ISSN 0253-2778

CN 34-1054/N

open
Free to Publish. Free to Read.
Open AccessOpen Access JUSTC Management Science and Engineering 20 April 2022

The influence and moderating effect of trust in streamers in a live streaming shopping environment

  • School of Management, University of Science and Technology of China, Hefei 230026, China

Cite this:
https://doi.org/10.52396/JUSTC-2021-0219
More Information
  • Author Bio:

    Qi Dai obtained her PhD degree from Southwest Jiaotong University in 2008 and is currently an associate professor at the University of Science and Technology of China. Her research interests include marketing, consumer behavior, and live streaming shopping

    Xiaolin Cui is currently a graduate student in Business Administration at the University of Science and Technology of China. His research interests include live streaming shopping and consumer behavior

  • Corresponding author: E-mail: cxlin@mail.ustc.edu.cn
  • Received Date: 15 November 2021
  • Accepted Date: 21 January 2022
    • Available Online: 20 April 2022
    Abstract

  • Abstract

    With its powerful real-time interaction and rich user experience, live streaming shopping has rapidly become consumers' new favorite. However, the frequent "rollover" incidents affecting the reputation of well-known streamers significantly reduce consumers' trust in the streamers. Academic research on trust in live streaming shopping has thus far mainly focused on purchase motivations. Few studies have focused on the factors influencing trust from the streamer's perspective, and they have ignored the moderating role of streamers and product factors, situational factors and individual characteristics of consumers. Therefore, this study introduces three new moderating variables – streamer-product matching, live streaming online reviews, and online shopping experience – to explore their moderating effects on streamers' reputation, popularity, and trust. The results show that streamers' reputation and popularity have a significant positive impact on trust in streamers, and streamer-product matching has a positive moderating effect on the relationship between streamers' reputation, streamers' popularity, and trust in streamers. Online reviews have a positive moderating effect on the relationship between streamers' popularity and trust, while online shopping experience has a positive moderating effect on the relationship between streamers' reputation and trust in streamers.

    Graphical abstract

      This is the hypothesis test result of this study. Two hypotheses, H5 and H8, are not supported.

    Abstract

    With its powerful real-time interaction and rich user experience, live streaming shopping has rapidly become consumers' new favorite. However, the frequent "rollover" incidents affecting the reputation of well-known streamers significantly reduce consumers' trust in the streamers. Academic research on trust in live streaming shopping has thus far mainly focused on purchase motivations. Few studies have focused on the factors influencing trust from the streamer's perspective, and they have ignored the moderating role of streamers and product factors, situational factors and individual characteristics of consumers. Therefore, this study introduces three new moderating variables – streamer-product matching, live streaming online reviews, and online shopping experience – to explore their moderating effects on streamers' reputation, popularity, and trust. The results show that streamers' reputation and popularity have a significant positive impact on trust in streamers, and streamer-product matching has a positive moderating effect on the relationship between streamers' reputation, streamers' popularity, and trust in streamers. Online reviews have a positive moderating effect on the relationship between streamers' popularity and trust, while online shopping experience has a positive moderating effect on the relationship between streamers' reputation and trust in streamers.

    • Public Summary

    • This study explains the observed phenomenon of "why more consumers prefer some specific streamers, such as Jiaqi Li".
    • Applying the matching theory to the live streaming shopping environment and expanding the research on celebrities to streamers. The results show that the matching theory is still effective in the live streaming shopping environment.
    • Online reviews and online shopping experience have different moderating effects on trust in streamers. And they are only partially effective in moderating trust in streamers in the live streaming shopping environment.

    FullText(HTML)
  • loading
    • References(107)
  • [1]
    Kim S, Park H. Effects of various characteristics of social commerce (s-commerce) on consumers' trust and trust performance. International Journal of Information Management, 2013, 33 (2): 318–332. doi: 10.1016/j.ijinfomgt.2012.11.006
    [2]
    Haimson O L, Tang J C. What makes live events engaging on Facebook Live, Periscope, and Snapchat. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. New York: ACM, 2017: 48-60.
    [3]
    Wohn D Y, Freeman G, Mclaughlin C, et al. Explaining viewers' emotional, instrumental, and financial support provision for live streamers. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. New York: ACM, 2018: No. 474.
    [4]
    Wongkitrungrueng A, Assarut N. The role of live streaming in building consumer trust and engagement with social commerce sellers. Journal of Business Research, 2018, 117: 543–556. doi: 10.1016/j.jbusres.2018.08.032
    [5]
    Cai J, Wohn D Y, Mittal A, et al. Utilitarian and hedonic motivations for live streaming shopping. In: Proceedings of the 2018 ACM International Conference on Interactive Experiences for TV and Online Video. New York: ACM, 2018: 81-88.
    [6]
    Addo P C, Fang J, Asare A O, et al. Customer engagement and purchase intention in live-streaming digital marketing platforms. The Service Industries Journal, 2021, 42: 1–20. doi: 10.1080/02642069.2021.1905798
    [7]
    Kang K, Lu J, Guo L, et al. The dynamic effect of interactivity on customer engagement behavior through tie strength: Evidence from live streaming commerce platforms. International Journal of Information Management, 2021, 56: 102251. doi: 10.1016/j.ijinfomgt.2020.102251
    [8]
    Park H J, Lin L M. The effects of match-ups on the consumer attitudes toward Internet celebrities and their live streaming contents in the context of product endorsement. Journal of Retailing and Consumer Services, 2020, 52: 101934. doi: 10.1016/j.jretconser.2019.101934
    [9]
    Tong J. A study on the effect of web live broadcast on consumers’ willingness to purchase. Open Journal of Business and Management, 2017, 5 (2): 280–289. doi: 10.4236/ojbm.2017.52025
    [10]
    Ma H, Mei H. Empirical research on the decision-making influence factors in consumer purchase behavior of webcasting platform. In: Proceedings of the Twelfth International Conference on Management Science and Engineering Management. Cham, Switzerland: Springer, 2018: 1017-1028.
    [11]
    Meng F. Research of opinion leaders' impact on purchase intention under social commerce context. Nanjing: Nanjing University, 2012.
    [12]
    Jia X F. Exploring consumer’ purchase and engagement intention on e-commerce live streaming platform. Beijing: Beijing University of Posts and Telecommunications, 2019.
    [13]
    Cheng D, Wang Z S, Sun Y B. Essence of live streaming with goods: Subversive innovation or expansion of traditional e-commerce model. Journal of Commercial Economics, 2021, (5): 86–89. doi: 10.3969/j.issn.1002-5863.2021.05.023
    [14]
    Meng L, Liu F J, Chen S Y, et al. Can I evoke you? A study on the influence mechanism of information source characteristics of different types of live broadcasting celebrity on consumers’ willingness to purchase. Nankai Business Review, 2020, 23 (01): 131–143. doi: 10.3969/j.issn.1008-3448.2020.01.013
    [15]
    Brynjolfsson E, Smith M D. Frictionless commerce? A comparison of Internet and conventional retailers. Management Science, 2000, 46 (4): 563–585. doi: 10.1287/mnsc.46.4.563.12061
    [16]
    Kim D J, Ferrin D L, Rao H R. A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 2008, 44 (2): 544–564. doi: 10.1016/j.dss.2007.07.001
    [17]
    Jeun S-T, Wu X, Cheon J. A study on the effect of perceived risks on trust and perceived transaction value in Chinese Internet shopping mall environment: Focused on the perceived usefulness control effect. Journal of Distribution and Management Research, 2019, 22 (4): 47–56. doi: 10.17961/jdmr.22.4.201908.47
    [18]
    Komiak S X, Benbasat I. Understanding customer trust in agent-mediated electronic commerce, web-mediated electronic commerce, and traditional commerce. Information Technology and Management, 2004, 5 (1): 181–207. doi: 10.1023/B:ITEM.0000008081.55563.d4
    [19]
    Farivar S, Turel O, Yuan Y. A trust-risk perspective on social commerce use: An examination of the biasing role of habit. Internet Research, 2017, 27 (3): 586–607. doi: 10.1108/IntR-06-2016-0175
    [20]
    Liu J H, North M, Li C. Relationship building through reputation and tribalism on companies’ Facebook pages: A uses and gratifications approach. Internet Research, 2017, 27 (5): 1149–1169. doi: 10.1108/IntR-03-2016-0078
    [21]
    San-Martín S, Jimenez N. Curbing electronic shopper perceived opportunism and encouraging trust. Industrial Management & Data Systems, 2017, 117 (10): 2210–2226. doi: 10.1108/IMDS-08-2016-0315
    [22]
    Cai J, Wohn D Y. Live streaming commerce: Uses and gratifications approach to understanding consumers’ motivations. In: Proceedings of the 52nd Hawaii International Conference on System Sciences, Hawaii, 2019: 2548-2557.
    [23]
    Gong W, Li X. Engaging fans on microblog: The synthetic influence of parasocial interaction and source characteristics on celebrity endorsement. Psychology & Marketing, 2017, 34 (7): 720–732. doi: 10.1002/mar.21018
    [24]
    Mccormick K. Celebrity endorsements: Influence of a product-endorser match on Millennials attitudes and purchase intentions. Journal of Retailing and Consumer Services, 2016, 32: 39–45. doi: 10.1016/j.jretconser.2016.05.012
    [25]
    Ma Q H, Zhao J, Zhang Y X, et al. A research on the formation mechanism of customers’ initial trust under C2C environment: The moderation effect of online shopping experience. Management Review, 2012, 24 (07): 70–81, 98. doi: 10.14120/j.cnki.cn11-5057/f.2012.07.006
    [26]
    Li H Y, Lin L. The moderating effects of purchase experience on customer satisfaction evaluation with online shopping platform. Soft Science, 2011, 25 (12): 137–142. doi: 10.3969/j.issn.1001-8409.2011.12.030
    [27]
    Wu J F, Hou D L, Zhang Y J. Study on influencing factors of customers' adoption intention in multichannel retailing system based on moderating role of online shopping experience. Journal of Beijing Technology and Business University (Social Sciences), 2016, 31 (4): 51–59. doi: 10.16299/j.1009-6116.2016.04.007
    [28]
    Rodgers W, Negash S, Suk K. The moderating effect of on-line experience on the antecedents and consequences of on-line satisfaction. Psychology & Marketing, 2005, 22 (4): 313–331. doi: 10.1002/mar.20061
    [29]
    Zhou F, Chen L, Su Q. Understanding the impact of social distance on users’ broadcasting intention on live streaming platforms: A lens of the challenge-hindrance stress perspective. Telematics and Informatics, 2019, 41: 46–54. doi: 10.1016/j.tele.2019.03.002
    [30]
    Bründl S, Matt C, Hess T. Consumer use of social live streaming services: The influence of co-experience and effectance on enjoyment.In: Proceedings of the 25th European Conference on Information Systems (ECIS), Guimarães, Portugal, 2017: 1775-1791.
    [31]
    Chen Z, Benbasat I, Cenfetelli R T. “Grassroots Internet celebrity plus live streaming” activating IT-mediated lifestyle marketing services at e-commerce websites. ICIS 2017 Proceedings, 2017: 7.
    [32]
    Cheng C, Hu Y, Lu Y, et al. Everyone can be a star in the digital economy: Quantifying the business value of live streaming technology in online retail. Rochester, NY: SSRN, 2019: 3422615.
    [33]
    Lin J B, Li L, Yan Y M, et al. Understanding Chinese consumer engagement in social commerce: The roles of social support and swift guanxi. Internet Research, 2018, 28 (1): 2–22. doi: 10.1108/IntR-11-2016-0349
    [34]
    Chang H H, Chen S W. The impact of online store environment cues on purchase intention: Trust and perceived risk as a mediator. Online Information Review, 2008, 32 (6): 818–841. doi: 10.1108/14684520810923953
    [35]
    Calder B J, Malthouse E C, Schaedel U. An experimental study of the relationship between online engagement and advertising effectiveness. Journal of Interactive Marketing, 2009, 23 (4): 321–331. doi: 10.1016/j.intmar.2009.07.002
    [36]
    Kim D, Benbasat I. Trust-assuring arguments in B2C e-commerce: Impact of content, source, and price on trust. Journal of Management Information Systems, 2009, 26 (3): 175–206. doi: 10.2753/MIS0742-1222260306
    [37]
    Hong-Kit Yim F, Anderson R E, Swaminathan S. Customer relationship management: Its dimensions and effect on customer outcomes. Journal of Personal Selling & Sales Management, 2004, 24 (4): 263–278.
    [38]
    Awad N F, Ragowsky A. Establishing trust in electronic commerce through online word of mouth: An examination across genders. Journal of Management Information Systems, 2008, 24 (4): 101–121. doi: 10.2753/MIS0742-1222240404
    [39]
    Sparks B A, Browning V. The impact of online reviews on hotel booking intentions and perception of trust. Tourism Management, 2011, 32 (6): 1310–1323. doi: 10.1016/j.tourman.2010.12.011
    [40]
    Mcknight D H, Choudhury V, Kacmar C. The impact of initial consumer trust on intentions to transact with a web site: A trust building model. The Journal of Strategic Information Systems, 2002, 11 (3–4): 297–323. doi: 10.1016/S0963-8687(02)00020-3
    [41]
    Tractinsky N, Jarvenpaa S, Vitale M, et al. Consumer trust in an Internet store: A cross-cultural validation. Journal of Computer-Mediated Communication, 1999, 5 (2): 1–5. doi: 10.1111/j.1083-6101.1999.tb00337.x
    [42]
    Kuan H-H, Bock G-W. Trust transference in brick and click retailers: An investigation of the before-online-visit phase. Information & Management, 2007, 44 (2): 175–187. doi: 10.1016/j.im.2006.12.002
    [43]
    Agag G, El-Masry A A. Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Computers in Human Behavior, 2016, 60: 97–111. doi: 10.1016/j.chb.2016.02.038
    [44]
    Wixom B H, Todd P A. A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 2005, 16 (1): 85–102. doi: 10.1287/isre.1050.0042
    [45]
    Zolfaghar K, Aghaie A. A syntactical approach for interpersonal trust prediction in social web applications: Combining contextual and structural data. Knowledge-Based Systems, 2012, 26: 93–102. doi: 10.1016/j.knosys.2010.10.007
    [46]
    Tu W, Yan C, Yan Y, et al. Who is earning? Understanding and modeling the virtual gifts behavior of users in live streaming economy. In: 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR). IEEE, 2018: 118-123.
    [47]
    Gao Y H. Research on the influence of network anchor characterics in e-commerce livestreaming on consumer's purchase intention. Harbin: Harbin Institute of Technology, 2020.
    [48]
    Rogers E M. Diffusion of Innovations. New York: Simon and Schuster, 2010.
    [49]
    Chao F. Research on the influence of network anchor characteristics on consumer attitudes — based on the regulation of interaction. Hefei: Anhui University, 2018.
    [50]
    Stern B B, Gould S J. The consumer as financial opinion leader. Journal of Retail Banking, 1988, 10 (2): 43–52.
    [51]
    Lyons B, Henderson K. Opinion leadership in a computer-mediated environment. Journal of Consumer Behaviour: An International Research Review, 2005, 4 (5): 319–329. doi: 10.1002/cb.22
    [52]
    Chen Y F, Tsai C W, Lin P H. The influence of perceived risk, shopping value and opinion leader to explore online consumer purchase intention: Using social network analysis. International Journal of E-Adoption, 2017, 9 (2): 31–58. doi: 10.4018/IJEA.2017070103
    [53]
    Raghupathi V, Fogel J. The impact of opinion leadership on purchases through social networking websites. Journal of Theoretical and Applied Electronic Commerce Research, 2015, 10 (3): 18–29. doi: 10.4067/S0718-18762015000300003
    [54]
    Chan K K, Misra S. Characteristics of the opinion leader: A new dimension. Journal of Advertising, 1990, 19 (3): 53–60. doi: 10.1080/00913367.1990.10673192
    [55]
    Li F, Du T C. Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs. Decision Support Systems, 2011, 51 (1): 190–197. doi: 10.1016/j.dss.2010.12.007
    [56]
    Sussman S W, Siegal W S. Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 2003, 14 (1): 47–65. doi: 10.1287/isre.14.1.47.14767
    [57]
    Chung S, Cho H. Fostering parasocial relationships with celebrities on social media: Implications for celebrity endorsement. Psychology & Marketing, 2017, 34 (4): 481–495. doi: 10.1002/mar.21001
    [58]
    Yoo J-W, Jin Y J. Reverse transfer effect of celebrity-product congruence on the celebrity's perceived credibility. Journal of Promotion Management, 2015, 21 (6): 666–684. doi: 10.1080/10496491.2015.1055046
    [59]
    Kamins M A. An investigation into the “match-up” hypothesis in celebrity advertising: When beauty may be only skin deep. Journal of Advertising, 1990, 19 (1): 4–13. doi: 10.1080/00913367.1990.10673175
    [60]
    Choi S M, Rifon N J. It is a match: The impact of congruence between celebrity image and consumer ideal self on endorsement effectiveness. Psychology & Marketing, 2012, 29 (9): 639–650. doi: 10.1002/mar.20550
    [61]
    Thwaites D, Lowe B, Monkhouse L L, et al. The impact of negative publicity on celebrity ad endorsements. Psychology & Marketing, 2012, 29 (9): 663–673. doi: 10.1002/mar.20552
    [62]
    Peterson R A, Kerin R A. The female role in advertisements: Some experimental evidence. Journal of Marketing, 1977, 41 (4): 59–63. doi: 10.1177/002224297704100407
    [63]
    Kamins M A, Gupta K. Congruence between spokesperson and product type: A matchup hypothesis perspective. Psychology & Marketing, 1994, 11 (6): 569–586. doi: 10.1002/mar.4220110605
    [64]
    Sengupta J, Goodstein R C, Boninger D S. All cues are not created equal: Obtaining attitude persistence under low-involvement conditions. Journal of Consumer Research, 1997, 23 (4): 351–361. doi: 10.1086/209488
    [65]
    Kim Y-J, Na J-H. Effects of celebrity athlete endorsement on attitude towards the product: The role of credibility, attractiveness and the concept of congruence. International Journal of Sports Marketing and Sponsorship, 2007, 8 (4): 23–33.
    [66]
    Roy S, Moorthi Y. Investigating endorser personality effects on brand personality: Causation and reverse causation in India. Journal of Brand Strategy, 2012, 1 (2): 164–179.
    [67]
    Ferris K O. The sociology of celebrity. Sociology Compass, 2007, 1 (1): 371–384. doi: 10.1111/j.1751-9020.2007.00019.x
    [68]
    Driessens O. Celebrity capital: redefining celebrity using field theory. Theory and Society, 2013, 42 (5): 543–560. doi: 10.1007/s11186-013-9202-3
    [69]
    Hennig-Thurau T, Walsh G, Walsh G. Electronic word-of-mouth: Motives for and consequences of reading customer articulations on the Internet. International Journal of Electronic Commerce, 2003, 8 (2): 51–74. doi: 10.1080/10864415.2003.11044293
    [70]
    Ba S, Pavlou P A. Evidence of the effect of trust building technology in electronic markets: Price premiums and buyer behavior. MIS Quarterly, 2002: 243–268. doi: 10.2307/4132332
    [71]
    Basuroy S, Chatterjee S, Ravid S A. How critical are critical reviews? The box office effects of film critics, star power, and budgets. Journal of Marketing, 2003, 67 (4): 103–117. doi: 10.1509/jmkg.67.4.103.18692
    [72]
    Racherla P, Friske W. Perceived ‘usefulness’ of online consumer reviews: An exploratory investigation across three services categories. Electronic Commerce Research and Applications, 2012, 11 (6): 548–559. doi: 10.1016/j.elerap.2012.06.003
    [73]
    Schuff D, Mudambi S. What makes a helpful online review? A study of customer reviews on Amazon. com. Social Science Electronic Publishing, 2012, 34 (1): 185–200.
    [74]
    Forman C, Ghose A, Wiesenfeld B. Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information Systems Research, 2008, 19 (3): 291–313. doi: 10.1287/isre.1080.0193
    [75]
    Cheung C M, Thadani D R. The effectiveness of electronic word-of-mouth communication: A literature analysis. BLED 2010 Proceedings, 2010, 23: 329–345.
    [76]
    Yue C. Exploring the relationship between retailer's image and private label brand purchasing—The moderating effect of trust propensity and face consciousness. Nanjing: Nanjing University, 2015.
    [77]
    Herr P M, Kardes F R, Kim J. Effects of word-of-mouth and product-attribute information on persuasion: An accessibility-diagnosticity perspective. Journal of Consumer Research, 1991, 17 (4): 454–462. doi: 10.1086/208570
    [78]
    Mittal V, Ross Jr W T, Baldasare P M. The asymmetric impact of negative and positive attribute-level performance on overall satisfaction and repurchase intentions. Journal of Marketing, 1998, 62 (1): 33–47. doi: 10.1177/002224299806200104
    [79]
    Mizerski R W. An attribution explanation of the disproportionate influence of unfavorable information. Journal of Consumer Research, 1982, 9 (3): 301–310. doi: 10.1086/208925
    [80]
    Chevalier J A, Mayzlin D. The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 2006, 43 (3): 345–354. doi: 10.1509/jmkr.43.3.345
    [81]
    Berger J, Sorensen A T, Rasmussen S J. Positive effects of negative publicity: When negative reviews increase sales. Marketing Science, 2010, 29 (5): 815–827. doi: 10.1287/mksc.1090.0557
    [82]
    Lee J, Park D-H, Han I. The effect of negative online consumer reviews on product attitude: An information processing view. Electronic Commerce Research and Applications, 2008, 7 (3): 341–352. doi: 10.1016/j.elerap.2007.05.004
    [83]
    Zhang L, Ma B, Cartwright D K. The impact of online user reviews on cameras sales. European Journal of Marketing, 2013, 47 (7): 1115–1128. doi: 10.1108/03090561311324237
    [84]
    Duan W, Gu B, Whinston A B. Do online reviews matter?—An empirical investigation of panel data. Decision Support Systems, 2008, 45 (4): 1007–1016. doi: 10.1016/j.dss.2008.04.001
    [85]
    Cheng Y-H, Ho H-Y. Social influence's impact on reader perceptions of online reviews. Journal of Business Research, 2015, 68 (4): 883–887. doi: 10.1016/j.jbusres.2014.11.046
    [86]
    Ghose A, Ipeirotis P G. Designing novel review ranking systems: Predicting the usefulness and impact of reviews. In: Proceedings of the Ninth International Conference on Electronic Commerce. New York: ACM, 2007: 303-310.
    [87]
    Hao Y Y, Ye Q, Li Y J. Research on online impact factors of customer reviews usefulness based on movie reviews data. Journal of Management Sciences in China, 2010, 13 (8): 78–88, 96.
    [88]
    Park D-H, Kim S. The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research and Applications, 2008, 7 (4): 399–410. doi: 10.1016/j.elerap.2007.12.001
    [89]
    Zeithaml V A, Parasuraman A, Malhotra A. Service quality delivery through web sites: A critical review of extant knowledge. Journal of the Academy of Marketing Science, 2002, 30 (4): 362–375. doi: 10.1177/009207002236911
    [90]
    Mathwick C, Malhotra N, Rigdon E. Experiential value: Conceptualization, measurement and application in the catalog and Internet shopping environment. Journal of Retailing, 2001, 77 (1): 39–56. doi: 10.1016/S0022-4359(00)00045-2
    [91]
    Moreau C P, Lehmann D R, Markman A B. Entrenched knowledge structures and consumer response to new products. Journal of Marketing Research, 2001, 38 (1): 14–29. doi: 10.1509/jmkr.38.1.14.18836
    [92]
    Childers T L. Assessment of the psychometric properties of an opinion leadership scale. Journal of Marketing Research, 1986, 23 (2): 184–188. doi: 10.1177/002224378602300211
    [93]
    Sheth J N, Parvatlyar A. Relationship marketing in consumer markets: Antecedents and consequences. Journal of the Academy of Marketing Science, 1995, 23 (4): 255–271. doi: 10.1177/009207039502300405
    [94]
    Boulding W, Kalra A, Staelin R, et al. A dynamic process model of service quality: From expectations to behavioral intentions. Journal of Marketing Research, 1993, 30 (1): 7–27. doi: 10.1177/002224379303000102
    [95]
    Montoya-Weiss M, Voss G B, Grewal D. Online channel use and satisfaction in a multichannel service context. MSI Reports, 2003, 2 (3): 19–35.
    [96]
    Petty R E, Cacioppo J T. The elaboration likelihood model of persuasion. In: Communication and Persuasion. New York: Springer, 1986: 1-24.
    [97]
    Koufaris M, Hampton-Sosa W. The development of initial trust in an online company by new customers. Information & Management, 2004, 41 (3): 377–397. doi: 10.1016/j.im.2003.08.004
    [98]
    Balasubramanian S K, Patwardhan H, Pillai D, et al. Modeling attitude constructs in movie product placements. Journal of Product & Brand Management, 2014, 23 (7): 516–531. doi: 10.1108/JPBM-04-2014-0552
    [99]
    Park D-H, Lee J, Han I. The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal of Electronic Commerce, 2007, 11 (4): 125–148. doi: 10.2753/JEC1086-4415110405
    [100]
    Limayem M, Hirt S G. Force of habit and information systems usage: Theory and initial validation. Journal of the Association for Information Systems, 2003, 4 (1): 3. doi: 10.17705/1jais.00030
    [101]
    Fornell C, Larcker D F. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 1981, 18 (1): 39–50. doi: 10.1177/002224378101800104
    [102]
    Chen M, Chen C C, Sheldon O J. Relaxing moral reasoning to win: How organizational identification relates to unethical pro-organizational behavior. Journal of Applied Psychology, 2016, 101 (8): 1082. doi: 10.1037/apl0000111
    [103]
    Hair J F, Black W C, Babin B J, et al. Multivariate Data Analysis. Upper Saddle River, NJ: Prentice-Hall, 2009.
    [104]
    Hair E, Halle T, Terry-Humen E, et al. Children's school readiness in the ECLS-K: Predictions to academic, health, and social outcomes in first grade. Early Childhood Research Quarterly, 2006, 21 (4): 431–454. doi: 10.1016/j.ecresq.2006.09.005
    [105]
    Marsh H W, Wen Z, Hau K-T. Structural equation models of latent interactions: Evaluation of alternative estimation strategies and indicator construction. Psychological Methods, 2004, 9 (3): 275. doi: 10.1037/1082-989X.9.3.275
    [106]
    Marsh H W, Wen Z, Hau K-T, et al. Structural equation models of latent interaction and quadratic effects. In: Structural Equation Modeling. A Second Course. Greenwich, CT: Information Age Publishing, 2013: 267-308.
    [107]
    Saris W E, Batista-Foguet J M, Coenders G. Selection of indicators for the interaction term in structural equation models with interaction. Quality & Quantity, 2007, 41 (1): 55–72. doi: 10.1007/s11135-005-3956-2
    • Supplements(0)
    • Related Articles
    • Track Citations
  • 加载中

Catalog

    Get Citation
    PDF
    XML

    Figure  1.  Conceptual model.

    [1]
    Kim S, Park H. Effects of various characteristics of social commerce (s-commerce) on consumers' trust and trust performance. International Journal of Information Management, 2013, 33 (2): 318–332. doi: 10.1016/j.ijinfomgt.2012.11.006
    [2]
    Haimson O L, Tang J C. What makes live events engaging on Facebook Live, Periscope, and Snapchat. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. New York: ACM, 2017: 48-60.
    [3]
    Wohn D Y, Freeman G, Mclaughlin C, et al. Explaining viewers' emotional, instrumental, and financial support provision for live streamers. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. New York: ACM, 2018: No. 474.
    [4]
    Wongkitrungrueng A, Assarut N. The role of live streaming in building consumer trust and engagement with social commerce sellers. Journal of Business Research, 2018, 117: 543–556. doi: 10.1016/j.jbusres.2018.08.032
    [5]
    Cai J, Wohn D Y, Mittal A, et al. Utilitarian and hedonic motivations for live streaming shopping. In: Proceedings of the 2018 ACM International Conference on Interactive Experiences for TV and Online Video. New York: ACM, 2018: 81-88.
    [6]
    Addo P C, Fang J, Asare A O, et al. Customer engagement and purchase intention in live-streaming digital marketing platforms. The Service Industries Journal, 2021, 42: 1–20. doi: 10.1080/02642069.2021.1905798
    [7]
    Kang K, Lu J, Guo L, et al. The dynamic effect of interactivity on customer engagement behavior through tie strength: Evidence from live streaming commerce platforms. International Journal of Information Management, 2021, 56: 102251. doi: 10.1016/j.ijinfomgt.2020.102251
    [8]
    Park H J, Lin L M. The effects of match-ups on the consumer attitudes toward Internet celebrities and their live streaming contents in the context of product endorsement. Journal of Retailing and Consumer Services, 2020, 52: 101934. doi: 10.1016/j.jretconser.2019.101934
    [9]
    Tong J. A study on the effect of web live broadcast on consumers’ willingness to purchase. Open Journal of Business and Management, 2017, 5 (2): 280–289. doi: 10.4236/ojbm.2017.52025
    [10]
    Ma H, Mei H. Empirical research on the decision-making influence factors in consumer purchase behavior of webcasting platform. In: Proceedings of the Twelfth International Conference on Management Science and Engineering Management. Cham, Switzerland: Springer, 2018: 1017-1028.
    [11]
    Meng F. Research of opinion leaders' impact on purchase intention under social commerce context. Nanjing: Nanjing University, 2012.
    [12]
    Jia X F. Exploring consumer’ purchase and engagement intention on e-commerce live streaming platform. Beijing: Beijing University of Posts and Telecommunications, 2019.
    [13]
    Cheng D, Wang Z S, Sun Y B. Essence of live streaming with goods: Subversive innovation or expansion of traditional e-commerce model. Journal of Commercial Economics, 2021, (5): 86–89. doi: 10.3969/j.issn.1002-5863.2021.05.023
    [14]
    Meng L, Liu F J, Chen S Y, et al. Can I evoke you? A study on the influence mechanism of information source characteristics of different types of live broadcasting celebrity on consumers’ willingness to purchase. Nankai Business Review, 2020, 23 (01): 131–143. doi: 10.3969/j.issn.1008-3448.2020.01.013
    [15]
    Brynjolfsson E, Smith M D. Frictionless commerce? A comparison of Internet and conventional retailers. Management Science, 2000, 46 (4): 563–585. doi: 10.1287/mnsc.46.4.563.12061
    [16]
    Kim D J, Ferrin D L, Rao H R. A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 2008, 44 (2): 544–564. doi: 10.1016/j.dss.2007.07.001
    [17]
    Jeun S-T, Wu X, Cheon J. A study on the effect of perceived risks on trust and perceived transaction value in Chinese Internet shopping mall environment: Focused on the perceived usefulness control effect. Journal of Distribution and Management Research, 2019, 22 (4): 47–56. doi: 10.17961/jdmr.22.4.201908.47
    [18]
    Komiak S X, Benbasat I. Understanding customer trust in agent-mediated electronic commerce, web-mediated electronic commerce, and traditional commerce. Information Technology and Management, 2004, 5 (1): 181–207. doi: 10.1023/B:ITEM.0000008081.55563.d4
    [19]
    Farivar S, Turel O, Yuan Y. A trust-risk perspective on social commerce use: An examination of the biasing role of habit. Internet Research, 2017, 27 (3): 586–607. doi: 10.1108/IntR-06-2016-0175
    [20]
    Liu J H, North M, Li C. Relationship building through reputation and tribalism on companies’ Facebook pages: A uses and gratifications approach. Internet Research, 2017, 27 (5): 1149–1169. doi: 10.1108/IntR-03-2016-0078
    [21]
    San-Martín S, Jimenez N. Curbing electronic shopper perceived opportunism and encouraging trust. Industrial Management & Data Systems, 2017, 117 (10): 2210–2226. doi: 10.1108/IMDS-08-2016-0315
    [22]
    Cai J, Wohn D Y. Live streaming commerce: Uses and gratifications approach to understanding consumers’ motivations. In: Proceedings of the 52nd Hawaii International Conference on System Sciences, Hawaii, 2019: 2548-2557.
    [23]
    Gong W, Li X. Engaging fans on microblog: The synthetic influence of parasocial interaction and source characteristics on celebrity endorsement. Psychology & Marketing, 2017, 34 (7): 720–732. doi: 10.1002/mar.21018
    [24]
    Mccormick K. Celebrity endorsements: Influence of a product-endorser match on Millennials attitudes and purchase intentions. Journal of Retailing and Consumer Services, 2016, 32: 39–45. doi: 10.1016/j.jretconser.2016.05.012
    [25]
    Ma Q H, Zhao J, Zhang Y X, et al. A research on the formation mechanism of customers’ initial trust under C2C environment: The moderation effect of online shopping experience. Management Review, 2012, 24 (07): 70–81, 98. doi: 10.14120/j.cnki.cn11-5057/f.2012.07.006
    [26]
    Li H Y, Lin L. The moderating effects of purchase experience on customer satisfaction evaluation with online shopping platform. Soft Science, 2011, 25 (12): 137–142. doi: 10.3969/j.issn.1001-8409.2011.12.030
    [27]
    Wu J F, Hou D L, Zhang Y J. Study on influencing factors of customers' adoption intention in multichannel retailing system based on moderating role of online shopping experience. Journal of Beijing Technology and Business University (Social Sciences), 2016, 31 (4): 51–59. doi: 10.16299/j.1009-6116.2016.04.007
    [28]
    Rodgers W, Negash S, Suk K. The moderating effect of on-line experience on the antecedents and consequences of on-line satisfaction. Psychology & Marketing, 2005, 22 (4): 313–331. doi: 10.1002/mar.20061
    [29]
    Zhou F, Chen L, Su Q. Understanding the impact of social distance on users’ broadcasting intention on live streaming platforms: A lens of the challenge-hindrance stress perspective. Telematics and Informatics, 2019, 41: 46–54. doi: 10.1016/j.tele.2019.03.002
    [30]
    Bründl S, Matt C, Hess T. Consumer use of social live streaming services: The influence of co-experience and effectance on enjoyment.In: Proceedings of the 25th European Conference on Information Systems (ECIS), Guimarães, Portugal, 2017: 1775-1791.
    [31]
    Chen Z, Benbasat I, Cenfetelli R T. “Grassroots Internet celebrity plus live streaming” activating IT-mediated lifestyle marketing services at e-commerce websites. ICIS 2017 Proceedings, 2017: 7.
    [32]
    Cheng C, Hu Y, Lu Y, et al. Everyone can be a star in the digital economy: Quantifying the business value of live streaming technology in online retail. Rochester, NY: SSRN, 2019: 3422615.
    [33]
    Lin J B, Li L, Yan Y M, et al. Understanding Chinese consumer engagement in social commerce: The roles of social support and swift guanxi. Internet Research, 2018, 28 (1): 2–22. doi: 10.1108/IntR-11-2016-0349
    [34]
    Chang H H, Chen S W. The impact of online store environment cues on purchase intention: Trust and perceived risk as a mediator. Online Information Review, 2008, 32 (6): 818–841. doi: 10.1108/14684520810923953
    [35]
    Calder B J, Malthouse E C, Schaedel U. An experimental study of the relationship between online engagement and advertising effectiveness. Journal of Interactive Marketing, 2009, 23 (4): 321–331. doi: 10.1016/j.intmar.2009.07.002
    [36]
    Kim D, Benbasat I. Trust-assuring arguments in B2C e-commerce: Impact of content, source, and price on trust. Journal of Management Information Systems, 2009, 26 (3): 175–206. doi: 10.2753/MIS0742-1222260306
    [37]
    Hong-Kit Yim F, Anderson R E, Swaminathan S. Customer relationship management: Its dimensions and effect on customer outcomes. Journal of Personal Selling & Sales Management, 2004, 24 (4): 263–278.
    [38]
    Awad N F, Ragowsky A. Establishing trust in electronic commerce through online word of mouth: An examination across genders. Journal of Management Information Systems, 2008, 24 (4): 101–121. doi: 10.2753/MIS0742-1222240404
    [39]
    Sparks B A, Browning V. The impact of online reviews on hotel booking intentions and perception of trust. Tourism Management, 2011, 32 (6): 1310–1323. doi: 10.1016/j.tourman.2010.12.011
    [40]
    Mcknight D H, Choudhury V, Kacmar C. The impact of initial consumer trust on intentions to transact with a web site: A trust building model. The Journal of Strategic Information Systems, 2002, 11 (3–4): 297–323. doi: 10.1016/S0963-8687(02)00020-3
    [41]
    Tractinsky N, Jarvenpaa S, Vitale M, et al. Consumer trust in an Internet store: A cross-cultural validation. Journal of Computer-Mediated Communication, 1999, 5 (2): 1–5. doi: 10.1111/j.1083-6101.1999.tb00337.x
    [42]
    Kuan H-H, Bock G-W. Trust transference in brick and click retailers: An investigation of the before-online-visit phase. Information & Management, 2007, 44 (2): 175–187. doi: 10.1016/j.im.2006.12.002
    [43]
    Agag G, El-Masry A A. Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Computers in Human Behavior, 2016, 60: 97–111. doi: 10.1016/j.chb.2016.02.038
    [44]
    Wixom B H, Todd P A. A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 2005, 16 (1): 85–102. doi: 10.1287/isre.1050.0042
    [45]
    Zolfaghar K, Aghaie A. A syntactical approach for interpersonal trust prediction in social web applications: Combining contextual and structural data. Knowledge-Based Systems, 2012, 26: 93–102. doi: 10.1016/j.knosys.2010.10.007
    [46]
    Tu W, Yan C, Yan Y, et al. Who is earning? Understanding and modeling the virtual gifts behavior of users in live streaming economy. In: 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR). IEEE, 2018: 118-123.
    [47]
    Gao Y H. Research on the influence of network anchor characterics in e-commerce livestreaming on consumer's purchase intention. Harbin: Harbin Institute of Technology, 2020.
    [48]
    Rogers E M. Diffusion of Innovations. New York: Simon and Schuster, 2010.
    [49]
    Chao F. Research on the influence of network anchor characteristics on consumer attitudes — based on the regulation of interaction. Hefei: Anhui University, 2018.
    [50]
    Stern B B, Gould S J. The consumer as financial opinion leader. Journal of Retail Banking, 1988, 10 (2): 43–52.
    [51]
    Lyons B, Henderson K. Opinion leadership in a computer-mediated environment. Journal of Consumer Behaviour: An International Research Review, 2005, 4 (5): 319–329. doi: 10.1002/cb.22
    [52]
    Chen Y F, Tsai C W, Lin P H. The influence of perceived risk, shopping value and opinion leader to explore online consumer purchase intention: Using social network analysis. International Journal of E-Adoption, 2017, 9 (2): 31–58. doi: 10.4018/IJEA.2017070103
    [53]
    Raghupathi V, Fogel J. The impact of opinion leadership on purchases through social networking websites. Journal of Theoretical and Applied Electronic Commerce Research, 2015, 10 (3): 18–29. doi: 10.4067/S0718-18762015000300003
    [54]
    Chan K K, Misra S. Characteristics of the opinion leader: A new dimension. Journal of Advertising, 1990, 19 (3): 53–60. doi: 10.1080/00913367.1990.10673192
    [55]
    Li F, Du T C. Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs. Decision Support Systems, 2011, 51 (1): 190–197. doi: 10.1016/j.dss.2010.12.007
    [56]
    Sussman S W, Siegal W S. Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 2003, 14 (1): 47–65. doi: 10.1287/isre.14.1.47.14767
    [57]
    Chung S, Cho H. Fostering parasocial relationships with celebrities on social media: Implications for celebrity endorsement. Psychology & Marketing, 2017, 34 (4): 481–495. doi: 10.1002/mar.21001
    [58]
    Yoo J-W, Jin Y J. Reverse transfer effect of celebrity-product congruence on the celebrity's perceived credibility. Journal of Promotion Management, 2015, 21 (6): 666–684. doi: 10.1080/10496491.2015.1055046
    [59]
    Kamins M A. An investigation into the “match-up” hypothesis in celebrity advertising: When beauty may be only skin deep. Journal of Advertising, 1990, 19 (1): 4–13. doi: 10.1080/00913367.1990.10673175
    [60]
    Choi S M, Rifon N J. It is a match: The impact of congruence between celebrity image and consumer ideal self on endorsement effectiveness. Psychology & Marketing, 2012, 29 (9): 639–650. doi: 10.1002/mar.20550
    [61]
    Thwaites D, Lowe B, Monkhouse L L, et al. The impact of negative publicity on celebrity ad endorsements. Psychology & Marketing, 2012, 29 (9): 663–673. doi: 10.1002/mar.20552
    [62]
    Peterson R A, Kerin R A. The female role in advertisements: Some experimental evidence. Journal of Marketing, 1977, 41 (4): 59–63. doi: 10.1177/002224297704100407
    [63]
    Kamins M A, Gupta K. Congruence between spokesperson and product type: A matchup hypothesis perspective. Psychology & Marketing, 1994, 11 (6): 569–586. doi: 10.1002/mar.4220110605
    [64]
    Sengupta J, Goodstein R C, Boninger D S. All cues are not created equal: Obtaining attitude persistence under low-involvement conditions. Journal of Consumer Research, 1997, 23 (4): 351–361. doi: 10.1086/209488
    [65]
    Kim Y-J, Na J-H. Effects of celebrity athlete endorsement on attitude towards the product: The role of credibility, attractiveness and the concept of congruence. International Journal of Sports Marketing and Sponsorship, 2007, 8 (4): 23–33.
    [66]
    Roy S, Moorthi Y. Investigating endorser personality effects on brand personality: Causation and reverse causation in India. Journal of Brand Strategy, 2012, 1 (2): 164–179.
    [67]
    Ferris K O. The sociology of celebrity. Sociology Compass, 2007, 1 (1): 371–384. doi: 10.1111/j.1751-9020.2007.00019.x
    [68]
    Driessens O. Celebrity capital: redefining celebrity using field theory. Theory and Society, 2013, 42 (5): 543–560. doi: 10.1007/s11186-013-9202-3
    [69]
    Hennig-Thurau T, Walsh G, Walsh G. Electronic word-of-mouth: Motives for and consequences of reading customer articulations on the Internet. International Journal of Electronic Commerce, 2003, 8 (2): 51–74. doi: 10.1080/10864415.2003.11044293
    [70]
    Ba S, Pavlou P A. Evidence of the effect of trust building technology in electronic markets: Price premiums and buyer behavior. MIS Quarterly, 2002: 243–268. doi: 10.2307/4132332
    [71]
    Basuroy S, Chatterjee S, Ravid S A. How critical are critical reviews? The box office effects of film critics, star power, and budgets. Journal of Marketing, 2003, 67 (4): 103–117. doi: 10.1509/jmkg.67.4.103.18692
    [72]
    Racherla P, Friske W. Perceived ‘usefulness’ of online consumer reviews: An exploratory investigation across three services categories. Electronic Commerce Research and Applications, 2012, 11 (6): 548–559. doi: 10.1016/j.elerap.2012.06.003
    [73]
    Schuff D, Mudambi S. What makes a helpful online review? A study of customer reviews on Amazon. com. Social Science Electronic Publishing, 2012, 34 (1): 185–200.
    [74]
    Forman C, Ghose A, Wiesenfeld B. Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information Systems Research, 2008, 19 (3): 291–313. doi: 10.1287/isre.1080.0193
    [75]
    Cheung C M, Thadani D R. The effectiveness of electronic word-of-mouth communication: A literature analysis. BLED 2010 Proceedings, 2010, 23: 329–345.
    [76]
    Yue C. Exploring the relationship between retailer's image and private label brand purchasing—The moderating effect of trust propensity and face consciousness. Nanjing: Nanjing University, 2015.
    [77]
    Herr P M, Kardes F R, Kim J. Effects of word-of-mouth and product-attribute information on persuasion: An accessibility-diagnosticity perspective. Journal of Consumer Research, 1991, 17 (4): 454–462. doi: 10.1086/208570
    [78]
    Mittal V, Ross Jr W T, Baldasare P M. The asymmetric impact of negative and positive attribute-level performance on overall satisfaction and repurchase intentions. Journal of Marketing, 1998, 62 (1): 33–47. doi: 10.1177/002224299806200104
    [79]
    Mizerski R W. An attribution explanation of the disproportionate influence of unfavorable information. Journal of Consumer Research, 1982, 9 (3): 301–310. doi: 10.1086/208925
    [80]
    Chevalier J A, Mayzlin D. The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 2006, 43 (3): 345–354. doi: 10.1509/jmkr.43.3.345
    [81]
    Berger J, Sorensen A T, Rasmussen S J. Positive effects of negative publicity: When negative reviews increase sales. Marketing Science, 2010, 29 (5): 815–827. doi: 10.1287/mksc.1090.0557
    [82]
    Lee J, Park D-H, Han I. The effect of negative online consumer reviews on product attitude: An information processing view. Electronic Commerce Research and Applications, 2008, 7 (3): 341–352. doi: 10.1016/j.elerap.2007.05.004
    [83]
    Zhang L, Ma B, Cartwright D K. The impact of online user reviews on cameras sales. European Journal of Marketing, 2013, 47 (7): 1115–1128. doi: 10.1108/03090561311324237
    [84]
    Duan W, Gu B, Whinston A B. Do online reviews matter?—An empirical investigation of panel data. Decision Support Systems, 2008, 45 (4): 1007–1016. doi: 10.1016/j.dss.2008.04.001
    [85]
    Cheng Y-H, Ho H-Y. Social influence's impact on reader perceptions of online reviews. Journal of Business Research, 2015, 68 (4): 883–887. doi: 10.1016/j.jbusres.2014.11.046
    [86]
    Ghose A, Ipeirotis P G. Designing novel review ranking systems: Predicting the usefulness and impact of reviews. In: Proceedings of the Ninth International Conference on Electronic Commerce. New York: ACM, 2007: 303-310.
    [87]
    Hao Y Y, Ye Q, Li Y J. Research on online impact factors of customer reviews usefulness based on movie reviews data. Journal of Management Sciences in China, 2010, 13 (8): 78–88, 96.
    [88]
    Park D-H, Kim S. The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research and Applications, 2008, 7 (4): 399–410. doi: 10.1016/j.elerap.2007.12.001
    [89]
    Zeithaml V A, Parasuraman A, Malhotra A. Service quality delivery through web sites: A critical review of extant knowledge. Journal of the Academy of Marketing Science, 2002, 30 (4): 362–375. doi: 10.1177/009207002236911
    [90]
    Mathwick C, Malhotra N, Rigdon E. Experiential value: Conceptualization, measurement and application in the catalog and Internet shopping environment. Journal of Retailing, 2001, 77 (1): 39–56. doi: 10.1016/S0022-4359(00)00045-2
    [91]
    Moreau C P, Lehmann D R, Markman A B. Entrenched knowledge structures and consumer response to new products. Journal of Marketing Research, 2001, 38 (1): 14–29. doi: 10.1509/jmkr.38.1.14.18836
    [92]
    Childers T L. Assessment of the psychometric properties of an opinion leadership scale. Journal of Marketing Research, 1986, 23 (2): 184–188. doi: 10.1177/002224378602300211
    [93]
    Sheth J N, Parvatlyar A. Relationship marketing in consumer markets: Antecedents and consequences. Journal of the Academy of Marketing Science, 1995, 23 (4): 255–271. doi: 10.1177/009207039502300405
    [94]
    Boulding W, Kalra A, Staelin R, et al. A dynamic process model of service quality: From expectations to behavioral intentions. Journal of Marketing Research, 1993, 30 (1): 7–27. doi: 10.1177/002224379303000102
    [95]
    Montoya-Weiss M, Voss G B, Grewal D. Online channel use and satisfaction in a multichannel service context. MSI Reports, 2003, 2 (3): 19–35.
    [96]
    Petty R E, Cacioppo J T. The elaboration likelihood model of persuasion. In: Communication and Persuasion. New York: Springer, 1986: 1-24.
    [97]
    Koufaris M, Hampton-Sosa W. The development of initial trust in an online company by new customers. Information & Management, 2004, 41 (3): 377–397. doi: 10.1016/j.im.2003.08.004
    [98]
    Balasubramanian S K, Patwardhan H, Pillai D, et al. Modeling attitude constructs in movie product placements. Journal of Product & Brand Management, 2014, 23 (7): 516–531. doi: 10.1108/JPBM-04-2014-0552
    [99]
    Park D-H, Lee J, Han I. The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal of Electronic Commerce, 2007, 11 (4): 125–148. doi: 10.2753/JEC1086-4415110405
    [100]
    Limayem M, Hirt S G. Force of habit and information systems usage: Theory and initial validation. Journal of the Association for Information Systems, 2003, 4 (1): 3. doi: 10.17705/1jais.00030
    [101]
    Fornell C, Larcker D F. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 1981, 18 (1): 39–50. doi: 10.1177/002224378101800104
    [102]
    Chen M, Chen C C, Sheldon O J. Relaxing moral reasoning to win: How organizational identification relates to unethical pro-organizational behavior. Journal of Applied Psychology, 2016, 101 (8): 1082. doi: 10.1037/apl0000111
    [103]
    Hair J F, Black W C, Babin B J, et al. Multivariate Data Analysis. Upper Saddle River, NJ: Prentice-Hall, 2009.
    [104]
    Hair E, Halle T, Terry-Humen E, et al. Children's school readiness in the ECLS-K: Predictions to academic, health, and social outcomes in first grade. Early Childhood Research Quarterly, 2006, 21 (4): 431–454. doi: 10.1016/j.ecresq.2006.09.005
    [105]
    Marsh H W, Wen Z, Hau K-T. Structural equation models of latent interactions: Evaluation of alternative estimation strategies and indicator construction. Psychological Methods, 2004, 9 (3): 275. doi: 10.1037/1082-989X.9.3.275
    [106]
    Marsh H W, Wen Z, Hau K-T, et al. Structural equation models of latent interaction and quadratic effects. In: Structural Equation Modeling. A Second Course. Greenwich, CT: Information Age Publishing, 2013: 267-308.
    [107]
    Saris W E, Batista-Foguet J M, Coenders G. Selection of indicators for the interaction term in structural equation models with interaction. Quality & Quantity, 2007, 41 (1): 55–72. doi: 10.1007/s11135-005-3956-2
    Recommended articles
    TrendMD
    Volume 52 Issue 2 page: 6
    Cover

    Article Metrics

    Article views (2662) PDF downloads(9411)
    Proportional views

    Copyright © Editorial Office of JUSTC, All Rights Reserved. 皖ICP备05002528号

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return