专注论文查重修改6年+经验

探讨Facebook打卡讯息的说服效果

【中文摘要】:随着Facebook的普及,人们开始透过打卡分

szwox.com_186
享自己的所到之处,店家更以换取优惠的方式吸引人们打卡,期望能透过口碑效应达到行销目的。本研究目的在于了解此类型的打卡行为是否能说服消费者,产生造访店家的意图;探讨在不同关係强度及不同打卡内容下,对于消费者造访店家意图的说服效果;此外本研究更结合思辨可能模式及消费者人际影响敏感度的角度来做深入研究。
本研究结果包含:(1)「意义」或「折扣」的打卡内容会影响到论点品质。(2)关係好的朋友感受到的来源可信度会高于关係不好的朋友。(3)在处理资讯时,有较高资讯性人际影响敏感度倾向的人,会提高论点品质的效用;有较高规範性人际影响敏感度倾向的人,则会提高来源可信度的效用。研究贡献在于了解打卡行为所造成的说服效果,以及探讨影响消费者造

毕业论文查重去哪里?文懂论文查重一站式服务,全球8大论文检测系统帮你杜绝防抄袭,提高论文原创水品。

访店家的因素,并给予店家制定行销策略的建议。
【英文摘要】:With the increasing of using Facebook, people began to share where they have been through check-in fu

文懂论文网,论文重复率修改靠谱,专业改抄袭,通过论文查重系统,提升论文品质的最佳选择

nction. In order to create word-of-mouth and achieve the effect of marketing, stores would offer discounts as long as people check in. The purpose of this study is to understand whether people’s check-in behavior could persuade their Facebook friends into visiting the store and observe the persuasive effect on their visiting intention under different kinds of content type and tie strength. Besides, this study combined elaboration likelihood model with the aptitude of consumers’ susceptibility to interpersonal influence to understand and explain the effect of behavior.
The results of this study include: (1) Meaning-based or discount-based content would influence the argument quality. (2) Friends with strong tie are perceived higher source credibility than friends with weak tie. (3) During the stage of information processing, people who have higher informational susceptibility to interpersonal influence would enhance the effect of argument quality, but people who have higher normative susceptibility to interpersonal influence would enhance the effect of source credibility. The contribution of this study is to understand the persuasive effect of check-in behavior, and the factors to influence stores’ visiting intention. This study also provides the advice of marketing strategy to dealers or service providers.
【参考文献】:

  • 104-Corporation. (2012). Are you check in today? A survey of Facebook check-in. Retrieved 11/4, 2013, from http://www.104survey.com/faces/newportal/viewPointCtx.xhtml?researchId=505
  • Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of the academy of marketing science, 27(2), 184-206.
  • Bearden, W. O., Netemeyer, R. G., & Teel, J. E. (1989). Measurement of consumer susceptibility to interpersonal influence. Journal of Consumer research, 15(4), 473-481.
  • Berthon, P. R., Pitt, L. F., Plangger, K., & Shapiro, D. (2012). Marketing meets Web 2.0, social media, and creative consumers: Implications for international marketing strategy. Business Horizons, 55(3), 261-271.
  • Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: an elaboration likelihood model. MIS quarterly, 30(4), 805-825.
  • Borden, N. H. (1964). The concept of the marketing mix. Journal of Advertising Research, 4(2), 2-7.
  • Burnkrant, R. E., & Cousineau, A. (1975). Informational and normative social influence in buyer behavior. Journal of Consumer research, 2(3), 206-215.
  • Carte, T. A., & Russell, C. J. (2003). In pursuit of moderation: Nine common errors and their solutions. MIS quarterly, 27(3), 479-501.
  • Cheung, C. M., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), 461-470.
  • Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189-217.
  • Chu, S.-C., & Kamal, S. (2008). The effect of perceived blogger credibility and argument quality on message elaboration and brand attitudes: an exploratory study. Journal of Interactive Advertising, 8(2), 26-37.
  • Chu, S.-C., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising, 30(1), 47-75.
  • Cramer, H., Rost, M., & Holmquist, L. E. (2011). Performing a check-in: emerging practices, norms and”conflicts” in location-sharing using foursquare. Paper presented at the Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services.
  • Daft, R. L., & Lengel, R. H. (1983). Information richness. A new approach to managerial behavior and organization design (Vol. 6, pp. 191-233): DTIC Document.
  • Deutsch, M., & Gerard, H. B. (1955). A study of normative and informational social influences upon individual judgment. The journal of abnormal and social psychology, 51(3), 629.
  • Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computer‐Mediated Communication, 12(4), 1143-1168.
  • Engel, J. F., Blackwell, R. D., & Kegerreis, R. J. (1969). How information is used to adopt an innovation. Journal of Advertising Research, 9(4), 3-8.
  • Facebook. (2012). Facebook reached 1 billion monthly active users on September 14 at 12.45 PM Pacific time. Retrieved 10/31, 2013, from http://newsroom.fb.com/imagelibrary/downloadmedia.ashx?MediaDetailsID=4227&SizeId=-1
  • Fagerstrøm, A., & Ghinea, G. (2009). The Persuasive Effects from Web 2.0 Marketing: A Case Study Investigating the Persuasive Effect from an Online Design Competition Human Interface and the Management of Information. Information and Interaction (pp. 10-16): Springer Berlin Heidelberg.
  • Feick, L. F., & Price, L. L. (1987). The market maven: A diffuser of marketplace information. The Journal of Marketing, 51(1), 83-97.
  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research.
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research (JMR), 18(1), 39-50.
  • Giffin, K. (1967). The contribution of studies of source credibility to a theory of interpersonal trust in the communication process. Psychological bulletin, 68(2), 104.
  • Gilly, M. C., Graham, J. L., Wolfinbarger, M. F., & Yale, L. J. (1998). A dyadic study of interpersonal information search. Journal of the academy of marketing science, 26(2), 83-100.
  • Granovetter, M. S. (1973). The strength of weak ties. American journal of sociology, 78(6), 1360-1380.
  • Guerrero, L., Colomer, Y., Guàrdia, M. D., Xicola, J., & Clotet, R. (2000). Consumer attitude towards store brands. Food Quality and Preference, 11(5), 387-395.
  • Gupta, P., & Harris, J. (2010). How e-WOM recommendations influence product consideration and quality of choice: a motivation to process information perspective. Journal of Business Research, 63(9), 1041-1049.
  • Harris, J. L., Brownell, K. D., & Bargh, J. A. (2009). The food marketing defense model: integrating psychological research to protect youth and inform public policy. Social Issues and Policy Review, 3(1), 211-271.
  • Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the internet? Journal of interactive marketing, 18(1), 38-52.
  • Hovland, C. I., Janis, I. L., & Kelley, H. H. (1953). Communication and persuasion; psychological studies of opinion change.
  • Huang, L.-T., Chiu, C.-A., Sung, K., & Farn, C.-K. (2011). A comparative study on the flow experience in web-based and text-based interaction environments. Cyberpsychology, Behavior, and Social Networking, 14(1-2), 3-11.
  • Jin, L., Long, X., Joshi, J. B., & Anwar, M. (2012). Analysis of access control mechanisms for users” check-ins in Location-Based Social Network Systems. Paper presented at the Information Reuse and Integration (IRI), 2012 IEEE 13th International Conference on.
  • Katz, E., & Lazarsfeld, P. F. (1970). Personal Influence, The part played by people in the flow of mass communications: Transaction Publishers.
  • Keil, M., Rai, A., & Liu, S. (2013). How user risk and requirements risk moderate the effects of formal and informal control on the process performance of IT projects. European Journal of Information Systems, 22(6), 650-672.
  • Kim, Y., & Srivastava, J. (2007). Impact of social influence in e-commerce decision making. Paper presented at the Proceedings of the ninth international conference on Electronic commerce.
  • Kotler, P. (1994). Marketing Management: Analysis Planning Implementation and Control: Prentice-Hall of India.
  • Lee, M. K., Cheung, C., Sia, C. L., & Lim, K. H. (2006). How positive informational social influence affects consumers’ decision of Internet shopping? Paper presented at the System Sciences, 2006. HICSS”06. Proceedings of the 39th Annual Hawaii International Conference on.
  • 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.
  • Lin, N. (1999). Building a network theory of social capital. Connections, 22(1), 28-51.
  • MacKenzie, S. B., & Podsakoff, P. M. (2012). Common method bias in marketing: causes, mechanisms, and procedural remedies. Journal of Retailing, 88(4), 542-555.
  • 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.
  • Mangold, W. G., & Faulds, D. J. (2009). Social media: The new hybrid element of the promotion mix. Business Horizons, 52(4), 357-365.
  • Martin, W. C., & Lueg, J. E. (2013). Modeling word-of-mouth usage. Journal of Business Research, 66(7), 801-808.
  • McCarthy, E. J. (1960). Basic marketing: a managerial approach. Homewood, IL: Richard D. Irwin. Inc., 1979McCarthyBasic Marketing: A Managerial Approach1979.
  • McGuire, W. J. (1968). Personality and susceptibility to social influence. Handbook of personality theory and research, 2, 1130-1187.
  • Mehdizadeh, S. (2010). Self-presentation 2.0: Narcissism and self-esteem on Facebook. Cyberpsychology, Behavior, and Social Networking, 13(4), 357-364.
  • Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230.
  • Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers” perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39-52.
  • Panovich, K., Miller, R., & Karger, D. (2012). Tie strength in question & answer on social network sites. Paper presented at the Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work.
  • Park, C. W., & Lessig, V. P. (1977). Students and housewives: Differences in susceptibility to reference group influence. Journal of Consumer research, 4(2), 102-110.
  • Park, D.-H., & Kim, S. (2009). The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research and Applications, 7(4), 399-410.
  • Petty, R., Barden, J., & Wheeler, S. (2009). The elaboration likelihood model of persuasion: developing health promotions for sustained behavioral change. Emerging theories in health promotion practice and research, 2, 185-214.
  • Petty, R. E. (2013). Two routes to persuasion: State of the art. International perspectives on psychological science, 2, 229-247.
  • Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion: Springer.
  • 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.
  • Petty, R. E., & Wegener, D. T. (1999). The elaboration likelihood model: Current status and controversies. 37-72.
  • Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of applied Psychology, 88(5), 879.
  • Raghubir, P., & Corfman, K. (1999). When do price promotions affect pretrial brand evaluations? Journal of Marketing Research, 36(2), 211-222.
  • Roger, E. M. (1995). Diffusion of innovations. New York: Free Press, 41, 1002-1037.
  • Smith, K. W., & Sasaki, M. S. (1979). Decreasing Multicollinearity A Method for Models with Multiplicative Functions. Sociological Methods & Research, 8(1), 35-56.
  • Steinfield, C., Ellison, N. B., & Lampe, C. (2008). Social capital, self-esteem, and use of online social network sites: A longitudinal analysis. Journal of Applied Developmental Psychology, 29(6), 434-445.
  • Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: an integrated approach to knowledge adoption. Information Systems Research, 14(1), 47-65.
  • Tam, K. Y., & Ho, S. Y. (2005). Web personalization as a persuasion strategy: An elaboration likelihood model perspective. Information Systems Research, 16(3), 271-291.
  • Toch, E., Cranshaw, J., Drielsma, P. H., Tsai, J. Y., Kelley, P. G., Springfield, J., . . . Sadeh, N. (2010). Empirical models of privacy in location sharing. Paper presented at the Proceedings of the 12th ACM international conference on Ubiquitous computing.
  • Turban, E., & Gehrke, D. (2000). Determinants of e-commerce website. Human Systems Management, 19(2), 111-120.
  • Van Noort, G., Antheunis, M. L., & Van Reijmersdal, E. A. (2012). Social connections and the persuasiveness of viral campaigns in social network sites: Persuasive intent as the underlying mechanism. Journal of Marketing Communications, 18(1), 39-53.
  • 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.
  • Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 36(1), 157-178.
  • Wang, J.-C., & Chang, C.-H. (2013). How online social ties and product-related risks influence purchase intentions: A Facebook experiment. Electronic Commerce Research and Applications, 12(5), 337-346.
  • Wang, S. S., & Stefanone, M. A. (2013). Showing Off? Human Mobility and the Interplay of Traits, Self-Disclosure, and Facebook Check-Ins. Social Science Computer Review, 00(0), 1-21.
  • Yang, B., Kim, Y., & Yoo, C. (2013). The integrated mobile advertising model: The effects of technology-and emotion-based evaluations. Journal of Business Research, 66(9), 1345-1352.
  • Zhao, L., Lu, Y., & Gupta, S. (2012). Disclosure Intention of Location-Related Information in Location-Based Social Network Services. International Journal of Electronic Commerce, 16(4), 53-90.
  • Zhao, S., Grasmuck, S., & Martin, J. (2008). Identity construction on Facebook: Digital empowerment in anchored relationships. Computers in Human Behavior, 24(5), 1816-1836.
  • Zhong, B., Hardin, M., & Sun, T. (2011). Less effortful thinking leads to more social networking? The associations between the use of social network sites and personality traits. Computers in Human Behavior, 27(3), 1265-1271.
  • 来源:中山大学;作者:卢赞名
    文懂论文-重复率修改第一品牌,http://www.szwox.com解决论文查重论文降重复,重复率高等各种论文难题的专家

    最新文章

    • 什么是学术不端行为
      什么是学术不端行为
      什么是学术不端行为 1992 年,由美国国家科学院、国家工程院和国家医学研究院组成的 22 位...
    • 论文降重复服务 1. 本网站及服务 szwox.com提供哪些服务? szwox.com是一个...

    联络我们

    QQ: 767326772
    文懂论文
    网站:http://www.szwox.com/
    E-mail: turuinit@foxmail.com

    我们的服务

    我们提供毕业论文、期刊论文、硕士论文、博士论文、会议论文格式排版,论文查重,重复率修改等服务。强大论文查重系统,一手老师资源,首创安全保密查重修改流程。充分保障客户论文查重安全以及修改后的品质,赢得了老师和同学们的信任和口碑。