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Will you buy my books? Investigating influential factors for the sales of user-generated e-books on a social commerce platform

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Abstract

In contrast to traditional e-commerce platforms, social commerce platforms offer users opportunities to communicate and profit, instead of merely rating and purchasing products. This study examines a sample of 1859 user-generated (UG) e-books from a popular Chinese social commerce website to identify the factors that impact consumers to purchase UG products. The network analysis results reveal that UG products on social commerce platforms exhibit varying sales patterns and form three distinct communities, comprising 1393, 291, and 175 e-books respectively. By employing the Elaboration Likelihood Model (ELM), this study examines the impact of certain variables on UG product sales within three communities. These variables encompass central route factors such as product rating and rating numbers, peripheral route factors like follower adoption, and the elaboration likelihood encompassing ability (the proportion of experienced purchasers) and motivation (the proportion of purchased transactions, serving as an indicator of the gifted marketing strategies). The findings of this study have implications for the design and improvement of UG product marketing in social commerce platforms.

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References

  1. Agmeka F, Wathoni RN, Santoso AS (2019) The influence of discount framing towards brand reputation and brand image on purchase intention and actual behaviour in e-commerce. In: Procedia computer science, The fifth information systems international conference, Surabaya, Indonesia, vol 161, pp 851–858. https://doi.org/10.1016/j.procs.2019.11.192)

  2. Allison TH, Davis BC, Webb JW, Short JC (2017) Persuasion in crowdfunding: an elaboration likelihood model of crowdfunding performance. J Bus Ventur 32(6):707–725. https://doi.org/10.1016/j.jbusvent.2017.09.002

    Article  Google Scholar 

  3. Bai Y, Yao Z, Dou Y-F (2015) Effect of social commerce factors on user purchase behavior: an empirical investigation from Renren.Com. Int J Inf Manag 35(5):538–550. https://doi.org/10.1016/j.ijinfomgt.2015.04.011

    Article  Google Scholar 

  4. Beisel D (2005) (The Beginnings of) social commerce. December 6. (https://genuinevc.com/2005/12/06/the-beginnings-of-social-commerce/)

  5. Bhattacherjee A, Sanford C (2006) Influence processes for information technology acceptance: an elaboration likelihood model. MIS Quart 30(4):805–825. https://doi.org/10.2307/25148755

    Article  Google Scholar 

  6. Blondel VD, Guillaume JL, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. J Stat Mech Theor Exp 2008(10):P10008. https://doi.org/10.1088/1742-5468/2008/10/P10008

    Article  Google Scholar 

  7. Cao H, Chen Z, Xu F, Wang T, Xu Y, Zhang L, Li Y (2020) When your friends become sellers: an empirical study of social commerce site Beidian. In: Proceedings of the international AAAI conference on web and social media vol 14, pp 83–94

  8. Chen C, Wu K, Srinivasan V, Zhang X (2013) Battling the internet water army: detection of hidden paid posters. In: 2013 IEEE/ACM international conference on advances in social networks analysis and mining (ASONAM 2013), August, pp 116–120. https://doi.org/10.1145/2492517.2492637

  9. Chen C-C, Hsiao K-L, Wu S-J (2018) Purchase intention in social commerce: an empirical examination of perceived value and social awareness. Library Hi Tech 36(4):583–604. https://doi.org/10.1108/LHT-01-2018-0007

    Article  Google Scholar 

  10. Chen J, Shen X-L (2015) Consumers’ decisions in social commerce context: an empirical investigation. Decision Support Syst 79:55–64. https://doi.org/10.1016/j.dss.2015.07.012

    Article  Google Scholar 

  11. Chen K, Li X, Luo P, Zhao JL (2021) News-induced dynamic networks for market signaling: understanding the impact of news on firm equity value. Inf Syst Res 32(2):356–377. https://doi.org/10.1287/isre.2020.0969

    Article  Google Scholar 

  12. Crowston K, Fagnot I (2018) Stages of motivation for contributing user-generated content: a theory and empirical test. Int J Human-Comput Stud 109:89–101. https://doi.org/10.1016/j.ijhcs.2017.08.005

    Article  Google Scholar 

  13. Doha A, Ghasemaghaei M, Hassanein K (2017) Social bundling: a novel method to enhance consumers’ intention to purchase online bundles. J Retail Consum Serv 35:106–117. https://doi.org/10.1016/j.jretconser.2016.11.008

    Article  Google Scholar 

  14. Esmaeili L, Hashemi GSA (2019) A systematic review on social commerce. J Strateg Market 27(4):317–355. https://doi.org/10.1080/0965254X.2017.1408672

    Article  Google Scholar 

  15. Estrella-Ramón A, García-de-Frutos N, Ortega-Egea JM, Segovia-López C (2019) How does marketers’ and users’ content on corporate Facebook fan pages influence brand equity? Electron Commer Res Appl 36:100867. https://doi.org/10.1016/j.elerap.2019.100867

    Article  Google Scholar 

  16. Flanagin AJ, Metzger MJ, Pure R, Markov A, Hartsell E (2014) Mitigating risk in ecommerce transactions: perceptions of information credibility and the role of user-generated ratings in product quality and purchase intention. Electron Commer Res 14(1):1–23. https://doi.org/10.1007/s10660-014-9139-2

    Article  Google Scholar 

  17. Girvan M, Newman ME (2002) Community structure in social and biological networks. Proc Natl Acad Sci 99(12):7821–7826

    Article  Google Scholar 

  18. Goh K-Y, Heng C-S, Lin Z (2013) Social media brand community and consumer behavior: quantifying the relative impact of user- and marketer-generated content. Inf Syst Res 24(1):88–107. https://doi.org/10.1287/isre.1120.0469

    Article  Google Scholar 

  19. Gonzalez Camacho LA, Alves-Souza SN (2018) Social network data to alleviate cold-start in recommender system: a systematic review. Inf Process Manag 54(4):529–544. https://doi.org/10.1016/j.ipm.2018.03.004

    Article  Google Scholar 

  20. Guo S, Guo X, Fang Y, Vogel D (2017) How doctors gain social and economic returns in online health-care communities: a professional capital perspective. J Manag Inf Syst 34(2):487–519. https://doi.org/10.1080/07421222.2017.1334480

    Article  Google Scholar 

  21. Hajli MN (2014) Social commerce for innovation. Int J Innov Manag 18(04):1450024. https://doi.org/10.1142/S1363919614500248

    Article  Google Scholar 

  22. Han H, Xu H, Chen H (2018) Social commerce: a systematic review and data synthesis. Electron Commer Res Appl 30:38–50. https://doi.org/10.1016/j.elerap.2018.05.005

    Article  Google Scholar 

  23. Hinz O, Skiera B, Barrot C, Becker JU (2011) Seeding strategies for viral marketing: an empirical comparison. J Market. https://doi.org/10.1509/jm.10.0088

    Article  Google Scholar 

  24. Hou R, Wu J, Du HS (2017) Customer social network affects marketing strategy: a simulation analysis based on competitive diffusion model. Physica A Stat Mech Appl 469:644–653. https://doi.org/10.1016/j.physa.2016.11.110

    Article  Google Scholar 

  25. Huang Z, Benyoucef M (2015) User preferences of social features on social commerce websites: an empirical study. Technol Forecast Soc Change 95:57–72. https://doi.org/10.1016/j.techfore.2014.03.005

    Article  Google Scholar 

  26. Jang S, Prasad A, Ratchford B (2012) How consumers use product reviews in the purchase decision process. Mark Lett 23(3):825–838

    Article  Google Scholar 

  27. Jin SV, Youn S (2022) They bought it, therefore i will buy it’: the effects of peer users’ conversion as sales performance and entrepreneurial sellers’ number of followers as relationship performance in mobile social commerce. Comput Human Behav 131:107212. https://doi.org/10.1016/j.chb.2022.107212

    Article  Google Scholar 

  28. Ju J, Ahn J-H (2016) The effect of social and ambient factors on impulse purchasing behavior in social commerce. J Org Comput Electron Commer 26(4):285–306. https://doi.org/10.1080/10919392.2016.1228353

    Article  Google Scholar 

  29. Jung L-S (2014) A research on the relationship of web-site usability and social commerce. In: Workshop on business, vol 8, pp 15–18

  30. Kaye DBV, Chen X, Zeng J (2020) The co-evolution of two Chinese mobile short video apps: parallel platformization of Douyin and TikTok. Mobile Media Commun 9(2):229–253. https://doi.org/10.1177/2050157920952120

    Article  Google Scholar 

  31. Kim N, Kim W (2018) Do your social media lead you to make social deal purchases? Consumer-generated social referrals for sales via social commerce. Int J Inf Manag 39:38–48

    Article  Google Scholar 

  32. Li Q, Zuo Z, Zhang Y, Wang X (2023) Exploring sentiment divergence on migrant workers through the lens of Sina Weibo. Int Res 33(4):1331–1371. https://doi.org/10.1108/INTR-04-2021-0224

    Article  Google Scholar 

  33. Liang T-P, Ho Y-T, Li Y-W, Turban E (2011) What drives social commerce: the role of social support and relationship quality. Int J Electron Commer 16(2):69–90. https://doi.org/10.2753/JEC1086-4415160204

    Article  Google Scholar 

  34. Lin J, Luo Z, Cheng X, Li L (2019) Understanding the interplay of social commerce affordances and swift Guanxi: an empirical study. Inf Manag 56(2):213–224. https://doi.org/10.1016/j.im.2018.05.009

    Article  Google Scholar 

  35. Lv J, Wang Z, Huang Y, Wang T, Wang Y (2020) How can e-commerce businesses implement discount strategies through social media? Sustainability 12(18):7459. https://doi.org/10.3390/su12187459

    Article  Google Scholar 

  36. McPherson M, Smith-Lovin L, Cook JM (2001) Birds of a feather: homophily in social networks. Ann Rev Soc 27(1):415–444. https://doi.org/10.1146/annurev.soc.27.1.415

    Article  Google Scholar 

  37. Mikalef P, Sharma K, Pappas IO, Giannakos M (2020) Seeking information on social commerce: an examination of the impact of user- and marketer-generated content through an eye-tracking study. Inf Syst Front 23:1273–1286. https://doi.org/10.1007/s10796-020-10034-3

    Article  Google Scholar 

  38. Mothersbaugh D, Hawkins D, Kleiser SB (2015) Consumer behavior: building marketing strategy, 13th edn. McGraw-Hill Education, New York

    Google Scholar 

  39. Mou J, Benyoucef M (2021) Consumer behavior in social commerce: results from a meta-analysis. Technol Forecast Soc Change 167:120734. https://doi.org/10.1016/j.techfore.2021.120734

    Article  Google Scholar 

  40. Newman MEJ (2004) Detecting community structure in networks. Eur Phys J B 38(2):321–330. https://doi.org/10.1140/epjb/e2004-00124-y

    Article  Google Scholar 

  41. Newman MEJ (2006) Finding community structure in networks using the eigenvectors of matrices. Phys Rev E 74(3):036104. https://doi.org/10.1103/PhysRevE.74.036104

    Article  Google Scholar 

  42. O’brien RM (2007) A caution regarding rules of thumb for variance inflation factors. Qual Quant 41:673–690

    Article  Google Scholar 

  43. O’Keefe DJ (2016) Persuasion: theory and research, SAGE Publications, Inc. (https://www.scholars.northwestern.edu/en/publications/persuasion-theory-and-research-3)

  44. Petty RE, Cacioppo JT (1986) The elaboration likelihood model of persuasion. In: L Berkowitz (ed) Advances in experimental social psychology, Academic Press, Cambridge, Vol. 19, pp. 123–205. https://doi.org/10.1016/S0065-2601(08)60214-2

  45. Phang DCW, Wang K, Wang Q, Kauffman RJ, Naldi M (2019) How to derive causal insights for digital commerce in China? A research commentary on computational social science methods. Electron Commer Res Appl 35:100837. https://doi.org/10.1016/j.elerap.2019.100837

    Article  Google Scholar 

  46. Radicchi F, Castellano C, Cecconi F, Loreto V, Parisi D (2004) Defining and identifying communities in networks. Proc Natl Acad Sci 101(9):2658–2663. https://doi.org/10.1073/pnas.0400054101

    Article  Google Scholar 

  47. Rosario AB, Sotgiu F, Valck KD, Bijmolt THA (2016) The effect of electronic word of mouth on sales: a meta-analytic review of platform, product, and metric factors. J Market Res. https://doi.org/10.1509/jmr.14.0380

    Article  Google Scholar 

  48. Scholz M, Schnurbus J, Haupt H, Dorner V, Landherr A, Probst F (2018) Dynamic effects of user-and marketer-generated content on consumer purchase behavior: modeling the hierarchical structure of social media websites. Decision Support Syst 113:43–55. https://doi.org/10.1016/j.dss.2018.07.001

    Article  Google Scholar 

  49. Shen W, Hu YJ, Ulmer JR (2015) Competing for attention: an empirical study of online reviewers’ strategic behavior. MIS Quart 39(3):683–696

    Article  Google Scholar 

  50. Sicilia M, Palazón M, López M (2020) Intentional vs. Unintentional influences of social media friends. Electron Commer Res Appl 42:100979. https://doi.org/10.1016/j.elerap.2020.100979

    Article  Google Scholar 

  51. Sohn JW, Kim JK (2020) Factors that influence purchase intentions in social commerce. Technol Soc 63:101365. https://doi.org/10.1016/j.techsoc.2020.101365

    Article  Google Scholar 

  52. Song T, Tang Q, Huang J (2019) Triadic closure, homophily, and reciprocation: an empirical investigation of social ties between content providers. Inf Syst Res 30(3):912–926. https://doi.org/10.1287/isre.2019.0838

    Article  Google Scholar 

  53. Tobon S, García-Madariaga J (2021) The influence of opinion leaders’ EWOM on online consumer decisions: a study on social influence. J Theor Appl Electron Commer Res 16(4):748–767. https://doi.org/10.3390/jtaer16040043

    Article  Google Scholar 

  54. Tsiotsou R (2006) The role of perceived product quality and overall satisfaction on purchase intentions. Int J Consum Stud 30(2):207–217. https://doi.org/10.1111/j.1470-6431.2005.00477.x

    Article  Google Scholar 

  55. Wang D, Li Z, Xiao B (2019) Social influence in first-time and upgrade adoption. Electron Commer Res Appl 34:100834. https://doi.org/10.1016/j.elerap.2019.100834

    Article  Google Scholar 

  56. Wang X, Chai Y, Li H, Wu D (2021) Link prediction in heterogeneous information networks: an improved deep graph convolution approach. Decision Support Syst 141:113448. https://doi.org/10.1016/j.dss.2020.113448

    Article  Google Scholar 

  57. Wang X, Wang W, Chai Y, Wang Y, Zhang N (2019) E-book adoption behaviors through an online sharing platform: a multi-relational network perspective. Inf Technol People 33(3):1011–1035. https://doi.org/10.1108/ITP-10-2018-0482

    Article  Google Scholar 

  58. Wang Y, Wang J, Yao T, Li M, Wang X (2020) How does social support promote consumers’ engagement in the social commerce community? The mediating effect of consumer involvement. Inf Process Manag 57(5):102272. https://doi.org/10.1016/j.ipm.2020.102272

    Article  Google Scholar 

  59. Wibisono N, Senalasari W, White ME, Februadi A (2023) E-WoM engagement and purchase intention on social commerce specialized in beauty products: a perspective from young female consumers. Int J Appl Bus Res 5(1):26–46. https://doi.org/10.35313/ijabr.v5i01.311

    Article  Google Scholar 

  60. Wu F, Huberman BA (2004) Finding communities in linear time: a physics approach. Eur Phys J B 38(2):331–338. https://doi.org/10.1140/epjb/e2004-00125-x

    Article  Google Scholar 

  61. Xiang L, Zheng X, Lee MKO, Zhao D (2016) Exploring consumers’ impulse buying behavior on social commerce platform: the role of parasocial interaction. Int J Inf Manag 36(3):333–347. https://doi.org/10.1016/j.ijinfomgt.2015.11.002

    Article  Google Scholar 

  62. Xu F, Pan Z, Xia R (2020) E-commerce product review sentiment classification based on a naïve bayes continuous learning framework. Inf Process Manag 57(5):102221. https://doi.org/10.1016/j.ipm.2020.102221

    Article  Google Scholar 

  63. Yang L, Xu M, Xing L (2022) Exploring the core factors of online purchase decisions by building an e-commerce network evolution model. J Retail Consum Serv 64:102784. https://doi.org/10.1016/j.jretconser.2021.102784

    Article  Google Scholar 

  64. Yusuf AS, Che Hussin AR, Busalim AH (2018) Influence of E-WOM engagement on consumer purchase intention in social commerce. J Serv Market 32(4):493–504. https://doi.org/10.1108/JSM-01-2017-0031

    Article  Google Scholar 

  65. Zhang W, Kang L, Jiang Q, Pei L (2018) From buzz to bucks: the impact of social media opinions on the locus of innovation. Electron Commer Res Appl 30:125–137. https://doi.org/10.1016/j.elerap.2018.04.004

    Article  Google Scholar 

  66. Zhao J-D, Huang J-S, Su S (2019) The effects of trust on consumers’ continuous purchase intentions in C2C social commerce: a trust transfer perspective. J Retail Consum Serv 50:42–49. https://doi.org/10.1016/j.jretconser.2019.04.014

    Article  Google Scholar 

  67. Zhao K, Stylianou AC, Zheng Y (2018) Sources and impacts of social influence from online anonymous user reviews. Inf Manag 55(1):16–30. https://doi.org/10.1016/j.im.2017.03.006

    Article  Google Scholar 

  68. Zhao WX, Li S, He Y, Chang EY, Wen J-R, Li X (2016) Connecting social media to E-commerce: cold-start product recommendation using microblogging information. IEEE Trans Knowl Data Eng 28(5):1147–1159. https://doi.org/10.1109/TKDE.2015.2508816

    Article  Google Scholar 

  69. Zheng C, Yu X, Jin Q (2017) How user relationships affect user perceived value propositions of enterprises on social commerce platforms. Inf Syst Front 19(6):1261–1271. https://doi.org/10.1007/s10796-017-9766-y

    Article  Google Scholar 

  70. Zhu F, Zhang X (2010) Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics. J Market 74(2):133–148. https://doi.org/10.1509/jm.74.2.133

    Article  Google Scholar 

  71. Zhu Z, Wang J, Wang X, Wan X (2016) Exploring factors of user’s peer-influence behavior in social media on purchase intention: evidence from QQ. Comput Human Behav 63:980–987. https://doi.org/10.1016/j.chb.2016.05.037

    Article  Google Scholar 

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Funding

This study is supported by National Natural Science Foundation of China (72104261, 71904215, 72274230, 62106290), Program for Innovation Research in Central University of Finance and Economics, and The Young Talents Support Program from the Central University of Finance and Economics (QYP2211).

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Wang, X., Tang, J., Li, Q. et al. Will you buy my books? Investigating influential factors for the sales of user-generated e-books on a social commerce platform. Inf Technol Manag (2023). https://doi.org/10.1007/s10799-023-00415-w

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