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FORSCHUNGSERGEBNISSE DER WIRTSCHAFTSUNIVERSITÄT WIEN Nicolas Knotzer Product Recommendations in E-Commerce Retailing Applications Nicolas Knotzer - 978-3-631-75452-8 Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access FORSCHUNGSERGEBNISSE DER WIRTSCHAFTSUNIVERSITÄT WIEN Nicolas Knotzer Product Recommendations in E-Commerce Retailing Applications The book deals with product recommendations generated by information systems referred to as recommender systems. Recommender systems assist consumers in making product choices by providing recommendations of the range of products and services offered in an online purchase environment. The quantitative research study investigates the influence of psychographic and sociodemographic determinants on the interest of consumers in personalized online book recommendations. The author presents new findings regarding the interest in recommendations, importance of product reviews for the decision process, motives for submitting ratings as well as comments, and the delivery of recommendations. The results show that opinion seeking, opinion leading, domain specific innovativeness, online shopping experience, and age are important factors in respect of the interest in personalized recommendations. Nicolas Knotzer studied business administration with the focus on information systems, management control and project management. From 2001 to 2006 he joined the Institute for Management Information Systems at the Vienna University of Economics and Business Administration. The author received his doctoral degree in 2006. Nicolas Knotzer - 978-3-631-75452-8 Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access Product Recommendations in E-commerce Retailing Applications Nicolas Knotzer - 978-3-631-75452-8 Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access Forschungsergebnisse der Wirtschaftsuniversitat Wien Band 17 PETER LANG Frankfurt am Main · Berlin · Bern• · Bruxelles· New York· Oxford · Wien Nicolas Knotzer - 978-3-631-75452-8 Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access Nicolas Knotzer Product Recommendations in E-commerce Retailing Applications £ PETER LANG lnternationaler Verlag der Wissenschaften Nicolas Knotzer - 978-3-631-75452-8 Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access Blbllographlc Information published by the Deutsche Natlonalblbllothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data is available in the internet at <http://www.d-nb.de>. Open Access: The online version of this publication is published on www.peterlang.com and www.econstor.eu under the interna- tional Creative Commons License CC-BY 4.0. Learn more on how you can use and share this work: http://creativecommons. org/licenses/by/4.0. Q) =!! This book is available Open Access thanks to the kind support of ZBW – Leibniz-Informationszentrum Wirtschaft. Cover design: Atelier Platen according to a design of the advertising agency Publique. University logo of the Vienna University of Economics and Business Administration. Printed with kindly permission of the University. Sponsored by the Vienna University of Economics and Business Administration. ISSN 1613-3056 ISBN 978-3-631-56622-0 ISBN 978-3-631-75452-8 (eBook) © Peter Lang GmbH lnternationaler Verlag der Wissenschaften Frankfurt am Main 2008 All rights reserved. All parts of this publication are protected by copyright. Any utilisation outside the strict limits of the copyright law, without the permission of the publisher, is forbidden and liable to prosecution. This applies in particular to reproductions, translations, microfilming, and storage and processing in electronic retrieval systems. Printed in Germany 1 2 3 4 5 7 www.peterlang.de Nicolas Knotzer - 978-3-631-75452-8 Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access Abstract The book deals with product recommendations generated by information sys- tems referred to as recommender systems. Recommender systems assist con- sumers in making product choices by providing recommendations of the range of products and services offered in an online purchase environment. The quan- titative research study investigates the influence of psychographic and sociode- mographic determinants on the interest of consumers in personalized online book recommendations. The book starts with an introductory chapter that sets out the research goal and presents the organization of the work. In Chapter 2 the author establishes working definitions, introduces a general classification and presents application models and business goals of recommender systems. Further, a model of the consumer decision process and the relevancy of virtual commwuties for recommendation purposes is described. Chapter 3 reviews functional aspects of recommender systems. Input and output data, measure- ment scales for preference elicitation as well as recommendation methods a.re elaborated in detail. Chapter 4 describes the research model, the hypothe- sis, and the methodology. The results of the empirical study a.re presented in Chapter 5. Structural equation modeling and regression analysis a.re used to verify the hypotheses. The author presents new findings regarding the interest in recommendations, importance of product reviews for the decision process, motives for submitting ratings and comments, and the delivery of recommen- dations. In particular the results show that ophuon seeking, opinion leading, domain specific innovativeness, online shopping experience, and age are impor- tant factors in respect of the interest in online recommendations. The book clos«:>,s with an chapter that summarizes the results, shows limitations of the research conducted, and points out directions for further research. Nicolas Knotzer - 978-3-631-75452-8 V Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access Nicolas Knotzer - 978-3-631-75452-8 Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access Acknowledgements Foremost, I would like to thank my supervisors Prof. Hans Robert Hansen and Prof. Gustaf Neumann. I am very grateful for the discussions, suggestions, and insights that helped me to complete this doctoral dissertation. In the last four years Prof. Hansen has given me a very productive and agreeable working environment and helped me to grow as a researcher as well as a person. Further, I would like to thank my colleagues at the Institute for Manage- ment Information Systems and the Institute for Information Systems and New Media, especially Maria Madlberger, Bernd Simon, Horst 1\·eiblmaier, and Christina Stahl. Last, but not least, my thanks go to my family and Katrin. I am very indebted to you. Without your support and patience the writing of this book would have not been possible. Nicolas Knotzer - 978-3-631-75452-8 vii Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access Nicolas Knotzer - 978-3-631-75452-8 Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access Contents 1 Introduction 1 1.1 Research Goal . 1 1.2 Contents and Organization . 3 2 Recommender Systems - Definition, Classification, and Mar- keting Perspectives 5 2.1 Working Definitions . 6 2.2 Classification . 7 2.3 Application Models of Recommender Systems 11 2.3.1 Broad Recommendation Lists ... 11 2.3.2 Customer Comments and Ratings . 12 2.3.3 Notification Services ........ 14 2.3.4 Product Associated Recommendations 15 2.3.5 Persistent Personalization 16 2.4 The Consumer Decision Process 18 2.4.1 Need Recognition . 20 2.4.2 Information Search 20 Nicolas Knotzer - 978-3-631-75452-8 ix Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access CONTENTS 2.4.3 Pre-Purchase Evaluation of Alternatives 23 2.4.4 Purchase ........ 28 2.4.5 Post-Pw-chase Processes 31 2.5 Virtual Communities . 34 2.5.1 Characteristics and Benefits 35 2.5.2 Virtual Communities and Network Effects 36 2.5.3 Community Building . 38 3 Recommender Systems - Functional Perspectives 47 3.1 Input Data of Recommender Systems . 48 3.2 Output Data of Recommender Systems 52 3.3 Measurement Scales for Preference Elicitation 57 3.4 Infonnation Delivery . 58 3.5 Recommendation Methods 59 3.5.1 Non-Personalized Recommendation Methods. 61 3.5.2 Personalized Recommendation Methods ... 63 3.5.2.1 Synopsis of Information Filtering Methods . 65 3.5.2.2 Human Approaches towards Information Fil- tering . 67 3.5.2.3 Collaborative Filtering . 68 3.5.2.4 Attribute-Based Filtering 73 3.5.2.5 Rules-Based Filtering . 76 X Nicolas Knotzer - 978-3-631-75452-8 Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access CONTENTS 4 Research Model, Hypotheses, and Methodology 79 4.1 Problem Statement . 79 4.2 Research Questions and Model . 80 4.3 Methodology and Research Design . 86 5 Results 91 5.1 Descriptive Results .............. 91 5.1.1 Sample Size and Demographic Data . 92 5.1.2 Internet Usage 99 5.1.3 Online Shopping . 102 5.1.4 Online Product Recommendations . 108 5.1.5 Ratings and Comments . 125 5.2 Verification of the Research Model . 134 5.2.1 Exploratory Factor Analysis . 135 5.2.2 Psychographic Hypotheses - Structural Equation Model 138 5.2.3 Psychographic Hypotheses - Regression Model . 141 5.2.4 Sociodemographic Hypotheses . 143 6 Summary and Directions for Further Research 149 6.1 Main Findings . 149 6.2 Limitations and Directions for Further Research . 151 Bibliography 153 Nicolas Knotzer - 978-3-631-75452-8 xi Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access CONTENTS Appendices 164 A AMOS Output 165 A. I Survey AUM . 165 A.2 Survey AON . 181 B Survey Items 197 xii Nicolas Knotzer - 978-3-631-75452-8 Downloaded from PubFactory at 01/11/2019 04:40:47AM via free access List of Figures 2.1 Classification of recommender systems .............. 8 2.2 Overview of application models and e-commerce business goals . 11 2.3 Barnsandnoble.com overall best seller list in the category "books" 13 2.4 Customer comments and ratings on CDs at Amazon.com 14 2.5 Notification service of Educanext.org ..........
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