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Examining online consumers’ initial trust building from an elaboration likelihood model perspective

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Abstract

Due to the high perceived risk and low switching costs, it is critical for online vendors to foster consumers’ initial trust in order to facilitate their online transactions. The extant research has focused on using the technology acceptance model to examine initial trust, and has seldom disclosed the processes through which initial trust develops. Drawing on the elaboration likelihood model, this research examined online consumers’ initial trust building when visiting a new website for the first time. The results indicated that initial trust develops along dual routes including a central route represented by argument quality and a peripheral route represented by source credibility. Self-efficacy significantly moderates the effect of argument quality on initial trust. In addition, we found the direct effects of both cultural variables-uncertainty avoidance and individualism-on initial trust.

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References

  • Amoako-Gyampah, K., & Meredith, J. R. (2007). Examining cumulative capabilities in a developing economy. International Journal of Operations and Production Management, 27(9), 928–950.

    Article  Google Scholar 

  • Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: the elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339–370.

    Google Scholar 

  • Ba, S., Whinston, A. B., & Zhang, H. (2003). Building trust in online auction markets through an economic incentive mechanism. Decision Support Systems, 35(3), 273–286.

    Article  Google Scholar 

  • Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  • Beldad, A., de Jong, M., & Steehouder, M. (2010). How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust. Computers in Human Behavior, 26(5), 857–869.

    Article  Google Scholar 

  • Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quarterly, 30(4), 805–825.

    Google Scholar 

  • Bock, G.-W., Lee, J., Kuan, H.-H., & Kim, J.-H. (2012). The progression of online trust in the multi-channel retailer context and the role of product uncertainty. Decision Support Systems, 53(1), 97–107.

    Article  Google Scholar 

  • Carlson, J., & O’Cass, A. (2011). Creating commercially compelling website-service encounters: an examination of the effect of website-service interface performance components on flow experiences. Electronic Markets, 21(4), 237–253.

    Article  Google Scholar 

  • Chen, R., & Sharma, S. K. (2013). Self-disclosure at social networking sites: an exploration through relational capitals. Information Systems Frontiers, 15(2), 269–278.

    Article  Google Scholar 

  • CNNIC (2012). China Internet Payment Security Report, China Internet Network Information Center.

  • CNNIC (2014). 33rd Statistical Survey Report on the Internet Development in China, China Internet Network Information Center.

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Article  Google Scholar 

  • Fuller, M. A., Serva, M. A., & Benamati, J. (2007). Seeing is believing: the transitory influence of reputation information on e-commerce trust and decision making. Decision Sciences, 38(4), 675–699.

    Article  Google Scholar 

  • Gefen, D., & Pavlou, P. A. (2012). The boundaries of trust and risk: the quadratic moderating role of institutional structures. Information Systems Research, 23(3), 940–959.

    Article  Google Scholar 

  • Gefen, D., Straub, D. W., & Boudreau, M. C. (2000). Structural equation modeling and regression: guidelines for research practice. Communications of the Association for Information Systems, 4(7), 1–70.

    Google Scholar 

  • Greiner, M. E., & Wang, H. (2011). Building consumer-to-consumer trust in e-finance marketplaces: an empirical analysis. International Journal of Electronic Commerce, 15(2), 105–136.

    Article  Google Scholar 

  • Hofstede, G. H. (1984). Culture’s consequences: International differences in work-related values. Beverly Hills: CA, Sage Publications.

    Google Scholar 

  • Hu, X., Wu, G., Wu, Y., & Zhang, H. (2010). The effects of Web assurance seals on consumers’ initial trust in an online vendor: a functional perspective. Decision Support Systems, 48(2), 407–418.

    Article  Google Scholar 

  • Hwang, Y., & Lee, K. C. (2012). Investigating the moderating role of uncertainty avoidance cultural values on multidimensional online trust. Information and Management, 49(3–4), 171–176.

    Article  Google Scholar 

  • Kim, D. (2008). Self-perception-based versus transference-based trust determinants in computer-mediated transactions: a cross-cultural comparison study. Journal of Management Information Systems, 24(4), 13–45.

    Article  Google Scholar 

  • Kim, J. B. (2012). An empirical study on consumer first purchase intention in online shopping: integrating initial trust and TAM. Electronic Commerce Research, 12(2), 125–150.

    Article  Google Scholar 

  • Kim, Y. H. and Kim, D. J. (2005). A study of online transaction self-efficacy, consumer trust, and uncertainty reduction in electronic commerce transaction. Proceedings of the 38th Hawaii International Conference on System Sciences.

  • Kim, S., & Park, H. (2013). Effects of various characteristics of social commerce (s-commerce) on consumers’ trust and trust performance. International Journal of Information Management, 33(2), 318–332.

    Article  Google Scholar 

  • Kim, G., Shin, B., & Lee, H. G. (2009). Understanding dynamics between initial trust and usage intentions of mobile banking. Information Systems Journal, 19(3), 283–311.

    Article  Google Scholar 

  • Lai, J. Y., Ulhas, K. R., & Lin, J. D. (2014). Assessing and managing e-commerce service convenience. Information Systems Frontiers, 16(2), 273–289.

    Article  Google Scholar 

  • Lee, M., & Lee, J. (2012). The impact of information security failure on customer behaviors: a study on a large-scale hacking incident on the internet. Information Systems Frontiers, 14(2), 375–393.

    Article  Google Scholar 

  • Li, C. Y. (2013). Persuasive messages on information system acceptance: a theoretical extension of elaboration likelihood model and social influence theory. Computers in Human Behavior, 29(1), 264–275.

    Article  Google Scholar 

  • Li, Y.-M., & Yeh, Y.-S. (2010). Increasing trust in mobile commerce through design aesthetics. Computers in Human Behavior, 26(4), 673–684.

    Article  Google Scholar 

  • Li, F., Pienkowski, D., van Moorsel, A., & Smith, C. (2012). A holistic framework for trust in online transactions. International Journal of Management Reviews, 14(1), 85–103.

    Article  Google Scholar 

  • Liang, H., Saraf, N., Hu, Q., & Xue, Y. (2007). Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. MIS Quarterly, 31(1), 59–87.

    Google Scholar 

  • Lim, K. H., Sia, C. L., Lee, M. K. O., & Benbasat, I. (2006). Do I trust you online, and if so, will I buy? An empirical study of two trust-building strategies. Journal of Management Information Systems, 23(2), 233–266.

    Article  Google Scholar 

  • Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: an empirical study of mobile banking services. Decision Support Systems, 49(2), 222–234.

    Article  Google Scholar 

  • Malhotra, N. K., Kim, S. S., & Patil, A. (2006). Common method variance in IS research: a comparison of alternative approaches and a reanalysis of past research. Management Science, 52(12), 1865–1883.

    Article  Google Scholar 

  • Marakas, G. M., Yi, M. Y., & Johnson, R. D. (1998). The multilevel and multifaceted character of computer self-efficacy: toward clarification of the construct and an integrative framework for research. Information Systems Research, 9(2), 126–163.

    Article  Google Scholar 

  • Marakas, G. M., Johnson, R. D., & Clay, P. F. (2007). The evolving nature of the computer self-efficacy construct: an empirical investigation of measurement construction, validity, reliability and stability over time. Journal of the Association for Information Systems, 8(1), 16–46.

    Google Scholar 

  • Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. The Academy of Management Review, 20(3), 709–734.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Nunnally, J. C. (1978). Psychometric theory. New York: McGraw-Hill.

    Google Scholar 

  • Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion: Central and peripheral routes to attitude change. New York: Springer.

    Book  Google Scholar 

  • Petty, R. E., & Wegener, D. T. (1999). The elaboration likelihood model: Current status and controversies. In S. Chaiken & Y. Trope (Eds.), Dual-process theories in social psychology. New York: Guilford Press.

    Google Scholar 

  • Petty, R. E., Cacioppo, J. T., & Goldman, R. (1981). Personal involvement as a determinant of argument-based persuasion. Journal of Personality and Social Psychology, 41(5), 847–855.

    Article  Google Scholar 

  • Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: problems and prospects. Journal of Management, 12(4), 531–544.

    Article  Google Scholar 

  • Sia, C. L., Lim, K. H., Lee, M. K. O., Huang, W. W., & Benbasat, I. (2009). Web strategies to promote internet shopping: is cultural-customization needed? MIS Quarterly, 33(3), 491–512.

    Google Scholar 

  • Slyke, C. V., Lou, H., Belanger, F., & Sridhar, V. (2010). The influence of culture on consumer-oriented electronic commerce adoption. Journal of Electronic Commerce Research, 11(1), 30–40.

    Google Scholar 

  • Straub, D., Boudreau, M.-C., & Gefen, D. (2004). Validation guidelines for IS positivist research. Communications of the Association for Information Systems, 13(1), 380–427.

    Google Scholar 

  • Tanriverdi, H. (2006). Performance effects of information technology synergies in multibusiness firms. MIS Quarterly, 30(1), 57–77.

    Google Scholar 

  • Wang, Y.-S., Yeh, C.-H., & Liao, Y.-W. (2013). What drives purchase intention in the context of online content services? The moderating role of ethical self-efficacy for online piracy. International Journal of Information Management, 33(1), 199–208.

    Article  Google Scholar 

  • Yoon, C. (2009). The effects of national culture values on consumer acceptance of e-commerce: online shoppers in china. Information and Management, 46(5), 294–301.

    Article  Google Scholar 

  • Zhou, T. (2011). An empirical examination of initial trust in mobile banking. Internet Research, 21(5), 527–540.

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by grants from the National Natural Science Foundation of China (71371004, 71332001), and a grant from the Research Center of Information Technology & Economic and Social Development in Zhejiang Province.

Author information

Authors and Affiliations

  1. School of Management, Hangzhou Dianzi University, Hangzhou, 310018, People’s Republic of China

    Tao Zhou

  2. School of Management, Huazhong University of Science and Technology, Wuhan, 430074, People’s Republic of China

    Yaobin Lu

  3. College of Business Administration, University of Texas-Pan American, Edinburg, TX, 78539, USA

    Bin Wang

Authors
  1. Tao Zhou
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  2. Yaobin Lu
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  3. Bin Wang
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Corresponding authors

Correspondence to Tao Zhou or Yaobin Lu.

Appendices

Appendix 1: The scales and items

  • Argument quality (AQ) (adapted from Bhattacherjee and Sanford (2006))

    1. AQ1

      The information provided by this website is helpful.

    2. AQ2

      The information provided by this website is valuable.

    3. AQ3

      The information provided by this website is persuasive.

  • Source credibility (SC) (adapted from Bhattacherjee and Sanford (2006))

    1. SC1

      This website looks like an expert of its field.

    2. SC2

      This website has a good reputation.

    3. SC3

      This website has rich knowledge in its field.

  • Uncertainty avoidance (UA) (adapted from Yoon (2009))

    1. UA1

      When starting a new job, I fear doing it.

    2. UA2

      I fear uncertainty about the future.

    3. UA3

      I fear ambiguous situations and unfamiliar adventures.

  • Individualism (IDV) (adapted from Yoon (2009))

    1. IDV1

      Individual rewards are more important than group welfare.

    2. IDV2

      Individual success is more important than group success.

    3. IDV3

      Having autonomy and independence is more important than being accepted as a member of a group.

  • Self-efficacy (SE) (adapted from Kim and Kim (2005))

    1. SE1

      I am confident I can always purchase exactly the item that I want online.

    2. SE2

      I am confident I can obtain relevant information from multiple sources (e.g. online forums, reputation sites, etc.) about the site from which I make purchases.

    3. SE3

      I am confident I can deal with the problems on my own if I meet with unsatisfactory things during online purchase.

  • Initial trust (TRU) (adapted from Lim et al. (2006))

    1. TRU1

      This website has the ability to fulfill its tasks.

    2. TRU2

      This website will keep its promises.

    3. TRU3

      This website will keep customers’ best interests in mind.

  • Purchase intention (PUR) (adapted from Lim et al. (2006))

    1. PUR1

      I am considering purchasing from this website now.

    2. PUR2

      I will recommend this website to other persons.

    3. PUR3

      I am likely to make future purchases from this website.

Appendix 2

Table 6 CMV test results using PLS
Full size table

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Zhou, T., Lu, Y. & Wang, B. Examining online consumers’ initial trust building from an elaboration likelihood model perspective. Inf Syst Front 18, 265–275 (2016). https://doi.org/10.1007/s10796-014-9530-5

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  • DOI: https://doi.org/10.1007/s10796-014-9530-5

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