參考文獻 |
中文文獻
《Opview社群口碑資料庫》. (2021). 疫情下火紅的互動模式:直播平台網路聲量分析. https://www.opview.com.tw/wp-content/file/OpView-Social-Watch-Vol.133.pdf
中華民國內政部戶政司全球資訊網. (2022). 02. 縣市人口數按性別及年齡(8909). https://www.ris.gov.tw/app/portal/346
中華民國交通部觀光局. https://www.taiwan.net.tw/m1.aspx?sNo=0000501
中華民國統計資訊網. (2020). 家庭收支調查-調查報告. https://www.stat.gov.tw/ct.asp?xItem=27900&ctNode=511&mp=4
未來流通. (2021). 【商業數據圖解】情報應援系列:2021/05疫情下台灣流通企業營收如何變化?. https://www.mirai.com.tw/taiwan-distribution-industry-under-the-pandemic/
行政院主計總處. (2020). 薪情體驗. https://earnings.dgbas.gov.tw/experience_sub_01.aspx
行政院主計總處. (2021). 行業統計分類-第11次修正(110年1月). https://mobile.stat.gov.tw/StandardIndustrialClassification.aspx
行政院性別平等會. (2021). 多維度查詢 - 婚姻狀況─按區域別、年齡別分. https://www.gender.ey.gov.tw/gecdb/Stat_Statistics_Query.aspx?sn=40kTsV0YPrkZxONPzODo6g%40%40&statsn=Kw0t!zwIsOxWgmaa6XhhqQ%40%40
吳統雄. (1984). 態 度 與 行 為 研 究 的 信 度 與 效 度: 理 論, 反 應, 反 省. 民 意 學 術 專 刊, 夏 季 號.
邱皓政. (2008). 結構方程模式的檢定力分析與樣本數決定. αβγ 量化研究學刊, 2(1), 139-173.
國家發展委員會. (2022). 都市及區域發展統計彙編. https://www.ndc.gov.tw/nc_77_4402
陳寬裕, & 王正華. (2021). 論文統計分析實務: SPSS 與 AMOS 的運用. 五南圖書出版股份有限公司.
黃芳銘. (2015). 結構方程模式-理論與應用. 台灣五南圖書出版股份有限公司.
榮泰生. (2008). Amos 與研究方法, 台北市: 五南.
數位時代. (2022). 【圖解】直播電商轉換率,比傳統電商高10倍?台灣如何打出獨步全球「+1」模式?. https://www.bnext.com.tw/article/68005/live-commerce
Mic台灣情報研究所. (2021). 社群與通訊消費者調查系列三】超過七成網友曾觀看過商品直播 FB與YouTube為最大宗 金融理財需求崛起 直播促成下單成效逐漸浮現. https://mic.iii.org.tw/news.aspx?id=613
Newzoo. (2021). Newzoo各世代玩家洞察報告. https://resources.newzoo.com/hubfs/Reports_CN/%5BCN%5DNewzoo_Gamer_Generations_Report.pdf?utm_medium=email&_hsmi=187224514&_hsenc=p2ANqtz-8dU_V_bdlotcymAWwzCpc1wMXqy2pQWeCnnnNVWL69io-VncMXauoNYZm5-dv9qKl-A3MCwhwP4_mS77O2Ki3S7X5ijA&utm_content=187224514&utm_source=hs_automation
Vogue. (2020). Y世代、Z世代之後,無法離開科技的C世代崛起了!. https://www.vogue.com.tw/fashion/article/c-generation
英文文獻
Akram, U., Hui, P., Khan, M., Saduzai, S., Akram, Z., & Bhati, M. (2017). The plight of humanity: Online impulse shopping in China. Human Systems Management, 36, 73-90. https://doi.org/10.3233/HSM-171768
Akram, U., Hui, P., Khan, M. K., Tanveer, Y., Mehmood, K., & Ahmad, W. (2018). How website quality affects online impulse buying: Moderating effects of sales promotion and credit card use. Asia Pacific Journal of Marketing and Logistics.
Al-Emadi, F. A., & Yahia, I. B. (2020). Ordinary celebrities related criteria to harvest fame and influence on social media. Journal of Research in Interactive Marketing.
Alba, J. W., & Williams, E. F. (2013). Pleasure principles: A review of research on hedonic consumption. Journal of consumer psychology, 23(1), 2-18.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
Anh, N. P. (2021). FACTORS AFFECTING LIVE STREAMING SHOPPING INTENTION IN VIETNAM: THE CASE OF FASHION PRODUCTS.
Animesh, A., Pinsonneault, A., Yang, S.-B., & Oh, W. (2011). An odyssey into virtual worlds: exploring the impacts of technological and spatial environments on intention to purchase virtual products. Mis Quarterly, 789-810.
Applebaum, W. (1951). Studying customer behavior in retail stores. Journal of marketing, 16(2), 172-178.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
Baker, M. J., & Churchill Jr, G. A. (1977). The impact of physically attractive models on advertising evaluations. Journal of Marketing research, 14(4), 538-555.
Bansal, H. S., & Voyer, P. A. (2000). Word-of-mouth processes within a services purchase decision context. Journal of service research, 3(2), 166-177.
Beatty, S. E., & Elizabeth Ferrell, M. (1998). Impulse buying: Modeling its precursors. Journal of retailing, 74(2), 169-191. https://doi.org/https://doi.org/10.1016/S0022-4359(99)80092-X
Bente, G., Rüggenberg, S., Krämer, N. C., & Eschenburg, F. (2008). Avatar-mediated networking: Increasing social presence and interpersonal trust in net-based collaborations. Human communication research, 34(2), 287-318.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological bulletin, 107(2), 238.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3), 588.
Biocca, F., & Harms, C. (2002). Defining and measuring social presence: Contribution to the networked minds theory and measure. Proceedings of PRESENCE, 2002, 1-36.
Biocca, F., Harms, C., & Burgoon, J. K. (2003). Toward a more robust theory and measure of social presence: Review and suggested criteria. Presence: Teleoperators & virtual environments, 12(5), 456-480.
Biocca, F., Harms, C., & Gregg, J. (2001). The networked minds measure of social presence: Pilot test of the factor structure and concurrent validity. 4th annual international workshop on presence, Philadelphia, PA,
Blog, B. (2022). Live Streaming Trends for 2022. https://www.bluejeans.com/blog/live-streaming-trends-2022
Bollen, K. A. (1989). Structural equations with latent variables (Vol. 210). John Wiley & Sons.
Bollen, K. A., & Long, J. S. (1993). Testing structural equation models (Vol. 154). Sage.
Boomsma, A. (1982). The robustness of LISREL against small sample sizes in factor analysis models. Systems under indirect observation: Causality, structure, prediction, 149-173.
Brown, W. J. (2015). Examining four processes of audience involvement with media personae: Transportation, parasocial interaction, identification, and worship. Communication Theory, 25(3), 259-283.
Brown, W. J., & Basil, M. D. (2010). Parasocial interaction and identification: Social change processes for effective health interventions. Health Communication, 25(6-7), 601-602.
Browne, M. W. (1984). Asymptotically distribution‐free methods for the analysis of covariance structures. British journal of mathematical and statistical psychology, 37(1), 62-83.
Busalim, A. H., & Ghabban, F. (2021). Customer engagement behaviour on social commerce platforms: An empirical study. Technology in Society, 64, 101437.
Camilleri, M. A., & Falzon, L. (2021). Understanding motivations to use online streaming services: integrating the technology acceptance model (TAM) and the uses and gratifications theory (UGT). Spanish Journal of Marketing - ESIC, 25(2), 217-238. https://doi.org/10.1108/SJME-04-2020-0074
Cha, J. (2013). Predictors of television and online video platform use: A coexistence model of old and new video platforms. Telemat. Inf., 30(4), 296–310. https://doi.org/10.1016/j.tele.2013.01.001
Chahal, H., & Rani, A. (2017). How trust moderates social media engagement and brand equity. Journal of Research in Interactive Marketing.
Chan, T. K., Cheung, C. M., & Lee, Z. W. (2017). The state of online impulse-buying research: A literature analysis. Information & Management, 54(2), 204-217.
Chang, H. H., & Chen, S. W. (2008). The impact of online store environment cues on purchase intention: Trust and perceived risk as a mediator. Online Information Review.
Chang, H. H., & Wang, I. C. (2008). An investigation of user communication behavior in computer mediated environments. Computers in Human Behavior, 24(5), 2336-2356.
Chen, A., Lu, Y., & Wang, B. (2017). Customers’ purchase decision-making process in social commerce: A social learning perspective. International journal of information management, 37(6), 627-638.
Chen, C.-C., & Chang, Y.-C. (2018). What drives purchase intention on Airbnb? Perspectives of consumer reviews, information quality, and media richness. Telematics Informatics, 35, 1512-1523.
Chen, J., & Liao, J. (2022). Antecedents of Viewers’ Live Streaming Watching: A Perspective of Social Presence Theory [Original Research]. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.839629
Chen, J., Shen, X.-L., & Chen, Z.-J. (2014). Understanding social commerce intention: A relational view. 2014 47th Hawaii International Conference on System Sciences,
Chen, T., Peng, L., Yang, J., Cong, G., & Li, G. (2021). Evolutionary game of multi-subjects in live streaming and governance strategies based on social preference theory during the COVID-19 pandemic. Mathematics, 9(21), 2743.
Chen, W.-K., Chen, C.-W., & Silalahi, A. D. K. (2022). Understanding Consumers′ Purchase Intention and Gift-Giving in Live Streaming Commerce: Findings from SEM and fsQCA. Emerging Science Journal, 6(3), 460-481.
Chin, W. W. (1998). Commentary: Issues and opinion on structural equation modeling. In (pp. vii-xvi): JSTOR.
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.
Choe, Y. C., Hwang, D.-R., Kim, M., & Moon, J. (2007). Product heterogeneity: Moderating effect on online consumer behavior. 2007 40th Annual Hawaii International Conference on System Sciences (HICSS′07),
Chung, N., Song, H. G., & Lee, H. (2017). Consumers’ impulsive buying behavior of restaurant products in social commerce. International Journal of Contemporary Hospitality Management.
Cohen, E. L., & Tyler, W. J. (2016). Examining perceived distance and personal authenticity as mediators of the effects of ghost-tweeting on parasocial interaction. Cyberpsychology, Behavior, and Social Networking, 19(5), 342-346.
Cohen, J., & Perse, E. (2003). Different strokes for different folks: An empirical search for different modes of viewer-character relationships. annual meeting of the international communication association, san Diego, CA,
Coupland, D. (2007). Generation X: tales for an accelerated culture. Teacher: The National Education Magazine(Oct 2007), 59.
Csikszentmihalyi, M. (2000). Beyond boredom and anxiety. Jossey-Bass.
Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological methods, 1(1), 16.
Cyr, D. (2008). Modeling web site design across cultures: relationships to trust, satisfaction, and e-loyalty. Journal of management information systems, 24(4), 47-72.
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results Massachusetts Institute of Technology].
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Mis Quarterly, 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
Dawson, S., Bloch, P. H., & Ridgway, N. M. (2002). Shopping motives, emotional states, and retail outcomes. The Environments of Retailing. London: Routledge, 65-81.
Dibble, J. L., Hartmann, T., & Rosaen, S. F. (2016). Parasocial interaction and parasocial relationship: Conceptual clarification and a critical assessment of measures. Human communication research, 42(1), 21-44.
Doll, W. J., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. Mis Quarterly, 453-461.
Dong, T.-P., Cheng, N.-C., & Wu, Y. J. (2014). A study of the social networking website service in digital content industries: The Facebook case in Taiwan. Comput. Hum. Behav., 30, 708-714.
Donovan, R. J., Rossiter, J. R., Marcoolyn, G., & Nesdale, A. (1994). Store atmosphere and purchasing behavior. Journal of retailing, 70(3), 283-294.
Emarketer. Livestream surges in popularity after pandemic—here are the top facts you need to know. https://www.insiderintelligence.com/insights/livestreaming-trends-stats/
Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2003). Empirical testing of a model of online store atmospherics and shopper responses. Psychology & marketing, 20(2), 139-150.
Fang, S., Zhang, C., & Li, Y. (2020). Physical attractiveness of service employees and customer engagement in tourism industry. Annals of Tourism Research, 80, 102756. https://doi.org/https://doi.org/10.1016/j.annals.2019.102756
Fang, Y.-H. (2014). Beyond the credibility of electronic word of mouth: Exploring eWOM adoption on social networking sites from affective and curiosity perspectives. International Journal of Electronic Commerce, 18(3), 67-102.
Fireworker, R. B., & Friedman, H. H. (1977). The effects of endorsements on product evaluation. Decision sciences, 8(3), 576-583.
Floh, A., & Madlberger, M. (2013). The role of atmospheric cues in online impulse-buying behavior. Electronic Commerce Research and Applications, 12(6), 425-439.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. In: Sage Publications Sage CA: Los Angeles, CA.
Frederick, E. L., Lim, C. H., Clavio, G., & Walsh, P. (2012). Why we follow: An examination of parasocial interaction and fan motivations for following athlete archetypes on Twitter. International journal of sport communication, 5(4), 481-502.
Fu, S., Chen, X., & Zheng, H. (2021). Exploring an adverse impact of smartphone overuse on academic performance via health issues: a stimulus-organism-response perspective. Behaviour & Information Technology, 40(7), 663-675.
Galbreth, M. R., Ghosh, B., & Shor, M. (2012). Social sharing of information goods: Implications for pricing and profits. Marketing Science, 31(4), 603-620.
Gao, J., Zhang, C., Wang, K., & Ba, S. (2012). Understanding online purchase decision making: The effects of unconscious thought, information quality, and information quantity. Decision Support Systems, 53(4), 772-781.
Gefen, D. (2000). E-commerce: the role of familiarity and trust. Omega, 28(6), 725-737.
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(6), 407-424. https://doi.org/https://doi.org/10.1016/j.omega.2004.01.006
Godey, B., Manthiou, A., Pederzoli, D., Rokka, J., Aiello, G., Donvito, R., & Singh, R. (2016). Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of Business Research, 69(12), 5833-5841.
Gu, J.-C., Lee, S.-C., & Suh, Y.-H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605-11616.
Guo, L., Hu, X., Lu, J., & Ma, L. (2021). Effects of customer trust on engagement in live streaming commerce: mediating role of swift guanxi. Internet Research, 31(5), 1718-1744.
Guo, Y., Goh, K. Y., & Ragab Sayed, M. (2019). Mobile live streaming: the roles of broadcasters’ screen presence and dynamic emotions in viewership engagement.
Guo, Y., Zhang, K., & Wang, C. (2022). Way to success: Understanding top streamer′s popularity and influence from the perspective of source characteristics. Journal of retailing and consumer services, 64, 102786.
Ha, N. M., & Lam, N. H. (2016). The Effects of Celebrity Endorsement on Customer’s Attitude toward Brand and Purchase Intention. International Journal of Economics and Finance, 9, 64-77.
Hair, J. F. (2009). Multivariate data analysis.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis 6th Edition. Pearson Prentice Hall. New Jersey. humans: Critique and reformulation. Journal of Abnormal Psychology, 87, 49-74.
Hargittai, E., & Litt, E. (2011). The tweet smell of celebrity success: Explaining variation in Twitter adoption among a diverse group of young adults. New media & society, 13(5), 824-842.
Hausman, A. (2000). A multi-method investigation of consumer motivations in impulse buying behavior. Journal of consumer marketing, 17, 403-426. https://doi.org/10.1108/07363760010341045
Heijden, H. v. d. (2000). Using the Technology Acceptance Model to Predict Website Usage: Extensions and Empirical Tests. research memorandum.
Hilligoss, B., & Rieh, S. Y. (2008). Developing a unifying framework of credibility assessment: Construct, heuristics, and interaction in context. Information Processing & Management, 44(4), 1467-1484.
Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption: emerging concepts, methods and propositions. Journal of marketing, 46(3), 92-101.
Horton, D., & Richard Wohl, R. (1956). Mass communication and para-social interaction: Observations on intimacy at a distance. Psychiatry, 19(3), 215-229.
Hou, F., Guan, Z., Li, B., & Chong, A. (2019). Factors influencing people′s continuous watching intention and consumption intention in live streaming. Internet Research.
Hsu, C.-L., & Lu, H.-P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868.
Hu, M., Zhang, M., & Wang, Y. (2017). Why do audiences choose to keep watching on live video streaming platforms? An explanation of dual identification framework. Computers in Human Behavior, 75, 594-606.
Huang, L.-T. (2016). Flow and social capital theory in online impulse buying. Journal of Business Research, 69(6), 2277-2283.
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.
Hung, K. (2014). Why celebrity sells: A dual entertainment path model of brand endorsement. Journal of advertising, 43(2), 155-166.
Hwang, Y., & Kim, D. J. (2007). Customer self-service systems: The effects of perceived Web quality with service contents on enjoyment, anxiety, and e-trust. Decision Support Systems, 43(3), 746-760. https://doi.org/https://doi.org/10.1016/j.dss.2006.12.008
Jacoby, J. (2002). Stimulus‐organism‐response reconsidered: an evolutionary step in modeling (consumer) behavior. Journal of consumer psychology, 12(1), 51-57.
Javed, M. K., & Wu, M. (2019). Effects of online retailer after delivery services on repurchase intention: An empirical analysis of customers’ past experience and future confidence with the retailer. Journal of retailing and consumer services, 54, 101942.
Jiang, Z., Chan, J., Tan, B. C., & Chua, W. S. (2010). Effects of interactivity on website involvement and purchase intention. Journal of the Association for Information Systems, 11(1), 1.
Joo, J., & Sang, Y. (2013). Exploring Koreans’ smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory. Computers in Human Behavior, 29(6), 2512-2518. https://doi.org/https://doi.org/10.1016/j.chb.2013.06.002
Jöreskog, K. G., & Sörbom, D. (1982). Recent developments in structural equation modeling. Journal of Marketing research, 19(4), 404-416.
Jöreskog, K. G., & Sörbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS command language. Scientific software international.
Kamboj, S., Sarmah, B., Gupta, S., & Dwivedi, Y. (2018). Examining branding co-creation in brand communities on social media: Applying the paradigm of Stimulus-Organism-Response. International journal of information management, 39, 169-185.
Kankanhalli, A., Tan, B. C., & Wei, K.-K. (2005). Contributing knowledge to electronic knowledge repositories: An empirical investigation. Mis Quarterly, 113-143.
Kerlinger, P. (2000). Avian mortality at communication towers: a review of recent literature, research, and methodology.
Kim, J., & Song, H. (2016). Celebrity′s self-disclosure on Twitter and parasocial relationships: A mediating role of social presence. Computers in Human Behavior, 62, 570-577.
Kim, K., Hwang, J., Zo, H., & Lee, H. (2014). Understanding users’ continuance intention toward smartphone augmented reality applications. Information development, 32(2), 161-174.
Kim, M., Yoo, C. W., & Choe, Y. C. (2008). The impact of product heterogeneity on online consumer behavior. World conference on agricultural information and IT, IAALD AFITA WCCA 2008, Tokyo University of Agriculture, Tokyo, Japan, 24-27 August, 2008,
Kim, S., & Park, H. (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.
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information systems research, 13(2), 205-223.
Kumar, P., Dass, M., & Topaloglu, O. (2011). Exploring satisfaction in business-to-business services: a path-analytic approach. Service business, 5(1), 13-27.
Labrecque, L. I. (2014). Fostering consumer–brand relationships in social media environments: The role of parasocial interaction. Journal of interactive marketing, 28(2), 134-148.
Ledbetter, A. M., & Meisner, C. (2021). Extending the personal branding affordances typology to parasocial interaction with public figures on social media: Social presence and media multiplexity as mediators. Computers in Human Behavior, 115, 106610.
Lee, C.-H., & Chen, C.-W. (2021). Impulse Buying Behaviors in Live Streaming Commerce Based on the Stimulus-Organism-Response Framework. Information, 12(6), 241. https://www.mdpi.com/2078-2489/12/6/241
Lee, E.-J. (2013). Effectiveness of politicians′ soft campaign on Twitter versus TV: Cognitive and experiential routes. Journal of communication, 63(5), 953-974.
Lee, E.-J., & Oh, S. Y. (2012). To personalize or depersonalize? When and how politicians′ personalized tweets affect the public′s reactions. Journal of communication, 62(6), 932-949.
Lee, H., Kim, D., Ryu, J., & Lee, S. (2011). Acceptance and rejection of mobile TV among young adults: A case of college students in South Korea. Telematics and Informatics, 28(4), 239-250.
Lee, K.-M., & Nass, C. (2005). Social-psychological origins of feelings of presence: Creating social presence with machine-generated voices. Media psychology, 7(1), 31-45.
Lee, K. M. (2004). Presence, explicated. Communication Theory, 14(1), 27-50.
Li, R. Y. M. (2015). Generation X and Y’s demand for homeownership in Hong Kong. Pacific Rim Property Research Journal, 21(1), 15-36.
Liang, T.-P., Ho, Y.-T., Li, Y.-W., & Turban, E. (2011). What drives social commerce: The role of social support and relationship quality. International Journal of Electronic Commerce, 16(2), 69-90.
Liébana-Cabanillas, F., Marinković, V., & Kalinić, Z. (2016). A SEM-neural network approach for predicting antecedents of m-commerce acceptance. International journal of information management, 37(2), 14-24.
Lim, S., Cha, S. Y., Park, C., Lee, I., & Kim, J. (2012). Getting closer and experiencing together: Antecedents and consequences of psychological distance in social media-enhanced real-time streaming video. Computers in Human Behavior, 28(4), 1365-1378.
Lin, A. (2006). The acceptance and use of a business-to-business information system. International journal of information management, 26(5), 386-400.
Liu, C., & Arnett, K. P. (2000). Exploring the factors associated with Web site success in the context of electronic commerce. Inf. Manag., 38, 23-33.
Liu, I.-F., Chen, M. C., Sun, Y. S., Wible, D., & Kuo, C.-H. (2010). Extending the TAM model to explore the factors that affect Intention to Use an Online Learning Community. Computers & Education, 54(2), 600-610.
Liu, Y., Li, H., & Hu, F. (2013). Website attributes in urging online impulse purchase: An empirical investigation on consumer perceptions. Decision Support Systems, 55(3), 829-837.
Lo, P.-S., Dwivedi, Y. K., Tan, G. W.-H., Ooi, K.-B., Aw, E. C.-X., & Metri, B. (2022). Why do consumers buy impulsively during live streaming? A deep learning-based dual-stage SEM-ANN analysis. Journal of Business Research, 147, 325-337.
Lombard, M., & Ditton, T. (1997). At the heart of it all: The concept of presence. Journal of computer-mediated communication, 3(2), JCMC321.
Lou, C., & Yuan, S. (2019). Influencer marketing: how message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19(1), 58-73.
Lu, B., & Chen, Z. (2021). Live streaming commerce and consumers’ purchase intention: An uncertainty reduction perspective. Information & Management, 58(7), 103509.
Lu, B., Fan, W., & Zhou, M. (2016). Social presence, trust, and social commerce purchase intention: An empirical research. Computers in Human Behavior, 56, 225-237.
Ma, L., Gao, S., & Zhang, X. (2022). How to Use Live Streaming to Improve Consumer Purchase Intentions: Evidence from China. Sustainability 2022, 14, 1045. https://doi.org/https://doi.org/10.3390/su14021045
Maccallum, R. C., & Hong, S. (1997). Power analysis in covariance structure modeling using GFI and AGFI. Multivariate behavioral research, 32(2), 193-210.
Marangunić, N., & Granić, A. (2014). Technology acceptance model: a literature review from 1986 to 2013. Universal access in the information society, 14(1), 81-95.
Marcus, G. E., Neuman, W. R., & Mackuen, M. (2000). Affective intelligence and political judgment. University of Chicago Press.
Marsh, H. W., Balla, J. R., & Mcdonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological bulletin, 103(3), 391.
Mciver, J., & Carmines, E. G. (1981). Unidimensional scaling (Vol. 24). sage.
Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. the MIT Press.
Metiu, A., & Rothbard, N. P. (2013). Task Bubbles, Artifacts, Shared Emotion, and Mutual Focus of Attention: A Comparative Study of the Microprocesses of Group Engagement. Organization Science, 24(2), 455–475.
Ming, J., Jianqiu, Z., Bilal, M., Akram, U., & Fan, M. (2021). How social presence influences impulse buying behavior in live streaming commerce? The role of SOR theory. International Journal of Web Information Systems.
Mo, Y., & Wang, Q. (2021). Exploring the Influence of Live Streaming in Social Commerce on Impulse Buying from a Affordance Perspective
Mollen, A., & Wilson, H. (2010). Engagement, telepresence and interactivity in online consumer experience: Reconciling scholastic and managerial perspectives. Journal of Business Research, 63(9-10), 919-925.
Moore, M. G., & Kearsley, G. (2011). Distance education: A systems view of online learning. Cengage Learning.
Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of marketing, 58(3), 20-38.
Mou, J., & Benyoucef, M. (2021). Consumer behavior in social commerce: Results from a meta-analysis. Technological Forecasting and Social Change, 167, 120734.
Munoz-Leiva, F., Climent-Climent, S., & Liébana-Cabanillas, F. (2017). Determinants of intention to use the mobile banking apps: An extension of the classic TAM model. Spanish Journal of Marketing-ESIC, 21(1), 25-38.
Nagy, J. T. (2018). Evaluation of online video usage and learning satisfaction: An extension of the technology acceptance model. International Review of Research in Open and Distributed Learning, 19(1).
Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of management review, 23(2), 242-266.
Nguyen, M. H., Gruber, J., Fuchs, J., Marler, W., Hunsaker, A., & Hargittai, E. (2020). Changes in Digital Communication During the COVID-19 Global Pandemic: Implications for Digital Inequality and Future Research. Social Media+ Society, 6(3), 2056305120948255.
Nicolaou, A. I., Ibrahim, M., & Van Heck, E. (2013). Information quality, trust, and risk perceptions in electronic data exchanges. Decision Support Systems, 54(2), 986-996.
Niehaves, B., & Plattfaut, R. (2014). Internet adoption by the elderly: employing IS technology acceptance theories for understanding the age-related digital divide. European Journal of Information Systems, 23(6), 708-726.
Nunnally, J. C., Knott, P. D., Duchnowski, A., & Parker, R. (1967). Pupillary response as a general measure of activation. Perception & psychophysics, 2(4), 149-155.
Pandita, S., Mishra, H. G., & Chib, S. (2021). Psychological impact of covid-19 crises on students through the lens of Stimulus-Organism-Response (SOR) model. Children and Youth Services Review, 120, 105783.
Parboteeah, D. V., Valacich, J. S., & Wells, J. D. (2009). The influence of website characteristics on a consumer′s urge to buy impulsively. Information systems research, 20(1), 60-78.
Park, E., & Kim, K. J. (2013). User acceptance of long‐term evolution (LTE) services: An application of extended technology acceptance model. Program.
Park, N. (2010). Adoption and Use of Computer-Based Voice Over Internet Protocol Phone Service: Toward an Integrated Model. Journal of communication, 60(1), 40-72. https://doi.org/10.1111/j.1460-2466.2009.01440.x
Park, N., Roman, R., Lee, S., & Chung, J. E. (2009). User acceptance of a digital library system in developing countries: An application of the Technology Acceptance Model. International journal of information management, 29(3), 196-209.
Park, S.-Y., & Yang, Y. (2010). The effect of celebrity conformity on the purchase intention of celebrity sponsorship brand: The moderating effects of symbolic consumption and face-saving. Journal of Global Fashion Marketing, 1(4), 215-229.
Pavlov, P. I. (2010). Conditioned reflexes: an investigation of the physiological activity of the cerebral cortex. Annals of neurosciences, 17(3), 136.
Piaget, J., Garcia, R., & Garcia Iii, R. (1989). Psychogenesis and the history of science. Columbia University Press.
Powell, L., Richmond, V. P., & Williams, G. C. (2011). Social Networking and Political Campaigns: Perceptions of Candidates as Interpersonal Constructs. North American Journal of Psychology, 13(2).
Rauniar, R., Rawski, G., Yang, J., & Johnson, B. (2014). Technology acceptance model (TAM) and social media usage: an empirical study on Facebook. Journal of Enterprise Information Management.
Raykov, T., & Marcoulides, G. A. (2008). An introduction to applied multivariate analysis. Routledge.
Research, G. V. (2022). Video Streaming Market Size Worth $330.51 Billion By 2030. https://www.grandviewresearch.com/press-release/global-video-streaming-market
Richard, M.-O., Chebat, J.-C., Yang, Z., & Putrevu, S. (2010). A proposed model of online consumer behavior: Assessing the role of gender. Journal of Business Research, 63(9-10), 926-934.
Richardson, J. C. (2001). Examining social presence in online courses in relation to students′ perceived learning and satisfaction. State University of New York at Albany.
Ridings, C. M., Gefen, D., & Arinze, B. (2002). Some antecedents and effects of trust in virtual communities. The journal of strategic information systems, 11(3-4), 271-295.
Rieh, S. Y. (2002). Judgment of information quality and cognitive authority in the Web. Journal of the American society for information science and technology, 53(2), 145-161.
Robert, D., & John, R. (1982). Store atmosphere: an environmental psychology approach. Journal of retailing, 58(1), 34-57.
Rogers, E. M. (2003). Diffusion of innovations. Free Press.
Rook, D. W. (1987). The buying impulse. Journal of consumer research, 14(2), 189-199.
Rubin, A. M., & Perse, E. M. (1987). Audience Activity and Soap Opera Involvement A Uses and Effects Investigation. Human communication research, 14(2), 246-268. https://doi.org/https://doi.org/10.1111/j.1468-2958.1987.tb00129.x
Rubin, A. M., Perse, E. M., & Powell, R. A. (1985). Loneliness, parasocial interaction, and local television news viewing. Human communication research, 12(2), 155-180.
Sarkar, S., Chauhan, S., & Khare, A. (2020). A meta-analysis of antecedents and consequences of trust in mobile commerce. International journal of information management, 50, 286-301.
Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13-35.
Shen, K. N., & Khalifa, M. (2012). System design effects on online impulse buying. Internet Research.
Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. Toronto; London; New York: Wiley.
Singer, B. D. (1983). The case for using “real people” in advertising. Business Quarterly, 48(4), 32-37.
Sjöblom, M., Törhönen, M., Hamari, J., & Macey, J. (2017). Content structure is king: An empirical study on gratifications, game genres and content type on Twitch. Computers in Human Behavior, 73, 161-171.
Skinner, B. (1935). The generic nature of the concepts of stimulus and response. The Journal of General Psychology, 12(1), 40-65.
Slade, E., Williams, M., Dwivedi, Y., & Piercy, N. (2015). Exploring consumer adoption of proximity mobile payments. Journal of Strategic Marketing, 23(3), 209-223.
Sokolova, K., & Kefi, H. (2019). Instagram and YouTube bloggers promote it, why should I buy? How credibility and parasocial interaction influence purchase intentions. Journal of retailing and consumer services, 53, 101742.
Song, S., & Kim, H.-Y. (2020). Celebrity endorsements for luxury brands: followers vs. non-followers on social media. International Journal of Advertising, 39(6), 802-823.
Stern, H. (1962). The significance of impulse buying today. Journal of marketing, 26(2), 59-62.
Stever, G. S., & Lawson, K. (2013). Twitter as a way for celebrities to communicate with fans: Implications for the study of parasocial interaction. North American Journal of Psychology, 15(2).
Su, B.-C., Wu, L.-W., Chang, Y.-Y.-C., & Hong, R.-H. (2021). Influencers on Social Media as References: Understanding the Importance of Parasocial Relationships. Sustainability, 13(19), 10919. https://www.mdpi.com/2071-1050/13/19/10919
Tajvidi, M., Richard, M.-O., Wang, Y., & Hajli, N. (2018). Brand co-creation through social commerce information sharing: The role of social media. Journal of Business Research, 121, 476-486.
Tefertiller, A. (2020). Cable cord-cutting and streaming adoption: Advertising avoidance and technology acceptance in television innovation. Telematics and Informatics, 51, 101416. https://doi.org/https://doi.org/10.1016/j.tele.2020.101416
Uscreen. (2022). Top 14 Live Streaming Trends to Know for 2022. https://www.uscreen.tv/blog/live-streaming-trends/
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
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, 157-178.
Verhagen, T., & Van Dolen, W. (2011). The influence of online store beliefs on consumer online impulse buying: A model and empirical application. Information & Management, 48(8), 320-327.
Verplanken, B., & Herabadi, A. (2001). Individual differences in impulse buying tendency: Feeling and no thinking. European Journal of personality, 15(1_suppl), S71-S83.
Wallace, L. G., & Sheetz, S. D. (2014). The adoption of software measures: A technology acceptance model (TAM) perspective. Information & Management, 51(2), 249-259.
Wang, S. W., & Scheinbaum, A. C. (2017). Trustworthiness trumps attractiveness and expertise: enhancing brand credibility through celebrity endorsement. Journal of Advertising Research.
Wells, J. D., Parboteeah, V., & Valacich, J. S. (2011). Online impulse buying: understanding the interplay between consumer impulsiveness and website quality. Journal of the Association for Information Systems, 12(1), 3.
Wiedmann, K.-P., & Von Mettenheim, W. (2020). Attractiveness, trustworthiness and expertise–social influencers’ winning formula? Journal of Product & Brand Management, 30(5), 707-725.
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.
Wongkitrungrueng, A., & Assarut, N. (2020). The role of live streaming in building consumer trust and engagement with social commerce sellers. Journal of Business Research, 117, 543-556.
Woodcock, J., & Johnson, M. R. (2019). The affective labor and performance of live streaming on Twitch. tv. Television & New Media, 20(8), 813-823.
Woodworth, R., & Marquis, D. (2014). Psychology (psychology revivals): A study of mental life. Psychology Press.
Wu, L., Chen, K.-W., & Chiu, M.-L. (2016). Defining key drivers of online impulse purchasing: A perspective of both impulse shoppers and system users. International journal of information management, 36(3), 284-296.
Xiang, L., Zheng, X., Lee, M. K. O., & Zhao, D. (2016). Exploring consumers’ impulse buying behavior on social commerce platform: The role of parasocial interaction. International journal of information management, 36(3), 333-347. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2015.11.002
Xu, P., Cui, B.-j., & Lyu, B. (2022). Influence of Streamer′s Social Capital on Purchase Intention in Live Streaming E-Commerce [Original Research]. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.748172
Xu, X., Li, Q., Peng, L., Hsia, T.-L., Huang, C.-J., & Wu, J.-H. (2017). The impact of informational incentives and social influence on consumer behavior during Alibaba′s online shopping carnival. Computers in Human Behavior, 76, 245-254.
Xu, X., Wu, J.-H., Chang, Y.-T., & Li, Q. (2019). The Investigation of Hedonic Consumption, Impulsive Consumption and Social Sharing in E-commerce Live-streaming Videos. PACIS,
Xu, X., Wu, J.-H., & Li, Q. (2020). What drives consumer shopping behavior in live streaming commerce? Journal of Electronic Commerce Research, 21( Vol. 21, Iss. 3), 144-167.
Xu, X.-Y., Luo, X. R., Wu, K., & Zhao, W. (2021). Exploring viewer participation in online video game streaming: A mixed-methods approach. International journal of information management, 58, 102297.
Yang, H., & Lee, H. (2017). Exploring user acceptance of streaming media devices: an extended perspective of flow theory. Information Systems and e-Business Management, 16(1), 1-27. https://doi.org/10.1007/s10257-017-0339-x
Yu, J., Lee, H., Ha, I., & Zo, H. (2017). User acceptance of media tablets: An empirical examination of perceived value. Telematics and Informatics, 34(4), 206-223.
Yuan, C., Moon, H., Wang, S., Yu, X., & Kim, K. H. (2021). Study on the influencing of B2B parasocial relationship on repeat purchase intention in the online purchasing environment: An empirical study of B2B E-commerce platform. Industrial Marketing Management, 92, 101-110. https://doi.org/https://doi.org/10.1016/j.indmarman.2020.11.008
Yuan, S., & Lou, C. (2020). How social media influencers foster relationships with followers: The roles of source credibility and fairness in parasocial relationship and product interest. Journal of Interactive Advertising, 20(2), 133-147.
Zhang, H., Lu, Y., Gupta, S., & Zhao, L. (2014). What motivates customers to participate in social commerce? The impact of technological environments and virtual customer experiences. Information & Management, 51(8), 1017-1030.
Zhao, Q., Chen, C.-D., Cheng, H.-W., & Wang, J.-L. (2017). Determinants of live streamers’ continuance broadcasting intentions on Twitch: A self-determination theory perspective. Telematics and Informatics, 35(2), 406-420.
Zhou, T. (2011). Examining mobile banking user adoption from the perspectives of trust and flow experience. Information Technology and Management, 13(1), 27-37.
Zhou, T. (2013). The effect of flow experience on user adoption of mobile TV. Behaviour & Information Technology, 32(3), 263-272.
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