نقش پلتفرم های استریم های آنلاین مبتنی بر رسانه های اجتماعی بر خرید های بدون برنامه مصرف کنندگان با توجه به ویژگی های منبع ارتباط و محصول
محورهای موضوعی : انتقال فناوري و تجاري‌سازي پژوهش
حسین حاجی بابائی
1
(استادیار، گروه مدیریت بازرگانی، دانشکده ادبیات و علوم انسانی، دانشگاه ملایر، ملایر، ایران)
مهزیار اکبری
2
(دانشجوی دکتری مدیریت بازاریابی، گروه مدیریت بازرگانی، دانشکده ادبیات و علوم انسانی، دانشگاه آزاد اسلامی،واحد همدان، همدان، ایران.)
کلید واژه: خرید های بدون برنامه, استریم آنلاین, ویژگی های منبع اطلاعات,
چکیده مقاله :
رشد و پیشرفت روزافزون فناوری های نوین مبتنی بر ارتباط اینترنتی سبب ایجاد و شکل گیری نوعی کانال ارتباطی بازاریابی به شدت تعاملی در بستر رسانه های اجتماعی گردیده است. استریم آنلاین مبتنی بر رسانه های اجتماعی، پلتفرمی جدید، کارا و جذاب بوده که در سال های اخیر شاهد افزایش میزان استفاده از آن به منظور تبلیغات بوده ایم که این موضوع خود نشانگر ایجاد فرصت هایی بیشمار برای رشد کسب و کارها در بستر این کانالها می باشد. این پژوهش با استفاده از مدل محرک، ارگانیسم و پاسخ ، در پی بررسی عوامل موثر بر خریدهای بدون برنامه افراد در پلتفرم های استریم آنلاین با تمرکز بر ویژگی های استریم کننده و خود محصول می باشد. این پژوهش ،کاربردی، توصیفی و پیمایشی بوده و با استفاده از پرسشنامه آنلاین به جمع آوری اطلاعات ازمخاطبان استریم های آنلاین پرداخته است. نتایج حاصل از مدل سازی معادلات ساختار نشان داد که جذابیت و تخصص استریم کننده (ویژگی های مرتبط با منبع) با تاثیر بر لذت ادراک شده و مواردی مانند سودمندی ادراک شده محصول، راحتی خرید و قیمت محصول (ویژگی های مرتبط با محصول) با تاثیر بر سودمندی ادراک شده، بر قصد خرید بدون برنامه افرد در محیط های استریم آنلاین تاثیر گذار می باشند.
The increasing growth and development of new technologies based on Internet communication has caused the creation and formation of a highly interactive marketing communication channel in the context of social media. Online streaming based on social media is a new, efficient and attractive platform that in recent years we have seen an increase in its use for advertising purposes, which indicates the creation of countless opportunities for business growth in the context of these channels. Using the stimulus, organism, and response model, this research investigates the factors affecting people's impulsive purchases in online streaming platforms, focusing on the features of the streamer and the product itself. This research is applied, descriptive and survey, and collected information from the audience of online streams using an online questionnaire. The results of structural equation modeling showed that the attractiveness and expertise of the streamer (characteristics related to the source) have an effect on the perceived enjoyment, and things such as the perceived usefulness of the product, ease of purchase, and the price of the product (characteristics related to the product) have an effect and they influence the perceived usefulness, and the intention to buy without an individual's plan in online streaming environments
1. Aditya, R., & Wardhana, A. (2016). Pengaruh perceived usefulness dan perceived ease of use terhadap behavioral intention dengan pendekatan Technology Acceptance Model (TAM) pada pengguna Instant Messaging LINE di Indonesia. Jurnal Siasat Bisnis, 20(1), 24-32.
2. Bergkvist, L., & Zhou, K. Q. (2016). Celebrity endorsements: a literature review and research agenda. International Journal of Advertising, 35(4), 642-663.
3. Berne-Manero, C., & Marzo-Navarro, M. (2020). Exploring how influencer and relationship marketing serve corporate sustainability. Sustainability, 12(11), 4392.
4. Cai, J., & Wohn, D. Y. (2019, January). Live streaming commerce: Uses and gratifications approach to understanding consumers’ motivations. In Proceedings of the 52nd Hawaii International Conference on System Sciences.
5. Cai, J., Wohn, D. Y., Mittal, A., & Sureshbabu, D. (2018, June). Utilitarian and hedonic motivations for live streaming shopping. In Proceedings of the 2018 ACM international conference on interactive experiences for TV and online video (pp. 81-88).
6. Carter, S. (2018). “80% of younger shoppers make impulse purchases online-here’s show sites trick you into spending”. Retrieved from https://www.cnbc.com/2018/12/11/80percent-of-young-people-made-an-impulse-buy-online-this-yearheres-why.html.
7. 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.
8. 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.
9. Chen, C. C., & Lin, Y. C. (2018). What drives live-stream usage intention? The perspectives of flow, entertainment, social interaction, and endorsement. Telematics and Informatics, 35(1), 293-303.
10. Chen, C. C., & Yao, J. Y. (2018). What drives impulse buying behaviors in a mobile auction? The perspective of the Stimulus-Organism-Response model. Telematics and Informatics, 35(5), 1249-1262.
11. Chen, J. V., Su, B. C., & Widjaja, A. E. (2016). Facebook C2C social commerce: A study of online impulse buying. Decision Support Systems, 83, 57-69.
12. Cheng, H. H. (2020, July). The Effects of Product Stimuli and Social Stimuli on Online Impulse Buying in Live Streams. In Proceedings of the 2020 International Conference on Management of e-Commerce and e-Government (pp. 31-35).
13. De Veirman, M., Cauberghe, V., & Hudders, L. (2017). Marketing through Instagram influencers: the impact of number of followers and product divergence on brand attitude. International journal of advertising, 36(5), 798-828.
14. Fu, S., Yan, Q., & Feng, G. C. (2018). Who will attract you? Similarity effect among users on online purchase intention of movie tickets in the social shopping context. International Journal of Information Management, 40, 88-102.
15. Gao, X., Xu, X. Y., Tayyab, S. M. U., & Li, Q. (2021). How the live streaming commerce viewers process the persuasive message: An ELM perspective and the moderating effect of mindfulness. Electronic Commerce Research and Applications, 49, 101087.
16. Gong, X., Ye, Z., Liu, K., & Wu, N. (2020). The effects of live platform exterior design on sustainable impulse buying: exploring the mechanisms of self-efficacy and psychological ownership. Sustainability, 12(6), 2406.
17. Gupta, S., & Kim, H. W. (2010). Value‐driven Internet shopping: The mental accounting theory perspective. Psychology & Marketing, 27(1), 13-35.
18. Hasim, M. A., Hassan, S., Ishak, M. F., & Razak, A. A. (2020). Factors influencing gen-Y in Malaysia to purchase impulsively: A mediating effect of perceived enjoyment. International Journal of Innovation, Creativity and Change, 11(5), 385-396.
19. Hou, F., Guan, Z., Li, B., & Chong, A. Y. L. (2019). Factors influencing people’s continuous watching intention and consumption intention in live streaming: evidence from China. Internet Research.
20. 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.
21. Huang, Y., & Suo, L. (2021). Factors Affecting Chinese Consumers’ Impulse Buying Decision of Live Streaming E-Commerce. Asian Social Science, 17(5).
22. Hussein, L. A., Baharudin, A. S., Jayaraman, K., & Kiumarsi, S. H. A. I. A. N. (2019). B2B e-commerce technology factors with mediating effect perceived usefulness in Jordanian manufacturing SMES. Journal of Engineering Science and Technology, 14(1), 411-429.
23. Ismagilova, E., Slade, E. L., Rana, N. P., & Dwivedi, Y. K. (2020). The effect of electronic word of mouth communications on intention to buy: A meta-analysis. Information Systems Frontiers, 22(5), 1203-1226.
24. Kang, K., Lu, J., Guo, L., & Li, W. (2021). The dynamic effect of interactivity on customer engagement behavior through tie strength: Evidence from live streaming commerce platforms. International Journal of Information Management, 56, 102251.
25. Khan, N., Hui, L. H., Chen, T. B., & Hoe, H. Y. (2016). Impulse buying behaviour of generation Y in fashion retail. International Journal of Business and Management, 11(1), 144.
26. Kim, A. J., & Johnson, K. K. (2016). Power of consumers using social media: Examining the influences of brand-related user-generated content on Facebook. Computers in Human Behavior, 58, 98-108.
27. Kim, J. H., & Lennon, S. (2012). Music and amount of information: do they matter in an online apparel setting?. The International Review of Retail, Distribution and Consumer Research, 22(1), 55-82.
28. 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.
29. Lee, C. H., Chen, C. W. D., Huang, S. F., Chang, Y. T., & Demirci, S. (2021). Exploring consumers’ impulse buying behavior on online apparel websites: An empirical investigation on consumer perceptions. International Journal of Electronic Commerce Studies, 12(1).
30. Lerner, J. S., Li, Y., Valdesolo, P., & Kassam, K. S. (2015). Emotion and decision making. Annual review of psychology, 66, 799-823.
31. Li, G., Zhang, R., & Wang, C. (2015). The role of product originality, usefulness and motivated consumer innovativeness in new product adoption intentions. Journal of Product Innovation Management, 32(2), 214-223.
32. Li, H. M., & Cui, Y. Q. (2010). Research on the influence factors of consumer behavior based on context theory. Journal of Business Research, 3, 163-166.
33. Li, X. X., Yu, Y. B., & Liu, Z. Z. (2018). Study on the relationship between price promotion and impulse purchase of customers. Journal of Northeastern University (Social Science Edition), 108(2), 33 -39.
34. Li, Y., & Shu, H. (2021, July). Research on Online Interaction and Consumer Impulsive Buying Behavior in Live Shopping Platform Based on the Structural Equation Model. In 2021 International Conference on Management Science and Software Engineering (ICMSSE) (pp. 72-76). IEEE.
35. Li, Y., Li, X., & Cai, J. (2021). How attachment affects user stickiness on live streaming platforms: A socio-technical approach perspective. Journal of Retailing and Consumer Services, 60, 102478.
36. Lin, S. W., & Lo, L. Y. S. (2016). Evoking online consumer impulse buying through virtual layout schemes. Behaviour & Information Technology, 35(1), 38-56.
37. Liu, G. H., Sun, M., & Lee, N. C. A. (2021, January). How can live streamers enhance viewer engagement in eCommerce streaming?. In Proceedings of the 54th Hawaii International Conference on System Sciences (p. 3079).
38. Lo, L. Y. S., Lin, S. W., & Hsu, L. Y. (2016). Motivation for online impulse buying: A two-factor theory perspective. International Journal of Information Management, 36(5), 759-772.
39. 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.
40. Luo, H., Cheng, S., & Zhou, W. (2021, March). The Factors Influencing Sales in Online Celebrities' Live Streaming. In 2021 IEEE International Conference on Information Communication and Software Engineering (ICICSE) (pp. 233-237). IEEE.
41. 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.
42. NGUYEN, O. T. (2020). Factors affecting the intention to use digital banking in Vietnam. The Journal of Asian Finance, Economics, and Business, 7(3), 303-310.
43. Ozturk, A. B., Nusair, K., Okumus, F., & Hua, N. (2016). The role of utilitarian and hedonic values on users’ continued usage intention in a mobile hotel booking environment. International Journal of Hospitality Management, 57, 106-115.
44. Park, E. J., Kim, E. Y., Funches, V. M., & Foxx, W. (2012). Apparel product attributes, web browsing, and e-impulse buying on shopping websites. Journal of Business Research, 65(11), 1583-1589.
45. Park, H. J., & Lin, L. M. (2020). 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, 52, 101934.
46. Parsad, C., Prashar, S., & Vijay, T. S. (2019). Comparing between product-specific and general impulse buying tendency: does shoppers’ personality influence their impulse buying tendency?. Asian Academy of Management Journal, 24(2).
47. Peng, L., Xia, X., & Su, X. (2020, November). The Effect of Consumer’s Loneliness on Impulse Buying in the Internet era: A Model Based on Para-social Interaction. In 2020 2nd International Conference on Economic Management and Model Engineering (ICEMME) (pp. 843-848). IEEE.
48. Saad, M., & Metawie, M. (2015). Store environment, personality factors and impulse buying behavior in Egypt: The mediating roles of shop enjoyment and impulse buying tendencies. Journal of Business and Management Sciences, 3(2), 69-77.
49. Shah, A. M., Yan, X., Shah, S. A. A., & Ali, M. (2020). Customers' perceived value and dining choice through mobile apps in Indonesia. Asia Pacific Journal of Marketing and Logistics.
50. Singh, P., Keswani, S., Singh, S., & Sharma, S. (2018). A study of adoption behavior for online shopping: an extension of TAM model. IJASSH.
51. Sjöblom, M., & Hamari, J. (2017). Why do people watch others play video games? An empirical study on the motivations of Twitch users. Computers in human behavior, 75, 985-996.
52. So, K. K. F., Kim, H., & Oh, H. (2020). What makes Airbnb experiences enjoyable? The effects of environmental stimuli on perceived enjoyment and repurchase intention. Journal of Travel Research, 0047287520921241.
53. Song, S., Yao, X., & Wen, N. (2021). What motivates Chinese consumers to avoid information about the COVID-19 pandemic?: The perspective of the stimulus-organism-response model. Information Processing & Management, 58(1), 102407.
54. Suleman, D. (2018). Faktor penentu keputusan konsumen Indonesia memilih tempat belanja disebuah e-commerce (Theory of Planned Behavior). Jurnal Doktor Manajemen, 1, 1-9.
55. Sun, Y., Shao, X., Li, X., Guo, Y., & Nie, K. (2019). How live streaming influences purchase intentions in social commerce: An IT affordance perspective. Electronic Commerce Research and Applications, 37, 100886.
56. Susanto, T. D., & Aljoza, M. (2015). Individual acceptance of e-Government services in a developing country: Dimensions of perceived usefulness and perceived ease of use and the importance of trust and social influence. Procedia Computer Science, 72, 622-629.
57. Syci, V. (2021). How Live Shopping Influences Impulse Buying Desire: An SOR Model Perspective.
58. WINARNO, W. A., MAS’UD, I., & PALUPI, T. W. (2021). Perceived Enjoyment, Application Self-efficacy, and Subjective Norms as Determinants of Behavior Intention in Using OVO Applications. The Journal of Asian Finance, Economics, and Business, 8(2), 1189-1200.
59. Winata, L., Permana, D., No, J. M. S., & Indonesia, J. B. (2020). The effect of electronic coupon value to perceived usefulness and perceived ease-of-use and its implication to behavioral intention to use server-based electronic money. International Journal of Innovative Science and Research Technology, 5(1), 147-158.
60. Wirtz, B. W., & Göttel, V. (2016). Technology acceptance in social media: Review, synthesis and directions for future empirical research. Journal of Electronic Commerce Research, 17(2), 97.
61. 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.
62. Wongkitrungrueng, A., Dehouche, N., & Assarut, N. (2020). Live streaming commerce from the sellers’ perspective: implications for online relationship marketing. Journal of Marketing Management, 36(5-6), 488-518.
63. Wu, L. J. (2012). Based on S - O - R model of apparel online purchase intention theory framework. Modern Science and Technology of Silk, 27(5), 190-194.
64. Wu, L., Chiu, M. L., & Chen, K. W. (2020). Defining the determinants of online impulse buying through a shopping process of integrating perceived risk, expectation-confirmation model, and flow theory issues. International Journal of Information Management, 52, 102099.
65. Wu, Y. L., & Li, E. Y. (2018). Marketing mix, customer value, and customer loyalty in social commerce: A stimulus-organism-response perspective. Internet Research.
66. Xiang, L., Zheng, X., Lee, M. K., & 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.
67. Xiao, M., Wang, R., & Chan-Olmsted, S. (2018). Factors affecting YouTube influencer marketing credibility: a heuristic-systematic model. Journal of media business studies, 15(3), 188-213.
68. Xu, X., Wu, J. H., & Li, Q. (2020). What drives consumer shopping behavior in live streaming commerce?. Journal of Electronic Commerce Research, 21(3), 144-167.
69. 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.
70. Yanev, V. (2021, Dec 7). “37+ Live Streaming Statistics Every Marketer Should Keep in Mind in 2021”. Retrieved from https://techjury.net/blog/live-streaming-statistics/.
71. Yi, S., & Jai, T. (2020). Impacts of consumers’ beliefs, desires and emotions on their impulse buying behavior: application of an integrated model of belief-desire theory of emotion. Journal of Hospitality Marketing & Management, 29(6), 662-681.
72. Zahari, N. H. M., Azmi, N. N. N., Kamar, W. N. I. W. A., & Othman, M. S. (2021). Impact of Live Streaming on Social Media on Impulse Buying. Asian Journal of Behavioural Sciences, 3(1), 13-23.
73. Zhang, M., Qin, F., Wang, G. A., & Luo, C. (2020). The impact of live video streaming on online purchase intention. The Service Industries Journal, 40(9-10), 656-681.
74. Zhao, Q., Chen, C. D., Cheng, H. W., & Wang, J. L. (2018). Determinants of live streamers’ continuance broadcasting intentions on Twitch: A self-determination theory perspective. Telematics and Informatics, 35(2), 406-420.
75. Zheng, X., Men, J., Yang, F., & Gong, X. (2019). Understanding impulse buying in mobile commerce: An investigation into hedonic and utilitarian browsing. International Journal of Information Management, 48, 151-160.
76. Zhou, R., & Feng, C. (2017). Difference between leisure and work contexts: The roles of perceived enjoyment and perceived usefulness in predicting mobile video calling use acceptance. Frontiers in psychology, 8, 350.
77. Zhu, Y. Q., Amelina, D., & Yen, D. C. (2020). Celebrity endorsement and impulsive buying intentions in social commerce-The case of Instagram in Indonesia: Celebrity Endorsement. Journal of Electronic Commerce in Organizations (JECO), 18(1), 1-17.