Consumer Motivations in Online Group Buying: a Means-End Chain Approach

Consumer Motivations in Online Group Buying: A Means-End Chain Approach

Lin Xiao

A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy

School of Information Systems, Technology and Management UNSW Business School

2015

PLEASE TYPE THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet

Surname or Family name: Xiao

First name: Lin Other name/s:

Abbreviation for degree as given in the University calendar: PhD

School: Information Systems, Technology and Management Faculty: University of New South Wales Business School

Title: Consumer motivations in online group buying: a means-end chain approach

Abstract 350 words maximum: (PLEASE TYPE) Online group buying, as a new form of e-commerce, is one of the most innovative e-commerce business models. This model offers great opportunities for e-marketers, but also brings new challenges. In the last four years, more than 5000 online group buying vendors in China have gone out of business. Existing literature suggests that online group buying is distinctive from online shopping, and consumers are motivated to use online group buying to enjoy different benefits. As little research has been conducted on understanding consumers in this context, group buying websites have few guidelines to follow to improve competitiveness.

This thesis addresses this challenge by exploring the hierarchical motivations underlying consumers' online group buying behaviour and the development of consumer typologies from a new perspective. Specifically, utilising a Uses and Gratifications (U&G) approach and Means-End Chain (MEC) theory perspective, this study aims not only to explore the content of online group buyers' motivations, but also uncover the inter relationships among these motivations. Moreover, it aims to introduce a new method to segment consumer, based on benefit-level motivations, which can provide more accurate consumer typologies.

To reach these objectives the laddering interview technique was used to collect data from 58 online group buyers in China. A context-specific hierarchical motive model was developed, based on the 35 motivations identified, which not only indicated consumer value/goal fulfilment paths, but also illustrated the relative importance of different paths. Moreover, three typologies of group buyers with distinct value/goal fulfilment paths were identified, fundamentally different from existing shopper typologies in the e-commerce context.

As a timely topic using a novel approach to explore consumer online group buying motivations, this study adds to the online group buying literature, introduces a new segmentation approach that overcomes the limitations of the traditional rating-scale based segmentation, and demonstrates theories and techniques derived from other disciplines that can be effectively applied to information systems and e-commerce research. This study will also help practitioners involved in online group buying businesses to better plan and design strategies to attract and retain current and potential consumers.

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I hereby grant to the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or in part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all property rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation.

I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstracts International (this is applicable to doctoral theses only) . XttUJ 02/04/2015 ...... L~n Witness Date Signature

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'I hereby grant the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstract International (this is applicable to doctoral theses only). I have either used no substantial portions of copyright material in my thesis or I have obtained permission to use copyright material; where permission has not been granted I have applied/will apply for a partial restriction of the digital copy of my thesis or dissertation.'

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Originality Statement

I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project’s design and conception or in style, presentation and linguistic expression is acknowledged.

Signed.... . Date...... 01/04/2015......

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Dedication

This dissertation is dedicated to my parents, Yonggui and Xiuqiong, the best parents in the world, have never denied me but have always encouraged my success.

My grandparents, who provided unlimited love, understanding, and encouragement to me.

Acknowledgements

Completing this doctoral study has proven to be one of the most challenging periods in my life and it would not be possible without tremendous help and support from many people.

In particular, my greatest debt to gratitude is to my supervisor - Dr Zixiu Guo, for her supervision, support, and encouragement over the years. Dr Zixiu Guo, who provided a start to my research experience, has continuously helped, supported, and encouraged me both in the arduous academic process and my life journey in the past 6 years. She has given generous time in helping me developing research proposal, guiding the data collection and data analysis, reviewing and commenting on my thesis manuscript. She is always there when I need help and I have learned a lot from her. Without her, it would not have been possible for me to finish this work.

I am also grateful to my co-supervisor, Associate Professor John D'Ambra, the colleagues in School of Information Systems at UNSW, and the panel members for my

Annual Reviews, who have given insightful suggestions and comments for me to improve the thesis.

Words cannot express how grateful I am to my parent, Yonggui and Xiuqiong, for their unending love and support. They encouraged me to start the academic journey and always supported me in this pursuit. I also want to thank my grandparents for their love.

I was fortunate to receive a UIPA scholarship and A Supplementary Scholarship which provided me with financial support at a particular lean time. Thus, I would like to acknowledge the support for the UNSW Australia and UNSW Business School.

I am extremely grateful to my friend, Zhiming, for his accompany and support. I would like to thank my friends, Dan, Wenlin, Young, Ketchet, Neo, Xi, Xiangling, and Yuan, for the joy and help given by them in the past few years.

Lastly, I would like to give my thanks to Bin who has helped my with my data collection and all the interviewees as this thesis could not have been written without their help. In addition, I would like to thank Elite Editing for the proof-reading service.

The editorial intervention was restricted to Standards D and E of the Australian

Standards for Editing Practice.

In closing I desire to send all of my love and blessing to everyone throughout my life journey, family, and friends who have touched my life at such an inspiration level.

List of Publications

Xiao L, Guo Z, D’Ambra J. “A Typology of Online Group Buyers: Using Means-end Structures for Benefit Segmentation”, Proceedings of the 35th International Conference on Information Systems, Auckland, New Zealand, 2014

Xiao L, Guo Z, D'Ambra J, Fu B. "Understanding Consumer Online Group Purchase Making: A Means-End Chain Approach", Proceedings of the 18th Pacific Asia Conference on Information Systems, Chengdu, China, 2014

Xiao L. "Understanding Consumer Motivations in Online Group Buying: A Means-End Chain Approach", Proceedings of the 17th Pacific Asia Conference on Information Systems, Jeju Island, Korea, 2013

Guo Z, Xiao L, Seo C, Lai Y. "Flow Experience and Continuance Intention toward Online Learning: An Integrated Framework", Proceedings of the 33rd International Conference on Information Systems, Orlando, USA, 2012

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Table of Contents

Table of Contents ...... viii

List of Tables ...... xii

List of Figures ...... xiv

List of Abbreviations ...... xv

Abstract ...... xvi

Chapter 1: Introduction ...... 1 1.1 Research Background ...... 1 1.2 Rationale ...... 3 1.3 Research Aims and Questions ...... 6 1.4 Research Significance and Contributions ...... 7 1.5 Organisation of the Thesis ...... 8

Chapter 2: Literature Review ...... 11 2.1 Introduction ...... 11 2.2 Offline Cooperative Purchasing ...... 11 2.3 Online Group Buying ...... 16 2.4 Online Group Buying History and Current Developments ...... 17 2.4.1 Dynamic-Price Online Group Buying ...... 19 2.4.1.1 Mechanisms for Group Buying Auctions ...... 20 2.4.1.2 Seller and Buyer Strategies ...... 22 2.4.1.3 Customer Participation ...... 22 2.4.1.4 Summary ...... 23 2.4.2 Fixed-Price Online Group Buying ...... 24 2.4.2.1 Profitability of Online Group Buying ...... 27 2.4.2.2 Online Group Buyer Characteristics ...... 28 2.4.2.3 Strategies in Fixed-Price Online Group Buying ...... 29 2.4.2.4 Factors Influencing Customer Participation ...... 30 2.4.2.5 Summary ...... 35 2.5 Internet Use Motivation ...... 36 2.5.1 Internet Use Activities ...... 36 2.5.2 Motivations for Using the Internet ...... 38 2.6 Traditional Retail Shopping Motivations ...... 47 2.7 Shopping Motivations in E-Commerce ...... 54 2.8 Challenges to Understanding Consumer Online Group Buying Motivations .. 62

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2.8.1 Understanding the Content of Motivations in Online Group Buying Contexts ...... 62 2.8.2 Understanding the Hierarchical Structure of Motivations in the Online Group Buying Context ...... 64 2.8.3 Understanding the Benefits-Based Segmentation in the Online Group Buying Context ...... 67 2.9 Theoretical Foundations ...... 79 2.9.1 U&G Theory ...... 79 2.9.2 MEC Theory ...... 86 2.10 Chapter Summary ...... 92

Chapter 3: Research Design ...... 93 3.1 Introduction ...... 93 3.2 Research Philosophies ...... 94 3.2.1 Positivism ...... 97 3.2.2 Interpretivism ...... 99 3.2.3 Critical Paradigm ...... 100 3.2.4 Post-Positivism ...... 102 3.3 Qualitative Research ...... 104 3.4 Study Context ...... 107 3.5 Research Procedure ...... 115 3.6 Data Collection ...... 115 3.6.1 Laddering Interview Technique ...... 116 3.6.1.1 Soft and Hard Laddering ...... 118 3.6.1.2 Soft Laddering Interview Procedures ...... 121 3.6.1.3 Summary ...... 134 3.6.2 Pilot Study ...... 135 3.6.2.1 Objectives ...... 135 3.6.2.2 Design of Pilot Interview Procedures ...... 136 3.6.2.3 Findings and Discussion ...... 137 3.6.2.4 Conclusion of Pilot Study ...... 140 3.6.3 Main Study Data Collection ...... 141 3.6.3.1 Research Participants ...... 142 3.6.3.2 Group Buying Websites Used by Participants ...... 146 3.6.3.3 Interview Environment ...... 149 3.6.3.4 Interview Procedure ...... 149 3.7 Ethical Considerations ...... 155 3.8 Data Analysis Procedure ...... 155 3.8.1 Transcription and Preparation ...... 156

3.8.2 Content Analysis ...... 157 3.8.2.1 Open Coding ...... 158 3.8.2.2 Translation ...... 165 3.8.2.3 Classifying Dimensions into Attributes, Benefits and Values/Goals166 3.8.2.4 Validity and Reliability ...... 170 3.8.2.5 Summary of Content Analysis ...... 174 3.8.3 Constructing a Summary Implication Matrix ...... 174 3.8.4 Constructing an Aggregate HVM ...... 176 3.8.4.1 Determining a Cut-Off Value ...... 177 3.8.4.2 Process of Developing an HVM ...... 179 3.8.5 Calculating Relative Importance of Motivations ...... 183 3.8.6 Market Segmentation: Cluster Analysis ...... 185 3.9 Chapter Summary ...... 189

Chapter 4: Data Analysis and Results ...... 190 4.1 Introduction ...... 190 4.2 Content Analysis Results ...... 192 4.3 Data Reduction Results ...... 192 4.3.1 Consolidation of Results ...... 194 4.3.2 Inter-Coder Reliability in Content Analysis ...... 209 4.3.3 Attributes, Benefits and Values/Goals Classification Results ...... 209 4.3.4 Motivations in Three Layers Identified from Content Analysis ...... 214 4.3.4.1 Attributes Layer Motives ...... 214 4.3.4.2 Benefits Layer Motives ...... 222 4.3.4.3 Values/Goals Layer Motives ...... 232 4.3.5 Summary ...... 234 4.4 SIM ...... 235 4.5 Hierarchical Structure of Motives ...... 237 4.5.1 Cut-Off Value Selection ...... 237 4.5.2 HVM ...... 239 4.5.3 Summary ...... 245 4.6 Relative Importance of Motives in HVM ...... 245 4.7 Benefits-Based Segmentation Results...... 249 4.7.1 Cluster Analysis Results ...... 249 4.7.2 SIMs for Three Clusters ...... 255 4.7.3 HVM for Three Clusters ...... 259 4.7.3.1 Selection of Cut-Off Values for Three Clusters ...... 259 4.7.3.2 HVM for Three Clusters ...... 261 4.8 Summary ...... 266

Chapter 5: Discussion ...... 267 5.1 Introduction ...... 267 5.2 Understanding the Motivations Underlying Consumer Online Group Buying Behaviour ...... 267 5.2.1 Motivations in Online Group Buying—Context Matters ...... 268 5.3 Understanding the Hierarchical Relationships Among Motivations ...... 285 5.4 Understanding Typologies of Customers ...... 293 5.4.1 Economic Shoppers ...... 299 5.4.2 Balanced Shoppers ...... 301 5.4.3 Destination Shoppers ...... 302 5.4.4 Summary ...... 303

Chapter 6: Conclusions ...... 304 6.1 Introduction ...... 304 6.2 Implications ...... 304 6.2.1 Theoretical Implications ...... 304 6.2.1.1 Adding Knowledge to E-Commerce Literature ...... 305 6.2.1.2 Contributing to Motivation Theory ...... 307 6.2.1.3 Contributing to Segmentation Research ...... 308 6.2.1.4 Contributing to IS Research ...... 310 6.2.2 Practical Implications ...... 310 6.2.2.1 Implications for Group Buying Websites ...... 311 6.2.2.2 Implications for Suppliers ...... 313 6.2.3 Limitations of Qualitative Research ...... 315 6.2.4 Limitations of Generalisation ...... 315 6.2.5 Limitations on MEC with Laddering Technique ...... 316 6.3 Directions for Future Research ...... 317 6.4 Concluding Remarks ...... 320

References ...... 321

Appendix A – Survey (English and Chinese versions) ...... 349 Appendix B – Participant Information Statement and Consent Form (for interview) ...... 358

Appendix C – Ethics Approval from UNSW ...... 364

Appendix D – Raw Constructs ...... 365

Appendix E – Cluster Analysis and ANOVA Results ...... 367

List of Tables

Table 2-1: A summary of selected studies in cooperative purchasing ...... 16 Table 2-2: Comparison of dynamic-price and fixed-price group buying on the Internet ...... 19 Table 2-3: Factors influencing online consumer behaviour in online group buying context ...... 34 Table 2-4: Studies exploring Internet use motivations ...... 43 Table 2-5: Studies exploring traditional retail shopping motivations ...... 50 Table 2-6: Studies exploring factors affecting online shopping intentions ...... 61 Table 2-7: Market segmentations in traditional retail shopping and e-commerce context ...... 78 Table 2-8: Studies exploring Internet-based technologies use motivations that use a U&G approach ...... 85 Table 2-9: Studies using MEC to explore motivations ...... 91 Table 3-1: Philosophical perspective of four research paradigms ...... 96 Table 3-2: Comparison of qualitative and quantitative research ...... 106 Table 3-3: Comparison of soft and hard laddering ...... 120 Table 3-4: Summary of different eliciting techniques ...... 127 Table 3-5: Key strengths and weaknesses of different elicitation techniques ...... 127 Table 3-6: Summary of problem solving techniques ...... 134 Table 3-7: Summary of distinctions obtained using three elicitation techniques ...... 139 Table 3-8: Top 10 cities in terms of percentages of online group buyers ...... 143 Table 3-9: Characteristics of participants ...... 146 Table 3-10: Group buying websites used by participants ...... 148 Table 3-11: Summary of interview questions across different stages...... 154 Table 3-12: Coding procedure ...... 159 Table 3-13: A sample of text coding ...... 160 Table 3-14: Codes consolidation and categorisation process ...... 164 Table 3-15: Sample SIM ...... 175 Table 3-16: Sample of sensitivity analysis...... 178 Table 3-17: Summary of five types of relations in HVM ...... 183 Table 4-1: Motives identified in content analysis ...... 205 Table 4-2: Classification results ...... 213 Table 4-3: SIM ...... 236 Table 4-4: Statistics for determining a cut-off level ...... 238 Table 4-5: Indices of motives ...... 247

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Table 4-6: Cluster centroids from K-means cluster analysis ...... 251 Table 4-7: Demographic information for three groups ...... 255 Table 4-8: SIM for Cluster 1 ...... 256 Table 4-9: SIM for Cluster ...... 257 Table 4-10: SIM for Cluster 3 ...... 258 Table 4-11: Statistics for determining cut-off level for three segments ...... 259 Table 4-12: Contrast of HVM for three clusters ...... 264 Table 5-1: A comparison of motivations between current study and extant literature . 278 Table 5-2: A comparison of chains/interrelationships between current study and extant literature...... 291 Table 5-3: A comparison of shopper typologies in this study with similar typologies in extant literature ...... 296 Table 5-4: A comparison of shopper typologies between current study and extant literature ...... 298

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List of Figures

Figure 2-1: Group buying auction ...... 20 Figure 2-2: Fixed-pricing mechanism ...... 25 Figure 2-3: Value chain of fixed-pricing mechanism model of online group buying ...... 26 Figure 2-4: MEC model (Olson 1989, p.174) ...... 87 Figure 3-1: Research design ...... 94 Figure 3-2: Comparison of the accumulated closed websites and operating websites in 2013 ...... 109 Figure 3-3: Number of online group buyers from 2010 to 2013...... 110 Figure 3-4: Group buying sales from 2011 to 2013 in China ...... 111 Figure 3-5: Comparison of online group buying sales from 2011 to 2013 ...... 111 Figure 3-6: Amount of sales by categories (billion Yuan) ...... 112 Figure 3-7: Market shares of different group buying websites in China ...... 114 Figure 3-8: Sample ladders got in laddering interview (Source: Reynolds and Gutman, 1988) ...... 117 Figure 3-9: Hard laddering (Source: (Botschen and Hemetsberger 1998a) ...... 119 Figure 3-10: Interview procedure...... 150 Figure 3-11: Data analysis procedure ...... 156 Figure 3-12: Chains started from carbonation ...... 181 Figure 4-1: Chapter 4 Structure...... 191 Figure 4-2: HVM for online group buying motivations ...... 241 Figure 4-3: Radar diagram of clusters ...... 252 Figure 4-4: HVM of Group 1 (economic shoppers, n=20) ...... 261 Figure 4-5: HVM for Group 2 (balanced shoppers, n=19) ...... 262 Figure 4-6: HVM for Group 3 (destination shoppers, n=13) ...... 263

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List of Abbreviations

B1: Benefit 1

B2: Benefit 2

B2C: Business-to-Customer

C2C: Customer-to-Customer

CECRC: China E-commerce Research Centre

CNNIC: China National Network Information Centre

CPI: Consumer Price Index

HVM: Hierarchical Value Map

IS: Information System

ISM: Interpretive Structural Modelling

LOV: List of Values

MEC: Means-End Chain

PC: Personal Computer

SMS: Short Message Service

SNS: Social Networking Sites

TAM: Technology Acceptance Model

U&G: Uses and Gratifications

Abstract

Online group buying, as a new form of e-commerce, is one of the most innovative e- commerce business models. This model offers great opportunities for e-marketers, but also brings new challenges. In the last four years, more than 5000 online group buying vendors in China have gone out of business. Existing literature suggests that online group buying is distinctive from online shopping, and consumers are motivated to use online group buying to enjoy different benefits. As little research has been conducted on understanding consumers in this context, group buying websites have few guidelines to follow to improve competitiveness.

This thesis addresses this challenge by exploring the hierarchical motivations underlying consumers’ online group buying behaviour and the development of consumer typologies from a new perspective. Specifically, utilising a U&G approach and MEC theory perspective, this study aims not only to explore the content of online group buyers’ motivations, but also uncover the inter-relationships among these motivations. Moreover, it aims to introduce a new method to segment consumer, based on benefit-level motivations, which can provide more accurate consumer typologies.

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fulfilment paths were identified, fundamentally different from existing shopper typologies in the e-commerce context.

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Chapter 1: Introduction

This study explores online consumers’ underlying motivations for online group buying, and the typologies of online consumers in the online group buying context. This introduction begins with a discussion of the research field, with a particular focus on the rationale for this research, followed by an outline of the research aims and questions.

The research significance is highlighted subsequently, and the organisation of the thesis is presented.

1.1 Research Background

Online group buying, which has exploded in popularity worldwide over the last few years, is a combination of ‘online platform’, ‘bulk purchase’ and ‘team buying’ (Lo et al.

2012). It is an e-business model in which customers recruit others to generate a volume of orders enough to generate a low transaction price (Cheng et al. 2013; Hsu et al. 2014).

The main idea of online group buying is that consumers can utilise collective bargaining power to lower the prices of products or services in which they are interested.

Concurrently, suppliers can minimise the cost of recruiting customers (Kauffman et al.

2010a). Therefore, group buying websites act as intermediaries, gathering geographically dispersed online consumers with common product or service interests to garner discounts, and contacting suppliers to provide opportunities to sell multiple items in minimum time. By connecting online consumers and suppliers, group buying websites earn profits and gain a reputation. Thus, the goal of Internet group buying is to create a three-win situation for online consumers, suppliers and intermediary group buying websites.

There are three distinctive features of online group buying. First, online group buying is not similar to online group auctions. When the minimum number of participants is reached, new customers can purchase the products at a fixed price, much like other business-to-customer (B2C) transactions. Second, the role of online group buying vendors is not as a distributor. Their role is as a platform that can serve as a bridge between providers and potential customers (Yang et al. 2014). Third, online group buying is not restricted to physical commodities, and can include virtual products and services (such as hairstyle or dining services).

The advantage of online group buying centres on its high discount rates and high participation of online customers. E-vendors can negotiate better offers at discounted rates from product or service providers as they have the means of gathering large groups of online customers (Van Horn et al. 2005). This benefits both online customers and suppliers. Online consumers enjoy significant discounts on premium products or services, so online group buying is becoming more popular and successful in today’s e- commerce environment (Edelman 2011).

Online group buying has become very popular and successful in many countries, such as the United States and China. According to surveys, the total transaction value of the online group buying market in the US is expected to reach $41.7 billion in 2015 (Shiau et al. 2012). In China, according to a report published by the China National Network

Information Center (CNNIC) (2013), the number of users of online group buying reached 141 million in 2013, an increase of 68.9 per cent from 2012, and accounted for

22.8 per cent of the netizens, while online shoppers accounted for 48.9 per cent of netizens. China’s online group buying revenue reached 53.289 billion Yuan (equivalent to 8.88 billion US dollars), an increase of 52.8 per from 2012 (CNNIC 2013). With the

growing number of people participating in online group buying, online group buying sites have proliferated in recent years. According to a study conducted by iResearch, more than 5000 online group buying sites arrived in China alone by the end of 2013.

Thus, it is evident that online group buying is considered an effective form of e- commerce, and a promising field.

1.2 Rationale

Despite the rapid growth of Internet group buying, and the large number of people participating, profitable group buying websites are said to be in a minority. According to iResearch (2013), the top 10 group buying websites accounted for 77.21 per cent of the market share in China, and their revenue accounted for 83.34 per cent of overall revenue in the group buying industry (Daraotuan.com 2012). According to people.com.cn, only 38 per cent of online group buying vendors are able to update their products in a week, and more than 8 per cent of online group buying vendors are not capable of renewing their product categories in one month. By the end of 2013, 6246 group buying websites appeared in China, of which 5376 have subsequently closed due to fierce competition (iResearch 2013), accounting for more than 80% of the total number of group buying websites. Thus, it is extremely difficult for group buying website to survive in the e-market place, since they compete not only with each other, but also with traditional brick-and-mortar stores and other online shops.

Considering the opportunities and difficulties of conducting e-businesses in this e- market, it is important for e-vendors to understand how to become competitive in this novel environment. E-commerce research has long supported the view that to ensure the

success of online business, it is important for e-vendors to understand their target customers, especially the factors motivating consumer behaviour (Delafrooz et al. 2009).

A motivation is defined as a desire, need or process that influences an individual’s behaviour (Smith et al. 1982). Dawson et al. (1990) also propose that motives bring consumers into the marketplace. From the e-marketers’ perspective, only if cyber- marketers know how online consumers are motivated can they adjust their marketing strategies to convert potential customers into real ones, and retain them. Although the incentive of saving money is frequently cited as a reason for online consumer participation in group buying in previous research, over time, factors motivating online consumers to engage in online group buying have become multi-faceted, due to the growth of network communities and the competitive e-market environment (Shiau et al.

2012). These factors are crucial for e-marketers seeking to increase sales. Thus, other motivators driving consumer online group buying are worthy of attention, given the potentially significant market gains offered by this e-business model.

In addition, the majority of group buying websites are run by small companies with limited resources. The profit margin has reduced from 50 per cent at the beginning to 10 per cent currently, as the number of websites in the e-market place has increased

(iResearch 2013). Therefore, only understanding consumers’ needs is not enough, as group buying websites need to understand how high level social or psychological needs can be gratified through actionable strategies. Further, consumers’ needs fulfilment path needs to be understood, to explore the motives with strong driving powers in the group buying context. Extant literature in online group buying (Chen et al. 2010; Yang et al.

2014; Zhang et al. 2014) has ignored this, even as needs and motivation theories have long emphasised the hierarchical structure of human needs and motives driving human behaviour. These theories view motivational hierarchies in terms of developmental

prerequisites, in which an individual’s fundamental basic needs must be satisfied first before less essential, higher-order needs become activated. Ignoring the hierarchical structural path can cause group buying websites to lack in-depth understanding of the consumers’ needs fulfilment process, and result in the inefficient allocation of resources.

Additionally, motivations considered together may seem equally important and sometimes override each other. The development of a hierarchical motive model can help group buying websites understand which motives are essential, and which more important, thereby helping them effectively make strategies focusing on the most important motives. Such a hierarchical model can help e-marketers know exactly how they should offer products and services, and what they should offer to meet consumers’ needs to truly gratify them, thus achieving high quality service with limited resources.

Finally, limited academic attention has been given to investigating the typologies of online consumers in the online group buying context. Effective online group buying marketing and management require an understanding of the existing e-market segments.

Identification of a clearly defined market segment permits specifically directed promotion programmes. So far, demographic and socio-economic characteristics have been used largely as the basis of segmentation. Marketers have increasingly pointed out that the most effective predictor of purchase behaviour should be the behaviour itself, including benefits and motivations. In this regard, online shoppers’ motivation-based segments are valuable for e-marketers in the online group buying industry. Typologies or classification schemes can provide a basis for understanding and targeting different groups of online consumers. As the online group buying industry is growing tremendously, a typology specific to this channel will enable e-marketers to identify distinct segments of online consumers, thereby enabling group buying websites to effectively tailor their offerings to these customer types. Additionally, online consumers

in different motivation-based segments have different hierarchical motive structures.

Thus, developing hierarchical motive models in different segments is necessary, as it can assist researchers better understand online customer knowledge, and help practitioners fully understand online consumers in the online group buying industry.

1.3 Research Aims and Questions

Based on the above discussion, the aim of this research is to provide a comprehensive understanding of online consumer hierarchical purchase motivations and online consumer typology in the online group buying context.

Based on this research aim, the three objectives and research questions of this research are:

 Research Objective (RO) 1: To understand the motivations underlying online

consumers’ group buying behaviour.

o Research Question (RQ) 1: What are the motivations for online

consumers’ online group buying behaviour?

 RO2: To understand the hierarchical structure of online group buying

motivations.

o RQ2: What is the hierarchical structure of motivations that drive online

group buyer behaviour?

o RQ3: What is the relative importance of these motivation factors?

 RO3: To understand online group buyer typologies and the motive hierarchy for

different clusters of online group buyers.

o RQ4: Are there different groups of online group buyers based on the

benefit layer motives?

o RQ5: If yes, what are the similarities and differences between the

hierarchical motive structures for different groups of online consumers?

1.4 Research Significance and Contributions

This research is important for theoretical and practical reasons. Theoretically, although researchers have begun to focus on the phenomenon of online group buying, studies to date have provided a limited view of this phenomenon, due to its newness. Most previous studies quantitatively examined various online group buying motivations by adopting motivations from other e-commerce contexts. This study is among the first to explore online consumers’ motivations for participating in online group buying qualitatively and systematically, so provides relevant and valuable information for future research on the topic, or for other e-business contexts. Additionally, this study provides valuable insight into motivation theory by exploring the inter-relationships between hierarchically arranged motives. Though motivation and need theories have indicated the hierarchical structure nature of human motives, only limited studies have applied and explored the hierarchical motive structure in the e-commerce context. This study provides suggestions for future research on better understanding the complexities underlying consumers’ motivational process in e-commerce contexts, such as online group buying. Finally, this is among the first studies to investigate online customer segmentation in the online group buying context, and to develop hierarchical motive models for different segments of online group buyers. Through using relevant motivations to segment online group buyers, this study can extend findings from prior research that uses variables—such as demographic and socio-economic characteristics—to segment the e-market. By developing different hierarchical motive models in each segment, this study provides comprehensive information on online

group buyer typologies, overlooked in prior research, and thus provides valuable suggestions for future research.

As many group buying sites have emerged in recent years, attracting consumers and suppliers is highly competitive for them. Practically, this study is significant for both intermediary group buying websites and suppliers. For group buying websites, this study not only provides the content of online consumers’ motives, but also the structure of motives, indicating online group buyers’ needs fulfilment paths. By understanding both the content and structure of the motives, group buying websites can not only efficiently understand what needs consumers are seeking to gratify, but also know how to satisfy these needs effectively through needs fulfilment paths. For instance, they could incorporate lower-level websites and service attributes that directly correspond with higher-level motives to gratify online consumers. Additionally, the motivation- based market segmentation provides the basis for understanding and targeting different groups of online consumers. It can contribute to a full understanding of the e-market, the ability to predict behaviour accurately and an increased likelihood of detecting and exploiting new e-market opportunities. The profiles of different groups of online customers would assist e-marketers in making promotion strategies in a more responsive manner. For suppliers, by uncovering online group buyers’ needs and benefits, the findings of this study could help them provide high quality service to online consumers, and select the right group buying website for their products/service.

1.5 Organisation of the Thesis

This thesis contains six chapters:

 Chapter 1 Introduction. This chapter discusses the scope of the research. It

provides the background and the rationale of this study. The aim and the

research questions are also included. It concludes with a discussion of the

significance of the research, including contributions from theoretical and

practical perspectives.

 Chapter 2 Literature Review. This chapter reviews the academic and business

publications related to group buying, online group buying, Internet-based

technology use motivation, traditional retail shopping motivation and online

consumer motivations in e-commerce. It begins with a discussion of the

cooperative purchasing and online group buying phenomenon. Reviews of

Internet use motivations, traditional retail shopping motivations and e-commerce

shopping motivations follow. Challenges in understanding consumers’ online

group buying motivations are discussed, and finally, the theoretical foundations

for this research are presented.

 Chapter 3 Research Design. This chapter introduces and justifies the research

methodology used in this study. It first discusses the research approach,

followed by a description of the state of online group buying in China, where the

data was collected. It then describes the data collection technique used in this

study, followed by the data collection process for both the pilot and the main

studies. Finally, data analysis methods are introduced.

 Chapter 4 Results. This chapter presents the results of the data analysis. Content

analysis results are presented first, which answer the first research question. The

hierarchical value map (HVM) illustrating the hierarchical relationships among

motivations is presented subsequently, which answers research questions two

and three. Then, the cluster analysis results are described, which answer research

questions four and five.

 Chapter 5 Discussion. This chapter discusses the research findings based on the

data analysis results. For each research question, key findings obtained from the

data analysis results are discussed.

 Chapter 6 Conclusion. This summarises the thesis. The implications of both

theoretical and practical perspectives are discussed, followed by the limitations

of this research. Finally, a number of important directions for future research are

included.

Chapter 2: Literature Review

2.1 Introduction

The primary aim of this research is to explore online consumers’ hierarchically structured motives for online group buying, and to develop a typology scheme based on benefits’ layer motives. This chapter reviews the literature on the topic, to address the gaps and link this research to the existing body of knowledge. Online group buying is an extension of the business model of cooperative purchasing, as it utilises the advantages of the Internet and social media-based technologies. The findings of previous studies have indicated that most group buyers are active Internet users and online shoppers (Tan et al. 2010). Thus, to understand the online group buying phenomenon, literature related to cooperative purchasing, Internet use motivations, traditional retail shopping motivations and online shopping motivations in e-commerce is critically reviewed to gain insights into online consumers’ online group buying motivations, and to highlight the context-based motivation characteristics. Additionally, two theories are presented to guide this study.

2.2 Offline Cooperative Purchasing

Offline group purchasing is also referred to as horizontal cooperative purchasing, group purchasing, collaborative purchasing, joint purchasing, consortium purchasing, shared purchasing or bundled purchasing. In the literature, group purchasing and cooperative purchasing are among the most popular terms. These are defined as the cooperation between two or more organisations in a purchasing group, in one or more steps of the

purchasing process, through sharing and/or bundling purchasing volumes, information and/or resources (Schotanus 2007). Typical advantages of cooperative purchasing are lower purchasing prices, higher quality, lower transaction costs, reduced workloads and reduced risks (Schotanus et al. 2010).

Purchasing in relatively small and intensive groups is becoming increasingly popular in both the private and public sectors (Tella et al. 2005). More and more organisations share their purchasing volumes, information and resources in purchasing groups, in which the members share the workload. By doing so, these organisations obtain lower purchase prices and reduce transaction inefficiency. In a large number of cases, the advantages of cooperative purchasing can outweigh the costs of cooperation and disadvantages, such as anti-trust issues and disclosure of sensitive information

(Schotanus et al. 2010).

Extensive research has been conducted on cooperative purchasing. Table 2-1 summarises the studies that have contributed to the cooperative purchasing literature.

These studies can be categorised into three groups. Studies in the first group explore the advantages and disadvantages of cooperative purchasing (Ball et al. 2000; Johnson 1999;

Nollet et al. 2005; Tella et al. 2005). Advantages include price reduction, administration cost reduction, easy access to knowledgeable personnel and information sharing.

Disadvantages include a reduction in supplier services, paying too much to maintain group cohesion, difficulty determining common objectives among members and an increase in tensions due to unclear beneficiaries.

Studies in the second group focus on exploring the motives, critical success factors and determinants of companies joining cooperative purchasing, and the factors that can help

manage purchasing groups. For instance, in a large-scale survey, Schotanus et al. (2010) identified a list of factors for managing small and intensive purchasing groups, including no enforced participation, sufficient total contribution of efforts, all members contributing with knowledge, continuity in member representation, communication and fair allocation of savings. Tella and Virolainen (2005) found that the main motives of purchasing groups were cost savings and the collection of information on supply markets.

Studies in the third group focus on examining structure of purchasing groups, development of purchasing groups over time (Johnson 1999), and different types of cooperative purchase in the market (Ball et al. 2000; Schotanus et al. 2007). For instance, Schotanus and Telgen (2007) identified five forms of cooperative purchasing:

1. piggy-backing groups, which are informal purchasing groups, and focus on

keeping cooperation simple;

2. third party groups, which mostly involve long term piggy backing, made

possible by public external parties or central authorities with devoted resources;

3. leading buying groups, which involve outsourcing purchasing activities to

another member of the group. Each item is purchased by the most suitable

organisation or external party according to their expertise, resources or

purchasing volume;

4. project group, a one-time purchasing group for a shared purchasing project;

5. programme groups, which involve representatives of the management teams of

cooperating organisations meeting regularly as a steering committee to discuss

cooperative projects.

Studies examining the development of purchasing groups over time (Ball et al. 2000;

Schotanus et al. 2007) indicate that organisations need to choose a suitable type of

purchasing groups for their specific situation, and there are different forms of cooperative purchasing at different stages for purchasing groups.

Authors Main contribution to cooperative purchasing Studies exploring the benefits and disadvantages of cooperative purchasing The author develops a five-stage conceptual model based on four cases of cooperative purchasing in steps of: (1) internal, (2) informal external, (3) developing external, (4) formal external, and (5) redevelopment.  Purchasing groups show many changes over time. They may become larger and active in other fields. Johnson (1999)  Advantages of cooperative purchasing: price reduction, reduced

transaction costs, ability to attract new suppliers, support specialisation of staff, greater resources and stronger management capabilities.  Disadvantages: complexity, coordination costs, uncertainty, standardisation, compliance, free riding, governance and declining savings. The authors describe the operations of some forms of cooperative purchasing. Their survey findings include:  Most purchasing groups in their early stages are organised Ball & Pye (2000) informally.  Besides hidden savings, purchasing prices will always remain an issue for organisations that spend public money.  Benefits of cooperative purchasing: price reduction, administrative cost reduction, easy access to knowledgeable personnel and Nollet & Beaulieu information sharing. (2005)  Disadvantages: price focus, potential supplier mergers, reduced supplier services, costs to maintain group cohesion, confidentiality of strategic information, determination of common objectives among members and unclear beneficiaries leading to tension. Studies exploring the motives and critical success factors of companies join in cooperative purchasing The author notes the importance of large purchasing groups in some sectors in the US, such as health care, showing that:  Significant positive associations are found between member commitment and information exchange, trust and the perceived Doucette (1997) commitment of other members.

 The suitability of alternatives to a purchasing group has a significant negative relationship with commitment.  When a group member believes that others are committed, s/he will also commit.

Authors Main contribution to cooperative purchasing The author describes that general practice fund-holders respond to the complexities of contracting by group purchasing. Based on interviews, three key issues of importance to the success of purchasing groups are found: Laing & Cotton  Common objectives and interests should exist. (1997)  Despite its recognised importance, communication is almost uniformly viewed as problematic. These problems are partly attributed to political rivalry and the long-established autonomy of practices.  There is an inevitable tendency for decision making towards compromises. This stifles contracting innovation. The objective of the author is to find the motives behind small purchasing groups. They review theoretical approaches explaining the cooperative purchasing rationale. The results of interviews indicate Tella & Virolainen that: (2005)  The main motives of purchasing groups are cost saving and the collection of information on supply markets.  Cost savings arise mainly from reduced transaction power, which leads to lower purchasing prices. They identify a group of success factors for managing small and intensive purchasing groups, by comparing successful and unsuccessful purchasing groups. The factors identified include:  All members contribute knowledge. Schotanus et al. (2010)  Continuity in member representation.  Communication.  Fair allocation of savings.  No enforced participation.  Sufficient total contribution of efforts. Studies exploring the structure of purchasing groups and types of cooperative purchasing The authors develop a conceptual phase model for large purchasing groups in the stages of birth, growth, maturity and concentration. Based on interviews, the authors identify several factors that may change over time: Nollet & Beaulieu  Players’ intervention (e.g. legislation influences). (2003)  Nature of benefits.

 Procurement strategy (e.g. diversification).  Nature of the relationship with suppliers (e.g. partnership).  Structure (e.g. autonomous).  Resources (e.g. electronic catalogue).

Authors Main contribution to cooperative purchasing They develop a typology of purchasing groups. Five main forms of cooperative purchasing are distinguished, based on seven main dimensions. The main identified dimensions of the typology are:  Extent of the costs and gains for members. Schotanus &  All members’ influence on the activities of the group. Telgen (2007)  Life plan of the group.  Member characteristics.  Number of different activities for the group.  Organisational structure of the group.  Size of the group.

Table 2-1: A summary of selected studies in cooperative purchasing

In summary, organisations are the main participants of offline cooperative purchasing.

They enjoy the benefits of cooperation with other organisations with the same product or service purchasing requirements. With the popularity and wide acceptance of e- commerce, marketers have begun to build group buying models on the Internet, referred to as online group buying, which is widely accepted by individual consumers.

2.3 Online Group Buying

Online group buying is a system that provides daily discounts for various services and products, and is a new form of e-commerce that has attracted the attention of both practitioners and academics (Erdogmus et al. 2011). It is facilitated by the Internet and the easy, fast group coalition process brought by social networks and social media

(Xiong 2010). Because of the many benefits it provides for suppliers, online group buying websites, and consumers, online group buying has been described as one the most successful and profitable online forms of business since 2008. To fully understand the group buying phenomenon, the history of online group buying, current

developments and two different group buying models, the literature on both group buying models will be discussed in the following sections.

2.4 Online Group Buying History and Current Developments

In October 1998, Accompany.com (later renamed as Mobshop.com), became a pioneer in online group buying auctions. In May 1999, Mercata.com became a new competitor.

In 2001, Mercata shut down and Mobshop changed its business strategy to Business-to-

Business (B2B) market. In the following years, many online group buying websites failed or reoriented their business models (Kauffman et al. 2008). Kauffman and Wang

(2001) note two reasons for the failures. First, market expectations of the profitability of dotcoms were exaggerated, which led to an indiscriminate issuance of equity and venture capital investments. Second, there was a market-wide lack of experience in the proper articulation of Internet-based business models. Compared to the success of e- business nowadays, it is clear that the low rate of Internet use and low acceptance of online shopping in the earlier were the main reasons for these companies’ failure.

Online group buying has once again been making inroads into the marketplace in recent years (Kauffman et al. 2010a). This is occurring in North America, Europe and Asia.

Online group buying is quite successful in the US. Groupon.com, a US-based online coupon seller, is a pioneer in the online group buying business, as its rapid growth in

2009 brought about the advent of the online group buying industry. Launched on

November 2008, Groupon currently offers deals in almost 500 markets in 44 countries.

According to a JP Morgan Report (2011), 33 per cent of US online shoppers have group buying website accounts, and 17 per cent made at least one purchase. As one example

of growth, the revenue earned by Groupon increased 23 per cent year-over-year to $752 million in the second quarter of 2014, compared with $609 million in the third quarter of 2013 (Groupon 2014).

Similar things have occurred in Europe. Most group buying in Europe and North

America is conducted through online intermediaries. Almost without exception, intermediaries charge suppliers a fee of up to 50 per cent of the total value of the deal

(Kauffman et al. 2010a). Intermediaries with identical business models are appearing daily, especially across the UK and Germany. The most notable characteristic of all intermediaries is the orientation towards local markets, bound to cities and towns.

Leaders include Groupon, LivingSocial, Plum District, and BuyWithMe, with hundreds of similar sites in different languages.

In Asia, online group buying has achieved an entirely different level of market acceptance and success, especially in China. In the last two years it has grown to include most service and physical products in Asian countries. More than 5000 imitators of Groupon existed in China by the end of 2013 (CECRC 2013), with more than 140 million users. This figure is predicted to reach 420 million by 2015 (iResearch 2013).

Online group buying has gained prominence in other Asian countries too. Websites have appeared in Taiwan, Singapore, Hong Kong, Thailand, Malaysia and the

Philippines. New sites likes Ensogo, Cashcashpinoy and Pinoy Vouchers are well- known group buying sites in Asia.

This background indicates a key point: an e-business model that had not flourished during the earlier years of the Internet appears to have tremendous e-market potential

nowadays. Given the interest in online group buying worldwide, it is productive to explore how online group buying can be made a more successful e-business mechanism.

Dynamic-price group buying Fixed-price group buying Selling method Auction Posted price Price Uncertain Fixed Deal title No standard form Standard as ‘$X for $Y worth of Z’ Customer cooperation Monetary motivation Self-enhancement motivation Worst customer Buying at the highest price Drawback for threshold not experience curve satisfied Duration Long, usually several weeks Short, usually one day

Table 2-2: Comparison of dynamic-price and fixed-price group buying on the

Internet

Source: adapted from Zhou et al. (2013)

Reviewing the literature, there are two types of online group buying models in the e- market: the dynamic-price group buying model and the fixed-pricing mechanism model.

The differences between the two are shown in Table 2-2.

2.4.1 Dynamic-Price Online Group Buying

Prior to the advent of Groupon-like group buying—known as fixed-price group buying—another kind of group buying existed, called dynamic-price, or auction-based group buying. Mobshop.com and Mercata.com used such mechanisms. On a group buying auction website, a product is put on sale with a specified start and end time, typically called an auction cycle. As more buyers join the group to purchase a product, the price drops according to a predetermined price change trajectory (Chen et al. 2007a).

Some websites reveal this price change trajectory, while others do not. The auction

cycle can also end before the specified end time if a maximum number of units sell. At the end, everyone who participated in the cycle would be charged the same final, lower price, even if some indicated an earlier willingness to buy at a higher price. Figure 2-1 shows the group buying auction model.

Figure 2-1: Group buying auction

Many studies on this type of group buying exist, which can be classified into the following categories.

2.4.1.1 Mechanisms for Group Buying Auctions

Li (2012) examined the implications of buyer heterogeneity in the context of group buying. They found that compared to individual purchases, buyers using group- bargaining opportunities only benefit if the seller’s bargaining power relative to the buyer group is low, and/or buyers’ preference towards the sellers are sufficiently differentiated. Chen and Roma (2011) showed that under linear demand curves, group buying is always preferable for symmetric retailers; for asymmetric retailers, group buying is beneficial for the smaller player, but can be detrimental to larger players.

Chen et al. (2009) suggested that cooperation between bidding ring members in online group buying auctions is a mutually beneficial strategy for ring members, bidders outside the ring and the seller. They also considered that online cooperation results in high social welfare, leading to market expansion that benefits buyer and sellers, as well as the auction intermediary. Lai et al. (2006) also found that group buying performs better in a market with narrow price dispersion.

However, research (e.g. Kauffman et al. 2010a; Lai et al. 2004) on online group buying auctions has noted problems with this type of group buying, which can lead to market failure. Consumers are interested in buying products at the lowest price. Potential participants are inclined to wait until the auction price falls to an acceptable level. As a result, the number of bids and orders received at the beginning of the auction are often few. This phenomenon is called startup inertia (Kauffman et al. 2010a). The auction operator will experience resistance to consumer participation. If not enough consumers participate, the price will not decrease efficiently, causing more resistance in customers.

To solve this problem, studies on online group buying auctions have explored incentive mechanisms that encourage consumers to participate. For instance, Lai and Zhuang

(2006) developed three participation incentive mechanisms to encourage consumers, including sequence-base incentive, time-based incentive and quantity-based incentive.

Further, Kauffman et al. (2010a) used an experimental test to examine how these three incentives work in the context of bakery cookies sales. The results indicated that compared to other incentive mechanisms, a sequence-based incentive mechanism gave consumers a sense of less procedural fairness, which could positively affect satisfaction and purchase intention.

2.4.1.2 Seller and Buyer Strategies

With the failure of many group buying auction websites, studies began to develop strategies for making the group buying auction model more economical. Chen et al.

(2002) investigated buyers’ bidding strategies, in order to help sellers set better auction parameters and achieve their expected goals. Anand and Aron (2003) compared the posted-pricing mechanism with the online group buying auction mechanism in different scenarios involving demand uncertainty and economies of scale. Using simple analytical models, they provided a guide to the conditions that favour the group buying auction mechanism. Chen et al. (2009) proposed that auction intermediary websites should provide a means for bidders to cooperate, to collectively express greater demand.

Through an analytical modelling analysis, they offered insights into how sellers can set their group buying auction price curves more effectively, to take advantage of bidder cooperation and to improve auction performance. They further argued that the goal of the auction intermediary should be to offer an information sharing mechanism, to facilitate bidding ring formation, and as a means of maximising the value of this market mechanism. Chen and Li (2013) proposed a duopoly firm model for examining when it is optimal for a buyer group to commit to exclusive purchase from a single seller, and if the presence of group buying and the exclusive purchase commitment affect firms’ incentives to invest in quality improvement.

2.4.1.3 Customer Participation

A few researchers have explored the factors that encourage consumers to participate in group buying auctions. One identified factor is the externalities effect, in which bids and orders generated by consumers have significant and positive effects on the number of

new orders and participants. The externality effect was first proposed by Kauffman and

Wang (2001). They used transaction data from Mobshop.com to analyse changes in the number of orders for Mobshop-listed products over various periods. Their results indicated that the number of existing orders had a significant positive effect on new orders placed during each three-hour period. They labelled this a positive participation externality effect, as the installed base of participation brings benefits to others who join in later, benefiting from the price drops that have already occurred.

Other identified factors include trust and price fairness. For instance, Kauffman et al.

(2010b) explored traditional group buying auctions from the trust and risk angle, and found that existing bids affect a consumer’s perceived trust in the auction initiator and the financial risk. Additionally, positive peer reviews and a greater number of bids appear to enhance perceived trust in the auction initiator and reduce the perception of financial risk. Kauffman et al. (2010a) showed that customers view participation discounts as primarily responsible for creating a perception of greater price fairness in online group buying auctions. A sequence-based incentive mechanism gives customers a sense of less procedural fairness, compared to other incentive mechanisms.

Perceptions of fairness tend to have a positive association with price satisfaction and purchase intention. Li et al. (2004) studied the problem of coalition formation and cost sharing in a Bayesian equilibrium framework. They found a positive correlation between stability and incentive compatibility in group buying.

2.4.1.4 Summary

Although the emergence of online group buying auctions attracted consumers willing to try new mechanisms for purchasing goods and services, the online group buying

auctions are unable to uphold their original promise. Once popular, dynamic-price group buying websites have declined over the past few years. Some have gone bankrupt

(such as LetsBuyIt.com), while others have transformed into a social buying platform

(such as eWinWin.com), or changed their dynamic-price mechanism to a fixed-price platform (such as Livingsocial.com). Recently there has been a proliferation of a new and successful online group buying model: the fixed-pricing mechanism model.

2.4.2 Fixed-Price Online Group Buying

In the fixed-price mechanism model, the online group buying company offers a certain product or service at a large discount price, principally more than 50 per cent. However, the price is static and does not lower as the number of buyers increases. The only condition is that the total number of buyers must be greater than the predetermined minimum. Figure 2-2 illustrates this e-business model. On most group buying websites, deals last for one day. The group buying website acts as an intermediary, making the contact and arranging group buying activities on the one hand, and publicising, attracting consumers to the website and inducing them to participate on the other. This online group buying market has few barriers to entry, and has gained global attention from online shoppers and businesses alike. Many group buying sites work by negotiating deals with local merchants and promising to deliver crowds in exchange for discounts.

Figure 2-2: Fixed-pricing mechanism

Groupon was the first group buying site to use this e-business model, and has been adopted by most group buying websites worldwide. The operation of Groupon is as follows: companies that aim to promote their products and services apply to Groupon. If they agree to cooperation, the Groupon website announces the campaign, including the actual price, discount rate, discounted price, number of minimum required users and other terms. Consumers check the campaigns daily, and buy the campaigns that attract them (Groupon 2011). In a short time, many similar sites, providing similar online group buying services, emerged in many countries.

Online Media Offline Media

 SNS/Internet Sites  Newpaper/Magazine  Portal  Friends/Relatives

Help to Promote

Suppliers Group Buying Sites Customers

 Service Suppliers  Service Oriented  Product Suppliers  Product Oriented  Hybrid

Help to Operate

Offline Service Online Service Hardware/Network Provider Provider

 Delivery  Site Solution Provider  Network Service  Customer Service  Bill/Payment Service Provider Outsourcing Provider  Server, Software and  Outsourcing Suppliers Hardware Supplier

Figure 2-3: Value chain of fixed-pricing mechanism model of online group buying

The entire value chain of this model is illustrated in Figure 2-3. The three main parties to online group buying are suppliers, group buying websites and customers. Suppliers can be service providers such restaurants, beauty salon or product providers, such as retailers. Group buying sites can be service oriented (only providing service-related deals, such as at spas and restaurants), product oriented (only providing physical products) or hybrid oriented (providing both service and physical products). Customers interested in the deals need to pay in advance to the group buying websites to obtain vouchers. Social media, such as social network sites (SNS) and portal sites are often

used by group buying websites to promote sales. Offline media such as newspapers, magazines or word of mouth can also aid promotion. For product oriented group buying sites, offline service providers—such as logistic delivery providers—and customer service outsourcing suppliers can help with the operation of after-sale service. Online service providers—such as site solution providers, bill/payment service providers, network service providers, servers, software or hardware providers—help with the operation of group buying websites.

Due to its relative newness, interest in this fixed-pricing mechanism group buying model has only occurred in recent years, and research in this area is sparse. Generally, the existing studies on fixed-price online group buying focus on the following aspects.

2.4.2.1 Profitability of Online Group Buying

Earlier studies focus on describing the advantages of group buying online. For instance,

Li et al. (2009) conducted qualitative research on group buying in China. Based on different initiators, they classified group buying into four modes: consumer initiated, self-employed individual initiated, group buying site initiated and media site initiated.

They summarised the characteristics of the four types of group buying in terms of value, life-cycle, demand and brand of available products, promotion media, information of the group buying activities, pricing and discount. Based on these characteristics, the roles of different types of group buying in the marketing channel were discussed. By comparing different modes of group buying, important role of group buying websites was confirmed in the market channels.

Other studies have empirically examined the profitability of online group buying. A conceptual framework by Dholakia (2011) was developed and empirically tested, specifying the determinants of a profitable Groupon promotion using a survey-based study of 150 businesses. The study found that the promotional offer and employee satisfaction affect consumer behaviour during Groupon redemption as well as in the long term, which in turn affects the profitability of the promotion. They also provided evidence of significant exposure value. Firms lost a small amount of money on the average Groupon user, but more than made this back through an increased rate of purchase by full price-paying customers, a result of the additional exposure. Edelman et al. (2010) used economic modelling to examine the profitability and implications of

Groupon promotions. The results show that Groupon promotions are more profitable for relatively unknown merchants, those who can handle losses in the short run and those with low marginal costs.

2.4.2.2 Online Group Buyer Characteristics

When more consumers undertake online group buying, studies will begin to examine buyer characteristics. Tan and Tan (2010) conducted an exploratory study comparing online and offline group buying, and found that online group buying was better than offline group buying in terms of convenience, provision of product information and price. People who were young and optimistic about technology preferred online group buying, as it requires consumers to face technology. Their results confirmed the findings of earlier studies, in that younger people and those optimistic about technology were more likely to use online group buying, while those uncomfortable with technology or older people were likely to shop offline. Analysis of the reasons for group buying indicated that all were related to social networks. This suggests opportunities for online

social networking sites to be the intermediaries for group buying. Such site operators, or in partnerships with group buying website operators, can leverage users’ profile information to identify buying groups. Chen and Wu’s (2010) study indicates that the dominant demographic in online group buying are females aged between 31 and 40, and the most frequently purchased items are food and daily necessities.

2.4.2.3 Strategies in Fixed-Price Online Group Buying

There are several drawbacks of the current group buying systems. For instance, the absence of security considerations, which could lead to breaches of privacy for participants. Further, buyers need to pay in advance without a trusted third party to monitor the purchase. To mitigate these risks, Lee and Lin (2013a) proposed the introduction of a group buying server to secure and monitor transactions. The server is regarded as a mediator that can help the buyer and e-vendor negotiate through a secure channel. Mutual authentication between the buyer and e-vendor is guaranteed. Liang et al. (2014) studied the group buying mechanism in a dynamic framework. They characterised customer behaviour within a rational expectations framework, and considered the effect of information and demand dynamics. Results show that whereas an improvement in information quality has a positive effect on customer surplus and the group buying success rate, the effect of inter-temporal demand correlation is mixed.

Liang et al. (2014) derived the condition to be satisfied at the optimal group size, and used the novel approach of employing methods from experimental economics to design and evaluate electronic market mechanisms and platform designs, applying this to an electronic group buying setting. Their study adds to the understanding of group decision making under pressure by considering the mitigating effects of offering communication capabilities on decision outcomes. Results suggest that introducing competition among

buyers and communication tools that support group coordination can help speed up inventory turnover, and also help protect profit margins for sellers.

2.4.2.4 Factors Influencing Customer Participation

Recognising the success of online group buying and the high enthusiasm of customers in this e-business market, a few empirical studies have explored the factors affecting consumer purchase or repurchase intentions in an online group buying context. These factors identified are related to four aspects:

1. economic related factors, such as price, discount rate and price fairness;

2. social related factors, such as peer reference and the crowd effect;

3. technology related factors, such as perceived usefulness and ease of use;

4. other factors, such as convenience and product quality.

Among these factors, economic related factors are the most frequently investigated.

Erdogmus and Cicek (2011) studied customers’ motivations, behaviours and perceptions of the online group buying system. Results indicated that price opportunity was the primary motive for participating in online group buying. Other motives mentioned were exploration of new activities and places, seeking joy and variety, trial of non-routine activities, socialising and need satisfaction. Using a data mining approach, Liao et al. (2011) investigated online group buying intentions, finding that the main reasons for consumers to participate in group buying were good product quality and low price. Yang and Mao’s (2014) results demonstrated that price and sales proneness, and trust in the vendor, can positively affect search and purchase intentions, while the discount rate does not correlate with search or purchase intention.

From a social perspective, Zhang et al. (2014) investigated how online social interactions influence consumers’ online impulse to purchase in the context of group buying websites. Their results show that online social interaction factors, including review quality, source credibility and observational learning, demonstrate important effects on perceived usefulness and positive affect. Positive affect further influences the urge to buy impulsively. Yeh’s (2014) study identified the critical antecedents of consumers’ hedonic participation and value creation in the online group buying environment, using social capital theory. They found that social interaction ties, trust, shared value and platform capability all influence hedonic participation and value creation in the online group buying context. Tsai et al. (2011) found that a sense of virtual community and trust in that community are determinants of online group buying intentions. Zhou et al. (2013) examined information diffusion in group buying. They found that mass media communication and interpersonal communication at the start of the process can positively affect sales, but leads to fewer sales during the end period in fixed-price group buying. Shiau and Luo (2012) explored the factors affecting online group buying intentions and satisfaction, a from social exchange theory perspective.

They found that reciprocity, reputation, trust and vendor creativity can influence satisfaction, which in turn affect intention to participate in online group buying.

From a technological perspective, Tsai et al. (2011) conducted a study to understand the motivations for a customer’s decision to purchase through online group buying websites.

They provided a research model to examine the effect of technology acceptance factors on online group buying. Using surveys from 346 buyers in Taiwan, they found that website quality, perceived ease of use, and perceived usefulness are important determinants of online group buying intentions. Liu et al. (2013) identified that website attributes such as product availability, visual appeal and website ease of use were

important factors affecting personality traits, which eventually led to impulse purchases in online group buying.

Authors Sample and data Dependent Motivations collection variables

Erdogmus and In depth interviews Purchase  Novelty and Cicek (2011) from 20 online intention extraordinary nature of group buyers the offer  Price advantage and discount amount Liao et al. (2011) Online surveys Purchase  Below-market price from 550 online intention benefit group buyers  Convenience  Credit card interest free  Curiosity  Exclusively back coupling  High quality gift  Instalment  Just-has demand Tsai et al. (2011) Online surveys Purchase  Perceived ease of use from 346 online intention  Perceived usefulness group buyers  Sense of virtual community  Trust in virtual community  Website quality Tai et al. (2012) Surveys from 264 Purchase  Gender online group intention  Initiator communication buyers  Initiator expert  Interpersonal influence

Authors Sample and data Dependent Motivations collection variables

 Perceived price fairness Cheng and Huang Online surveys Purchase  Relational embeddedness (2013) from 373 online intention  Structural embeddedness group buyers and  System quality attitude behaviour

Liu et al. (2013) 231 students with Impulsive  Impulsiveness experience of purchase  Instant gratification visiting online  Normative evaluation group buying  Product availability websites  Visual appeal  Website ease of use Zhang et al. (2013) Secondary data Return  Buyer number from 862 group intention  Discount rate buying deals in  Popularity Shanghai, China  Satisfaction improvement  Service quality Hsu et al. (2014) 253 Groupon users Repurchase  Perceived quality of in Taiwan intention seller  Perceived quality of website  Perceived size of seller  Perceived size of website  Reputation of website  Reputation of sellers  Satisfaction with sellers  Satisfaction with website  Trust in sellers  Trust in website

Authors Sample and data Dependent Motivations collection variables

Zhang et al. (2014) Online surveys Impulsive  Observational learning from 315 online buying  Perceived usefulness group buyers  Positive affect  Review quality  Source credibility Yang and Mao Experiment with Search  Participation volume (2014) 160 college intention  Perceived ease of use students and  Perceived usefulness purchase  Price and sales proneness intention  Trust in vendor Yeh et al. (2014) Online surveys Hedonic  Platform capability from 663 online participation  Shared value group buyers and value  Social interaction tie creation  Trust Table 2-3: Factors influencing online consumer behaviour in online group buying context

A few studies have examined the factors that can influence online consumer repurchasing intentions in the online group buying context. For instance, using data collected from 862 restaurant group buying deals, Zhang et al. (2013) found that discount rate, popularity and service quality can influence buyer numbers and satisfaction improvement, which in turn influence return intentions. Integrating DeLone

& McLean’s Information System (IS) success model and the literature of trust, Hsu et al.

(2014) found that on the one hand, a website’s reputation and perceived size can influence trust, further affecting the perceived quality of and satisfaction with sites, leading to repurchase intentions. On the other hand, size, the seller’s reputation and perceived size can affect trust in sellers, influencing the perceived quality of and

satisfaction with sellers, leading to repurchase intentions. Table 2-3 summarises the studies exploring factors that influence online consumer behaviour in the online group buying context

2.4.2.5 Summary

From the studies reviewed above, it is clear that researchers recognise the potential of the online group buying model in the e-business market. Although studies have shifted from describing the online group buying phenomenon or consumer characteristics to empirically examining consumers’ behaviour, the extant studies have provided a limited understanding of consumers. Most studies examined consumer behaviour from economic and social perspectives. A few studies attempt to investigate online group buyer behaviour from a technological perspective. However, only quite limited technology related factors (such as perceived ease of use and perceived usefulness, from

Technology Acceptance Model [TAM]) have been studied. Additionally, the examined factors are all adapted from other e-commerce contexts, such as B2C or customer-to- customer (C2C), and most studies use quantitative methods to test the relationships between motivation factors and purchase or repurchase intentions. Few studies use a qualitative approach to comprehensively explore the motivation factors in the new e- business context.

Due to these limited understandings, there are a lack of guidelines and suggestions for e-marketers to design group buying websites and develop appropriate strategies for attracting potential online consumers and retaining current online consumers. Thus, further studies should provide more comprehensive motivation factors for consumers’ online group buying behaviour. Additionally, though Chen and Wu’s (2010) and Tan

and Tan’s (2010) studies have provided the dominant demographic information on online group buyers, the information is too general and difficult for e-marketers to utilise in devising promotion strategies. Thus, more effective segmentation studies that provide specific online consumer information are needed.

Overall, online group buying is a new form of e-commerce that takes advantages of

Internet technologies and social media. Extant studies have indicated that online group buyers are active Internet users (Tan et al. 2010). To understand these online customers fully, it is necessary to revisit studies related to Internet-based technology use motivation.

2.5 Internet Use Motivation

Two streams of research are generally popular in Internet use related studies. The first has examined Internet usage patterns primarily from a demographic perspective, and compared how different groups of people use different aspects of the Internet. The second stream moves beyond examining types of activities undertaken by online users, to study user motivations.

2.5.1 Internet Use Activities

The Internet is unlike any other medium, in that reasons for its use vary. This is partly due to the nature of communication activities available on the web. Users can use the

Internet to do an array of things, such as communicate with friends, find news information or shop. According to Michailidis et al. (2011), email and social networking are the primary uses of the Internet. Shopping, searching for information and education

have also been ranked as important by Internet users. Vanea (2011) examined the relationship between Internet usage, Internet usage purposes and dimensions of Internet addiction. The results showed that email, forums, blogs, online social networks, online shopping and video-sharing websites have become an indispensable part of the online practices and Internet activities of Internet users.

Internet usage differs according to demographic characteristics such as race, gender and age. Extant studies have demonstrated that males and females use the Internet for different reasons. For instance, Weiser’s (2000) study assessing gender differences in specific uses of the Internet showed that males used it mainly for purposes related to entertainment and leisure, whereas women used it primarily for interpersonal communication and educational assistance. Teo and Lim (2000) used surveys to explore the gender differences in Internet usage and task preferences in Singapore. Results suggested that males engaged in downloading activities more often than females. In terms of the four generic online activities, browsing for information and messaging were more prevalent than downloading and purchasing activities for both males and females, which confirmed Teo et al.’s (1997) results. Tsai and Tsai (2010) investigated the gender differences in junior high school students’ Internet usage. Their results demonstrated that boys and girls used the Internet for significantly different purposes: boys were more exploration-oriented Internet users, who use the Internet for games, searching behaviour and news, whereas girls were more communication-oriented users, who use the Internet for shopping and communicating with friends. Papastergiou and

Solomonidou’s (2005) study confirmed that boys were more likely to use the Internet for entertainment and web page creation. However, they found no gender difference in pupils’ Internet activities such as email communication, web surfing or searching for information for personal or school purposes.

These studies have comprehensively explored users’ activities on the Internet and how these activities differ between genders. What is missing is any indication of motivations causing people to use a specific Internet-based application for a specific activity.

2.5.2 Motivations for Using the Internet

Another stream of research is moving beyond examining what types of activities online users undertake, to exploring users’ underlying motivations for conducting these activities on the Internet. These activities include commercial website usage, general web usage, general Internet usage, blog usage and SNS usage. Initial studies have segmented user motivations into two modes: goal-directed and experiential. Goal- directed usage suggests that online users use the Internet in an intentional and selective manner, reflecting purposive exposure to specific content (Rodgers et al. 1999). In contrast, experiential usage suggests that individuals use the Internet for diversion, escape and/or relaxation (Rodgers et al. 2000). Table 2-4 summarises studies exploring motivations for use of the Internet or Internet-based applications. Though there are some common motivations—such as information seeking, convenience and entertainment—that can be applied to all contexts, there are specific differences among different Internet-based technology contexts.

Sample and data Context Authors Motivations collection

 Entertainment value Commercial  Information Experiment with 176 website Eighmey (1997) involvement Internet users  Personal relevance

Sample and data Context Authors Motivations collection

 Cognitive needs Part one: online  Entertainment needs surveys from 98 web  Searching need Stanford and users  Social needs Stanford (2001) Part two: 343  Unique and new needs convenience sample

 Entertainment Surveys from 207  Escape students at a  Information Kaye (1998) medium-sized  Pass time Midwestern university  Social interaction  Website preference World Wide Six focus groups  Economic motivation Web (WWW) with undergraduate  Information

and graduate  Interactive control Kargaonkar et al. students;  Socialization (1999) Surveys from 401  Social escapism consumers from a  Transactional security large south-eastern and privacy metropolitan area

Surveys from 59  Economic Information Consumer Joines et al. web users  Interactive control Web usage in (2003) subscribing to an  Socialization e-commerce online service

 Interactive control Internet Surveys from 185  Information Ko (2000) college students  Pass time  Social escapism

Sample and data Context Authors Motivations collection

 Convenience Papacharissi and  Entertainment Surveys from 279 Rubin (2000)  Information seeking college students  Interpersonal utility  Pass time  Excitement and Parker and Plank Surveys from 204 relaxation needs (2000) college students  Need for learning  Social needs  Diversion Surveys from 498  Personal status Song et al. college students in  Relationship (2004) two Midwestern maintenance universities  Virtual community Part 1: surveys from  Content gratification 97 Internet users  Process gratification Stafford and (qualitative);  Social gratifications Stafford (2004) Part 2: surveys from

1258 Internet users (quantitative)

Internet use  Perceived ease of use activities: Online surveys from  Perceived enjoyment messaging, Teo (2001) browsing, 1370 Internet users  Perceived usefulness downloading, purchasing  Convenient Internet  Entertainment components Kaye and Online surveys from  Guidance for political Johnson (2004) 442 Internet users information  Information seeking  Social utility

Sample and data Context Authors Motivations collection

Part 1: focus group  Career opportunities Internet use for interviews from 30  Global exchange the cybercafé college students;  Relaxation Roy (2009) visitors in Part 2: surveys from  Self-development Indian context 525 visitors in  User friendly cybercafés  Wide exposure

 Entertainment  Information seeking  Media drenching and Surveys from 302 Dogruer et al. performance students at English (2011)  Passing time Preparatory School  Personal status  Relation maintenance  Self-expression  Entertainment  Free flow of information Moradabadi et Surveys from 396 Facebook  Freedom of al. (2012) college students communication  Information sharing  Social credit  Entertainment  Escapism  Information sharing Alhabash et al. Online surveys from  Medium appeal (2014) 3172 Facebook users  Self-documentation  Self-expression  Socialization

Sample and data Context Authors Motivations collection

Facebook  Communication Krause et al. Online survey from music listening  Entertainment (2014) 576 Facebook users applications  Habitual diversion

 Entertainment Online surveys from Brandtzaeg and  Information 5233 social Heim (2009)  Personal identity networking sites  Social interaction  Enjoyment  Number of members Lin and Lu Online surveys from  Number of peers (2011a) 402 Facebook users  Perceived complementarity  Usefulness  Convenience  Entertainment Kim et al. Surveys from 589  Information (2011b) college students SNS  Seeking friends  Social support  Entertainment  Friendship Pornsakulvanich  In trend Online surveys from and Dumrongsiri  Passing time 451 SNS users (2013)  Relationship maintenance  Relaxation  Information  Entertainment Omar et al. Conceptual study  Social interaction (2014)  Personal identify  Self-disclosure

Sample and data Context Authors Motivations collection

 Connectivity

Interviews from 15  Convenience university students  Content management Guo et al. (2010)  Information seeking Surveys from 266 Computer-  Problem solving college students mediated  Social context cues communication  Social presence (CMC) media  Accessibility use for Interviews from 17  Communication goal students in university students  Communication learning who have experience mode context Guo et al. (2011) of using various  Content management CMC media in  Interaction learning  Information seeking environments  Problem solving  Self-disclosure  Perceived probability of enhancing self- image  Perceived satisfaction Online in helping other Tong et al. Experiment with 168 feedback consumers (2013) university students systems  Perceived satisfaction in influencing the product  Presence of economic rewarding mechanism

Table 2-4: Studies exploring Internet use motivations

For commercial website usage, Eighmey (1997) determined that personal relevance, information involvement and entertainment value are the major motivations for browsing commercial websites. Stafford and Stafford (2001) provided five factors representing consumer motivations or needs for using commercial websites:

1. searching needs (for information updates and resources);

2. cognitive needs (a mix of learning and information searching, highly content-

specific);

3. entertainment needs (playing games and having fun, a process type of use);

4. social needs (interacting with friends and in news groups);

5. unique and new needs (finding new and interesting ideas).

While searching needs and cognitive needs are content-based goal-directed motivations, and entertainment needs are process-based experiential motivations, social needs are arguably dependent on purpose to determine whether they are goal-directed or experiential.

For web usage motivations, Kaye (1998) found six motivation factors: entertainment, social interaction, to pass time, escape, information and website preference. Five of these motivations are confirmed by Kargaonkar et al.’s (1999) study. Additionally,

Kargaonkar et al.’s (1999) study obtained two other motivation factors: transactional security and privacy, and economic motivation. Rodger and Sheldon (1999) identified four motivations for web usage: research, communication, shopping and surfing. Their study highlighted the challenges in adopting a dichotomous, goal-directed/experiential framework of web usage. They suggested that research and shopping would be considered goal-directed motivations, and surfing an experiential one. However, the

communication motivation is considered to be being dependent on the purpose to determine whether it is goal-directed or experiential.

In later studies, individual motivations for Internet use are classified into three general types according to values: functional, experiential and social. Functional and experiential values are self-referent—that is, the referent of these values is oneself without relation to other users (Babin et al. 1994). Social values are group-referent values, the referent of which is oneself in relation to other users.

Functional values refer to purposeful, rational and task-related values derived from accomplishing predetermined tasks, such as buying a product, solving a problem or obtaining and providing information using the Internet (Babin et al. 1994; Dholakia et al.

2004). This kind of value is increased by task achievement rather than by usage experience itself (Babin et al. 1994). Functionally motivated users usually have special purposes for using the Internet.

Experiential values are generated solely from the experience of Internet usage process.

For example, many users use the Internet for enjoyment and relaxation, through random browsing and surfing (Ko et al. 2005; Stafford et al. 2004). Compared to functional values, experiential values are gratified by the act of the medium or technology usage itself, regardless of whether or not predetermined tasks are completed.

Social values refer to social benefits derived from establishing and maintaining interaction with other users (Dholakia et al. 2004). Prior research has shown that many users use the Internet primarily to meet and interact with like-minded individuals and look for social support and companionship (Stafford et al. 2004) .

Studies exploring individuals’ motivations for general Internet usage have identified a list of motivation factors. Ko (2000) identified four motivation factors: social escapism, to pass time, interactive control and information. Papacharissi and Rubin (2000) identified five primary motivations for using the Internet: interpersonal utility, to pass time, information seeking, convenience and entertainment. Song et al. (2004) uncovered seven gratification factors specific to Internet use: virtual community, information seeking, aesthetic experience, monetary compensation, diversion, personal status and relationship maintenance. Stafford and Stafford (2004) established three types of gratifications as perceived by Internet users: content gratifications (entertainment, information), process gratifications (Internet surfing, experiencing a new technology) and social gratifications (interpersonal communication and social networking). Using samples from the Indian context, Roy (2009) found six gratifications for Internet use: self-development, wide exposure, user friendly, relaxation, career opportunities and global exchange. Though some studies try to classify these motivations into types based on their values, Joines et al. (2003) argue that it is difficult to definitively classify these motivations into three types as some online activities might have both experiential and functional values. For instance, one might be motivated by the enjoyable process of online shopping as well as by the outcome (having the desired product).

As the Internet has been integrated into the fabric of everyday life, many different

Internet-based applications (such as Facebook, other social networking sites and blogs) emerge and are used. It becomes more difficult to distinguish different motivations definitively into types based on values. Researchers exploring motivations for these kinds of Internet-based applications have added additional insights to the potential motives of Internet use. For instance, Dogruer et al. (2011) explored motives for

Facebook usage, and found that besides general Internet use motives—such as

information seeking, passing time, entertainment and relationship maintenance—people also have self-expression, media drenching and performance motives. Lin and Lu

(2011a) conducted a study to explore factors affecting users’ joining of social networking sites. Results confirmed that networking externalities (number of members, peers and perceived complementarity) were important factors affecting Internet users.

In summary, Internet users have different motivations for using different types of

Internet-based technology or applications in different contexts. To understand online consumers’ motivations in this new e-business context fully, both traditional retail shopping motivation literature and online shopping motivation literature in the e- commerce context are critically reviewed in the following sections, to provide insights into online consumers’ buying behaviour from different perspectives (social, psychological and technological perspectives).

2.6 Traditional Retail Shopping Motivations

Shopping motivation is recognised as a key concept in research on consumer shopping behaviour. In addition to its importance in theory building, shopping motivation exhibits a high managerial relevance, and is often used for the purpose of market segmentation and the development of retail marketing strategies (Westbrook et al. 1985). Due to this high theoretical and practical relevance, shopping motivation has remained a current topic, having been discussed in leading academic journals for more than 30 years.

Shopping Sample and data Motivations Authors context collection

 Communication with others having a similar interest  Diversion  Learning about new trends  Peer group attraction  Physical activity Tauber General Convenient sample  Pleasure of bargaining (1972) shopping of 30 people  Role playing  Self-gratification  Sensory stimulation  Social experience outside the home  Status and authority  Affiliation Urban retail Structured personal department  Anticipated utility Westbrook interviews from stores  Choice optimization 203 adult female and Black  Negotiation Mall and shoppers (1985)  Power and authority shopping  Role enactment centre retailer  Stimulation  Assortment  Company responsiveness  Convenience  Economic utility Eastlick and Surveys from 458 Catalogue  Home environment Feinberg mail catalogue shopping  Information (1999) shoppers  Order services  Perceived value  Reputation 

Shopping Sample and data Motivations Authors context collection

Surveys from 1097  Brand-name merchandise Shopping Reynolds et shoppers in  Convenience malls and al. (2002) traditional mall and  Entertainment factory 827 shoppers in the  Mall essentials outlets outlet mall

 Adventure  Gratification Arnold and Interviews from 98 Retail  Idea shopping Reynolds undergraduate shopping  Role (2003) students  Social  Value Surveys from 467  Diversion Jin and Kim Discount married female  Socialization (2003) store discount shoppers  Utilitarian

Mall-intercept  Eating interviews with 419  Diversion and aesthetic Kim et al. Mall people who are 55 appreciation (2005) shopping or elder in large  Service consumption malls.  Value consumption

 Brand loyal  Brand conscious  Confused by choice  Gratification seeking Surveys from 400 Jamal et al.  Hedonic shopping Supermarket supermarket (2006)  Role playing shoppers  Social high quality seeking  Utilitarian shopping  Value seeking 

Shopping Sample and data Motivations Authors context collection

 Assortment innovation  Assortment uniqueness  Bargain hunting  Efficiency shopping  Gift shopping  Gratification Wagner and  Inspiration General Surveys from 503 Rudolph  Personal friendless shopping shoppers (2010)  Prices  Recreation  Sensory stimulation  Socialization  Service convenience  Store atmosphere  Task-fulfilment Goldsmith et General Surveys from 258  Brand engagement al. (2011) shopping college students  Materialism

Yim et al. Grocery Surveys from 167  Hedonic shopping motivation (2014) shopping in people in the  Impulsiveness superstores superstore  Shopping duration

Table 2-5: Studies exploring traditional retail shopping motivations

Motives are defined as ‘forces instigating behaviour to satisfy internal need states’

(Westbrook et al. 1985, p.89). McGuire (1974) believes that the motivation is the need and desire that drive people to achieve the target. Shopping motives, then, could be defined as the drivers of behaviour that bring consumers to the marketplace to satisfy their needs. Motivation is widely deemed a critical antecedent to a shopper’s behaviour

(Dawson et al. 1990). Various research has recognised the need to understand shopping motivations, in order to help marketers make marketing decisions (Wagner 2007), enhance shopper values (Koo et al. 2008), segment markets (Jin et al. 2003) and predict shopper’s attitudes and behaviours (Delafrooz et al. 2009). Prior research on shopping motives suggests that consumers shop for a variety of reasons. Drawing upon the extant literature, the various shopping motives are summarised in Table 2-5.

Shopping motives can largely be classified into two categories: shopping for product acquisition and shopping for enjoyment of the activity. The product acquisition shopping motive refers to consumers’ retail store visits for the purpose of product acquisition, also referred to as utilitarian shopping motivation. Enjoying shopping as an activity refers to seeking pleasure, inherent in the retail store visit. This shopping motive is referred to as hedonic shopping motivation.

Utilitarian motivation is defined as mission-critical, rational, decision-effective and goal-oriented (Hirschman et al. 1982). Utilitarian motivation shows that shopping starts from a mission or task, and the acquired benefits depend on whether the mission is completed or not, or whether the mission is completed efficiently during the process

(Babin et al. 1994). A list of utilitarian motivations has been identified in previous studies. For instance, in Westbrook and Black’s (1985) study, two dimensions of utilitarian motivation are used to segment consumers: choice optimisation and anticipated utility. Choice optimisation means that consumers can find the right product in the least amount of time. Anticipated utility refers to acquiring the new item to replace the old one, or creating a new image. Adapting items from scales developed by

Babin et al. (1994), Kim (2005) found two dimensions of utilitarian motivation in his study: efficiency and achievement. Efficiency means that consumers need to save time

and resources, while achievement refers to a goal related shopping orientation. Eastlick and Feinberg (1999) explored consumers’ shopping motives for mail catalogue shopping, and found a few utilitarian motives, such as perceived value, order services and convenience.

Motivational theorists have typically regarded human behaviour as the product of both internal need states and external stimuli perceived by the individual (Tauber 1972).

When traditional product acquisition explanations may not fully reflect the motivations for shopping (Bloch et al. 1983), researchers begin to include hedonic motivation factors to explain shopping behaviour (Babin et al. 1994; Wakefiled et al. 1998).

Hedonic motivation refers to those consumption behaviours in search of happiness, fantasy, awakening, sensuality and enjoyment (Hirschman et al. 1982). The benefit of hedonic motivation is experiential and emotional. The reason that hedonic consumers love to shop is that they enjoy the shopping process, rather than the obtaining of the physical product or completing the mission. The fundamental hedonic motivations underlying shopping behaviour have been examined by Tauber (1972), whose basic premise is that shopping behaviour is motivated by a variety of psychosocial needs other than those strictly related to acquiring products. These motivations can be classified as personal and social. The personal motivations include the needs of role playing, diversion, self-gratification, learning about new trends, physical activity and sensory stimulation. Conversely, social motives include the need for social experiences, communication with others, peer group attractions, status, authority and pleasure in bargaining. Tauber’s (1972) major contribution to shopping motive research is his suggestion that acquisition of products is not the only motive, as many of the motives he identified have little to do with product acquisition.

As Tauber’s (1972) study proposed the fundamental motivations for shopping, many subsequent studies extended his research, based on his findings. For instance,

Hirschman and Holbrook (1982) extended Tauber’s (1972) idea by including other hedonic factors such as pleasure, feeling, aesthetics, emotion and enjoyment as additional shopping motivations, and comparing them with traditional utilitarian shopping motivations. They believed that this original viewpoint expanded the scope confined by traditional research on shopping. Their study has not only provided clear definitions of hedonic shopping motivations, but also built the foundation for future studies on consumers’ shopping intentions. Westbrook and Black (1985) linked

Tauber’s (1972) framework to McGuire’s (1974) typology of 16 fundamental human motivations, and proposed seven shopping motivation dimensions from both utilitarian and hedonic perspectives, including anticipated utility (the benefits provided by the product acquired via shopping), role enactment (identifying and assuming culturally prescribed roles), negotiation (seeking economic advantage via bargaining), choice optimisation (searching for and securing the right products to fit one’s demands), affiliation (with others, directly and indirectly), power and authority (attainment of elevated social position) and stimulation (seeking novel and interesting stimuli).

Westbrook and Black’s (1985) study is more comprehensive, including both utilitarian and hedonic motives.

The studies discussed above are based on the general shopping context. Some studies have also explored motivations in other specific shopping contexts, such as catalogue shopping, shopping malls, factory outlets and discount stores. For instance, using a mail survey undertaken by a sample of catalogue shoppers, Eastlick and Feinberg (1999) established a list of motives influencing preferences for catalogue shopping: perceived value, convenience, economic utility, home environment, merchandise assortment,

order services, company clientele, information services, salesperson interaction, company responsiveness and company reputation. Jin and Kim (2003) conducted an exploratory examination of Korean discount shoppers’ shopping motives, and identified three shopping motives: socialisation, diversion and utility. Kim et al. (2005) implemented 419 mall-based intercept interviews with people in large malls, and identified five mall shopping motivations: service consumption, value consumption, eating, diversion and aesthetic.

In summary, consumer shopping motivations in offline contexts varied from utilitarian- related factors to hedonic-related factors. Most studies focused more on the hedonic- related factors. When the Internet and information and communication technologies became a necessity in daily life, e-commerce emerged and changed business operations from brick-and-mortar to click-and-mortar. Various new styles of e-business models in e-commerce have significantly changed ways of conducting business. The following section reviews online consumer shopping motivations in the e-commerce context.

2.7 Shopping Motivations in E-Commerce

Since the late 1990s, e-commerce has taken off, as an increasing number of consumer purchases diversified products available on the Internet. As attracting and retaining online consumers is critical to the success of an e-business, research on the factors affecting online consumers’ purchase intentions has attracted widespread attention.

Researchers have demonstrated that consumers’ acceptance of e-commerce is affected by a number of factors.

Table 2-6 summarises the studies exploring factors affecting online consumers’ purchase intentions. Drawing upon the extant literature, these factors can be summarised in four categories:

1. functional advantages of the Internet as a sale channel;

2. utilitarian and hedonic benefits brought by the shopping process;

3. normative beliefs;

4. consumer characteristics.

Unlike traditional shopping, Internet shopping requires consumers to use Internet technology as the transaction medium, bringing benefits and potential threats to consumers. Factors related to Internet use benefits include perceived ease of use

(Bagdniene et al. 2009; Ganesh et al. 2010; Monsuwe et al. 2004; Shang et al. 2005), perceived usefulness (Monsuwe et al. 2004), online convenience (Bagdniene et al. 2009;

Chiang et al. 2003; Morganosky et al. 2000; Rohm et al. 2004; Schroder et al. 2008; To et al. 2007), Internet self-efficacy (Khalifa et al. 2003; Lian et al. 2008), transaction cost and information availability (Bagdniene et al. 2009; Joines et al. 2003; To et al. 2007).

However, Internet shopping also poses risks to consumers. Some web-use related factors can motivate consumers to accept online shopping if it is controlled well by retailers, but if this is not emphasised by e-retailers, consumers may be demotivated.

These factors include security and privacy perception (Khalifa et al. 2003; Lian et al.

2008; Schroder et al. 2008), delivery-related risk (Schroder et al. 2008), trust (Kim et al.

2010b; Monsuwe et al. 2004), web page loading speed, navigation efficiency and site accessibility (Khalifa et al. 2003).

The second category of factors relate to the utilitarian and hedonic benefits brought by the shopping process. Parsons (2002) applied Tauber’s (1972) personal and social

motives to Internet shoppers in the e-commerce context. They found that the motives of role playing, diversion, self-gratification, learning about new trends, physical activity, sensory stimulation, social experience outside the home, communication with others, peer group attraction, status, authority and the pleasure of bargaining can all apply to

Internet shoppers. Ganesh et al. (2010) proposed that a few segments of online shoppers were very similar to regular shopper groups. Using data collected from 3059 online shoppers, they revealed that there were more similarities than differences among traditional shoppers and online shoppers, in terms of motivations and store attribute importance. Generally, factors in this group include product type (Chiang et al. 2003), role enactment (Ganesh et al. 2010; Lian et al. 2008; Parsons 2002), economic utility

(Chiang et al. 2003; Khalifa et al. 2003; Lian et al. 2008), idea (O'Brien 2010; Parsons

2002), adventure/gratification (O'Brien 2010; Parsons 2002), enjoyment (Monsuwe et al.

2004; Schroder et al. 2008) and fashion involvement (Shang et al. 2005).

The third category of factors are normative beliefs, referring to ‘the perceived behavioural expectations of such important referent of individuals or groups as the person’s spouse, family, friends’ (Azjen 1991). Normative beliefs can motivate behaviour through ‘subjective norms’ (the perceived social pressure to engage or not in a behaviour) based on the theory of planned behaviour (TPB) (Azjen 1991). Studies have found that the referent influence (such as recommendation from friends or relatives) and media influences (Foucault et al. 2002; Limayem et al. 2000) are important factors motivating online shopping intentions. There are inconsistent findings regarding the impact of friends’ influence on online shopping intentions. For example, Limayem et al.

(2000) found that family influence was less important than media influence on online shopping intention, and friends’ influence was not significant in influencing online

shopping intentions. However, friends’ influence was found to be significant in a study of online textbook purchases (Foucault et al. 2002).

The fourth category of factors are consumer characteristics. Variables belonging to this category include innovativeness (Donthu et al. 1999; Limayem et al. 2000), self- efficacy, need for interaction (Monsuwe et al. 2004) and personality traits (Bosnjak et al.

2007; O'Cass et al. 2003). Self-efficacy refers to individuals’ beliefs that they have the ability and resources to perform a specific task successfully. Research has demonstrated that consumers with higher levels of self-efficacy are more likely to use the Internet for shopping (Lian et al. 2008; Parsons 2002). A need for interaction is defined as the importance of human interaction to the consumer in service encounters, and has been found to be positively related to online shopping behaviour (Dabholkar et al. 2002).

Bosnjak et al. (2007) found that personality traits can be divided into three hierarchical levels, including elemental traits, compound traits and situational traits. Elements such as neuroticism, conscientiousness, extraversion, openness and agreeableness are elemental traits. Need for cognition, evaluation, arousal and material resources are the compound traits. Affective involvement and cognitive involvement are situational traits.

All three levels of personality traits served as underlying motivations for online shoppers.

Authors Sampling and data Online shopping motives collection

 Avoid impulse buying

 Buying for a business Morganosky and Surveys from 240 online  Convenience/time Cude (2000) shoppers  Do not like standing in line

 Hate grocery shopping

Authors Sampling and data Online shopping motives collection

 Physical constraints

 Communications with others having similar interest

 Diversion

 Learning about new trends Surveys from 208 online Parsons (2002)  Peer group attraction shoppers  Status and authority

 Self-gratification

 Social experiences outside the home

 Convenience characteristic of Surveys from 147 Chiang and shopping channels consumers in train Dholakia (2003)  Perceived price of the product travelling  Product type characteristics

Surveys from 59  Information motivations

Joines et al. undergraduate students  Interactive control motivations

(2003) and 59 New York State  Socialization motivations residents

 Cheaper prices

 Comparative shopping

 Improved customer service

 Navigation efficiency

 Product description Khaliea and Surveys from 705 Internet  Saving time Limayem (2003) shoppers  Security breach

 Site accessibility

 Social influences

 Transaction efficiency

 Web page loading speed

 Consumer traits Monsuwe et al. Literature review  Ease of use

Authors Sampling and data Online shopping motives collection

(2004)  Enjoyment

 Previous online shopping experiences

 Product characteristics

 Situational factors

 Trust in online shopping

 Usefulness

 Information use in planning and Rohm and shopping Mail surveys from 429 Swaminathan  Online convenience online consumers (2004)  Physical store orientation

 Variety seeking

 Cognitive absorption Shang et al. Surveys from 523 online  Fashion involvement (2005) shoppers  Perceived ease of use

 Affective involvement,

 Agreeableness

 Cognitive involvement

 Conscientiousness

 Extraversion Bosnjak et al. Surveys from 808 Internet  Need for cognition, (2007) users  Need for evaluate

 Need for arousal

 Need for material resources

 Neuroticism

 Openness

 Adventure

 Authority &status Surveys from 157 Internet To et al. (2007)  Convenience shoppers  Cost saving

 Information availability

Authors Sampling and data Online shopping motives collection

 Selection

 Perceived ease of use Lin (2007b) Surveys from 305 students  Perceived usefulness

 Internet self-efficacy

 Perceived web security,

Lian and Lin  Personal innovativeness of Surveys from 123 students (2008) information technology

 Privacy concerns,

 Product involvement

 Convenience orientation

 Delivery-related risk aversion Multi-channel retailing Schroder and  Independence orientation

Zaharia (2008) 525 telephone surveys  Product and payment-related risk aversion

 Recreational orientation

 Brand

Surveys from convenient  Convenience Bagdoniene and sample of 251 online  Information depth Zemblyte (2009) shoppers  Product variety

 Purchase surrounding

 Choice optimization

 Economic utility

Chang et al. Surveys from 293  Emotional utility

(2010) adolescent online shoppers  Role enactment

 Sensory stimulation

 Social interaction

 Affiliation Interviews from 105  Avant-gardism Ganesh et online shoppers and  Online bidding/haggling al.(2010) surveys from 3059 online  Personalized services consumers  Role enactment

Authors Sampling and data Online shopping motives collection

 Stimulation

 Web shopping convenience

 Perceived entertainment

Kim et al. Surveys from 264 online  Perceived informativeness

(2010b) shoppers  Product involvement

 Trust toward websites

 Adventure/gratification

 Idea Surveys from 802 online O’Brien (2010)  Social shoppers  Value and achievement shopping

 Choice and availability Freathy and Interview of 38 Internet  Financial saving Calderwood users  Improved shopping experience (2013)  Time saving

 Adventure shopping

 Gratification shopping Lee et al. (2013b) Surveys from 903 online  Impulsiveness

auction participants  Price sensitivity

 Risk-consciousness

 Variety-seeking

Table 2-6: Studies exploring factors affecting online shopping intentions

In summary, online consumer purchasing motivations in the e-commerce context not only cover utilitarian and hedonic motivations—which are similar to those in offline shopping contexts—but also related to context factors related to Internet technology, online consumers’ personality and experience towards new technology or innovation.

Based on the literature discussed above, the key challenges to understanding online

consumer motivations in the online group buying context are discussed in the following sections.

2.8 Challenges to Understanding Consumer Online Group Buying Motivations

Understanding consumer motivations has been recognised as important in the e-business context (Childers et al. 2001; O'Brien 2010). Although the online group buying phenomenon has attracted researchers in e-commerce, to date there is limited research on online consumers’ motivations for participating in this new type of e-business. As online group buying is driven by the demand of online consumers, understanding consumers’ needs or motivations is important. Generally, three issues need to be addressed to understand online consumers’ motivations in the online group buying context fully.

2.8.1 Understanding the Content of Motivations in Online Group Buying Contexts

Due to the newness of group buying online, there are a lack of studies comprehensively exploring consumers’ motivations for participation. It is imperative for e-marketers to understand the factors motivating online customers, and make promotional strategies based on these factors to attract online customers. Thus, it is important to explore the content of motives influencing online consumers’ consumption behaviours. Although many studies have provided insights into consumers’ motivations for using Internet- based technologies or applications (Joines et al. 2003; Kim et al. 2011b; Roy 2009), most are conducted within general Internet use (Ko 2000; Papacharissi et al. 2000;

Parker et al. 2000; Song et al. 2004) and e-commerce contexts (Bagdniene et al. 2009;

Chiang et al. 2003; Shang et al. 2005; To et al. 2007). Existing research suggests that consumers’ Internet-based technology use motivations are related to a specific context

(Dogruer et al. 2011; Guo et al. 2010), as the needs for different Internet-based applications are different, or the need for the same Internet-based application in different contexts is different. Online group buying is different from B2C or C2C e- commerce in both the purchasing procedure and platform, and may have different motivations. Therefore, it would be inappropriate to simply adopt motivations identified in B2C or C2C e-commerce contexts into the online group buying context.

Few studies have comprehensively examined online consumers’ motivations for participating in online group buying. The extant studies exploring motivation factors are all quantitative in nature (e.g. Chen et al. 2010; Tsai et al. 2011; Yang et al. 2014; Yeh et al. 2014) and the content of motivations are all adapted from prior literature on B2C,

C2C and online auctions. Moreover, a majority of these studies were from an economic perspective, and claimed price as the main motivation factor. Although a few studies tried to incorporate social and technological motivation factors, limited factors—such as review quality, source credibility from a social perspective, perceived ease of use and perceived usefulness from technological perspective—were examined. Motivation and needs theories have demonstrated that most human behaviours are social, goal-directed behaviours. Consumers are not totally rational decision makers motivated by economic factors; they are also motivated by other social and psychological factors (Fullerton

2011). In the e-commerce context, research has emphasised and demonstrated the importance of technological factors in influencing online consumer behaviour (e.g.

Monsuwe et al. 2004; Shang et al. 2005; To et al. 2007). Thus, to explore the content of motivations from social, psychological and technological perspectives, the Use and

Gratification (U&G) theory can be incorporated. Guo et al.’s (2010) study demonstrated

that U&G theory is more appropriate for exploring consumers’ technology use motivations from social and psychological perspectives.

Although the findings of the extant literature have provided some insights into online consumers’ group buying motivations on the Internet, it lacks a comprehensive investigation of the content of motivations. Tsai et al. (2011) and Liao et al. (2011) called for a more comprehensive empirical study to explore more motivation factors behind customers’ decisions to buy through online group buying websites. Given the current focus of e-retailers on this new e-business model, and the lack of suggestions and guidelines for e-marketers in this area, there is clearly a need to conduct research on online consumers’ motivations for using this new e-commerce application, to provide theoretical and practical contributions to e-marketers and suppliers.

2.8.2 Understanding the Hierarchical Structure of Motivations in the Online

Group Buying Context

The hierarchical structure of buyers’ motivations for participating in online group buying is unclear. Research in psychology and organisational behaviour has long recognised the importance of studying the hierarchical structure of human motivation.

Motivation or need theories view motivational hierarchies in terms of developmental prerequisites, in which an individual’s basic needs must be satisfied first before less essential, higher-order needs become activated (Maslow 1970), or hierarchies of subsidisation stating that several lower-level goals may be pursued by an individual to accomplish one ultimate, higher-level goal (Murray 1938). Hierarchies of motivations attempt to capture complex motivational processes (Vallerand et al. 2002), and have emerged as a dominant conceptualisation in various areas of research in the social

sciences. Overall, theories contained in this body of literature share basic principles: human motivations are hierarchically organised (Wicker et al. 1984). Motives on higher levels are more relevant for behaviour than lower-level motives. In this view, different motivational levels are ‘complementary and focus on different aspects of a single underlying mechanism’ (Hyland 1988, p.642).

Reynolds et al. (1995) emphasise that understanding the content of motivations has utility to marketers, but the organisation or structure of the content is also important. As noted by Gutman (1982), the implicative relationships between the content— representing the structure of content—should be a central focus. Despite the recognised importance of the hierarchical nature of motives, e-commerce studies have ignored this.

Most studies (Cameron et al. 2005; Childers et al. 2001; Khalifa et al. 2003) only explore the content of online consumers’ motivations, without exploring the structure of such motives. For instance, Chen and Wu (2010) proposed a list of online group buying motivations, including ordering convenience, lower price, detailed product information, variety of goods, advertising promotions, transaction security, user interface, familiarity and convenience. These motivation variables are seen as isolated variables, which provide suggestions for group buying websites on what they should focus on to attract customers, but fails to indicate how they should do so to satisfy consumers’ needs and motivate them.

A few studies have demonstrated that correlations among motivations exist. For instance, Tsai et al. (2011) explored the motivations behind a customer’s decision to purchase through online group buying websites, finding five interrelated dimensions: website quality, perceived ease of use, perceived usefulness, trust in the virtual community and a sense of virtual community. When Zhang et al. (2014) proposed a

model to describe the motivations of impulse buying behaviour in the online group buying context, results showed inter-relationships between five motivations: review quality, source credibility, observable learning, perceived usefulness and positive affect.

Motivation factor of review quality, source credibility and observable learning were positively related to perceived usefulness and positive affect. Though these studies conducted in the online group buying context have demonstrated and examined the correlations among motivations, the possible underlying hierarchical relationship among motivations have not been addressed.

The Mean-end Chain (MEC) theory can shed light on the hierarchical structure of motivations. It has been extensively used in marketing research to explore the structure of motivations. For instance, in the context of shopping, Wagner (2007) conducted a study to understand consumers’ shopping motivations from a hierarchical perspective.

Based on MEC theory, the study provided insights on how consumers’ cognitive structure relating to the benefits of shopping are hierarchically organised. Likewise,

Zanoli and Naspetti (2002) used MEC to understand consumers’ hierarchical motives in the purchase of organic food. Though the structure of the motivations has been emphasised in these studies, they are all conducted in the offline shopping context, and this has been overlooked in the e-commerce context. Additionally, by combing U&G theory with MEC theory, both the content and structure of motivations can be explored.

For instance, drawing upon a U&G approach and MEC perspective, Guo et al. (2012) investigated how student technology use motivations can be represented as a set of interrelated and hierarchically organised elements. Based on interview data from 16 students, a five-level student technology use hierarchical framework was proposed.

However, the study only used MEC as the theoretical foundation to explain the different

hierarchy of motives, rather than using MEC as the approach to construct the hierarchical motive model.

An investigation of the hierarchical structure of buying motivations has the potential to increase understanding of shoppers’ underlying social, experiential and utilitarian needs, pursued through the shopping process. However, motivation is commonly known to be context specific (Kaltcheva et al. 2006). Whereas research in the offline shopping context has investigated the hierarchical nature of human motivations, this phenomenon has been widely ignored in the e-commerce context. Wagner’s (2007) and Wagner and

Rudolph’s (2010) studies called for research to build a hierarchical motive model in alternative shopping contexts, such as the e-business context. Thus, this study aims to combine the U&G and MEC theory to explore both the content and structure of online consumers’ motivations for participating in online group buying.

2.8.3 Understanding the Benefits-Based Segmentation in the Online Group Buying

Context

Market segmentation is an effort to increase a company’s precision marketing, and has long been recognised as a central concept in both literature and practice (Green et al.

1991). The identification of target customer groups (a homogeneous group with similar needs/wants) is called ‘market segmentation’, in which customers with similar requirements (expectations) and buying characteristics are aggregated into the same group (Kara et al. 1997). Dickson and Ginter (1987, p.4) state that ‘heterogeneity in demand functions exists such that market demand can be disaggregated into segments with distinct demand functions’. The essence of this definition is that market segmentation presupposes heterogeneity in buyers’ preferences for products/service,

and that companies can react to, or possibly produce, preference heterogeneity by modifying their current product/service attributes, distribution and advertising/promotion (Green et al. 1991). As Wind (1978, p.320) states: ‘market segmentation involves viewing a heterogeneous market as a number of smaller homogeneous markets, in response to differing preferences, attributable to the desires of consumers for more precise satisfaction of their varying wants’.

The need for segmentation arises from increasing affluence of consumers, and an increase in the number of alternative products and services available to them. Mass marketing has become less effective in economies in which people differ significantly from others in their motivations, needs, decision processes and buying behaviours

(Wind 1978). It is broadly agreed that the use of segmentation research can help organisations align market strategy with the selected market segments (Wind 1978).

Further, the process of segmenting and selecting markets makes the allocation of corporate resources more efficient, in that funds and human resources are allocated to relatively smaller groups of consumers than if the whole market was the target (Wedel et al. 2000). The practice of segmentation also makes the design of marketing strategy more effective, because managers have the sense of directing resources at specific and identifiable groups of people rather than diverse collections of individuals (Foxall et al.

1994).

Despite its managerial importance, there is a lack of research on e-consumer segmentation in the online group buying context. Research suggests that the identification of online consumer segments has been identified as one of the most important and necessary avenues of research in the field of e-commerce (Brengman et al.

2005). Most segmentation studies in e-commerce or traditional retail shopping contexts

are based on background variables, behavioural variables and motivation variables.

Prior research has indicated that each individual segmentation variable has distinct characteristics, and therefore can be of advantage—as well as disadvantage—to the terms of application (Sun 2007). ‘Background variables’, such as demographics, are relatively objective and easy to measure; however, it is widely acknowledged that a lack of homogeneity within members of a segment—in terms of motivations, needs and behaviour patterns—makes segmentation based on these variables appropriate to locating a target market, but fails to provide accurate information for strategic marketing planning (Hooley et al. 1993). ‘Behavioural variables’ are often used for segmentation, primarily because of the ease in obtaining this sort of data from secondary sources (Wedel et al. 2000). However, behavioural segmentation is most likely to suffer from a lack of ‘causal’ relations between the resultant behaviours and reasons. Thus, segmentation based on behavioural variables can describe the differences in consumers, but fail to explain them. The ‘motivation variables’ based segmentation studies can effectively discern separate homogeneous groups of customers, according to consumers’ preferred benefits, which are the reasons for true market segmentation

(Haley 1968). However, traditional motivation variables-based segmentation studies are mainly items-based, as shown in Table 2-7, which bear the following risks (Botschen et al. 1999):

 several motivations may not be relevant to the respondents, but due to the fact

that all of them are presented, he/she is forced to evaluate them all;

 respondents tend to rate any motivations sought relatively high on the

corresponding rating scale, even those that are not relevant;

 some important motives might be overlooked in the in-depth or focus-group

interviews;

 depending on the number of items, respondents tend to lose concentration.

Additionally, Botschen et al. (1999) have argued that most of motivation variable-based studies did not distinguish between benefits sought by consumers and the corresponding attributes associated with the benefits. Both benefits and attributes are used as motivations for segmentation, which seems problematic (Botschen et al. 1999).

Botschen et al. (1999) argued that using the benefit to segment consumers offers better prospects from both theoretical and practical perspectives. Theoretically, the belief underlying benefit segmentation is that the benefits people are seeking by consuming a product/service are the reasons for the existence of ‘true’ market segments (Haley 1968).

Thus, benefits-based segmentation lies in using causal, as opposed to descriptive, factors for segmentation criteria. This classifies consumers more accurately, based on a causal linkage to consumer behaviour, and identifies potential market segments, normally overlooked by other traditional approaches. From a practical perspective, benefits segmentation based on MEC should allow a deeper understanding of why people seek certain attributes. To focus on the underlying benefits sought permits marketers to adapt their marketing strategies to customers’ underlying expectations, and helps improve customer satisfaction. The corresponding attributes associated with benefits can be applied as a tool for developing advertising strategy. It can provide actionable information for organisational operation. Reynolds and Rochon (2001) argued that many segmentation approaches are limited in their ability to provide actionable guidance to managers, because the segments exist more in data than in the realities of the marketplace. In contrast, the benefits-based segmentation methodology promises to provide segmentation schemes that are actionable in practice, and are thus more valuable than other approaches (Reynolds et al. 2001b). Thus, a benefits-based segmentation study in the online group buying context is valuable and necessary.