 8 of distribution placement. This was aligned with TCin = Kyriazis and Cloete (2018), and Mouton (2014). 0.00029 Generally, anchor tenant is pivotal in the = 27,590 sqft creation of the image of the shopping centre, attracting shopper traffic and other tenants to the Therefore, before calculating the percentage shopping centre (Kyriazis and Cloete, 2018). placement of retail mix classes, the total NLA The anchor tenant is acknowledged as an for the subject property should deduct the total instrumental in positioning the shopping centre standard area of cinema, as expressed as in relation to its competitors, and therefore, it follows: allocates the largest space for distribution placement in a shopping centre. Although the TNLA − TCin = TsqftExCIN percentages distribution placement of retail mix TsqftExCIN = R1,2,3….(%) (Equation 5) classes in Figure 5 was not exactly the same to Mouton (2014), the pattern of distribution where, placement between the two quite similar and TNLA = Total sqft of NLA of the parallel. subject property, TCin = Are defined above,

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

PERCENTAGES DISTRIBUTION PLACEMENT OF RETAIL MIX CLASSES 0.26% 10.31% 1.15% 2.56% 0.39% 10.61% 0.13% 2.86% 6.93%

7.41% 28.59% 1.46% 9.42%

0.88% 5.46% 3.19%

1.62% 0.81% 3.81% 1.54% 0.61% Mum/Baby (0.26%) Clothing/Fashion (10.31%) Shoe (2.56%) Pet shop (0.13%) Supermarket (28.59%) Health/Beauty (3.19%) Furniture (0.81%) Sport/Fashion (0.61%) Showroom (1.54%) Book/gift (3.81%) Hardware/DIY (5.46%) Mobile/CD (1.62%) Homefurnishing (9.42%) Jewel/accessories (0.88%) Services (1.46%) F&B(1) (7.41%) F&B(2) (2.86%) Entertainment (6.93%) Bag/luggage (0.39%) Optic/watch (1.15%) Vacant (10.61%)

Figure 5: Percentages Distribution Placement of Retail Mix Classes

4.1.1 Validation Result: Percentages Johor Bahru. The Paradigm Mall Johor Bahru Distribution Placement of Retail Mix was adopted as a comparison because it was a Classes new , growing and becoming a focus and the divisions of retail mix placement There are a few techniques of validation and one consist of the variety of compatible retail and of them is a comparison to other models service providers. (Sargent, 2011) whereby various results (e.g., Figure 6 and Table 8 show the percentages outputs) of the simulation model being validated of retail mix classes developed in this study are compared to results of other (valid) models. against the actual percentages of retail mix In the context of this study, the percentages of classes within the paradigm mall. It shows a retail mix placement in Figure 5 were validated similar pattern and a small range of differences by comparing them with the actual percentages in percentages. of retail mix placement of the paradigm mall

PERCENTAGES DISTRIBUTION PLACEMENT OF RETAIL MIX CLASSES (OUTPUTS VS. REAL SITUATION) 35% 30% 25% Paradigm 20% Mall 15% Output 10% 5% 0%

Figure 6: Percentages Distribution Placement of Retail Mix Classes (Output vs. Real Situation)

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

Table 8: Differences Percentages Distribution Placement of Retail Mix Classes (Output vs. Real Situation)

Retail Mixes Classification Differences Mum/Baby 0.18% Clothing/Fashion -4.08% Shoe ware 1.26% Pet shop -0.01% Supermarket 7.52% Health/Beauty -0.17% Furniture -0.11% Sport/Fashion -0.47% Showroom -0.11% Book/gift -0.24% Hardware/DIY 4.97% Mobile/CD 0.65% Home furnishing -3.92% Jewel/Accessories -0.09% Services 1.09% F & B (restaurant, food court) -2.73% F & B (coffee, bakery, cake) 1.19% Entertainment 1.35% Bag/Luggage 0.09% Optic/Watch 0.38% Cinema -4.88% Vacant -1.85% Notes: The differences between them are small, less than 5% except for the supermarket. However, the differences of less than 10% for the anchor tenant (supermarket) are considered acceptable. Usually, percentages placement of the anchor tenant is depending on the size of a shopping centre; the larger the size of a particular shopping centre, the greater of the percentage placement is given to the anchor tenant.

4.2 Employment Density Parameter the EQ figure was based on the average EQ for each retail mix of all comparable groups (Table The EQ in Table 6 was calculated by dividing 9). the total number of workers of a retail business Table 9: EQ by Retail Mix Classes class with the total square footage of floor space of the said retail business class. ED parameter Retail Profile EQ was then derived from the set of employment Mum & Baby Product 0.0036 quotients as mentioned in the previous section. Clothing/Fashion wear 0.0069 The employment quotient was computed as Shoe wear 0.0029 follows: Pet shop 0.0033 Supermarket 0.0016 Health & Beauty 0.0077 NWr Furniture 0.0038 EQr = ∑ (Equation 6) Tsqftr Sport & Fashion 0.0061 Showroom 0.0006 where, Book & gift 0.0039 EQ = Employment quotient Hardware store/DIY 0.0013 r Mobile phone/CD/DVD 0.0077 according to retail mix classes, Home furnishing 0.0038 NWr = Total number of worker Jewelry/accessories 0.0076 according to retail mix classes, Services 0.0076 F & B (restaurant, food court) 0.0091 Tsqftr = Total net-lettable are of floor space by retail mix classes, F & B (coffee, bakery, cake) 0.0117 Entertainment 0.0058 Bag/Luggage 0.0051 Table 6 above shows the EQ for each retail Optic/Watch 0.0068 mix classes of the CG6, and therefrom, the data Cinema 0.0010 were analyzed and then, a set of EQ by retail mix classes was developed. The development of

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

There were twenty-one predictor variables EDE =  + NLAj for one criterion variable. The employment density equation (EDE) was estimated as per The value of autonomous employment () is as Equation 2 above, expressed as: per Table 4 above. Therefore:

ED = (0.0037 x NoLA) + (TsqftMB x 0.0036) + (TsqftCF x 0.0069) + (TsqftSW x 0.0029) + (TsqftPS x 0.0033) + (TsqftS x 0.0016) + (TsqftHB x 0.0077) + (TsqftF x 0.0038) + (TsqftSF x 0.0061) + (TsqftSR x 0.0006) + (TsqftBG x 0.0039) + (TsqftDIY x 0.0013) + (TsqftMC x 0.0077) + (TsqftHF x 0.0038) + (TsqftJA x 0.0076) + (TsqftSV x 0.0076) + (TsqftF&B1 x 0.0091) + (TsqftF&B2 x 0.0117) + (TsqftE x 0.0058) + (TsqftBL x 0.0051) + (TsqftOW x 0.0068) + (TsqftCN x 0.0010) where, TsqftDIY = total sqft Hardware store/DIY ED = total employment density TsqftMC = total sqft Mobile/CD/DVD NoLA = non-lettable area TsqftHF = total sqft Home Furnishing TsqftMB = total sqft Mum & Baby Product TsqftJA = total sqft Jewelry/Accessories TsqftCF = total sqft Clothing/Fashion TsqftSV = total sqft Services TsqftSW = total sqft Shoe ware TsqftF&B1 = total sqft F&B (restaurant, food TsqftPS = total sqft Pet shop court) TsqftS = total sqft Supermarket TsqftF&B2 = total sqft F&B (coffee, bakery, TsqftHB = total sqft Health & Beauty cafe) TsqftF = total sqft Furniture TsqftE = total sqft Entertainment TsqftSF = total sqft Sport/Fashion TsqftBL = total sqft Bag/Luggage TsqftSR = total sqft Showroom TsqftOW = total sqft Optic/Watch TsqftBG = total sqft Book & Gift TsqftCN = total sqft Cinema

4.2.1 Validation of Employment Density (hereinafter referred to as the project) was a shopping centre at Jalan Tampoi, Johor. It was The EDE abovementioned was validated by two built on a 3 ha. flat commercial land. The project following techniques: was planned to be a three-storey building having a gross floor area of 620,000 square feet and net a) Case Simulation let-table area of 480,000 square feet. It was a multi-purpose, one-stop shopping centre that A brief statement of the case study is given here. will offer a range of consumer products. This example gives some perspective of the From the analysis above, the retail mix ‘problem’ at hand; how a shopping centre classification placement and employment development generates employment density were as follows (Table 10): opportunities. The proposed development

Table 10: Simulation of the Proposed Project

Gross floor area = 620,000 sqft Net lettable area = 480,000 sqft Non-lettable area (NoLA) = 620,000 sqft – 480,000 sqft = NLA without cinema (a) = 480,000 sqft - 27,590 sqft = 452,590 sqft Percentages Total ED ED Retail Mix Classes placement(b) (sqft)(c) EQ(d) (person)(e) (person/sqft)(f) Mum & Baby Product 0.26% 1,177 0.0036 4 278 Clothing/Fashion wear 10.31% 46,662 0.0069 322 145 Shoe wear 2.56% 11,586 0.0029 34 345 Pet shop 0.13% 588 0.0033 2 303 Supermarket 28.59% 129,395 0.0016 207 625

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

Health & Beauty 3.19% 14,438 0.0077 111 130 Furniture 0.81% 3,666 0.0038 14 263 Sport & Fashion 0.61% 2,761 0.0061 17 164 Showroom 1.54% 6,970 0.0006 4 1667 Book & gift 3.81% 17,244 0.0039 67 256 Hardware store/DIY 5.46% 24,711 0.0013 32 769 Mobile phone/CD/DVD 1.62% 7,332 0.0077 56 130 Home furnishing 9.42% 42,634 0.0038 162 263 Jewelry/accessories 0.88% 3,983 0.0076 30 132 Services 1.46% 6,608 0.0076 50 132 F&B (restaurant, food court) 7.41% 33,537 0.0091 305 110 F&B (coffee, bakery, cake) 2.86% 12,944 0.0117 151 85 Entertainment 6.93% 31,364 0.0058 182 172 Bag & luggage 0.39% 1,765 0.0051 9 196 Optic & watch 1.15% 5,205 0.0068 35 147 Cinema 27,590 0.0010 28 1000 Vacant 10.61% 48,020 0 Total 100% 480,000 1824 Notes: The figures were based on (b)(d)ground survey of CG6; (c)Total sqft of each retail mix classes = (b)x(a); (e)Employment density = (c)x(d); (f)Employment density per person = (c)/(e)

From the EDE, the total employment density of b) Comparison to the Existing Literature the case study was as follows: Employment density proposed by Deloitte ED = (0.0037 x 140,000) + (1,177 x 0.0036) (2010) and Dancer (2015) as per Table 02 were + (46,662 x 0.0069) + (11,586 x 0.0029) compared with the outcome of this study (Table + (588 x 0.0033) + (129,395 x 0.0016) 11) as follows: + (14,438 x 0.0077) + (3,666 x 0.0038) + (2,761 x 0.0061) + (6,970 x 0.0006) Table 11: Comparison of Employment Density + (17,244 x 0.0039) + (24,711 x 0.0013) Retail mix Sub-sector Employment This + (7,332 x 0.0077) + (42,634 x 0.0038) classification Density by Study + (3,983 x 0.0076) + (6,608 x 0.0076) Deloitte & (sqm) + (33,537 x 0.0091) + (12,944 x 0.0117) Dancer + (31,364 x 0.0058) + (1,765 x 0.0051) (sqm) + (5,205 x 0.0068) + (27,590 x 0.0010) Retail (NIA) High Street 15 - 20 12 - 32 = 2,342 workers Food store 15 - 20 12 - 58 Retail 90 24 - 71 Warehouse As per International Finance Corporation Finance & Professional 16 12 (IFC) (2008), a shopping centre typically Services (NIA) requires one worker per 20 sqm of space, thus, a Restaurants & Cafes (NIA) 15 - 20 8 - 10 medium-sized, 50,000 sqm of shopping centre (a)Fitness Budget 100 Centre Mid- could have employed approximately 2,500 full- 108 Market 65 time retail staff. In the case of ‘subject Family property’, with the total of 57,600 sqm., as many Cinema (GIA) 90-200 93 as 2,342 of full-time retail employment could (b)Visitor & Cultural 30 – 300 87- 155 have been generated. This figure was equivalent Attractions (GIA) (c)Amusement & to 24 sqm of space per worker. A small 70 16 - 93 difference between the outcome (subject Entertainment Centre (GIA) Note: The item of (a), (b) and (c) were separated to shows the property) and the figure cited from literature was comparison value of square meters per person between the existing considered acceptable. literature and the outcome. However, in this study, those items are classified into the same class and therefore, the employment quotient gives the same value.

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

As per Table 11, the differences were contribution to the body of knowledge, considered acceptable for not being too far particularly in the employment analysis of retail between the two. Furthermore, the employment industry. density of different country might vary according to several aspects such as; energy REFERENCES efficiency (sustainable design attempt to reduce energy consumption such as using natural Kyriazis, A. N. and Cloete, C. E. (2018). ventilation rather than energy-intensive air- ‘Tenant Mix in Shopping Centres: South conditioning), economic cycles, the unique Africa and the United Kingdom Compared’, historical background in income, etc (Deloitte, Journal of Business and Retail Management 2010). Research (JBRMR), 12(2). Baker, M. (1999). ‘A review of mall tenant 5.0 LIMITATION space allocation’, ICSC Research. Bhattacherjee, A. (2012). ‘Social Science This study attempted to estimate employment Research: Principle, Methods, and opportunities generated by a proposed shopping Practices’. USF Tampa Bay Open Access centre development project using physical Textbooks Collection. Book 3. Retrieved parameters. Generally, the development of a from: shopping centre will be able to create a wide http://scholarcommons.usf.edu/os_textbooks range of employment opportunities. In this /3. study, however, the analysis did not cover all Bowen, G. (2005). ‘Preparing a Qualitative types of employment. It only measured Research-Based Dissertation: Lessons employment opportunities generated on the basis Learnt’, The Qualitative Report, 10(2), 208- of physical space (net-lettable area – NLA) 222. available within a particular shopping centre. Bryman, A. & Bell, E. (2007). ‘Business Other elements of potential employment such as Research Methods’. 2nd edition. New York: those from kiosks, cleaning, security, Oxford University Press Inc. maintenance, gardening, and parking were not Bruwer, J. de W. (1997). ‘Solving the ideal included in the analysis. Differences in tenant mix puzzle for a proposed shopping autonomous employment among shopping centre: a practical research methodology’, centres were also not analyzed. Property Management, 15(3), 160. Nevertheless, employment density equation BusinessDictionary.com (2019). Parameter developed in this study can be used as a basis for definition. Retrieved from: estimating the number of employment that can http://www.businessdictionary.com/definitio be generated based on the NLA of a new n/parameter.html. proposed shopping centre. Carson, D., Gilmore, A., Perry, C., and Gronhaug, K., (2001). ‘Qualitative 6.0 CONCLUSION Marketing Research’. Sage Publication, London. This study has demonstrated the application of Charles C. Carter & Marcus T. Allen (2012). ‘A GTM for estimating employment opportunities Method for Determining Optimal Tenant that can be generated from a proposed shopping Mix (Including Location) in Shopping centre using employment density equation. This Centres’, Cornell Real Estate View. 10(10). equation was derived from a set of variables Charmaz, K. (2003). ‘Grounded Theory: analyzed from selected comparable groups. The Objectivist and Constructivist Methods’. In GTM was an important tool that has contributed N.K.D.Y.S. Lincoln (Ed), Strategies of to the development of this equation. qualitative inquiry (2nd ed., pp. 249-291). Besides the employment density equation London: Sage. developed in, this paper has also suggested an Charmaz, K. (2006). ‘Constructing grounded ideal set of retail mix in a particular shopping theory: A practical guide through qualitative centre. The outcome of this study made a analysis’. Thousand Oaks: Sage.

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Applying Grounded Theory Method for Measuring Employment Opportunities Generated by a Shopping Centre Development

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