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    Title: 以TPE探討影響Instagram社群商務使用者滿意度與黏著度之因素
    A Study of Exploring Social Commerce User Satisfaction and Stickiness based on TPE: Taking Instagram as an Example
    Authors: 張妗璘
    Chang, Chin-Lin
    Contributors: 洪為璽
    季延平

    Hung, Wei-Hsi
    Chi, Yan-Ping

    張妗璘
    Chang, Chin-Lin
    Keywords: 社群商務
    TPE
    任務科技適配理論
    使用者滿意度
    黏著度
    Social Commerce
    TPE
    Task-Technology Fit
    User Satisfaction
    Stickiness
    Date: 2021
    Issue Date: 2022-02-10 13:24:45 (UTC+8)
    Abstract: 近年來社群商務發展快速,無論是社群媒體融入商務元素或是電子商務融入社群元素各平台皆希望能夠同時滿足使用者對於社交與購物體驗的需求。疫情緣故,使用者更為依賴線上與他人進行互動和購買商品。若社群商務平台讓使用者在使用上感到滿意並願意長時間瀏覽與重複使用即能產生黏著度。過往研究顯示,使用者的滿意度和黏著度得以用來預測使用者參與度、持續使用意願甚至是未來在該平台上的購物意願。本研究以科技—個人—環境模型(TPE)為基礎,加入科技準備度、任務科技適配度、知覺互動性、社群參與和社群認同所涵蓋之構面,以問卷形式針對Instagram的使用者進行調查,欲了解哪些因素將影響使用者對Instagram是否產生滿意度及黏著度。研究結果顯示,科技準備度中的樂觀性、任務科技適配度、知覺互動性中的知覺控制、社群參與和社群認同對使用者滿意度有正向影響。使用者滿意度對黏著度有正向影響。科技準備度中的不適應性和不安全性對使用者滿意度有負向影響。科技準備度中的創新性、知覺互動性中的知覺反應和知覺個人化則為不顯著。因此,Instagram應著重於讓使用者在使用上獲得正向感受,降低使用者對無論新舊功能感到恐懼並懷疑其效用的狀況產生。在個人任務、能力與科技使用上需讓其感知一致,同時,提升系統的可控制性及增加使用者的社群參與與社群認同程度方可提升滿意度,最終使用者將對Instagram產生黏著度,相對於使用其他社群商務平台更願意延長及重複使用。
    In recent years, social commerce has developed rapidly. Whether it is social media integrating business elements or e-commerce integrating community elements, all platforms hope to meet the needs of users for social and shopping experience at the same time. Because of Covid-19, users are more reliant on online communities to interact with others and purchase goods online. If social commerce can satisfy users and make them willing to spend more time browsing and reusing, it can generate user stickiness. Past research has shown that user satisfaction and stickiness can be used to predict user engagement, continual usage intention and even influence future purchase intentions on the platform. This study is based on the Technological-Personal-Environmental (TPE) model, adding variables covered by technology readiness, task-technology fit, perceived interactivity, community engagement, and social identity. This study surveyed Instagram users to find out what factors influence users` satisfaction and stickiness. The results show that optimism in technology readiness, task-technology fit, perceived control in perceived interactivity, community engagement and social identity have positive effects on user satisfaction. User satisfaction has a positive effect on user stickiness. Discomfort and insecurity in technology readiness have a negative impact on user satisfaction. Innovativeness in technology readiness, perceived responsiveness and perceived personalization in perceived interactivity were insignificant. In terms of personal tasks, abilities, and technology use, users need to be consistent in their perception in order to adopt the technology. At the same time, it is necessary to improve the controllability of the system and increase the user`s community engagement and social identity to improve satisfaction. In the end, users will become attached to Instagram, and are more willing to extend their usage duration on the platform, leading to the users’ preference in reusing Instagram over other social commerce platforms.
    Reference: 中文文獻
    1.財團法人台灣網路資訊中心(2019)。2020台灣網路報告。
    2.陳寬裕(2018)。結構方程模型分析實務: SPSS 與 SmartPLS 的運用。臺北市:五南圖書出版股份有限公司。
    3.蔡齡瑤,2015,電子商務新通路 -初探「社群商務」,財金資訊季刊,第二十八期;22~28 頁。

    英文文獻
    1.Algesheimer, Rene, Utpal M. Dholakia & Andreas Herrmann (2005), The Social Influence of Brand Community:Evidence from European Car Clubs, Journal of Marketing, Vol. 69, 19-34.
    2.Ashforth, B.E. & Meal, F. (1989). Social Identity Theory and the Organization, Academy of The Management Review, (14), 20-39.
    3.Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411.
    4.Abdullah, D., Jayaraman, K., Shariff, D.N., Bahari, K.A., & Nor, N.M. (2016). The Effects of Perceived Interactivity , Perceived Ease of Use and Perceived Usefulness on Online Hotel Booking Intention: A Conceptual Framework.
    5.Adila, T. M., Bintang, W. S., Ikhsan, R. B., & Fahlevi M. (2020). Instagram as Information In Developing Purchase Intentions: The Role Of Social E-Wom And Brand Attitude. International Conference on Information Management and Technology, 2020, 427-431.
    6.Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS Quarterly, 25(3), 351-370.
    7.Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. MIS Quarterly, 32(2), 201-214.
    8.Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
    9.Bergami, M. & Bagozzi, R.P. Self-Categorization, Affective Commitment, and Group Self-Esteem as Distinct Aspects of Social Identity in an Organization. British Journal of Social Psychology, (39:4),2000, 555-577.
    10.Bagnall R. G.(1989). Researching Participation in Adult Education: A Case of Quantified Distortion. International Journal of Lifelong Education, 8(3), 251-260.
    11.Bhattacharya, C. B., & Sen, S. (2003). Consumer-company identification: A framework for understanding consumers’ relationships with companies. Journal of marketing, 67(2), 76-88.
    12.Beddoe-Stephens, Paul, "Yahoo: Gettin`` Sticky with It," Wired News. 1999.
    13.Bhatnagar, A. & Ghose, S., 2004, An analysis of frequency and duration of search on the Internet. Journal of Business, 77, pp. 311 – 330.
    14.Bolton, R. N., & Lemon, K. N. (1999). A dynamic model of customers’ usage of services: Usage as an antecedent and consequence of satisfaction. Journal of Marketing Research, 171-186.
    15.Cha, J. (2009). Shopping on Social Networking Web Sites: Attitudes Toward Real Versus Virtual Items. Journal of Interactive Advertising, 10(1), 77-93.
    16.Chen, J., & Shen, X. L. (2015). Consumers decisions in social commerce context: An empirical investigation, Decision Support Systems, 79, 55-64.
    17.Chen, S. C. (2012). To use or not to use: understanding the factors affecting continuance intention of mobile banking. International Journal of Mobile Communications, 10(5), 490-507.
    18.Chen, C. C., Mitchell, A. J., & Hunsinger, S. (2012). Understanding Continuance of Using VoIP Applications to Improve Intercultural Communication. International Journal of Social and Organizational Dynamics, IT 2(1), 1-16.
    19.Cardozo, R. N. (1965). An experimental study of customer effort, expectation and satisfaction. Journal of Marketing Research, .2(3) 244-249.
    20.Chiang, H. S. & Hsiao, K. L. (2015). YouTube stickiness: the needs, personal, and environmental perspective, Internet Research, 25(1), 85-106.
    21.Chen, D., Lin, Z., & Lai, F. (2010). Crossing the chasm-understanding china`s rural digital divide. Journal of Global Information Technology Management, 13(2), 4-36.
    22.Cheng, Y. M. (2019). How does task-technology fit influence cloud-based e-learning continuance and impact? Education Training, 61(4), 480-499. https://doi.org/10.1108/ET-09-2018-0203
    23.Chen, Y., & Huang, S.Y. (2017). The effect of task-technology fit on purchase intention: The moderating role of perceived risks. Journal of Risk Research, 20, 1418-1438.
    24.Chang, Y. W. & Chen, J.H. (2021). What motivates customers to shop in smart shops? The impacts of smart technology and technology readiness, Journal of Retailing and Consumer Services, 58, 102325, ISSN 0969-6989, https://doi.org/10.1016/j.jretconser.102325.
    25.Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
    26.Drucker, Peter. 1946. Concept of the Corporation. New York: John Day Company.
    27.Djafarova, E., & Bowes, T. (2021).‘Instagram made Me buy it’: Generation Z impulse purchases in fashion industry. Journal of Retailing and Consumer Services, Elsevier, 59(C).
    28.Dabholkar, P. A. (1996). Consumer evaluations of new technology-based self-service options: an investigation of alternative models of service quality. International Journal of Research in Marketing, 13(1), 29-51.
    29.Dabholkar, P. A., & Bagozzi, R. (2002). An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. Journal of the Academy of Marketing Science, 30(3), 184-201.
    30.Dutton, J.E., Dukerich, J.M. & Harquail, C.V. “Organization Images and Member Identification,"Administrative Science Quarterly (39:2), 1994, 239-263.
    31.Ellemers, N., Kortekaas, P., & Ouwerkerk, J. W. (1999). Self-categorisation, commitment to the group and group self esteem as related but distinct aspects of social identity. European Journal of Social Psychology, 29(2-3), 371-389.
    32.Emdad, A. F., Badamas, M., & Mouakket, S. (2009). Factors and impacts of low utilization of internet: the case of Arab Countries. Journal of International Technology and Information Management, 18(3), 299-320.
    33.Elliot, S., Choi, C., & Li, G. (2009). An application of a model of online travel community behavior: Beliefs, attitudes and behaviors in C-Trip, a Chinese Online Travel Community, TTRA Annual Conference Proceedings.
    34.Fortin, D. R., & Dholakia, R. R. (2005). Interactivity and vividness effects on social presence and involvement with a web-based advertisement. Journal of Business Research, 58(3), 387-396.
    35.Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
    36.Ferreira, J., Rocha, A. d., & Silva, J. F. d. (2014). Impacts of technology readiness on emotions and cognition in Brazil. Journal of Business Research, 67(5), 865.
    37.Friedrich, T., Schlauderer, S., & Overhage, S. (2019). The impact of social commerce feature richness on website stickiness through cognitive and affective factors: An experimental study. Electronic Commerce Research, Appl., 36.
    38.Gvili, Y. & Levy, S. (2016), “Antecedents of attitudes toward eWOM communication: differences across channels”, Internet Research, Vol. 26 No. 5, pp. 1030-1051.
    39.Goodhue, D. L. (1995). Understanding user evaluations of information systems. Management Science, 41(12), 1827-1844.
    40.Goodhue, D. L. (1998). Development and measurement validity of a tasktechnology fit instrument for user evaluatios of information systems. Decision Sciences, 29(1), 105-138.
    41.Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213-236.
    42.Goodhue, D. L., Klein, B. D., & March, S. T. (2000). User evaluation of IS as surrogates for objective performance. Information & Management, 38(2), 87-101.
    43.Geng, S., Law, K.M.Y. & Niu, B., (2019). Investigating self-directed learning and technology readiness in blending learning environment. International Journal of Educational Technology in Higher Education, 16, 17. https://doi.org/10.1186/s41239-019-0147-0
    44.Hunafa, K., Hidayantox, A. N., & Sandhyaduhita, P. (2017). Investigating mobile payment acceptance using technological-personal-environmental (TPE) framework: A case of Indonesia. International Conference on Advanced Computer Science and Information Systems (ICACSIS), 159-165, doi: 10.1109/ICACSIS.2017.8355027.
    45.Howard, J. A., & J. N. Sheth (1969). The Theory of Buyer Behavior. New York: John Willey and Sons.
    46.Ha, L. & James, E. L. (1998). Interactivity reexamined: A baseline analysis of early business websites. Journal of Broadcasting and Electronic Media, 42(4), 457-474.
    47.Hair, J., Black, W., & Babin, B. (1998). RE Anderson, RL Tatham, and W. C. Black, Multivariate data analysis.(5th ed.). NJ: Prentice—Hall.
    48.Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.
    49.Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195-204.
    50.Hu, T., Dai, H., & Salam, A. F. (2019). Integrative qualities and dimensions of social commerce: Toward a unified view. Information and Management, 56 (2): 249–270.
    51.Hsu, C. L., & Lin, C. C. (2016). Effect of perceived value and social influences on mobile app stickiness and in-app purchase intention. Technological Forecasting and Social Change, 108, 42–53.
    52.Harcourt, M., Lam, H., & Harcourt, S. (2005). Discriminatory practices in hiring: institutional and rational economic perspectives. International Journal of Human Resource Management, 16(11), 2113-2132.
    53.Harsandaldeep Kaur, Mandakini Paruthi, JamidUl Islam, & Linda D. Hollebeek. (2020). The role of brand community identification and reward on consumer brand engagement and brand loyalty in virtual brand communities, Telematics and Informatics, Volume 46, 101321, ISSN 0736-5853, https://doi.org/10.1016/j.tele.2019.101321.
    54.Jarupathirun, S., & Zahedi, F. M. (2007). Exploring the influence of perceptual factors in the success of web-based spatial DSS. Decision Support Systems, 43(3), 933–951.
    55.Jo, S., & Kim, Y.(2003). The effect of Webcharacteristics on relationship building. Journal of Public Relations Research, 15(3),199-223.
    56.Jiang, Y., Chen, D. & Lai , F. (2010), Technological-Personal-Environmental (TPE) Framework: A Conceptual Model for Technology Acceptance at the Individual Level. Journal o f International Technology and Information Management, 19, 3, 89-98.
    57.Karsen, M., Chandra, Y. U.,& Juwitasary, H. (2019). Technological Factors of Mobile Payment: A Systematic Literature Review. Procedia Computer Science, 157, 489-498.
    58.Koh, J., & Kim, Y. (2004). Knowledge sharing in virtual communities: an e-business perspective. Expert Systems with Applications, 26(2), 155-166.
    59.Kim, H., Suh, K.-S., & Lee, U.-K. (2013). Effects of collaborative online shopping on shopping experience through social and relational perspectives. Information & Management, 50(4), 169-180.
    60.Kaur, H., Paruthi, M., Islam, J., & Hollebeek, L. D. (2019). The Role of Brand Community Identification and Reward on Consumer Brand Engagement and Brand Loyalty in Virtual Brand Communities. Telematics and Informatics, 46.
    61.Kaur, H., Paruthi, M., Islam, J., & Hollebeek, L. D. (2019). Consumers’ relationships with brands and brand communities – The multifaceted roles of identification and satisfaction, Journal of Retailing and Consumer Services, 35, 46-56.
    62.Lin, J. C. C. (2007). Online stickiness: Its antecedents and effect on purchasing intention. Behaviour and Information Technology, 26(6), 507-516.
    63.Lin T. C., & Huang C. C. (2008). Understanding knowledge management system usage antecedents: An integration of social cognitive theory and task technology fit. Information & Management, 45(6), 410-417.
    64.Lin, W, S. (2012). Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. International Journal of Human-Computer Studies, 70(7), 498-507.
    65.Langerak , F., Verhoef P.C., Verlegh P.W., & DeValck, K. (2003). The effect of members’ satisfaction with a virtual community on member participation. ERIM Report Series Research in Management, 2003-004-MKT, Erasmus Research Institute of Management Erasmus University Rotterdam.
    66.Lin, J. C., & Hsieh, P. L. (2006). The role of technology readiness in customers, perception and adoption of self-service technologies. International Journal of Service Industry Management, 17(5), 497-517.
    67.Lien, C. H., Cao, Y., & Zhou, X. (2017). Service quality, satisfaction, stickiness, and usage intentions: An exploratory evaluation in the context of WeChat services. Computers in Human Behavior, Volume 68, 403-410, ISSN 0747-5632, https://doi.org/10.1016/j.chb.2016.11.061.
    68.Loureiro, S. M., & Sarmento, E. M. (2019). Exploring the Determinants of Instagram as a Social Network for Online Consumer-Brand Relationship. Journal of Promotion Management, 25, 354 - 366.
    69.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.
    70.Mittal, B. & Walfried M. L. (1996). The Role of Personalization in Service Encounters. Journal of Retailing, 72 (Spring), 95-109.
    71.McMillan, S. J., & Hwang, J.-S. (2002). Measures of perceived interactivity: An exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity. Journal of Advertising, 31(3), 29-42.
    72.Marcolin B.L., Compeau D.R., Munro M.C., & Huff, S. L.(2000). Assessing user competence: conceptualization and measurement. Information Systems Research 11 (1), 37–60.
    73.Mick, David Glenn & Susan Fournier (1998), “Paradoxes of Technology: Consumer Cognizance, Emotions, and Coping Strategies,” Journal of Consumer Research, 25 (September), 123-47.
    74.Newhagen, J. E., Cordes, J. W., & Levy, M. R. (1995). Nightly at NBC.Com: Audience Scope and the Perception of Interactivity in Viewer Mail on the Internet, Journal of Communication, 21(2), 164-175.
    75.Nandi, S., Nandi, M.L. & Khandker, V. (2021). Impact of perceived interactivity and perceived value on mobile app stickiness: an emerging economy perspective, Journal of Consumer Marketing, 38 (6), 721-737. https://doi.org/10.1108/JCM-02-2020-3661
    76.Oliver Richard, L. (1997). Satisfaction: A behavioral perspective on the consumer. New York, NY: Irwin-McGraw-Hill.
    77.Patchen, M. Participation, Achievement, and Involvement on the Job, Englewood Cliffs, Prentice Hall, New Jersey, 1970.
    78.Polites, G. L., Williams, C. K., Karahanna, E., & Seligman, L. (2012). A theoretical framework for consumer E-satisfaction and site stickiness: An evaluation in the context of online hotel reservations. Journal of Organizational Computing and Electronic Commerce, 22(1), 1–37.
    79.Pham, L., Williamson, S., Lane, P., Limbu, Y., Nguyen, P. T. H. & Coomer, T. (2020). Technology readiness and purchase intention: role of perceived value and online satisfaction in the context of luxury hotels. International Journal of Management and Decision Making, 19(1): 91-117.
    80.Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4): 307-20.
    81.Parasuraman, A., & Colby, C. L. (2001). Techno-ready marketing: how and why your customers adopt technology. New York, NY: The Free Press.
    82.Parasuraman, A., & Colby, C. L. (2014). An updated and streamlined technology readiness index: TRI 2.0. Journal of Service Research, 18(1), 59-74.
    83.Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). E-S-QUAL: a multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213-233.
    84.Park, H. & Kim, S. (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.
    85.Park, M., & Yoo, J. (2020). Effects of perceived interactivity of augmented reality on consumer responses: A mental imagery perspective. Journal of Retailing and Consumer Services, 52, [101912]. https://doi.org/10.1016/j.jretconser.2019.101912
    86.Q. Al-Maatouk, M. S. Othman, A. Aldraiweesh, U. Alturki, W. M. Al-Rahmi & A. A. Aljeraiwi. (2020) Task-Technology Fit and Technology Acceptance Model Application to Structure and Evaluate the Adoption of Social Media in Academia," in IEEE Access, vol. 8, 78427-78440, doi: 10.1109/ACCESS.2020.2990420.
    87.Rosenbaum, M. S., Ostrom, A. L., & Kuntze, R. (2005). Loyalty programs and a sense of community. Journal of Services Marketing, 19(4), 222-233.
    88.Statista (2021). Number of social network users of select social media platforms worldwide in 2019 and 2023. Retrieved July 21, 2021, from https://www.statista.com/statistics/1109866/number-social-media-users-worldwide-select-platforms/
    89.Sarstedt, M., Ringle, C. M., Henseler, J., & Hair, J. F. (2014). On the emancipation of PLS-SEM: A commentary on Rigdon (2012). Long Range Planning, 47(3), 154-160.
    90.Sakun B. I . (2015). Managing self-service technology service quality to enhance e-satisfaction. International Journal of Quality and Service Sciences, 7, 374-391.
    91.Suh, J.-C. & Yi, Y. (2006). When brand attitudes affect the customer satisfaction-loyalty relation: The moderating role of product involvement, Journal of Consumer Psychology, Vol. 16 No. 2, 145-155.
    92.Shi, W., Shambare, N., & Wang, J. (2008). The adoption of internet banking: an institutionatl theory perspective. Journal of Financial Services Marketing, 12(4), 272-286.
    93.Sheng, M. & Hartono, R. (2015). An exploratory study of knowledge creation and sharing in online community: a social capital perspective. Total Quality Management & Business Excellence, 26, 93-107.
    94.Scott, W. R. (2001). Institutions and Organizations. Thousand Oaks, CA; Sage.
    95.Sihombing, E. S., Budi, I., & Munajat, Q. (2020). Factors affecting the urge of impulsive buying on social commerce Instagram. International Journal of Internet Marketing and Advertising, 14(3), 236-257. https://doi.org/10.1504/IJIMA.2020.108716
    96.Shao, Z., Zhang, L., Chen, K., & Zhang, C. (2020). Examining user satisfaction and stickiness in social networking sites from a technology affordance lens: uncovering the moderating effect of user experience. Industrial Management & Data Systems; Wembley, 120, Iss. 7, 1331-1360. DOI:10.1108/IMDS-11-2019-0614
    97.Song, J. H., & Zinkhan, G. M. (2008). Determinants of perceived web site interactivity. Journal of Marketing, 72(2), 99-113.
    98.Saprikis, V., & Avlogiaris, G. (2021). Modeling users’ acceptance of mobile social commerce: the case of ‘Instagram checkout’. Electronic Commerce Research. https://doi.org/10.1007/s10660-021-09499-4.
    99.Tsiotsou, R. H. (2020). Social Media and Customer Engagement. In The Routledge Handbook of Service Research Insights and Ideas by Eileen Bridges and Kentra Fowler (eds), Routledge, Bisbaine.
    100.Tajfel, H., Billig, M.G., Bundy, R.P. & Flament, C. (1971). Social Categorization and Intergroup Behaviour. European Journal of Social Psychology (1:2), 1971, 149-178.
    101.Tajfel, H. (1981). Human Groups and Social Categories: Studies in the Social Psychology, Cambridge University Press, New York.
    102.Tornatzky, L.G. & Fleischer, M. (1990). The Processes of Technological Innovation, Lexington, MA: Lexington Books.
    103.Teo, T. (2002). Attitude toward online shopping and the Internet. Behaviour & Information Technology, 21, 259 – 271.
    104.Tsai, H. T., & Huang, H. C. (2007). Determinants of e-repurchase intentions: An integrative model of quadruple retention drivers. Information & Management, 44(3), 231-239.
    105.Williams, L. J., & Hazer, J. T. (1986). Antecedents and consequences of satisfaction and commitment in turnover models: A reanalysis using latent variable structural equation methods. Journal of Applied Psychology, 71(2), 219.
    106.Wang, Y., & Yu, C. (2015). Social interaction-based consumer decision-making model in social commerce: the role of word of mouth and observational learning. International Journal of Information Management, 37(3), 179-189.
    107.Wang, C., & Zhang, P. (2012). The Evolution of Social Commerce: The People, Management, Technology, and Information Dimensions. Communications of the Association for Information Systems, 31, 105-127.
    108.Williams, L. J., & Hazer, J. T. (1986). Antecedents and consequences of satisfaction and commitment in turnover models: A reanalysis using latent variable structural equation methods. Journal of Applied Psychology, 71(2), 219.
    109.Wang, Y., So, K.K.F., & Sparks, B.A. (2017). Technology Readiness and Customer Satisfaction with Travel Technologies: A Cross-Country Investigation. Journal of Travel Research. 56(5):563-577.
    110.Wang, Y., Lo, H. P., & Yang, Y. (2004). An integrated framework for service quality, customer value, satisfaction: Evidence from China’s telecommunication industry. Information Systems Frontiers, 6(4), 325-340.
    111.Wang, X., Wong, Y. D., Chen, T., & Yuen, K. F. (2021). Adoption of shopper-facing technologies under social distancing: A conceptualisation and an interplay between task-technology fit and technology trust. Computers in Human Behavior, 124, 106900. doi:10.1016/j.chb.2021.106900
    112.Wu, G. (2006). Conceptualizing and measuring the perceived interactivity of Web sites. Journal of Current Issues and Research in Advertising, 28(1), 87–104.
    113.Wu, J., Liu, L., & Cui, T. (2021). What drives consumer website stickiness intention? The role of website service quality and website involvement. International Journal of Services Technology and Management, 27(3), 189-208. DOI: 10.1504/IJSTM.2021.115163
    114.Wang, K., Chih, W., & Hsu, L. (2020). Building Brand Community Relationships on Facebook Fan Pages: The Role of Perceived Interactivity. International Journal of Electronic Commerce, 24, 211-231.
    115.Yoo, W. S., Lee, Y., & Park, J. (2010). The role of interactivity in e-tailing: Creating value and increasing satisfaction. Journal of Retailing and Consumer Services, 17(2), 89-96.
    116.Zott, C., Amit, R., & Donlevy, J. (2000). Strategies for value creation in ecommerce: Best practice in Europe. European Management Journal, 18(5), 463−475.
    Description: 碩士
    國立政治大學
    企業管理研究所(MBA學位學程)
    109363057
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0109363057
    Data Type: thesis
    DOI: 10.6814/NCCU202200127
    Appears in Collections:[企業管理研究所(MBA學位學程)] 學位論文

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