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Outline

Title
Abstract
Introduction
Theoretical Background 2.1. Live Streaming Sales
Conceptual Model and Hypotheses
Research Methodology
Sample and Data Collection Procedure
Testing for Common Method Bias
Data Analysis and Results
Structural Model Evaluation and Hypothesis Test
Discussion and Implications
Managerial Implications
Limitations and Further Research Avenues
References
All Topics
Computer Science
Information Systems

How Streamers Foster Consumer Stickiness in Live Streaming Sales

Profile image of Yongbing JiaoYongbing Jiao

Journal of Theoretical and Applied Electronic Commerce Research

https://doi.org/10.3390/JTAER18030061
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21 pages

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Abstract

Streamers play a critical role in fostering consumer stickiness in live streaming sales. Thus, it is necessary to make clear the mechanism of how streamers influence consumer stickiness. Based upon the theories of social support, social identification and consumer stickiness, this study investigates the effects of consumers’ perceived emotional support, informational support, financial support, affectionate support and social network support from streamers on consumer–streamer identification, which in turn affects consumer–streamer stickiness and consumer–brand stickiness in live streaming sales settings. Based on the structural equation modeling analysis of 280 online questionnaires, using the software of Smart PLS 3.0, the results demonstrate that perceived emotional support, perceived informational support, perceived financial support and perceived affectionate support enhance consumer–streamer identification, thereby enhancing consumer–streamer stickiness and consumer–brand stic...

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References (71)

  1. Wongkitrungrueng, A.; Dehouche, N.; Assarut, N. Live streaming commerce from the sellers' perspective: Implications for online relationship marketing. J. Mark. Manag. 2020, 36, 488-518. [CrossRef]
  2. Wu, C.-W.; Shieh, M.-D.; Lien, J.-J.J.; Yang, J.-F.; Chu, W.-T.; Huang, T.-H.; Hsieh, H.-C.; Chiu, H.-T.; Tu, K.-C.; Chen, Y.-T.; et al. Enhancing Fan Engagement in a 5G Stadium with AI-Based Technologies and Live Streaming. IEEE Syst. J. 2022, 16, 3169553.
  3. Fan, T.; Wang, L.; Song, Y. Impact of live commerce spillover effect on supply chain decisions. Ind. Manag. Data Syst. 2022, 122, 1109-1127. [CrossRef]
  4. Xue, J.; Liu, M.T. Investigating the live streaming sales from the perspective of the ecosystem: The structures, processes and value flow. Asia Pac. J. Mark. Logist. 2023, 35, 1157-1186. [CrossRef]
  5. Sun, Y.; Shao, X.; Li, X.; Guo, Y.; Nie, K. How Live Streaming Influences Purchase Intentions in Social Commerce: An IT Affordance Perspective. Electron. Commer. Res. Appl. 2019, 37, 100886. [CrossRef]
  6. Kim, M.; Kim, H.-M. What online game spectators want from their twitch streamers: Flow and well-being perspectives. J. Retail. Consum. Serv. 2022, 66, 102951. [CrossRef]
  7. Li, Y.; Li, X.; Cai, J. How attachment affects user stickiness on live streaming platforms: A socio-technical approach perspective. J. Retail. Consum. Serv. 2021, 60, 102478. [CrossRef]
  8. Törhönen, M.; Giertz, J.; Weiger, W.H.; Hamari, J. Streamers: The new wave of digital entrepreneurship? Extant corpus and research agenda. Electron. Commer. Res. Appl. 2021, 46, 101027. [CrossRef]
  9. Zhang, X.; Cheng, X.; Huang, X. "Oh, My God, Buy It!" Investigating Impulse Buying Behavior in Live Streaming Commerce. Int. J. Hum.-Comput. Int. 2023, 39, 2436-2449. [CrossRef]
  10. Hu, M.; Zhang, M.; Wang, Y. Why do audiences choose to keep watching on live video streaming platforms? an explanation of dual identification framework. Comput. Hum. Behav. 2017, 75, 594-606. [CrossRef]
  11. Friedrich, T.; Schlauderer, S.; Overhage, S. The Impact of Social Commerce Feature Richness on Website Stickiness through Cognitive and Affective Factors: An Experimental Study. Electron. Commer. Res. Appl. 2019, 36, 100861. [CrossRef]
  12. Hu, L.; Min, Q.; Han, S.; Liu, Z. Understanding Followers' Stickiness to Digital Influencers: The Effect of Psychological Responses. Int. J. Inf. Manag. 2020, 54, 102169. [CrossRef]
  13. Xu, F.; Qi, Y.; Li, X. What affects the user stickiness of the mainstream media websites in China? Electron. Commer. Res. Appl. 2018, 29, 124-132. [CrossRef]
  14. Hsu, C.L.; Liao, Y.C. Exploring the Linkages between Perceived Information Accessibility and Microblog Stickiness: The Moderating Role of a Sense of Community. Inf. Manag. 2014, 51, 833-844. [CrossRef]
  15. 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. J. Retail. Consum. Serv. 2020, 52, 101934. [CrossRef]
  16. Rosenbaum, M.S.; Massiah, C.A. When Customers Receive Support from Other Customers: Exploring the Influence of Intercus- tomer Social Support on Customer Voluntary Performance. J. Serv. Res. 2007, 9, 257-270. [CrossRef]
  17. Zhu, D.; Sun, H.; Chang, Y. Effect of Social Support on Customer Satisfaction and Citizenship Behavior in Online Brand Communities: The Moderating Role of Support Source. J. Retail. Consum. Serv. 2016, 31, 287-293. [CrossRef]
  18. Wongkitrungrueng, A.; Assarut, N. The role of live streaming in building consumer trust and engagement with social commerce sellers. J. Bus. Res. 2020, 117, 543-556. [CrossRef]
  19. Xue, J.L.; Liang, X.J.; Xie, T.; Wang, H.Z. See now, act now: How to interact with customers to enhance social commerce engagement? Inf. Manag. 2020, 57, 103324. [CrossRef]
  20. Graupensperger, S.; Benson, A.J.; Kilmer, J.R.; Evans, M.B. Social (Un)distancing: Teammate Interactions, Athletic Identity, and Mental Health of Student-Athletes During the COVID-19 Pandemic. J. Adolesc. Health 2020, 67, 662-670. [CrossRef]
  21. Hagiwara, G.; Tsunokawa, T.; Iwatsuki, T.; Shimozono, H.; Kawazura, T. Relationships among student-athletes' identity, mental health, and social support in Japanese student-athletes during the COVID-19 pandemic. Int. J. Environ. Res. Public Health 2021, 18, 7032. [CrossRef] [PubMed]
  22. Shehadeh, N.; Rubens, M.; Attonito, J.; Jennings, T. Social Support and Its Impact on Ethnic Identity and HIV Risk among Migrant Workers. J. Racial Ethn. Health Disparities 2018, 5, 96-103. [CrossRef] [PubMed]
  23. Toyoshima, A.; Nakahara, J. The Effects of Familial Social Support Relationships on Identity Meaning in Older Adults: A Longitudinal Investigation. Front. Psychol. 2021, 12, 650051. [CrossRef]
  24. Liang, T.P.; Ho, Y.T.; Li, Y.W.; Turban, E. What drives social commerce: The role of social support and relationship quality. Int. J. Electron. Commer. 2012, 16, 69-90. [CrossRef]
  25. Hu, M.; Chaudhry, S.S. Enhancing consumer engagement in e-commerce live streaming via relational bonds. Internet Res. 2021, 30, 1019-1041. [CrossRef]
  26. Xu, P.; Cui, B.J.; Lyu, B. Influence of Streamer's Social Capital on Purchase Intention in Live Streaming E-Commerce. Front. Psychol. 2022, 12, 748172. [CrossRef] [PubMed]
  27. Zhang, M.; Qin, F.; Wang, G.A.; Luo, C. The impact of live video streaming on online purchase intention. Serv. Ind. J. 2020, 40, 656-681. [CrossRef]
  28. Gao, X.; Xu, X.-Y.; Tayyab, S.M.U.; Li, Q. How the live streaming commerce viewers process the persuasive message: An ELM perspective and the moderating effect of mindfulness. Electron. Commer. Res. Appl. 2021, 49, 101087. [CrossRef]
  29. McLaughlin, C.; Wohn, D.Y. Predictors of parasocial interaction and relationships in live streaming. Convergence 2021, 27, 1714-1734. [CrossRef]
  30. Rungruangjit, W. What drives Taobao live streaming commerce? The role of parasocial relationships, congruence and source credibility in Chinese consumers' purchase intentions. Heliyon 2022, 8, e09676. [CrossRef]
  31. Liao, J.; Chen, K.; Qi, J.; Li, J.; Yu, I.Y. Creating immersive and parasocial live shopping experience for viewers: The role of streamers' interactional communication style. J. Res. Interact. Mark. 2023, 17, 140-155. [CrossRef]
  32. Alutaybi, A.; Al-Thani, D.; McAlaney, J.; Ali, R. Combating Fear of Missing Out (FoMO) on Social Media: The FoMO-R Method. Int. J. Environ. Res. Public Health 2020, 17, 6128. [CrossRef]
  33. Durao, M.; Etchezahar, E.; Genol, M.A.A.; Muller, M. Fear of Missing Out, Emotional Intelligence and Attachment in Older Adults in Argentina. J. Intell. 2023, 11, 22. [CrossRef]
  34. Leung, F.F.; Gu, F.F.; Palmatier, R.W. Online influencer marketing. J. Acad. Mark. Sci. 2022, 50, 226-251. [CrossRef]
  35. Dolega, L.; Rowe, F.; Branagan, E. Going digital? The impact of social media marketing on retail website traffic, orders and sales. J. Retail. Consum. Serv. 2021, 60, 102501. [CrossRef]
  36. Lee, Y.; Kim, D.-E. The influence of technological interactivity and media sociability on sport consumer value co-creation behaviors via collective efficacy and collective intelligence. Int. J. Sport. Mark. Spons. 2022, 23, 18-40. [CrossRef]
  37. Sherbourne, C.D.; Stewart, A.L. The MOS social support survey. Soc. Sci. Med. 1991, 32, 705-714. [CrossRef]
  38. Wohn, D.Y.; Freeman, G.; McLaughlin, C. Explaining viewers' emotional, instrumental, and financial support provision for live streamers. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal, QC, Canada, 21-26 April 2018.
  39. Tang, J.; Chen, M.; Yang, C.; Chung, T.; Lee, Y. Personality traits, interpersonal relationships, online social support, and Facebook addiction. Telemat. Inform. 2016, 33, 102-108. [CrossRef]
  40. Jiao, Y.; Jo, M.-S.; Sarigollü, E. Social Value and Content Value in Social Media: Two Paths to Psychological Well-being. J. Organ. Comput. Electron. Commer. 2017, 27, 3-24. [CrossRef]
  41. Jiao, Y.; Ertz, M.; Jo, M.-S.; Sarigollü, E. Social value, content value, and brand equity in social media brand communities: A comparison of Chinese and US consumers. Int. Mark. Rev. 2018, 35, 18-41. [CrossRef]
  42. Hogg, M.A.; Abrams, D. Social Identifications: A Social Psychology of Intergroup Relations and Group Processes, 1st ed.; Routledge: London, UK, 1988; pp. 6-56.
  43. Hogg, M.A.; Turner, J.C. Interpersonal attraction, social identification and psychological group formation. Eur. J. Soc. Psychol. 1985, 15, 51-66. [CrossRef]
  44. Stets, J.E.; Burke, P.J. Identity theory and social identity theory. Soc. Psychol. Q. 2000, 63, 224-237. [CrossRef]
  45. Ashforth, B.E.; Mael, F. Social identity theory and the organization. Acad. Manag. Rev. 1989, 14, 20-39. [CrossRef]
  46. Papista, E.; Dimitriadis, S. Exploring consumer brand relationship quality and identification: Qualitative evidence from cosmetics brands. Qual. Mark. Res. 2012, 15, 33-56. [CrossRef]
  47. Black, H.G.; Jeseo, V.; Vincent, L.H. Promoting customer engagement in service settings through identification. J. Serv. Mark. 2021, 35, 473-486. [CrossRef]
  48. Kaufmann, H.R.; Loureiro, S.M.C.; Basile, G.; Vrontis, D. The increasing dynamics between consumers, social groups and brands. Qual. Mark. Res. 2012, 15, 404-419. [CrossRef]
  49. Millán, Á.; Díaz, E. Analysis of consumers' response to brand community integration and brand identification. J. Brand Manag. 2014, 21, 254-272. [CrossRef]
  50. Ahearne, M.; Bhattacharya, C.B.; Gruen, T. Antecedents and consequences of customer-company identification: Expanding the role of relationship marketing. J. Appl. Psychol. 2005, 90, 574-585. [CrossRef] [PubMed]
  51. Li, D.; Browne, G.J.; Wetherbe, J.C. Why Do Internet Users Stick with a Specific Web Site? A Relationship Perspective. Int. J. Electron. Commer. 2006, 10, 105-141. [CrossRef]
  52. Lin, J.C.-C. Online Stickiness: Its Antecedents and Effect on Purchasing Intention. Behav. Inf. Technol. 2007, 26, 507-516. [CrossRef]
  53. Zott, C.; Amit, R.; Donlevy, J. Strategies for Value Creation in E-commerce: Best Practice in Europe. Eur. Manag. J. 2000, 18, 463-475. [CrossRef]
  54. Lien, C.-H.; Cao, Y.; Zhou, X. Service Quality, Satisfaction, Stickiness, and Usage Intentions: An Exploratory Evaluation in the Context of WeChat services. Comput. Hum. Behav. 2017, 68, 403-410. [CrossRef]
  55. Chiang, H.-S.; Hsiao, K.-L. Youtube stickiness: The needs, personal, and environmental perspective. Internet Res. 2015, 25, 85-106.
  56. Huang, J.W.; Lin, C.P. To Stick or Not to Stick: The Social Response Theory in the Development of Continuance Intention from Organizational Cross-level Perspective. Comput. Hum. Behav. 2011, 27, 1963-1973. [CrossRef]
  57. Hsiao, Y.-H.; Chen, L.-F.; Chang, C.-C.; Chiu, F.-H. Configurational path to customer satisfaction and stickiness for a restaurant chain using fuzzy set qualitative comparative analysis. J. Bus. Res. 2016, 69, 2939-2949. [CrossRef]
  58. Wang, W.-T.; Wang, Y.-S.; Liu, E.-R. The stickiness intention of group-buying websites: The integration of the commitment-trust theory and e-commerce success model. Inf. Manag. 2016, 53, 625-642. [CrossRef]
  59. Zhang, M.; Guo, L.; Hu, M.; Liu, W. Influence of customer engagement with company social networks on stickiness: Mediating effect of customer value creation. Int. J. Inf. Manag. 2017, 37, 229-240. [CrossRef]
  60. Rather, R.A.; Tehseen, S.; Parrey, S.H. Promoting customer brand engagement and brand loyalty through customer brand identification and value congruity. Span. J. Mark.-ESIC 2018, 22, 321-339. [CrossRef]
  61. Ladhari, R.; Massa, E.; Skandrani, H. Youtube vloggers popularity and influence: The roles of homophily, emotional attachment, and expertise. J. Retail. Consum. Serv. 2020, 54, 102027. [CrossRef]
  62. Podsakoff, P.M.; MacKenzie, S.B.; Podsakoff, N.P. Sources of method bias in social science research and recommendations on how to control it. Annu. Rev. Psychol. 2012, 63, 539-569. [CrossRef] [PubMed]
  63. Kock, F.; Berbekova, A.; Assaf, A.G. Understanding and managing the threat of common method bias: Detection, prevention and control. Tour. Manag. 2021, 86, 104330. [CrossRef]
  64. Podsakoff, P.M.; MacKenzie, S.B.; Lee, J.Y.; Podsakoff, N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psychol. 2003, 88, 879-903. [CrossRef] [PubMed]
  65. Fuller, C.M.; Simmering, M.J.; Atinc, G.; Atinc, Y.; Babin, B.J. Common methods variance detection in business research. J. Bus. Res. 2016, 69, 3192-3198. [CrossRef]
  66. Hair, J.F., Jr.; Hult, G.T.M.; Ringle, C.M.; Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd ed.; Sage: Thousand Oaks, CA, USA; Los Angeles, CA, USA, 2017; pp. 81-190.
  67. Hair, J.F., Jr.; Howard, M.C.; Nitzl, C. Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. J. Bus. Res. 2020, 109, 101-110. [CrossRef]
  68. Guha, A.; Bressgott, T.; Grewal, D.; Mahr, D.; Wetzels, M.; Schweiger, E. How artificiality and intelligence affect voice assistant evaluations. J. Acad. Mark. Sci. 2022. [CrossRef]
  69. Rigdon, E.E. Choosing PLS path modeling as analytical method in European management research: A realist perspective. Eur. Manag. J. 2016, 34, 598-605. [CrossRef]
  70. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39-50. [CrossRef]
  71. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

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Religion, Education, and Social Laa Roiba Journal/Reslaj, 2024

Researchers also believe that Live Streaming-Interaction on TikTok can increase purchasing decisions because more and more people know about brand types, brand quality, brand suitability, brand identity, and so on. Therefore, this research aims to analyze the influence of Live-Streamer Interaction on Purchasing Decisions. Different from previous research, this research adds the Brand Love variable as a moderating variable. This research is quantitative research with an explanatory approach. The data used in this research was obtained from distributing online questionnaires to 350 TikTok shop sellers and buyers on certain dates. These data can be called primary data. These data were analyzed using the smart PLS 4.0 analysis tool. The result in this article show the Live-Streaming Interaction variable can have a positive relationship and a significant influence on purchasing decisions because the P-Values value is positive and is below the significance level of 0.05, namely 0.004. Otherwise, the Brand Love variable can moderate the influence of the Live-Streamer Interaction variable on the Purchase Decision variable because the P-Values results show a positive direction and are below 0.05. Thus the first and second hypotheses in this research can be proven and accepted.

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The Influence of Live-Streamers on Somethinc’s Purchase Intention at Tiktok Shop Mediated by Consumer Trust
Liza Dian

Jurnal Informatika Ekonomi Bisnis

The trend that is happening nowadays is online transactions through live-streaming or what is commonly known as live-streaming shopping. This study aims to determine the effect of live-streamers on purchase intention with consumer trust as an intervening variable. This research uses descriptive quantitative method. The population in this study are state university students who use social media TikTok in Malang City. The sample in this study amounted to 195 respondents, determined using a purposive sampling technique with criteria such as students aged 18-28 years who are TikTok social media users in Malang City who have watched live-streaming on the official TikTok account of @Somethincofficial, and have ever used TikTok Shop feature. The data analysis technique used in this study is Structural Equation Modeling (SEM) Partial Least Square (PLS) or SEM-PLS with the help of SmartPLS 3.0 software. The results of this study indicate that live-streamers have a positive and significant ef...

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Will you purchase what I recommend? The role of interaction orientation, parasocial relation, and product involvement
MAMAN SURATMAN

Asian Management and Business Review, 2024

In recent years, sales in online platforms have received huge attention from generation Z in Indonesia, along with live streaming business model which has undergone rapid development in recent years. Although the way live streaming with consumers has been known as the key to influence consumer behavior, only a few research has studied the style of streaming communication in affecting purchase intentions. Based on the social influence theory, this study attempts to examine the influence of interaction orientation, parasocial relation, and digital influencer credibility on purchase intention. In addition, the present study also investigates the role of product involvement advertised by streamers as moderator. The quantitative approach with the survey is used through samples of 200 respondents selected by purposive sampling. The data is collected online through disseminating questionnaires using Google Form, which is then analyzed using SEM-PLS technique. The findings indicate that interaction orientation positively influences purchase intention and parasocial relation, while parasocial relation positively influences digital influencer credibility, and digital influencer credibility positively influences purchase intention. In addition, product involvement has a moderating role that can strengthen the influence of interaction orientation and purchase intention. This study provides implications for how an interaction can be delivered online and how the involvement of a credible influencer can affect purchase intention.

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THE IMPACT OF SOCIAL PRESENCE IN THE LIVESTREAM ENVIRONMENT ON CUSTOMERS' IMPULSE BUYING BEHAVIOR IN VIETNAM
IJARW Research Publication

IJARW, 2024

This study examines the impact of factors related to the livestream environment, including the presence of streamers, viewers, and products, on customers' impulse buying behavior in Vietnam. Survey results from 478 online shoppers on platforms such as TikTok, Facebook, and Shopee indicate that factors like direct interaction, social presence, and product appeal positively influence affective reactions, thereby driving impulse buying urges and behaviors. The research also suggests solutions for e-commerce businesses to improve customer experience and optimize sales effectiveness through livestreaming.

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How can live streamers enhance viewer engagement in eCommerce streaming?
gloria Liu

Proceedings of the 54th Hawaii International Conference on System Sciences

eCommerce live streaming has enabled new forms of customer engagement, where live streamers, viewers and platform owners engage each other in real time to hawk and trade goods and services. Central to live streaming sales are live streamers. It is therefore critical to discover techniques to maximize live streamers' engagement with viewers. Based on the intimacy theory, we propose the perceived intimacy live streamers created improves online engagement with viewers. Our survey results suggest streamers' authenticity, attitudinal similarity and customer response capability enhance intimacy perceived by online viewers, leading to viewers' online engagement. Contributions of our study are discussed.

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