Open Journal Systems

Impact of social support, TAM constructs and consumers’ purchase intentions in social commerce platforms: The pathway to post COVID-19

Nurkhalida Makmor, Zalena Mohd, Khalilah Abd Hafiz, Nur Husna Hamzah, Aza Azlina Md Kassim

Article ID: 1960
Vol 9, Issue 3, 2024, Article identifier:

VIEWS - 571 (Abstract) 98 (PDF)


Online social supports empower consumers to communicate and share their knowledge and experiences with each other through social commerce platforms. The communication becomes more important for online communities during the COVID-19 pandemic. Existing scholars have studied social commerce; however, lack of studies has focused on social supports and TAM constructs. Also, a growing concern on the reliability and validity of comments of online consumers would jeopardize the success of social commerce business. Therefore, the research addresses the research gap by proposing a conceptual model. On the basis of the technology adoption model (TAM), this research considers social supports, consumers online purchase intentions and the role of trust as a mediator in Malaysian context. A total of 200 respondents participated. The data are collected via online platforms and analyzed using PLS-SEM software. The results reveal that the social support, perceived ease of use and perceived usefulness have significant effects toward purchase intention in social commerce platforms. Meanwhile, trust mediated the relationship of social support and purchase intention. The present study discusses the research implications, limitations, and future directions.


social commerce; social support; TAM; trust; purchase intention

Full Text:



1. Razimi UNA, Ayrizan MZT, Ishak Z. Online social media platform for marketing generator. In: Proceedings of the ISCAIE 2021-IEEE 11th Symposium on Computer Applications and Industrial Electronics; 3–4 April 2021; Penang, Malaysia. pp. 146–150.

2. Most popular social networks worldwide as of January 2022, ranked by number of monthly active users. Available online: (accessed on 23 June 2022).

3. Salem SF, Tarofder AK, Chaichi K, Musah, AA. Brand love impact on the social media and stages of brand loyalty. Polish Journal of Management Studies 2019; 20(1): 382–393. doi: 10.17512/pjms.2019.20.1.33

4. Rashid RM, Pitafi AH, Qureshi MA, Sharma A. Role of social commerce constructs and social presence as moderator on consumers’ buying intentions during COVID-19. Frontiers in Psychology 2022; 13: 1–11. doi: 10.3389/fpsyg.2022.772028

5. Yusak NAM, Mohd Z, Yusran NFN. An empirical study of online impulsive buying behavior. Environment-Behaviour Proceedings Journal 2022; 7(SI8): 27–32. doi: 10.21834/ebpj.v7isi8.3912

6. Tseng HT. Shaping path of trust: the role of information credibility, social support, information sharing and perceived privacy risk in social commerce. Information Technology and People 2023; 36(2): 683–700. doi: 10.1108/ITP-07-2021-0564

7. Azman NH. 5 major concerns in online purchase. Utusan Malaysia 2018; 17.

8. Watanabe T, OmoriY. Online consumption during and after the COVID 19 Pandemic: Evidence from Japan. The Impact of COVID-19 on E-Commerce 2020.

9. Ahmad Z, Azizan FL, Atiqah N, et al. Examining the determinants of social shopping behaviour among Malaysian social media users. Advances in Business Research International Journal 2022; 8(1): 10–20.

10. Mustika DV, Wahyudi L. Does the quality of beauty e-commerce impact online purchase intention? The role of perceived enjoyment and perceived trust. International Journal of Economics, Business and Management Research 2022; 6(4): 199–218. doi: 10.51505/ijebmr.2022.6415

11. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 1989; 13(3): 319–340. doi: 10.1016/S0305-0483(98)00028-0

12. Alsukaini AKM, Sumra K, Khan R, et al. New trends in digital marketing emergence during pandemic times. International Journal of Innovation Science 2022; 15(1): 167–185. doi: 10.1108/ijis-08-2021-0139

13. Arifin R, Andriansyah, Syahputra RA, et al. Factor influencing consumer’s purchase intention on e-commerce in Indonesia during pandemic Covid-19 based on gender moderation. In: Proceedings of the Conference on Broad Exposure to Science and Technology 2021 (BEST 2021); 31 August 2021; Banten, Indonesia. pp. 223–229.

14. Candra S, Nuruttarwiyah F, Hapsari IH. Revisited the technology acceptance model with e-trust for peer-to-peer lending in Indonesia (Perspective from Fintech Users). International Journal of Technology 2020; 11(4): 710–721. doi: 10.14716/ijtech.v11i4.4032

15. Fitri RA, Wulandari R. Online purchase intention factors in Indonesian millenial. International Review of Management and Marketing 2020; 10(3): 122–127. doi: 10.32479/irmm.9852

16. Seo KH, Lee JH. The emergence of service robots at restaurants: Integrating trust, perceived risk, and satisfaction. Sustainability 2021; 13(8): 4431. doi: 10.3390/su13084431

17. Ventre I, Mollá-Descals A, Frasquet M. Drivers of social commerce usage: a multi-group analysis comparing Facebook and Instagram. Economic Research-Ekonomska Istrazivanja 2021; 34(1): 570–589. doi: 10.1080/1331677X.2020.1799233

18. Ara Eti I, Horaira MA, Bari MM. Power and stimulus of social media marketing on consumer purchase intention in Bangladesh during the COVID-19. International Journal of Research in Business and Social Science 2021; 10(1): 28–37. doi: 10.20525/ijrbs.v10i1.1011

19. Öztürk R. Health or death? The online purchase intentions of consumers during the COVID-19 pandemic. Transnational Marketing Journal 2020; 8(2): 219–241. doi: 10.33182/tmj.v8i2.1069

20. Cobb S. Social support as a moderator of life stress. Psychosomatic Medicine 1976; 38(5): 300–314. doi: 10.1097/00006842-197609000-00003

21. Kozinets RV, Ferreira DA, Chimenti P. How do platforms empower consumers? Insights from the affordances and constraints of Reclame Aqui. Journal of Consumer Research 2021; 48(3): 428–455.

22. Huang TC, Wang YJ, Lai HM. What drives internet entrepreneurial intention to use technology products? An investigation of technology product imagination disposition, social support, and motivation. Frontiers in Psychology 2022; 1–13. doi: 10.3389/fpsyg.2022.829256

23. Yahia IB, Al-Neama N, Kerbache L. Investigating the drivers for social commerce in social media platforms: Importance of trust, social support and the platform perceived usage. Journal of Retailing and Consumer Services 2018; 41: 11–19. doi: 10.1016/j.jretconser.2017.10.021

24. Jalal AN, Bahari M, Tarofder AK, Musa WMNMW. Factors influencing customer social relationship management implementation and its benefits in healthcare industry. Polish Journal of Management Studies 2019; 19(2): 196–205. doi: 10.17512/pjms.2019.19.2.16

25. Wang J, Shahzad F, Ahmad Z, et al. Trust and consumers’ purchase intention in a social commerce platform: A meta-analytic approach. SAGE Open 2022; 12(2): 215824402210912. doi: 10.1177/21582440221091262

26. Leong LY, Hew TS, Ooi KB, et al. Understanding trust in ms-commerce: The roles of reported experience, linguistic style, profile photo, emotional, and cognitive trust. Information & Management 2021; 58(2): 103416. doi: 10.1016/

27. Saputra UWE, Darma GS. The intention to use blockchain in Indonesia using extended approach Technology Acceptance Model (TAM). CommIT Journal 2022; 16(1): 27–35. doi: 10.21512/commit.v16i1.7609

28. Acikgoz F, Busalim A, Gaskin J, et al. An integrated model for information adoption & trust in mobile social commerce. Journal of Computer Information Systems 2023; 1–23. doi: 10.1080/08874417.2023.2251449

29. Song J, Xu P. Healthier together: Social support, self-regulation and goal management for chronic conditions in online health communities. Information & Management 2023; 60(7): 103830. doi: 10.1016/

30. Filieri R. What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. Journal of Business Research 2015; 68(6): 1261–1270. doi: 10.1016/j.jbusres.2014.11.006

31. Hajli N, Wang Y, Tajvidi M, et al. People, technologies, and organizations interactions in a social commerce era. IEEE Transactions on Engineering Management 2017; 64(4): 594–604. doi: 10.1109/tem.2017.2711042

32. Aloqool A, Alsmairat MAK. The impact of social commerce on online purchase intention: The mediation role of trust in social network sites. International Journal of Data and Network Science 2022; 6(2): 509–516. doi: 10.5267/j.ijdns.2021.12.003

33. Hajli M. A research framework for social commerce adoption. Information Management & Computer Security 2013; 21(3): 144–154. doi: 10.1108/imcs-04-2012-0024

34. Dhagarra D, Goswami M, Kumar G. Impact of trust and privacy concerns on technology acceptance in healthcare: An Indian perspective. International Journal of Medical Informatics 2020; 141: 104164. doi: 10.1016/j.ijmedinf.2020.104164

35. Hansen JM, Saridakis G, Benson V. Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers’ use of social media for transactions. Computers in Human Behavior 2018; 80: 197–206. doi: 10.1016/j.chb.2017.11.010

36. Sitthipon T, Siripipatthanakul S, Phayaphrom B, et al. Determinants of customers’ intention to use healthcare chatbots and apps in Bangkok, Thailand. International Journal of Behavioral Analytics 2022; 2(2): 1–15.

37. Siagian H, Tarigan ZJH, Basana SR, et al. The effect of perceived security, perceived ease of use, and perceived usefulness on consumer behavioral intention through trust in digital payment platform. International Journal of Data and Network Science 2022; 6(3): 861–874. doi: 10.5267/j.ijdns.2022.2.010

38. Song Y, Yang Y, Cheng P. The investigation of adoption of Voice‐User Interface (VUI) in smart home systems among Chinese older adults. Sensors 2022; 22(4): 1614. doi: 10.3390/s22041614

39. Udayana IBN, Cahya AD, Aqdella FA. The effect of perceived usefulness, perceived ease of use on behavioral intention to use through the intervening attitude toward using variables in the study of Shopee pay e-wallet services (Case study on ShopeePay Users in Yogyakarta). Journal of Applied Management and Entrepreneurship 2022; 8(1): 143.

40. Viviana N, Mulyono KB. Determinants of students e-money intention empirical studies of Semarang State University students. Proceedings of the 2nd International Conference of Strategic Issues on Economics, Business and, Education (ICoSIEBE 2021) 2022; 204: 315–320.

41. Zhang Z, Xia E, Huang J. Impact of the moderating effect of national culture on adoption intention in wearable health care devices: Meta-analysis. JMIR mHealth and uHealth 2022; 10(6): e30960. doi: 10.2196/30960

42. Karim RA, Rahayu A, Mahmud N, et al. An application of TAM model towards influencing online purchase intention during Covid-19 pandemic for fresh agricultural products: A preliminary findings. AIP Conference Proceedings 2021; 2347: 1–9. doi: 10.1063/5.0052849

43. 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

44. Algharabat RS, Rana NP. Social commerce in emerging markets and its impact on online community engagement. Information Systems Frontiers 2021; 23(6): 1499–1520. doi: 10.1007/s10796-020-10041-4

45. Hawkins RJ, Swanson B, Kremer MJ, et al. Content validity testing of questions for a patient satisfaction with general anesthesia care instrument. Journal of Perianesthesia Nursing 2014; 29(1): 28–35. doi: 10.1016/j.jopan.2013.05.011

46. Lewis JR. Multipoint scales: Mean and median differences and observed significance levels. International Journal of Human-Computer Interaction 1993; 5(4): 383–392. doi: 10.1080/10447319309526075

47. Churchill GA, Peter JP. Design effects the of rating meta-analysis. Journal of Marketing Research 1984; 21(4): 360–375.

48. Finstad K. Response interpolation and scale sensitivity: Evidence against 5-point scales usability metric for user experience view project. Journal of Usability Studies 2010; 5(3): 104–110.

49. Liang TP, Ho YT, Li YW, et al. What drives social commerce: The role of social support and relationship quality. International Journal of Electronic Commerce 2011; 16(2): 69–90. doi: 10.2753/jec1086-4415160204

50. Gefen D, Straub DW. Consumer trust in B2C e-commerce and the importance of social presence: Experiments in e-products and e-services. Omega 2004; 32(6): 407–424. doi: 10.1016/

51. Han B, Windsor JC. Users’ Willingness to Pay on Social Network Sites. User’s Willingness to Pay on Social Network Sites 2011; 51(4): 31.

52. Liu H, Chu H, Huang Q, et al. Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce. Computers in Human Behavior 2016; 58: 306–314. doi: 10.1016/j.chb.2016.01.012

53. Commission Factory. Malaysia social media statistics and facts 2023. Available online: studies have shown that,than seven times a day (accessed on 22 November 2023).

54. Nielsen. The Nielsen Total Audience Report: September 2019. Available online: (accessed on 11 December 2019).

55. Kline R. Principles and Practice of Structural Equation Modeling. 1998.

56. Wilson Van Voorhis CR, Morgan BL. Understanding power and rules of thumb for determining sample sizes. Tutorials in Quantitative Methods for Psychology 2007; 3(2): 43–50. doi: 10.20982/tqmp.03.2.p043

57. Barclay D, Higgins C, Thompson R. The partial least squares (PLS) approach to causal modelling: personal computer adaptation and use as an illustration. Technology Studies 1995; 2(2): 286–309.

58. Hair JF, Hult GTM, Ringle C, Sarstedt M. A Primer on Partial Least Squares Structural Modeling (PLS-SEM), 2nd ed. SAGE Publications Ltd; 2017.

59. Peng DX, Lai F. Using partial least squares in operations management research: A practical guideline and summary of past research. Journal of Operations Management 2012; 30(6): 467–480. doi: 10.1016/j.jom.2012.06.002

60. Hair JF, Risher JJ, Sarstedt M, et al. When to use and how to report the results of PLS-SEM. European Business Review 2019; 31(1): 2–24. doi: 10.1108/ebr-11-2018-0203

61. Hair JF, Ringle CM, Sarstedt M. PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice 2011; 19(2): 139–152. doi: 10.2753/mtp1069-6679190202

62. Hair JF, Hult GTM, Ringle C, Sarstedt M. A Primer on Partial Least Squares Structural Modeling (PLS-SEM). SAGE Publications Ltd; 2014.

63. Wasko MM, Faraj S. Why should I share? Examining social capital and knowledge contribution in electronic network of practice. MIS Quarterly 2005; 29(1): 35–57. doi: 10.2307/25148667

64. Zikmund WG, Babin BJ, Carr JC, Griffin M. Business Research Methods, 9th ed. Mason, OH: Cengage Learning; 2013.

65. Rajalahti T, Kvalheim OM. Multivariate data analysis in pharmaceutics: A tutorial review. International Journal of Pharmaceutics 417(1–2): 280–290. doi: 10.1016/j.ijpharm.2011.02.019

66. Shrestha N. Detecting multicollinearity in regression analysis. American Journal of Applied Mathematics and Statistics 2020; 8(2): 39–42. doi: 10.12691/ajams-8-2-1

67. Durbin J, Watson GS. Testing for serial correlation in least sqares regression. Biometrika 1951; 38(1): 159–177. doi: 10.1093/biomet/72.2.241

68. Preacher KJ, Hayes AF. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods 2008; 40(3): 879–891. doi: 10.3758/brm.40.3.879

69. Liu Y, Su X, Du X, et al. How social support motivates trust and purchase intentions in mobile social commerce. Revista Brasileira de Gestao de Negocios 2019; 21(4): 839–860. doi: 10.7819/rbgn.v21i5.4025

70. Hallegatte D, Nantel J. The intertwined effect of perceived usefulness, perceived ease of use and trust in a website on the intention to return. The E-Business Review 2006; 6: 1–5.

71. Sidanti H, Murwani FD, et al. Online purchasing intention using the technology acceptance model (TAM) approach. Economic Annals-ХХI 2021; 193(9–10): 85–91. doi: 10.21003/ea.v193-10

72. Xu A, Li W, Chen Z, et al. A study of young Chinese intentions to purchase “Online Paid Knowledge”: An extended technological acceptance model. Frontiers in Psychology 2021; 12. doi: 10.3389/fpsyg.2021.695600

73. Bao Z. Exploring continuance intention of social networking sites: an empirical study integrating social support and network externalities. Aslib Journal of Information Management 2016; 68(6): 736–755. doi: 10.1108/AJIM-05-2016-0064

(571 Abstract Views, 98 PDF Downloads)


  • There are currently no refbacks.

Copyright (c) 2023 Nurkhalida Makmor, Zalena Mohd, Khalilah Abd Hafiz, Nur Husna Hamzah, Aza Azlina Md Kassim

License URL: