基于“心流体验”视角的在线消费者购买行为影响因素研究
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摘要
网络购物作为一种崭新的消费模式,日益受到商家和消费者的关注。根据Iresearch艾瑞市场咨询2004年中国网络购物研究报告预期,国内网络购物市场今后三年的市场规模年均增长率将达到87.5 %,2007年总市场规模约为296亿人民币。随着网络购物市场的迅猛发展,网上商家之间的竞争也越来越激烈,而对于网上商家而言,要想在网络销售中获利,处于竞争的有利地位,把握消费者网络购物行为的特征非常重要,而且随着产品同质化程度的提高,“眼球经济”时代的到来,消费者体验日益受到重视,“心流体验”理论是消费者体验理论中一个非常重要的方面,也是消费体验理论中引用最多的概念之一,本文将“心流体验”理论与在线消费者网络购物行为研究相结合,对在线消费者心流体验及其购物行为之间的关系进行了研究,并提出了理论模型,进而利用结构方程模型的方法对其进行了验证,得出了有意义的结论。
本研究发现在线消费者购物过程中所形成的“远程感知(tele-presense)”和“感知控制力(perceived control)”对于其产生心流体验具有重要的作用,另外消费者与网站之间的交互响应速度、消费者技能水平、购物过程中的挑战水平以及感知易用性也对消费者产生心流体验有一定的影响作用,同时,这种“心流体验”又会正向影响到他/她的购物行为,包括无计划购物行为和重返购买行为,除此之外,本研究发现消费者对网站的“感知实用性”也是影响其作出重复购买决策的重要变量。
本研究结论表明为了发挥购物网站的最大效用,电子商务企业或网站设计人员应将“创造用户的心流体验”作为重要目标之一,而要做到如此,就必须重视网站的“情境导向”,而不仅仅注重内容与产品层面的设计,同时,网站的实用性也是需要考虑的重要变量。另外,消费者与网站之间的互动也是要着重考虑的要素之一,但在注重提高互动性的同时,也不能以牺牲消费者的“感知易用性”为代价。
As a new kind of consumptive pattern, online shopping has been paid more and more attention by the companies and consumers. According to the research on 2004 Chinese Online Shopping made by Iresearch, the average rising rate of the market size of Chinese online shopping in the following three years will reach 87.5% and the total market size in 2007 is about 296 billion RMB. As the online shopping market developing swiftly and violently, the competition among online companies is becoming more and more fiercely. For the online companies, it is important to capture the characteristics of online consumers in order to make profits from the electronic commerce and obtain big market size. What’s more, as the quality of products or services is becoming more and more homogeneous and the appearance of“Eye Economy”, the shopping experience of consumers is being paid more attention. Flow theory is one of the most important aspects of consumer experience theory and also one of the most common-used concepts. This research will apply flow theory into online consumer purchasing behavior research and analyze the relationship between them. A conceptual model is proposed to achieve some meaningful conclusions through the test with Structural Equation Model method.
It is concluded that“tele-presense”and“perceived control”of the online consumers formed in the process of online shopping play an important role in the factors affecting flow experience, as well as the“interactive speed”,“skill of consumer”,“challenge”and“perceived ease of use”. At the same time, this flow experience will positively affect his or her online purchasing behavior, including unplanned purchase and intention of repeat purchase. Besides, it is found that“perceived usefulness”of the website plays a vital role in online consumers’making repeat purchase decisions.
This research has demonstrated that flow is a useful and practical tool to understand consumers’experience while shopping online. In order to maximize the effectiveness of a website, the goal should be the creation of a beneficial flow experience. The context-based presentation of the website must be paid more attention, not only the content-based presentation. What’s more, the usefulness of the website and the interactivity between online consumers and website are also indispensable factors. However, improving a website’s interactivity shouldn’t sacrifice the website’s ease of use.
本研究发现在线消费者购物过程中所形成的“远程感知(tele-presense)”和“感知控制力(perceived control)”对于其产生心流体验具有重要的作用,另外消费者与网站之间的交互响应速度、消费者技能水平、购物过程中的挑战水平以及感知易用性也对消费者产生心流体验有一定的影响作用,同时,这种“心流体验”又会正向影响到他/她的购物行为,包括无计划购物行为和重返购买行为,除此之外,本研究发现消费者对网站的“感知实用性”也是影响其作出重复购买决策的重要变量。
本研究结论表明为了发挥购物网站的最大效用,电子商务企业或网站设计人员应将“创造用户的心流体验”作为重要目标之一,而要做到如此,就必须重视网站的“情境导向”,而不仅仅注重内容与产品层面的设计,同时,网站的实用性也是需要考虑的重要变量。另外,消费者与网站之间的互动也是要着重考虑的要素之一,但在注重提高互动性的同时,也不能以牺牲消费者的“感知易用性”为代价。
As a new kind of consumptive pattern, online shopping has been paid more and more attention by the companies and consumers. According to the research on 2004 Chinese Online Shopping made by Iresearch, the average rising rate of the market size of Chinese online shopping in the following three years will reach 87.5% and the total market size in 2007 is about 296 billion RMB. As the online shopping market developing swiftly and violently, the competition among online companies is becoming more and more fiercely. For the online companies, it is important to capture the characteristics of online consumers in order to make profits from the electronic commerce and obtain big market size. What’s more, as the quality of products or services is becoming more and more homogeneous and the appearance of“Eye Economy”, the shopping experience of consumers is being paid more attention. Flow theory is one of the most important aspects of consumer experience theory and also one of the most common-used concepts. This research will apply flow theory into online consumer purchasing behavior research and analyze the relationship between them. A conceptual model is proposed to achieve some meaningful conclusions through the test with Structural Equation Model method.
It is concluded that“tele-presense”and“perceived control”of the online consumers formed in the process of online shopping play an important role in the factors affecting flow experience, as well as the“interactive speed”,“skill of consumer”,“challenge”and“perceived ease of use”. At the same time, this flow experience will positively affect his or her online purchasing behavior, including unplanned purchase and intention of repeat purchase. Besides, it is found that“perceived usefulness”of the website plays a vital role in online consumers’making repeat purchase decisions.
This research has demonstrated that flow is a useful and practical tool to understand consumers’experience while shopping online. In order to maximize the effectiveness of a website, the goal should be the creation of a beneficial flow experience. The context-based presentation of the website must be paid more attention, not only the content-based presentation. What’s more, the usefulness of the website and the interactivity between online consumers and website are also indispensable factors. However, improving a website’s interactivity shouldn’t sacrifice the website’s ease of use.
引文
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[42] Bezjian-Avery, A., Calder, B. & Iacobussi, D. 1998. New media interactive advertising vs. traditional advertising. Journal of Advertising Research 38(4) 23-32.
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[44] Ellis, Gary D., Judith E. Voelkl, Catherine Morris. 1994. Measurement and analysis issues with explanation of variance in daily experience using the flow model. J. Leisure Res. 26(4) 337-356.
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[2] Straub, DW. Watson, RT. 2001. Researching IT and Electronic Commerce: Transfromational Issues. Information Systems Research.
[3] Csikszentmihalyi, Mihaly. Judith LeFevre. 1989. Optimal experience in work and leisure. J. Personality and Social Psychology 56(5) 815-822.
[4] 王静慧. 1998. 网络浏览涉入与流畅经验之相关性研究 [P]. 中山大学企业管理研究所硕士论文.
[5] 黄琼慧. 2000. 从沉浸理论探讨台湾大专学生之网络使用行为 [P]. 交通大学传播所硕士论文.
[6] 黄立文. 1998. 网络使用的快感与神迷——游戏理论与网络浏览行为之初探[C]. 高雄:中山大学.
[7] Csikszentmihalyi. M. 1993. The evolving self: a psychology for the third millennium [M]. New York: Harper-Collins.
[8] Trevino, Linda Klebe, Jane Webster. 1992. Flow in computer-mediated communication. Comm. Res. 19(5) 539-573.
[9] Ghani, Jawaid A., Satish P. Deshpande. 1994. Task characteristics and the experience of optimal flow in human-computer interaction. J. Psychology 128(4) 381-391.
[10] Webster, Jane, L.K. Trevino, L. Ryan. 1993. The dimensionality and correlates of flow in human computer interactions. Comput. Human Behavior 9(4) 411-426.
[11] Csikszentmihalyi. M. 1990. Flow: The psychology of Optimal Experience. New York: Harper and Row.
[12] Leone, C. & Burns, J. 2000. ‘The measurement of locus of control: Assessing more than meets the eye ?’. Journal of Psychology 134(1): 63-76.
[13] Edwards, J. R., Baglioni, A. J. & Cooper, C. L. 1990. Examining the relationshipsamong self-report measures of the Type A behavior pattern: The effects of dimensionality, measurement error, and differences in underlying constructs. Journal of Applied Psychology 75(4): 440-454.
[14] Novak, Thomas P. 1999. Internet marketing: influences, themes and directions. Paper presented at the AMA/Sheth Foundation Doctoral Consortium, University of Southern California, August 3-7.
[15] Csikszentmihalyi, M. 1975. Beyond boredom and anxiety. San Francisco, CA: Jossey-Bass.
[16] Moneta, G. B. & Csikszentmihalyi, M. 1996. The effect of perceived challenges and skills on the quality of subjective experience. Journal of Personality 64(2): 275-310.
[17] Massimini, F. & Carli, M. 1988. The systematic assessment of flow in daily experience. Cambridge University Press, Cambridge 266-287.
[18] Clarke, S. G. & Haworth, J. T. 1994. “Flow” experience in the daily lives of sixth form college students. British Journal of Psychology 85: 511-523.
[19] Jackson, S. A. & Marsh, H. W. 1996. Development and validation of a scale to measure optimal experience: The flow state scale. Journal of Sport & Exercise Psychology 18(1): 17-35.
[20] Sato, I. 1988. Bosozoku: Flow in Japanese motorcycle gangs, in Csikszentmihalyi, M. Optimal Experience: Psychological Studies of Flow in Consciousness, Cambridge University Press, Cambridge, 92-117.
[21] Maslow, A. H. 1970. Motivation and Personality, 2nd edn, Harper& Row, New York.
[22] Privette, G. 1983. Peak experience, peak performance, and flow: A comparative analysis of positive human experience, Journal of Personality and Social Psychology 45(6): 1361-1368.
[23] Trevino, L. K. & Webster, J. 1992. Flow in computer-mediated communication: Electronic mail and voice mail evaluation and impacts. Communication Research 19(5): 539-573.
[24] Hoffman, D. L. & Novak, T. P. 1997. A new marketing paradigm for electroniccommerce. The Information Society 13(1): 43-54.
[25] Hoffman, D. L. & Novak, T. P. 1996. Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing 60(3): 50-68.
[26] Steuer, J. 1992. Defining virtual reality: Dimensions determining telepresense. Journal of Communication 42(4): 73-93.
[27] Novak, T. P., Hoffman, D. L., Yung, Y. F. 2000. Measuring the customer experience in online environments: a structural modeling approach. Marketing Science. 19(1) 22-42.
[28] Chen, H., Wigand, R. T. & Nilan, M. 1998. Optimal flow experience in Web navigation, in Khosrowpour, M. Effective Utilization and Management of Emerging Information Techonologies, Idea Group Publishing, Hershey, Pennsylvania 633-636.
[29] 胡子超. 2006. 网络购物行为的影响因素分析[M]. 科技创新(8): 68-69.
[30] 何其帼. 林梅华. 2006. 网上购物行为影响因素实证研究. 经济管理·新管理(10): 44-49.
[31] Javenpaa, S. L. & Todd, P. A. 1996. Consumer Reactions To Electronic Shopping On the World Wide Web. Journal of Electronic Commerce 1(2): 69-88.
[32] 郑冉冉. 宋泽. 2007. 网上购物意图影响因素实证研究. 商业经济与管理(7): 54-67.
[33] Miyazaki, A. D. & Fernandez, A. 2001. Consumer perception of privacy and security risks for online shopping. The Journal of Consumer Affairs 35(1): 27-44.
[34] 陈慧卿. 2006. 消费者购买行为分析. 商业经济(1): 96-98.
[35] 蔡雅琦. 施俊琦. 王垒. 2004. 冲动性购买行为的研究综述. 应用心理学(3): 53-57.
[36] Rook, D.W. 1987. The buying impulse. Journal of Consumer Research 14:189-199.
[37] Christy, M.K., Cheung, Lei Zhu, Timothy Kwong, Gloria, W.W., Chan, Moez Limayem. 2003. Online consumer behavior: A review and Agenda for Future research. 16th Bled eCommerce Conference.
[38] Fung, R.K.K. & Lee, M.K.O. 1999. EC-Trust (Trust in Electronic Commerce): Exploring the antecedent factors. Proceedings of the fifth Americas Coference on Information Systems. 517-519.
[39] Khalifa, M. & Liu, V. 2001. Satisfaction with internet-based services: A longitudinal study. Proceedings of the International Conference of Information Systems 601-606.
[40] Liang, T.P. & Lai, H.J. 2002. Effect of Store Design on Consumer Purchases: An empirical stud of online bookstores. Information& Management 39(6): 431-444.
[41] Gefen, D. & Devine, P. 2001. Customer loyalty to an online store: The meaning of online service quality. Proceedings of the International Conference of Information Systems 613-618.
[42] Bezjian-Avery, A., Calder, B. & Iacobussi, D. 1998. New media interactive advertising vs. traditional advertising. Journal of Advertising Research 38(4) 23-32.
[43] Christina M. Finneran, Ping Zhang. 2005. Communications of the Association for Information Systems 15 82-101.
[44] Ellis, Gary D., Judith E. Voelkl, Catherine Morris. 1994. Measurement and analysis issues with explanation of variance in daily experience using the flow model. J. Leisure Res. 26(4) 337-356.
[45] Fang Wan, Ning Nan, Malcolm Smith. 2004. Web users’ optimal online experience: a proposed examination of a matching hypothesis. Frontiers of E-business Research. 13-22.
[46] Havlena, William J., Morris B. Holbrook. 1986. The varieties of consumption experience: comparing two typologies of emotion in consumer behavior. J. Consumer Res. 13(December) 394-404.
[47] Hoffman, Donna L., W. D. Kalsbeek, T. P. Novak. 1996. Internet and Web use in the United States: Baselines for commercial development. Special Section on“Internet in the Home” Communication of the ACM 39(December) 36-46.
[48] Jackson, S.A. 1995. Factors influencing the occurrence of flow state in elite athletes. Journal of Applied Sports Psychology. 138-166.
[49] Mannell, Roger C., Jiri Zuzanek, Reed Larson. 1988. Leisure states and ‘flow’ experiences: testing perceived freedom and intrinsic motivation hypotheses. J. Leisure Res. 20(4) 289-304.
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