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Electronic Markets

, Volume 19, Issue 2–3, pp 89–98 | Cite as

The impact of uncertainty avoidance, social norms and innovativeness on trust and ease of use in electronic customer relationship management

  • Yujong HwangEmail author
Focus Theme

Abstract

Social and individual factors and their relationships to trust in electronic customer relationship management (eCRM) are important topics for e-commerce designers and information systems researchers. In spite of several previous studies of online trust and consumer behavior, none has adequately examined the influences of social and individual factors on online trust in eCRM. In this paper, the relationships among uncertainty avoidance, social norms, personal innovativeness in IT, and multidimensions of online trust (integrity, benevolence, and ability) as well as perceived ease of use (PEOU) are tested, based on a PLS analysis with 209 student samples. Social norms influence all three dimensions of online trust, while uncertainty avoidance affects only the benevolence and ability dimensions. Personal innovativeness in IT affects PEOU, and PEOU influences all three dimensions of online trust. Theoretical and practical implications of these findings beneficial to our understanding of customer relationships in the electronic marketplace are discussed in the paper.

Keywords

eCRM Online trust Uncertainty avoidance Social norms Personal innovativeness in IT 

JEL classification

M15 

References

  1. Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.CrossRefGoogle Scholar
  2. Ba, S., & Pavlou, P. (2002). Evidence of the effect of trust building technology in electronic markets: Price premiums and buyer behavior. MIS Quarterly, 26(3), 243–268.CrossRefGoogle Scholar
  3. Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares approach to causal modeling: Personal computer adoption and use as an Illustration. Technology Studies, 2, 285–309.Google Scholar
  4. Bhattacherjee, A. (2002). Individual trust in online firms: Scale development and initial test. Journal of MIS, 19(1), 211–241.Google Scholar
  5. Birkhofer, B., Schagel, M., & Tomczak, T. (2000). Transaction- and trust-based strategies in E-commerce—a conceptual approach. Electronic Markets, 10(3), 169–175.CrossRefGoogle Scholar
  6. Chin, W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  7. Davis, F., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1002.CrossRefGoogle Scholar
  8. Doney, P., Cannon, J., & Mullen, M. (1998). Understanding the influence of national culture on the development of trust. Academy of Management Review, 23(3), 601–621.CrossRefGoogle Scholar
  9. Doong, H.-S., Wang, H.-C., & Shih, H.-C. (2008). Exploring loyalty intention in the electronic marketplace. Electronic Markets, 18(2), 142–149.CrossRefGoogle Scholar
  10. Dorfman, P. W., & Howell, J. P. (1988). Dimensions of national culture and effective leadership patterns: Hofstede revisited. Advances in International Comparative Management, 3, 127–150.Google Scholar
  11. Falk, R. F., & Miller, N. B. (1992). A Primer for soft modeling. Akron, Ohio: The University of Akron.Google Scholar
  12. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior, an introduction to theory and research. Reading, MA: Addison--Wesley.Google Scholar
  13. Flynn, L., & Goldsmith, R. (1993). A validation of the Goldsmith and Hofacker innovativeness scale. Educational and Psychological Measurement, 53, 1105–1116.CrossRefGoogle Scholar
  14. Fornell, C., & Bookstein, L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19, 440–452.CrossRefGoogle Scholar
  15. Gefen, D. (2002a). Customer loyalty in e-commerce. Journal of the AIS, 3, 27–51.Google Scholar
  16. Gefen, D. (2002b). Reflections on the dimensions of trust and trustworthiness among online consumers. Data Base for Advances in Information Systems, 33(3), 38–53.Google Scholar
  17. Gefen, D., & Straub, D. (2004). Consumer trust in B2C e-commerce and the importance of social presence: Experiments in e-products and e-services. Omega, 31, 407–424.CrossRefGoogle Scholar
  18. Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90.Google Scholar
  19. Goldsmith, R., & Hofacker, C. (1991). Measuring consumer innovativeness. Journal of Academic Marketing Science, 19, 209–221.CrossRefGoogle Scholar
  20. Grazioli, S., & Jarvenpaa, S. (2000). Perils of Internet fraud: An empirical investigation of deception and trust with experienced Internet consumers. IEEE Transactions on Systems, Man, and Cybernetics, 30(4), 395–410.CrossRefGoogle Scholar
  21. Han, K., & Noh, M. (2000). Critical failure factors that discourage the growth of electronic commerce. International Journal of Electronic Commerce, 4(2), 25–43.Google Scholar
  22. Jarvenpaa, S., Tractinsky, N., & Vitale, M. (2000). Consumer trust in an Internet store. Information Technology and Management, 1, 45–71.CrossRefGoogle Scholar
  23. Kale, S. (1991). Culture-specific marketing communications: An analytical approach. International Marketing Review, 8(2), 18–30.CrossRefGoogle Scholar
  24. Kale, S., & Barnes, J. (1992). Understanding the domain of cross-national buyer–seller interactions. Journal of International Business Studies, 23(1), 101–132.CrossRefGoogle Scholar
  25. Kale, S., & Mcintyre, R. P. (1991). Distribution channel relationships in diverse cultures. International Marketing Review, 8(3), 31–45.CrossRefGoogle Scholar
  26. Kegerreis, R. J., Engel, J. F., & Blackwell, R. D. (1970). Innovativeness and diffusiveness: A marketing view of the characteristics of early adopters. In D. Kollat, R. Blackwell, & J. Engels (Eds.), Research in consumer behavior pp. 671–689. New York: Holt, Rineholt, and Winston.Google Scholar
  27. Kraut, R., Mukhopadhyay, T., Szczypula, J., Kiesler, S., & Scherlis, B. (1999). Information and communication: Alternative uses of the Internet in households. Information Systems Research, 10(3), 287–303.CrossRefGoogle Scholar
  28. Lekvall, P., & Wahlbin, C. (1973). A study of some assumptions underlying innovation diffusion functions. Swedish Journal of Economics, 75, 362–377.CrossRefGoogle Scholar
  29. Leonard, L. N. K., & Riemenschneider, C. K. (2008). What factors influence the individual impact of the web? An initial model. Electronic Markets, 18(1), 75–90.CrossRefGoogle Scholar
  30. Leonard-Barton, D., & Deschamps, I. (1988). Managerial influence in the implementation of new technology. Management Science, 34(10), 1252–1265.CrossRefGoogle Scholar
  31. Lewis, D., & Weigert, A. (1985). Trust as a social reality. Social Forces, 63, 967–985.CrossRefGoogle Scholar
  32. Lewis, W., Agarwal, R., & Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: An empirical study of knowledge workers. MIS Quarterly, 27(4), 657–678.Google Scholar
  33. Li, D., Browne, G., & Chau, P. (2006). An empirical investigation of Web site use using a commitment-based model. Decision Sciences, 37(3), 427–444.CrossRefGoogle Scholar
  34. Liang, T., & Huang, J. (1998). An empirical study on consumer acceptance of products in electronic markets: a transaction cost model. Decision Support Systems, 24, 29–43.CrossRefGoogle Scholar
  35. Liao, Z., & Cheung, M. T. (2001). Internet based e-shopping and consumer attitudes: An empirical study. Information & Management, 38, 299–306.CrossRefGoogle Scholar
  36. Limayem, M., Khalifa, M., & Frini, A. (2000). What makes consumers buy from Internet? A longitudinal study of online shopping. IEEE Transactions on Systems, Man, and Cybernetics, 30(4), 421–432.CrossRefGoogle Scholar
  37. Mayer, R., & Davis, J. (1999). The effects of the performance appraisal system on trust in management: A field quasi-experiment. Journal of Applied Psychology, 84(1), 123–136.CrossRefGoogle Scholar
  38. McKnight, D. H., Kacmar, C. J., & Choudhury, V. (2004). Shifting factors and the ineffectiveness of third party assurance seals: A two-stage model of initial trust in a web business. Electronic Markets, 14(3), 252–266.CrossRefGoogle Scholar
  39. McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 13(3), 334–359.CrossRefGoogle Scholar
  40. McKnight, D. H., & Chervany, N. L. (2002). What trust means in e-commerce customer relationships: an interdisciplinary conceptual typology. International Journal of Electronic Commerce, 6(3), 35–60.Google Scholar
  41. Moore, G., & Benbasat, I. (1991). Development of instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.CrossRefGoogle Scholar
  42. Nakata, C., & Sivakumar, K. (1996). National culture and new product development: An integrative review. Journal of Marketing, 60(1), 61–72.CrossRefGoogle Scholar
  43. Pathasarathy, M., & Bhattacherjee, A. (1998). Understanding post-adoption behavior in the context of online services. Information Systems Research, 9(4), 362–379.CrossRefGoogle Scholar
  44. Paul, D. L., & McDaniel, R. R. J. (2004). A field study of the effect of interpersonal trust on virtual collaborative relationship performance. MIS Quarterly, 28(2), 183–227.Google Scholar
  45. Pavlou, P. (2003). Consumer acceptance of electronic commerce: Integrating, trust and risk with the TAM. International Journal of Electronic Commerce, 7(3), 101–134.Google Scholar
  46. Pelto, P. J. (1968). The difference between “tight” and “loose” societies. Transaction, 37, 37–40.Google Scholar
  47. Pennington, R., Wilcox, D., & Grover, V. (2004). The role of system trust in business-to-consumer transactions. Journal of MIS, 20(3), 197–226.Google Scholar
  48. Rogers, E. M. (1983). Diffusion of innovations (3rd ed.). New York: Free.Google Scholar
  49. Saeed, K., Grover, V., & Hwang, Y. (2003a). Creating synergy with a click and mortar approach. Communications of the ACM, 46(12), 206–212.CrossRefGoogle Scholar
  50. Saeed, K., Hwang, Y., & Grover, V. (2003b). Investigating the impact of web site value and advertising on firm performance in electronic commerce. International Journal of Electronic Commerce, 7(2), 121–143.Google Scholar
  51. Saeed, K., Hwang, Y., & Yi, M. (2003c). Toward an integrative framework for online consumer behavior research: A meta-analysis approach. Journal of End User Computing, 15(4), 1–13.Google Scholar
  52. Schlenker, B., Helm, R., & Tedeschi, J. (1973). The effects of personality and situational variables on behavioral trust. Journal of Personality and Social Psychology, 25, 419–427.CrossRefGoogle Scholar
  53. Schoder, D., & Haenlein, M. (2004). The relative importance of different trust constructs for sellers in the online world. Electronic Markets, 14(1), 48–57.CrossRefGoogle Scholar
  54. Simpson, L. (2002). The real reason why CRM initiatives fail. Training, 39, 50–56.Google Scholar
  55. Singh, J. (1990). Managerial culture and work-related values in India. Organization Studies, 11, 75–101.CrossRefGoogle Scholar
  56. Slyke, C. V., Comunale, C. L., & Belanger, F. (2002). Gender differences in perceptions of Web-based shopping. Communications of the ACM, 45(7), 82–86.CrossRefGoogle Scholar
  57. Srite, M., & Karahanna, E. (2006). The role of espoused national cultural values in technology acceptance. MIS Quarterly, 30(3), 679–704.Google Scholar
  58. Thatcher, J. B., & Perrewe, P. L. (2002). An empirical examination of individual traits as antecedents to computer anxiety and computer self-efficacy. MIS Quarterly, 26(4), 381–396.CrossRefGoogle Scholar
  59. Ueno, S., & Sekaran, U. (1992). The influence of culture on budget control practices in the U.S. and Japan: An empirical study. Journal of International Business Studies, 23, 659–674.CrossRefGoogle Scholar
  60. Vellido, A., Lisboa, P., & Meehan, K. (2000). Quantitative characterization and prediction of online purchasing behavior: A latent variable approach. International Journal of Electronic Commerce, 4(4), 83–104.Google Scholar
  61. Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.Google Scholar
  62. Yi, M., & Hwang, Y. (2003). Predicting the use of web-based information systems: Self-efficacy, enjoyment, learning goal orientation, and the TAM. International Journal of Human Computer Studies, 59, 431–449.CrossRefGoogle Scholar

Copyright information

© Institute of Information Management, University of St. Gallen 2009

Authors and Affiliations

  1. 1.School of Accountancy and MIS, DePaul UniversityChicagoUSA

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