Understanding Online Group Purchase Decision Making: a Means-End Chain Approach

Given the enormous growth and significant impacts of group buying on Internet business marketplaces, this study aims to understand consumer decision making process in an online group buying context from a Means-end Chain (MEC) theory perspective. The laddering interview technique was used to interview 58 online group buying users and to capture their reasons behind the online shopping behaviour, with grounded theory used to determine categories. The study found 35 factors in relation to consumer decision making process, which were classified into attributes, consequences, and values. The hierarchical relationships among 35 factors were developed, in which consumer decision making paths were identified. This study has the potential to make significant contributions to both IS research and e-business regarding consumer online group buying decision making process by identifying not only the major consequences/ benefits consumers emphasising, but also the concrete attributes which directly correspond with these benefits as well as the goals/values consumers aim to achieve.

[1]  Joon Koh,et al.  A Comparison of Online Trust Building Factors between Potential Customers and Repeat Customers , 2004, J. Assoc. Inf. Syst..

[2]  H. Schröder,et al.  Linking multi-channel customer behavior with shopping motives: An empirical investigation of a German retailer , 2008 .

[3]  Tillmann Wagner.  Shopping motivation revised: a means‐end chain analytical perspective , 2007 .

[4]  Norizan M. Kassim,et al.  Customer Loyalty in e-Commerce Settings: An Empirical Study , 2008, Electron. Mark..

[5]  Hsi-Peng Lu,et al.  Why people use social networking sites: An empirical study integrating network externalities and motivation theory , 2011, Comput. Hum. Behav..

[6]  Uma Kumar,et al.  Role of Different Electronic-Commerce (Ec) Quality Factors on Purchase Decision: A Developing Country Perspective , 2008 .

[7]  Hao Li,et al.  A Qualitative Research of Tuangou: Modes, Characteristics and Roles of the New E-Business Model , 2009, 2009 International Symposium on Information Engineering and Electronic Commerce.

[8]  Wuu-Yee Chen,et al.  Factors Affecting Consumers' Motivation in Online Group Buyers , 2010, 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[9]  H. Raghav Rao,et al.  A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents , 2008, Decis. Support Syst..

[10]  Jian Chen,et al.  Comparison of the group-buying auction and the fixed pricing mechanism , 2007, Decis. Support Syst..

[11]  T. J. Reynolds,et al.  Laddering theory, method, analysis, and interpretation. , 2001 .

[12]  Yong Liu,et al.  Website attributes in urging online impulse purchase: An empirical investigation on consumer perceptions , 2013, Decis. Support Syst..

[13]  T. J. Reynolds,et al.  Understanding consumer decision making : the means-end approach to marketing and advertising strategy , 2001 .

[14]  Chia-Chen Chang,et al.  Mining customer knowledge for exploring online group buying behaviour , 2012, Expert Syst. Appl..

[15]  Mesut Çiçek,et al.  Online Group Buying: What Is There For The Consumers? , 2011 .

[16]  Matthijs Dekker,et al.  An overview of means-end theory: potential application in consumer-oriented food product design , 2004 .

[17]  Chechen Liao,et al.  Shopping motivations on Internet: A study based on utilitarian and hedonic value , 2007 .

[18]  Peiyu Pai,et al.  User adoption of social networking sites: Eliciting uses and gratifications through a means-end approach , 2013, Comput. Hum. Behav..

[19]  Moez Limayem,et al.  Drivers of Internet shopping , 2003, CACM.

[20]  K. Grunert,et al.  Measuring subjective meaning structures by the laddering method: Theoretical considerations and methodological problems , 1995 .

[21]  Daniel L. Sherrell,et al.  Communications of the Association for Information Systems , 1999 .

[22]  Yoonhyuk Jung,et al.  User goals in social virtual worlds: A means-end chain approach , 2010, Comput. Hum. Behav..

[23]  Jun Yang,et al.  Experiential goods with network externalities effects: An empirical study of online rating system , 2010 .

[24]  Chao-Min Chiu,et al.  Applying means-end chain theory to eliciting system requirements and understanding users perceptual orientations , 2005, Inf. Manag..

[25]  Ming-Tien Tsai,et al.  Understanding online group buying intention: the roles of sense of virtual community and technology acceptance factors , 2011 .

[26]  Tommi Laukkanen,et al.  Mapping the reasons for resistance to Internet banking: A means-end approach , 2007, Int. J. Inf. Manag..

[27]  Hsin Hsin Chang,et al.  The impact of customer interface quality, satisfaction and switching costs on e-loyalty: Internet experience as a moderator , 2008, Comput. Hum. Behav..

[28]  T. J. Reynolds,et al.  A means-end analysis of brand persuasion through advertising , 1995 .

[29]  Dietram A. Scheufele,et al.  Exploring motivations for consumer Web use and their implications for e‐commerce , 2003 .

[30]  S. Naspetti,et al.  Consumer motivations in the purchase of organic food , 2002 .

[31]  J. Gutman.  A Means-End Chain Model Based on Consumer Categorization Processes , 1982 .

[32]  Wee-Kheng Tan,et al.  Online or offline group buying? , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.