Modelling Electronic Customer Relationship Management

Topics: Customer service, Customer, Customer relationship management Pages: 32 (10829 words) Published: January 22, 2013
Behaviour & Information Technology Vol. 28, No. 4, July–August 2009, 373–387

Modelling electronic customer relationship management success: functional and temporal considerations M. Khalifaa* and K.N. Shenb
a

Information Systems Department, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong; bDepartment of Management Information Systems, Abu Dhabi University, PO Box 59911, Abu Dhabi, United Arab Emirates (Received 23 November 2006; final version received 26 January 2008) Previous information systems satisfaction research predominantly focused on generic technological attributes, failing to account for the specificity of the artefact. Furthermore, viewing satisfaction as a static evaluation state, the prevalent cross-sectional approach could not account for the dynamic nature of satisfaction. In this study, we address these gaps by following a functional approach and taking a temporal view in developing and testing a model explaining the effects of various types of electronic customer relationship management (eCRM) functions on customer satisfaction in the context of online shopping. A framework based on the transaction cycle is used to classify eCRM functions into pre-, at-, and post-purchase eCRM. Two distinct temporal phases, i.e. attraction and retention, are identified. The results of a longitudinal survey involving 670 customers of hardware retailers demonstrate the appropriateness of the functional approach in investigating eCRM success and the necessity of the temporal conceptualisation of customer satisfaction. The theoretical and practical implications of these results are discussed. Keywords: online customer satisfaction; electronic customer relationship management; information systems success

1.

Introduction

As organisations are transforming from product- or brand-centric marketing to a relational-centric approach, the importance of customer relationship management (CRM) is hardly questioned. Taking a broad view, CRM encompasses any application or initiative designed to help an organisation optimise interactions with customers, suppliers, or prospects via one or more touch points (e.g. call centre, salesperson and/or website) so as to identify, establish, maintain and enhance long-term associations with customers (Goodhue et al. 2002, Jayachandran et al. 2005). Electronic customer relationship management (eCRM) is concerned with the same principles as a CRM application, but tailored more towards e-commerce and online customers (Romano and Fjermestad 2001). The e-commerce website, therefore, reflects most CRM attributes and serves as the main interface for the customers’ interaction with the company (Horn et al. 2005). Nowadays, eCRM is increasingly used by companies to enhance their electronic marketing capabilities. According to a recent survey by Jupiter, the investment in CRM to back up electronic customer contact will grow from 870 million in 2005 to 4.7 billion in 2006.1 However, the implementation challenges appear to be enormous, as evidenced by commercial marketing research studies.

Approximately 70% of CRM projects result in either losses or no bottom-line improvement in company performance (cf. Reinartz et al. 2004). Rigby and Ledingham (2004) attribute it to the lack of consideration of the customer relationship cycle. Specifically for eCRM, Feinberg and Kadam’s (2002) survey suggests that eCRM failure may be due to the implementation of features that executives believe affect customer satisfaction, but in reality do not have any effect at all. Other studies (e.g. Kohli et al. 2004) pointed to the inadequate support of the customer’s decision-making process as possible reasons for eCRM failure. Given the important role of eCRM in e-commerce in general and e-marketing in particular, there is a growing interest in understanding eCRM success. In information systems (IS) literature, the IS success model (DeLone and McLean 1992) has long provided the theoretical basis for...

References: Agarwal, R. and Venkatesh, V., 2002. Assessing a firm’s web presence: a heuristic evaluation procedure for the measurement of usability. Information Systems Research, 13, 168–186. Ajzen, I., 1991. The theory of planned behavior. Organizational Behavioral and Human Decision Processes, 50, 179– 211. Aladwani, A.M. and Palvia, P.C., 2002. Developing and validating an instrument for measuring userperceived Web quality. Information and Management, 39, 467–476. Anderson, E.W. and Fornell, C., 1994. A customer satisfaction research prospectus. In: R.L. Oliver and R.T. Rust, eds. Frontiers in services marketing. Newbury Park, CA: Sage Publications. Anderson, J.C. and Gerbing, D.W., 1988. Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin, 103, 411–423. Anderson, R.E. and Srinivasan, S.S., 2003. E-satisfaction and e-loyalty: a contingency framework. Psychology and Marketing, 20, 123–138. Anton, J. and Hoeck, M., 2002. E-Business customer service. Santa Monica, CA: The Anton Press. Bailey, J.B. and Pearson, S.W., 1983. Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29 (5), 530–545. Barclay, D.W., Thompson, R.W., and Higgins, C.A., 1995. The partial least squares (PLS) approach to causal modelling: personal computer adoption as an illustration. Technology Studies: Special Issue on Research Methodology, 2, 285–324. Bhattacherjee, A. and Premkumar, G., 2004. Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. MIS Quarterly, 28 (2), 229–254. Bollen, K., 1989. Structural equations with latent variables. New York: Wiley. Bolton, R.N. and Lemon, K.N., 1999. A dynamic model of customers’ usage of services: usage as an antecedent and consequence of satisfaction. Journal of Marketing Research, 36 (2), 171–186. Bower, G.H. and Hilgard, E.R., 1981. Theories of learning. Jersey: Prentice-Hall.
Chin, W.W., 1998. The partial least squares approach for structural equation modelling. In: A.M. George, ed. Modern methods for business research. Mahwah, NJ: Lawrence Erlbaum Associates, 295–336. Cotteman, W.W. and Senn, J.A., 1992. Challenges and strategies for research in systems development. Chichester: Wiley. Davis, F.D., Bagozzi, R.P., and Warshaw, P.R., 1989. User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35, 982– 1003. DeLone, W.H. and McLean, E.R., 1992. Information systems success: the quest for the dependent variable. Information Systems Research, 3, 60–95. DeLone, W.H. and McLean, E.R., 2003. The DeLone and McLean model of information systems success: a tenyear update. Journal of Management Information Systems, 19, 9–30. DeLone, W.H. and McLean, E.R., 2004. Measuring ecommerce success: applying the DeLone & McLean information systems success model. International Journal of Electronic Commerce, 9, 31–47. Ein-Dor, P. and Segev, E., 1978. Organizational context and the success of management information systems. Management Science, 24, 1064–1077. Engel, J.F., Blackwell, R.D., and Miniard, P.W., 1990. Consumer behaviour. Orlando: Dryden Press. Fazio, R., et al., 1982. Attitude accessibility, attitudebehavior consistency, and the strength of the objectevaluation association. Journal of Experimental Social Psychology, 18, 339–357. Feinberg, R.A. and Kadam, R., 2002. E-CRM web service attributes as determinants of customer satisfaction with retail web sites. International Journal of Service Industry Management, 13, 432–451. Feinberg, R.A., et al., 2002. The state of electronic customer relationship management in retailing. International Journal of Retail and Distribution Management, 30, 470–481. Festinger, L., 1957. A theory of cognitive dissonance. Stanford: Stanford University Press. Fiske, S. and Neuberg, S.L., 1990. A continuum of impression formation, from category-based to individual processes: influences of information and motivation on attention and interpretation. In: M.P. Zanna, ed. Advanced in Experimental Social Psychology. New York: Academic Press, 1–74. Fornell, C., 1987. A second generation of multivariate analysis: classification of methods and implications for marketing research. In: M.J. Houston, ed. Review of Marketing. Chicago: American Marketing Association, 407–450. Fournier, S. and Mick, D.G., 1999. Rediscovering satisfaction. Journal of Marketing, 63, 5–23. Gable, G.G., Sedera, D., and Chan, T., 2003. Enterprise systems success: a measurement model, The 24th international conference on information systems, Association for Information Systems. Seattle, Washington. Garrity, E.J. and Sander, G.L., 1998. Information systems success measurement. Hershey: Idea Group Publishing. Goodhue, D.L., Wixom, B., and Watson, H.J., 2002. Realizing business benefits through CRM: hitting the right target in the right way. MIS Quarterly Executive, 1, 79–94. Hair, J.F., et al., 1998. Multivariate data analysis. Englewood Cliffs, NJ: Prentice Hall.
386
M. Khalifa and K.N. Shen
Lu, J., 2003. A model for evaluating e-commerce based on cost/benefit and customer satisfaction. Information Systems Frontiers, 5, 265–277. Lynch, J.G. Jr., Marmorstein, H., and Weigold, M.F., 1988. Choices from sets including remembered brands: use of recalled attributes and prior overall evaluations. Journal of Consumer Research, 15, 169–184. McKinney, V., Yoon, K., and Zahedi, F., 2002. The measurement of web-customer satisfaction: an expectation and disconfirmation approach. Information Systems Research, 13, 296–315. Mittal, V., Kumar, P., and Tsiros, M., 1999. Attribute-level performance, satisfaction, and behavioural intentions over time: a consumption-system approach. Journal of Marketing, 63, 88–101. Nunnally, J.C., 1978. Psychometric theory. New York: McGraw Hill. Oliver, R.L., 1997. Satisfaction: a behavioural perspective on the consumer. New York: McGraw-Hill. Pashler, H.E., 1998. The psychology of attention. Cambridge, MA: The MIT Press. Peter, J.P. and Olson, J.C., 1990. Consumer behaviour and marketing strategy. Homewood: Irwin. Pitkow, J.E. and Recker, M.M., 1995. Using the web as a survey tool: results from the second WWW user survey. Journal of Computer Networks and ISDN Systems, 27, 809–822. Pitt, L.F., Watson, R.T., and Kavan, C.B., 1995. Service quality: a measure of information systems effectiveness. MIS Quarterly, 19, 173–187. Podsakoff, P.M. and Organ, D.W., 1986. Self-reports in organizational research: problems and prospects. Journal of Management, 12, 531–544. Rai, A., Lang, S.S., and Welker, R.B., 2002. Assessing the validity of IS success models: an empirical test and theoretical analysis. Information Systems Research, 13, 50–69. Reinartz, W., Krafft, M., and Hoyer, W.D., 2004. The CRM process: its measurement and impact on performance. [online]. Available from: http://www.ebusinessforum.gr/ content/ Reynolds, T. and Whitlard, D., 1995. Applying laddering data to communications strategy and advertising practice. Journal of Advertising Research, 35, 9–16. Rigby, D.K. and Ledingham, D., 2004. CRM done right. Harvard Business Review, 82, 118–129. Romano, N.C. Jr. and Fjermestad, J., 2001. Electronic commerce customer relationship management: an assessment of research. International Journal of Electronic Commerce, 6, 61–113. Rust, R.T. and Zahorik, A.J., 1993. Customer satisfaction, customer retention, and market share. Journal of Retailing, 69, 193–215. Seddon, P.B., 1997. A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8, 240–253. Seddon, P.B., et al., 1999. Dimensions of information systems success. Communications of the Association for Information Systems, 2 Article 20. Sheng, Y.P., 2002. A business model and framework for electronic customer relationship management. In: The 8th Americas conference on information systems. Association for Information Systems, Dallas Spreng, R.A., Mackenzie, S.B., and Olshavsky, W.O., 1996. A re-examination of the determinants of consumer satisfaction. Journal of Marketing, 60, 15–32.
Helson, H., 1964. Adaptation-level theory: an experimental and systematic approach to behavior. New York: Harper & Row. Higgins, E.T., 1996. Knowledge activation: accessibility, applicability, and salience. In: E.T. Higgins and A.W. Kruglanski, eds. Social psychology: handbook of basic principles. New York: Guilford, 133–168. Hoch, S.J. and Deighton, J., 1989. Managing what consumers learn from experience. Journal of Marketing, 53, 1–20. Hoffman, D.L. and Novak, T.P., 1996. Marketing in hypermedia computer-mediated environments: conceptual foundations. Journal of Marketing, 60, 50–68. Homburg, C., Hoyer, W.D., and Fassnacht, M., 2002. Service orientation of a retailer’s business strategy: dimensions, antecedents, and performance outcomes. Journal of Marketing, 66, 86–101. Horn, D., Feinberg, R., and Salvendy, G., 2005. Determinant elements of customer relationship management in ebusiness. Behaviour & Information Technology, 24, 101– 109. Hulland, J., 1999. Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management Journal, 20, 195–204. Iacobucci, D. and Ostrom, A.L., 1994. The calculus of service quality and customer satisfaction: theoretical and empirical differentiation and integration. In: T.A. Swartz, D.E. Bowen, and S.W. Brown, eds. Advances in services marketing and management: research and practice. Greenwich, Conn: JAI Press, 1–67. Jayachandran, S., et al., 2005. The role of relational information processes and technology use in customer relationship management. Journal of Marketing, 69, 177– 192. Jiang, J.J. and Klein, G., 1999. User evaluation of information systems: by system typology. IEEE Transactions on Systems, Man and Cybernetics: Part A, 29, 111–116. Karahanna, E., Straub, D.W., and Chervany, N.L., 1999. Information technology adoption across time: a crosssectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23, 183–213. Khalifa, M. and Liu, V., 2003. Determinants of satisfaction at different adoption stages of Internet-based services. Journal of AIS, 4, 206–232. Khalifa, M., Limayem, M., and Liu, V., 2002. Online consumer stickiness: a longitudinal study. Journal of Global Information Management, 10, 1–15. Kim, H.W., Lee, G.H., and Pan, S., 2002. Exploring the critical success factors for customer relationship management and electronic customer relationship management systems. In: The 23rd international conference on information systems. Association for Information Systems, Barcelona, Spain. Kohli, R., Devaraj, S., and Mahmood, M.A., 2004. Understanding determinants of online consumer satisfaction: a decision process perspective. Journal of Management Information Systems, 21, 115–135. Limayem, M., Cheung, C.M.K., and Chan, G.W.W., 2003. Explaining information systems adoption and post-adoption: toward an integrated model. In: The 23rd international conference on information systems. Association for Information Systems, Barcelona, Spain. Liu, C. and Arnett, K.P., 2000. Exploring the factors associated with web site success in the context of electronic commerce. Information and Management, 38, 23–33.
Behaviour & Information Technology
Tam, J.L.M., 2005. Examining the dynamics of consumer expectations in a Chinese context. Journal of Business Research, 58, 777–786. Winer, R.S., 2001. A framework for customer relationship management. California Management Review, 43, 89– 105. Wolfinbarger, M.F. and Gilly, M.C., 2001. Shopping online for freedom control and fun. California Management Review, 43, 34–55. Wyer, R.S. and Srull, T.K., 1986. Human cognition in its social context. Psychological Review, 93, 322–359.
387
Zhang, P. and von Dran, G.M., 2000. Satisfiers and dissatisfiers: a two-factor model for website design and evaluation. Journal of American Society for Information Science, 51, 1253–1268. Zhu, K. and Kraemer, K.L., 2002. E-commerce metrics for net-enhanced organizations: assessing the value of ecommerce to firm performance in the manufacturing sector. Information Systems Research, 13, 275–295.
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