Segmenting online customers to manage business resources: A study of the impacts of sales channel strategies on consumer preferences

This study extends our current knowledge in the area of online consumer behavior by examining how a business's sales channel strategy could influence consumer's sales channel preferences. It makes a new argument that business strategies could play an important role in consumer sales channel preference development. When a business offers multiple sales channels (a hybrid model), its customers can compare sales channels either within or outside of the same corporate business. Such freedom is, however, diminished when a business employs the Internet as the only transaction medium (pure Internet store). A matrix was developed to demonstrate how business strategies could interplay in the consumer preference formation process and later was used to segment our respondents into three different groups. They were segmented according to the sales channel strategies of their selected Internet store and the brick-and-mortar store that they used to make a comparison. MANOVA and structural equation modeling tests were performed on 435 survey respondents. Four preferential factors, including transaction cost, product, risk, and social experience, were used as examples and tested across three groups of respondents. Results revealed that online users employ different sets of preferential factors when comparing different sets of sales channels. Such results were thereafter used to draw a new set of online strategies that could be used to allocate business resources more effectively.

[1]  Prabhudev Konana,et al.  Customer Satisfaction in Virtual Environments: A Study of Online Investing , 2003, Manag. Sci..

[2]  A. Tversky Intransitivity of preferences. , 1969 .

[3]  KonanaPrabhudev,et al.  Customer Satisfaction in Virtual Environments , 2003 .

[4]  Detmar W. Straub,et al.  The Relative Importance of Perceived Ease of Use in IS Adoption: A Study of E-Commerce Adoption , 2000, J. Assoc. Inf. Syst..

[5]  Allan D. Shocker,et al.  Multiattribute Approaches for Product Concept Evaluation and Generation: A Critical Review , 1979 .

[6]  Peter A. Todd,et al.  Consumer Reactions to Electronic Shopping on the World Wide Web , 1996, Int. J. Electron. Commer..

[7]  James R. Bettman,et al.  Formal Models of Consumer Behavior: A Conceptual Overview , 1972 .

[8]  Gerald L. Lohse,et al.  Predictors of online buying behavior , 1999, CACM.

[9]  Lei-da Chen,et al.  Enticing online consumers: an extended technology acceptance perspective , 2002, Inf. Manag..

[10]  Y. Braunstein,et al.  Information management , 1996 .

[11]  William L. Wilkie,et al.  Issues in Marketing's use of Multi-Attribute Attitude Models , 1973 .

[12]  M. C. Hill,et al.  Evaluating Model Fit , 2005 .

[13]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[14]  Peng S. Chan,et al.  Succeeding in the Dotcom Economy: Challenges for Brick & Mortar Companies , 2003 .

[15]  Detmar W. Straub,et al.  Validating Instruments in MIS Research , 1989, MIS Q..

[16]  Nigel Magson,et al.  Time to fly: An approach to segmentation and modelling customer dynamics in the travel sector , 2004 .

[17]  Yannis Bakos,et al.  The emerging role of electronic marketplaces on the Internet , 1998, CACM.

[18]  P. F. Anderson Marketing, Strategic Planning and the Theory of the Firm , 1982 .

[19]  Robert E. Kraut,et al.  Information and Communication: Alternative Uses of the Internet in Households , 1999, Inf. Syst. Res..

[20]  F. Kardes,et al.  The Role of Direction of Comparison, Attribute-Based Processing, and Attitude-Based Processing in Consumer Preference , 1999 .

[21]  Prashant Palvia,et al.  Explaining Alternative Behaviors of Online Consumers: An Integration of the Technology Acceptance Model to Preferential Decision , 2003, AMCIS.

[22]  John G. Lynch,et al.  Interactive Home Shopping: Consumer, Retailer, and Manufacturer Incentives to Participate in Electronic Marketplaces , 1997 .

[23]  Michelle B. Kunz,et al.  Online customers: identifying store, product and consumer attributes which influence shopping on the internet , 1997 .

[24]  Fatemeh Zahedi,et al.  The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach , 2002, Inf. Syst. Res..

[25]  Joseph M. Jones,et al.  Print and Internet catalog shopping: assessing attitudes and intentions , 2000, Internet Res..

[26]  Bart J. Bronnenberg,et al.  Exploring the implications of the internet for consumer marketing , 1997 .

[27]  Ting-Peng Liang,et al.  Effect of store design on consumer purchases: an empirical study of on-line bookstores , 2002, Inf. Manag..

[28]  Peter H. Reingen,et al.  Modeling Individual Preference Evolution and Choice in a Dynamic Group Setting , 1996 .

[29]  C. Ranganathan,et al.  Key dimensions of business-to-consumer web sites , 2002, Inf. Manag..

[30]  Gilbert A. Churchill A Paradigm for Developing Better Measures of Marketing Constructs , 1979 .

[31]  Yoram Wind,et al.  Multiattribute decisions in marketing : a measurement approach , 1973 .

[32]  A. Tversky,et al.  BELIEF IN THE LAW OF SMALL NUMBERS , 1971, Pediatrics.

[33]  Lu-Ping Douglas Tseng A generic choice heuristic model for the description, explanation, and prediction of consumer preferential decisions , 1988 .

[34]  Bob D. Cutler,et al.  Dogmatism and Internet Usage by University Students: Are Dogmatics Late Adopters? , 1998 .

[35]  Gurpreet Dhillon,et al.  TORKZADEH AND DHILLON Measuring Factors that Influence the Success of Internet , 2015 .

[36]  C. Marcus A practical yet meaningful approach to customer segmentation , 1998 .

[37]  H. J. Einhorn Use of nonlinear, noncompensatory models as a function of task and amount of information , 1971 .

[38]  Albert H. Segars,et al.  Re-examining perceived ease of use and usefulness , 1993 .

[39]  H. Raghav Rao,et al.  On risk, convenience, and Internet shopping behavior , 2000, CACM.

[40]  A. Nation Online: How Americans Are Expanding Their Use of the Internet , 2002 .

[41]  C I HOVLAND,et al.  Assimilation and contrast effects of anchoring stimuli on judgments. , 1958, Journal of experimental psychology.

[42]  Mark L. Gillenson,et al.  The hybrid clicks and bricks business model , 2003, CACM.

[43]  A. Tversky,et al.  On the psychology of prediction , 1973 .

[44]  Rajiv Kohli,et al.  Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics , 2002, Inf. Syst. Res..

[45]  Jorgen P. Bansler,et al.  Corporate Intranet Implementation: Managing Emergent Technologies and Organizational Practices , 2000, J. Assoc. Inf. Syst..

[46]  Naveen Donthu,et al.  The Internet Shopper , 1999 .

[47]  João Carlos Mota [At risk]. , 2007, Revista portuguesa de cirurgia cardio-toracica e vascular : orgao oficial da Sociedade Portuguesa de Cirurgia Cardio-Toracica e Vascular.

[48]  M. Browne,et al.  Alternative Ways of Assessing Model Fit , 1992 .

[49]  김정남 고객과 지식 Marketing , 2003 .

[50]  A. Tversky,et al.  Subjective Probability: A Judgment of Representativeness , 1972 .

[51]  Eric Walden,et al.  The Impact of E-Commerce Announcements on the Market Value of Firms , 2001, Inf. Syst. Res..

[52]  A. Rangaswamy,et al.  Consumer Choice Behavior in Online and Traditional Supermarkets: The Effects of Brand Name, Price, , 2000 .

[53]  Deepak Prem Subramony,et al.  Why Users Choose Particular Web Sites Over Others: Introducing a "Means-End" Approach to Human-Computer Interaction , 2002, J. Electron. Commer. Res..

[54]  M. Dekimpe,et al.  The Market Valuation of Internet Channel Additions , 2002 .

[55]  Prashant C. Palvia,et al.  Developing and validating an instrument for measuring user-perceived web quality , 2002, Inf. Manag..

[56]  R. Hoyle Structural equation modeling: concepts, issues, and applications , 1997 .