Skip to main content
SpringerLink
Log in

Mood and social presence on consumer purchase behaviour in C2C E-commerce in Chinese culture

  • General Research
  • Published:
Electronic Markets Aims and scope Submit manuscript

Abstract

While the importance of mood and emotion has been recognized in Information Systems research, they have been studied only tangentially. To explore the influence of mood and social presence on consumer purchase behaviour in consumer-to-consumer (C2C) e-Commerce, a lab experiment with 200 participants is conducted in China. The structural model explains 36.9 % of the variance in purchase intention. The results indicate that mood plays an important role in consumer purchase behaviour, which has significant impacts on perceived benefit and purchase intention. Social presence has moderating effects between mood and perceived benefit, and between mood and purchase intention. We also find that two cultural dimensions (individualism and uncertainty avoidance) have significant impacts on purchase intention.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  • Bauer, R. A. (1967). Consumer behavior as risk taking. In D. F. Cox (Ed.), Risk taking and information handling in consumer behavior (pp. 23–33). Boston University Press.

  • Beaudry, A., & Pinsonneault, A. (2010). The other side of acceptance: studying the direct and indirect effects of emotions on information technology use. MIS Quarterly, 34(4), 689–710.

    Google Scholar 

  • Chin, W. W., Gopal, A., & Salisbury, W. D. (1997). Advancing the theory of adaptive structuration: the development of a scale to measure faithfulness of appropriation. Information Systems Research, 8(4), 342–367.

    Article  Google Scholar 

  • Chou, K. L., Lee, T. M., & Ho, A. H. (2007). Does mood state change risk taking tendency in older adults. Psychology and Aging, 22(2), 310–318.

    Article  Google Scholar 

  • Chu, K.-K., & Li, C.-H. (2008). A study of the effect of risk-reduction strategies on purchase intentions in online shopping. International Journal of Electronic Business Management, 6(4), 213–226.

    Google Scholar 

  • Clark, M. S., & Isen, A. M. (1982). Toward understanding the relationship between feeling states and social behavior. New York: Elsevier/North Holland.

    Google Scholar 

  • CNNIC (2009). Statistical survey report on the internet development in China: China Internet Network Information Centero. Document Number)

  • Compeau, D., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: a longitudinal study. MIS Quarterly, 23(2), 145–158.

    Article  Google Scholar 

  • Dash, S., & Saji, K. B. (2007). the role of consumer self-efficacy and website social-presence in customers’ adoption of B2C online shopping an empirical study in the Indian context. Journal of International Consumer Marketing, 20(2), 33–49.

    Article  Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

    Article  Google Scholar 

  • Djamasbi, S., & Strong, D. M. (2008). The effect of positive mood on intention to use computerized decision aids. Information Management, 45(1), 43–51.

    Article  Google Scholar 

  • Djamasbi, S., Strong, D. M., & Dishaw, M. (2010). Affect and acceptance: examining the effects of positive mood on the technology acceptance model. Decision Support Systems, 48, 383–394.

    Article  Google Scholar 

  • Forgas, J. P. (1995) Mood and Judgment: The Affect Infusion Model (AIM). Psychological Bulletin, 117(1), 39–66.

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

    Article  Google Scholar 

  • Fredrickson, B. L. (2003). Positive emotions and upward spirals in organizations. San Francisco: Berret Koehler Publishers.

    Google Scholar 

  • Fulk, J., Steinfield, C. W., Schmitz, J., & Power, J. G. (1987). A social information processing model of media use in organizations. Communication Research, 14(5), 520–552.

    Article  Google Scholar 

  • Gabriel, I. J., & Nyshadham, E. (2008). A cognitive map of people ’s online risk perceptions and attitudes an empirical study. Proceedings of the 41st Hawaii International Conference on System Sciences, (pp. 1–10).

  • Gefen, D., & Straub, D. (2003). Managing user trust in B2C e-Services. e-Service Journal, 2(2), 7–24.

    Article  Google Scholar 

  • Gefen, D., & Straub, D. W. (2004). Consumer trust in B2C e-Commerce and the importance of social presence: experiments in e-Products and e-Services. Omega, 32, 407–424.

    Article  Google Scholar 

  • George, J. M. (1989). Mood and absence. Journal of Applied Psychology, 74(2).

  • George, J. M., & Jones, G. R. (1996). The experience of work and turnover intentions: interactive effects of value attainment, job satisfaction, and positive mood. Journal of Applied Psychology, 81(3).

  • Gratch, J., & Marsella, S. (2004). A domain-independent framework for modeling emotion. Cognitive Systems Research, 5, 269–306.

    Article  Google Scholar 

  • Hassanein, K., & Head, M. (2007). Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping. International Jounal Human-Computer Studies, 65, 689–708.

    Article  Google Scholar 

  • Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions and organizations across nations. Thousand Oaks: Sage Publications.

    Google Scholar 

  • Hsu, M.-H., & Chiu, C.-M. (2004). Predicting electronic service continuance with a decomposed theory of planned behavior. Behaviour and Information Technology, 23(5), 359–373.

    Article  Google Scholar 

  • Paul Peter, J., & Tarpey, L. X. (1975). A comparative analysis of three consumer decision strategies. Journal of Consumer Research, 2(1), 29–37.

    Article  Google Scholar 

  • Kim, D. J., Cho, B., & Rao, H. R. (2000). Effects of consumer lifestyles on purchasing behavior on the internet: A conceptual framework and empirical validation. Paper presented at the Proceedings of the twenty first international conference on Information systems, Brisbane, Queensland, Australia

  • 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, 544–564.

    Article  Google Scholar 

  • Kim, D. J., Ferrin, D. L., & Rao, H. R. (2009). Trust and satisfaction, two stepping stones for successful e-commerce relationships. Information Systems Research, 20(2), 237–257.

    Article  Google Scholar 

  • Kumar, N., & Benbasat, I. (2002). Para-social presence and communication capabilities of a web site: a theoretical perspective. e-Service Journal, 1(3), 5–24.

    Article  Google Scholar 

  • Kumar, N., & Benbasat, I. (2006). The influence of recommendations and consumer reviews on evaluations of websites. Information Systems Research, 17(4), 425–439.

    Article  Google Scholar 

  • Lee, M.-C. (2009). Factors influencing the adoption of internet banking an integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8, 130–141.

    Article  Google Scholar 

  • 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 

  • Li, H., Sarathy, R., & Zhang, J. (2008). The role of emotions in shaping consumers’ privacy beliefs about unfamiliar onlne vendors. Journal of Information Privacy and Security, 4(3).

  • Li, H., Sarathy, R., & Xu, H. (2011). The role of affect and cognition on online consumers’ decision to disclose personal information to unfamiliar online vendors Decision Support Systems.

  • Liu, X., & Wei, K. K. (2003). An empirical study of product differences in consumers’E-commerce adoption behavior. Electronic Commerce Research and Applications, 2, 229–239.

    Article  Google Scholar 

  • Malhotra, Y., & Galletta, D. (2005). A multidimensional commitment model of volitional systems adoption and usage behavior. Journal of Management Information Systems, 22(1), 117–151.

    Google Scholar 

  • Mano, H. (1999). The influence of pre-existing negative affect on store purchase intentions. Journal of Retailing, 75(2), 149–172.

    Article  Google Scholar 

  • Martin, L. L., Ward, D. W., Achee, J. W., & Wyer, R. S., Jr. (1993). Mood as input: people have to interpret the motivational implications of their moods. Journal of Personality and Social Psychology, 64, 317–326.

    Article  Google Scholar 

  • Mathwick, C., Malhotra, N. K., & Rigdon, E. (2001). Experiential value: conceptualization, measurement and application in the catalogue and Internet shopping environment. Journal of Retailing, 77(1), 39–56.

    Article  Google Scholar 

  • McKinney, L. N. (2004). Creating a satisfying internet shopping experience via atmospheric variables. International Journal of Consumer Studies, 28(3), 268–283.

    Article  Google Scholar 

  • McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site a trust building model. The Journal of Strategic Information Systems, 11, 297–323.

    Article  Google Scholar 

  • Miranda, S. M., & Saunders, C. S. (2003). The social construction of meaning: an alternative perspective on information sharing. Information Systems Research, 14(1), 87–106.

    Article  Google Scholar 

  • Moon, J., Chadee, D., & Tikoo, S. (2008). Culture, product type, and price influences on consumer purchase intention to buy personalized products online. Journal of Business Research, 61, 31–39.

    Article  Google Scholar 

  • Mulder, M. (1977). The daily power game. Leiden: Martinnus Nijhoff.

    Book  Google Scholar 

  • Neelankavil, J. P., Mathur, A., & Zhang, Y. (2000). Determinants of managerial performance: a cross-cultural comparison of the perceptions of middle-level managers in four countries. Journal of International Business Studies, 31(1), 121–140.

    Article  Google Scholar 

  • Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.

    Google Scholar 

  • Park, J., Lennon, S. J., & Stoel, L. (2005). On-line product presentation: effects on mood, perceived risk, and purchase intention. Psychology and Marketing, 22(9), 695–719.

    Article  Google Scholar 

  • Peter, J. P., & Ryan, M. J. (1976). An investigation of perceived risk at the brand level. Journal of Marketing Research, 13, 184–188.

    Article  Google Scholar 

  • Rice, R. E., Hughes, D., & Love, G. (1989). Usage and outcomes of electronic messaging at an R and D organization: situational constraints, job level, and media awareness. Office, Technology and People, 5(2), 141–161.

    Article  Google Scholar 

  • Rogers, E. M. (1983). Diffusion of innovations. New York: Free Press.

    Google Scholar 

  • Shang, Rong-An, Chen, Yu-Chen, & Shen, L. (2005). Extrinsic versus intrinsic motivations for consumers to shop on-line. Information Management, 42, 401–413.

    Article  Google Scholar 

  • Samadi, M., & Yaghoob-Nejadi, A. (2009). A survey of the effect of consumers perceived risk on purchase intention in e-shopping. Business Intelligence Journal, 2(2), 261–275.

    Google Scholar 

  • Shih, H.-P. (2004). An empirical study on predicting user acceptance of eshopping on the web. Information Management, 41, 351–368.

    Article  Google Scholar 

  • Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. London: Wiley.

    Google Scholar 

  • Steinfield, C. W. (1986). Computer-mediated communications in an organizational setting: Explaining task-related and socio-emotional uses. Newbury Park, CA.

  • Straub, D., & Karahanna, E. (1998). Knowledge worker communications and recipient availability: toward a task closure explanation of media choice. Organization Science, 9(2), 160–175.

    Article  Google Scholar 

  • Swan, K., & Shih, L. F. (2005). On the nature and development of social presence in online course discussions. Journal of Asynchronous Learning Networks, 9(3), 115–136.

    Google Scholar 

  • Thayer, R. E. (1989). The biopsychology of mood and arousal. New York: Oxford University Press.

    Google Scholar 

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478.

    Google Scholar 

  • Wixom, B. H., & Watson, H. J. (2001). An empirical investigation of the factors affecting data warehousing. MIS Quarterly, 25(1), 17–41.

    Article  Google Scholar 

  • Yoo, Y., & Alavi, M. (2001). Media and group cohesion: relative influences on social presence, task participation, and group consensus. MIS Quarterly, 25(3), 371–390.

    Article  Google Scholar 

  • Zimmer, J. C., Arsal, R., Al-Marzouq, M., Moore, D., & Grover, V. (2010). Knowing your customers: using a reciprocal relationship to enhance voluntary information disclosure. Decision Support Systems, 48, 395–406.

    Article  Google Scholar 

  • Zuboff, S. (1988). In the age of the smart machine: The future of work and power. New-York: Basic Books.

    Google Scholar 

Download references

Acknowledgment

This research is partially supported by The National Nature Science Foundation in China (No.71172126, 70872073)

This research is partially supported by the National Natural Science Foundation in China (No.70801049) and the “Project 211(Phase III)” of Southwestern University of Finance and Economics in China.

Author information

Authors and Affiliations

  1. School of Business Administration, Southwestern University of Finance and Economics University, Chengdu, China

    Hanpeng Zhang

  2. Information Sciences & Technology, The Pennsylvania State University, 76 University Dr. Hazleton, PA, 18202, USA

    Yong Lu

  3. Foreign Language Department, Ningbo City College, Zhejiang, China

    Xiaoli Shi

  4. Shanghai Jiaotong University, Shanghai, China

    Zongming Tang

  5. Ohio State University, Columbus, OH, USA

    Zhijian Zhao

Authors
  1. Hanpeng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaoli Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zongming Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhijian Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zongming Tang.

Additional information

Responsible editor: Xin Luo

Appendices

Appendix A

Table 3

Table 3 Survey instrument
Full size table

Appendix 2

Table 4

Table 4 Summary of measurement model
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhang, H., Lu, Y., Shi, X. et al. Mood and social presence on consumer purchase behaviour in C2C E-commerce in Chinese culture. Electron Markets 22, 143–154 (2012). https://doi.org/10.1007/s12525-012-0097-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12525-012-0097-z

Keywords

JEL classification

Search

Navigation