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How user relationships affect user perceived value propositions of enterprises on social commerce platforms

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Abstract

Social commerce is a popular topic issue in the academic field. Prior research mostly focused on the effectiveness of social commerce on consumers. However, the effect of social commerce on electronic commerce enterprises has rarely been involved. By combining social network theories, information theories, and the value theory of electronic commerce, with information quality and credibility as the path, this study investigates how inter-user relationship on a social commerce platform affect user’s perceptions of the value proposition of electronic commerce enterprises. The results show that the instrumental inter-user relationships can significantly improve a consumer’s perceptions of a product’s quality and information, and then improve the perception of efficiency value proposition and novelty value proposition of electronic commerce enterprises. The expressive relationships between users can effectively improve the expression of consumer awareness of product credibility, and thus enhance the consumer’s perception of the value proposition of electronic commerce enterprises.

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References

  • Amit, R., & Zott, C. (2001). Value creation in e-business. Strategic Management Journal, 22(6–7), 493–520.

    Article  Google Scholar 

  • Anderson, J. C., & Narus, J. A. (2006). Customer value propositions in business markets. Harvard Business Review, 84(3), 1–11.

    Google Scholar 

  • Ballantyne, D., & Varey, R. J. (2006). Creating value-in-use through marketing interaction: The exchange logic of relating, communicating and knowing. Marketing Theory, 6(3), 335–348.

    Article  Google Scholar 

  • Bharati, P., & Chaudhury, A. (2004). An empirical investigation of decision-making satisfaction in web-based decision support systems. Decision Support Systems, 37(2), 187–197.

    Article  Google Scholar 

  • Cheung, C. M., Lee, M. K., & Rabjohn, N. (2008). The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities. Internet Research, 18(3), 229–247.

    Article  Google Scholar 

  • Cheung, M. Y., et al. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. International Journal of Electronic Commerce, 13(4), 9–38.

    Article  Google Scholar 

  • Chiu, C.-M., Hsu, M.-H., & Wang, E. T. (2006). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42(3), 1872–1888.

    Article  Google Scholar 

  • Cross, R., Borgatti, S. P., & Parker, A. (2001). Beyond answers: Dimensions of the advice network. Social Networks, 23(3), 215–235.

    Article  Google Scholar 

  • Curty, R. G., & Zhang, P. (2011). Social commerce: Looking back and forward. Proceedings of the American Society for Information Science and Technology, 48(1), 1–10.

    Article  Google Scholar 

  • DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of informantion systems success: A ten-year update. Journal of Management Information Systems, 19, 9–30.

    Article  Google Scholar 

  • DeLone, W. H., & McLean, E. R. (2004). Measuring electronic commerce success: Applying the DeLone & McLean information systems success model. International Journal of Electronic Commerce, 9(1), 31–47.

    Google Scholar 

  • Dennison, G., Bourdage-Braun, S., & Chetuparambil, M. (2009). Social commerce defined. IBM White Paper.

  • Doll, W. J., & Torkzadeh, G. (1988). The measurement of end-user computing satisfaction. MIS Quarterly, 12(2), 259–274.

    Article  Google Scholar 

  • Doney, P. M., & Cannon, J. P. (1997). An examination of the nature of trust in buyer-seller relationships. Journal of Marketing, 61, 35–51.

    Article  Google Scholar 

  • Gaffney, M., & Rafferty, P. (2009). Making the long tail visible: social networking sites and independent music discovery. (Translated from English). Program, 43(4), 375–391 (in English).

    Article  Google Scholar 

  • Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27, 51–90.

    Google Scholar 

  • Gibbons, D. E. (2004). Friendship and advice networks in the context of changing professional values. Administrative Science Quarterly, 49(2), 238–262.

    Google Scholar 

  • Granovetter, M. (1983). The strength of weak ties: A network theory revisited. Sociological Theory, 1(1), 201–233.

    Article  Google Scholar 

  • Hung, K. H., & Li, S. Y. (2007). The influence of eWOM on virtual consumer communities: Social capital, consumer learning, and behavioral outcomes. Journal of Advertising Research, 47(4), 485.

    Article  Google Scholar 

  • Hung, K., Li, S. Y., & Tse, D. K. (2011). Interpersonal trust and platform credibility in a Chinese multibrand online community. Journal of Advertising, 40(3), 99–112.

    Article  Google Scholar 

  • Ibarra, H., & Andrews, S. B. (1993). Power, social influence, and sense making: Effects of network centrality and proximity on employee perceptions. Administrative Science Quarterly, 38, 277–303.

    Article  Google Scholar 

  • Jaynes, E. T. (1957). Information theory and statistical mechanics. Physical Review, 106(4), 620–631.

    Article  Google Scholar 

  • Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544–564.

    Article  Google Scholar 

  • Kim, H.-W., Gupta, S., & Koh, J. (2011). Investigating the intention to purchase digital items in social networking communities: A customer value perspective. Information Management, 48(6), 228–234.

    Article  Google Scholar 

  • Ko, D.-G., Kirsch, L. J., & King, W. R. (2005). Antecedents of knowledge transfer from consultants to clients in enterprise system implementations. MIS Quarterly, 29, 59–85.

    Google Scholar 

  • Komiak, S. Y. X., & Benbasat, I. (2006). The effects of personalizaion and familiarity on trust and adoption of recommendation agents. MIS Quarterly, 30(4), 941–960.

    Google Scholar 

  • Levin, D. Z., & Cross, R. (2004). The strength of weak ties you can trust: The mediating role of trust in effective knowledge transfer. Management Science, 50(11), 1477–1490.

    Article  Google Scholar 

  • Liang, T.-P., & Turban, E. (2011). Introduction to the special issue social commerce: A research framework for social commerce. International Journal of Electronic Commerce, 16(2), 5–14.

    Article  Google Scholar 

  • Liang, T.-P., Lai, H.-J., & Ku, Y.-C. (2006). Personalized content recommendation and user satisfaction: Theoretical synthesis and empirical findings. Journal of Management Information Systems, 23(3), 45–70.

    Article  Google Scholar 

  • Manev, I. M., & Stevenson, W. B. (2001). Nationality, cultural distance, and expatriate status: Effects on the managerial network in a multinational enterprise. Journal of International Business Studies, 32, 285–303.

    Article  Google Scholar 

  • Marsden, P. V. (1988). Homogeneity in confiding relations. Social Networks, 10(1), 57–76.

    Article  Google Scholar 

  • McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for electronic commerce: An integrative typology. Information Systems Research, 13(3), 334–359.

    Article  Google Scholar 

  • Murray, K. B., & Häubl, G. (2009). Personalization without interrogation: Towards more effective interactions between consumers and feature-based recommendation agents. Journal of Interactive Marketing, 23(2), 138–146.

    Article  Google Scholar 

  • Nambisan, S. (2002). Designing virtual customer environments for new product development: Toward a theory. Academy of Management Review, 27(3), 392–413.

    Google Scholar 

  • Parker, G. G., & Alstyne, M. W. V. (2005). Two-sided network effects: A theory of information product design. Management Science, 51(10), 1494–1504.

    Article  Google Scholar 

  • Podolny, J. M., & Baron, J. N. (1997). Resources and relationships: Social networks and mobility in the workplace. American Sociological Review, 62, 673–693.

    Article  Google Scholar 

  • Shriver, S. K., Nair, H. S., & Hofstetter, R. (2013). Social ties and user-generated content: Evidence from an online social network. Management Science, 59(6), 1425–1443.

    Article  Google Scholar 

  • Stephen, A. T., & Toubia, O. (2010). Deriving value from social commerce networks. Journal of Marketing Research, 47(2), 215–228.

    Article  Google Scholar 

  • Stewart, K. J. (2003). Trust transfer on the world wide web. Organization Science, 14(1), 5–17.

    Article  Google Scholar 

  • Suarez, F. F. (2005). Network effects revisited: The role of strong ties in technology selection. Academy of Management Journal, 48(4), 710–720.

    Article  Google Scholar 

  • Surowiecki, J. (2004). The wisdom of crowds: Why the many are smarter and how collective wisdom shapes business, economies, societies, and nations. New York: Doubleday.

    Google Scholar 

  • Van den Bulte, C., & Joshi, Y. V. (2007). New product diffusion with influentials and imitators. Marketing Science, 26(3), 400–421.

    Article  Google Scholar 

  • Wang, J.-C., & Chiang, M.-J. (2009). Social interaction and continuance intention in online auctions: A social capital perspective. Decision Support Systems, 47(4), 466–476.

    Article  Google Scholar 

  • Xiao, B., & Benbasat, I. (2007). Electronic commerce product recommendation agents: Use, characteristics, and impact. MIS Quarterly, 31(1), 137–209.

    Google Scholar 

  • Ye, Q., et al. (2011). The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings. Computers in Human Behavior, 27(2), 634–639.

    Article  Google Scholar 

  • Zhao, J. (2013). Case study on social electronic commerce modle based on grounded theory. Master theis, Nanjing: Nanjing University.

  • Zhou, S., Siu, F., & Wang, M. (2010). Effects of social tie content on knowledge transfer. Journal of Knowledge Management, 14(3), 449–463.

    Article  Google Scholar 

  • Zhu, X. (2011). The effect of different value propositions and their interaction on electronic commerce corporate performance. Master thesis, Nanjing: Nanjing University.

  • Zott, C., & Amit, R. (2007). Business model design and the performance of entrepreneurial firms. Organization Science, 18(2), 181–199.

    Article  Google Scholar 

  • Zott, C., & Amit, R. (2008). The fit between product market strategy and business model: Implications for firm performance. Strategic Management Journal, 29(1), 1–26.

    Article  Google Scholar 

  • Zott, C., & Amit, R. (2010). Business model design: An activity system perspective. Long Range Planning, 43(2–3), 216–226.

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. School of Business, Nanjing University, Nanjing, China

    Chengde Zheng, Xiaofeng Yu & Qiming Jin

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  1. Chengde Zheng
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  2. Xiaofeng Yu
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  3. Qiming Jin
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Correspondence to Xiaofeng Yu.

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Zheng, C., Yu, X. & Jin, Q. How user relationships affect user perceived value propositions of enterprises on social commerce platforms. Inf Syst Front 19, 1261–1271 (2017). https://doi.org/10.1007/s10796-017-9766-y

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  • DOI: https://doi.org/10.1007/s10796-017-9766-y

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