Факторы, влияющие на принятие покупателями Нигерии электронных точек продаж (E-POS)
https://doi.org/10.25587/2587-8778-2025-2-25-43
Аннотация
В настоящее время банковские услуги переходят с ручного на электронный уровень, но не все страны мира сумели перенести свою платежную систему в электронную среду из-за некоторых культурных традиций. В развивающихся странах, таких как Нигерия, внедрение электронного банкинга прошло в несколько этапов, начиная с улучшения способа оплаты и заканчивая предоставлением нескольких электронных платежных платформ клиентам в качестве альтернативы оплаты наличными. Успех этих электронных платежных платформ зависит от уровня принятия потребителями. Растущая зависимость от цифровых финансовых транзакций во всем мире оставила пробел в понимании моделей принятия в развивающихся странах. Целью данного исследования является выявление и анализ факторов, влияющих на использование нигерийскими розничными покупателями электронных систем точек продаж (POS). Был проведен структурированный опрос среди 237 респондентов в шести геополитических зонах Нигерии с использованием SEM (моделирования структурных уравнений) для проверки гипотез, полученных из Единой теории принятия и использования технологий (UTAUT). Результаты показывают, что ожидаемая производительность, простота использования и социальное влияние существенно влияют на намерение пользователей принять POS-системы. Данное исследование подчеркивает важность технологического соответствия, простоты и мнения окружающих для повышения темпов принятия, предоставляя действенные идеи для политиков и финансовых учреждений в схожих социально-экономических контекстах.
Ключевые слова
Об авторах
М. Н. ОколиРоссия
Околи Морис ‒ докторская степень по экономике, научный сотрудник, Институт Африки и Институт мировой экономики и международных отношений Российской академии наук, преподаватель
г. Якутск
Б. Е. Одигбо
Нигерия
Одигбо Бенедикт ‒ докторская степень по маркетингу, профессор кафедры маркетинга
г. Калабар
Д. Н. Нзекву
Нигерия
Нзекву Дэвид ‒ докторская степень по маркетингу, главный исполнительный директор Службы внутренних доходов штата Анамбра
г. Энугу
Список литературы
1. Jadil Y., Rana N. P., Dwivedi Y. K. A meta-analysis of the UTAUT model in the mobile banking literature: The moderating role of sample size and culture. Journal of Business Research, Elsevier. 2021,132(C):354–372. Available at: https://ideas.repec.org/a/eee/jbrese/v132y2021icp354-372.html
2. Bhatiasevi V. An extended UTAUT model to explain the adoption of mobile banking. Sage Journals. 2015;32(4). Available at: https://journals.sagepub.com/doi/10.1177/0266666915570764
3. European Central Bank. Annual Report – 2020, Available at: https://www.ecb.europa.eu/press/annual-reports-financial-statements/annual/html/ar2020~4960fb81ae.en.html
4. KPMG. Banking Industry Customer Satisfaction Survey – 2014. Available at: http://www.kpmg.com/ng/en/pages/bankingindustrycustomersatisfactionsurvey.aspx.
5. NIBSS. POS adoption and usage: A study on Lagos State. Available at: http://www.nibss-plc.com.ng/wp-content/uploads/2015/05/NIBSS-2015-POS-Adoption-Study-Lagos-State.pdf
6. Oney E., Guven O.G., Rizvi W.H. The determinants of electronic payment systems usage from consumers’ perspective. Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals. 2017;30(1):394–415. Available at: https://ideas.repec.org/a/taf/reroxx/v30y2017i1p394-415.html
7. Kabir M.A., Saidin S.Z., Ahmi A. Adoption of e-Payment Systems: A review of Literature. Proceedings of the International Conference on E-Commerce held on 20-22 October 2015 at Kuching, Sarawak, Malasya Available at: https://www.researchgate.net/publication/303329794_Adoption_of_e-Payment_Systems_A_Review_of_Literature
8. Kalinić Z., Marinković V. Determinants of users’ intention to adopt m-commerce: an empirical analysis. Information Systems and e-Business Management, Springer. 2016;14(2):367–387. Available at: https://ideas.repec.org/a/spr/infsem/v14y2016i2d10.1007_s10257-015-0287-2.html
9. Batucan G.B., Gonzales G.G., Balbuena M.G., et al. An Extended UTAUT Model to Explain Factors Affecting Online Learning System Amidst COVID-19 Pandemic: The Case of a Developing Economy. Frontiers in Artificial Intelligenc. 2022;5. https://doi.org/10.3389/frai.2022.768831
10. Hamid A.A., Razak F.Z.A., Bakar A.A., Abdullah W.W.W. The effects of perceived usefulness and perceived ease of use on continuance intention to use E-government. Procedia Economics and Finance. 2016;35:644–649
11. Oliveira T, Popovič A. Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management. 2014;34(1):1–13.
12. Karsen M., Chandra Y.U., Juwitasary H. Technological factors of Mobile Payment: A Systematic Literature Review. Procedia Computer Science. 2019. DOI: 10.1016/j.procs.2019.09.00410.1016/j.procs.2019.09.0040.1016/j.p
13. Marinković V., Kalinić Z. Antecedents of customer satisfaction in mobile commerce: Exploring the moderating effect of customization. Online information review. 2017;41(2):138–154. DOI:10.1108/oir-11-2015-0364
14. Vasic, N., Kilibarda, M., Kaurin, T. The Influence of Online Shopping Determinants on Customer Satisfaction in the Serbian Market. Journal of Theoretical and Applied Electronic Commerce Research. 2019:14:2–18. https://doi.org/10.4067/S0718-18762019000200107
15. Bolt W., Humphrey D.B., Uittenbogaard R. Transaction Pricing and the Adoption of Electronic Payments: A Cross-Country Comparison. International Journal of Central Banking. 2018;4(1):89–123. Available at: https://www.researchgate.net/publication/5115072_Transaction_Pricing_and_the_Adoption_of_Electronic_Payments_A_Cross-Country_Comparison
16. Eze, F.J., Odigbo, B.E., Bassey, A.E., et al. Product Attributes of Household Electronic Appliances and Consumers Preferences. International Journal of Disaster Recovery and Business Continuit., 2020;11(3):1521–1545.
17. Sivathanu В. Adoption of digital payment systems in the era of demonetization in India: An empirical study. Journal of Science and Technology Policy Management. 2019;10(1):143–171. https://doi.org/10.1108/JSTPM-07-2017-0033
18. Savić J., Pešterac A. Antecedents of Mobile Banking: UTAUT Model. The European Journal of Applied Economics. 2019;16:20–29. https://doi.org/10.5937/EJAE15-19381
19. Patil P., Tamilmani K., Rana N.P., Raghavan V. Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management, Elsevier. 2020;54(C). DOI: 10.1016/j.ijinfomgt.2020.102144
20. Pešterac A., & Tomić, N. Loss of privacy in electronic payment systems. Anali Ekonomskog Fakulteta U Subotici. 2020;56(43):135–149. https://doi.org/10.5937/AnEkSub2001135P
21. Adedoyi O. B., Soykan E. COVID-19 Pandemic and Online Learning: The Challenges and Opportunities. Interactive Learning Environment. 2020. https://doi.org/10.1080/10494820.2020.1813180
22. Chao C.-M. Factors determining the behavioral intention to use mobile learning: an application and extension of the UTAUT model. Frontiers in Psychology. 2019;10:1652. doi: 10.3389/fpsyg.2019.01652
23. Celik H. Customer online shopping anxiety within the Unified Theory of Acceptance and Use Technology (UTAUT) framework. Asia Pacific Journal of Marketing and Logistics. 2016;28(2). https://doi.org/10.1108/APJML-05-2015-0077
24. Wu W-H., Chen C-Y., Kao H-Y., Wu Y-C.J. Review of trends from mobile learning studies: A meta-analysis. Computers & Education. 2012;59(2):817–827. DOI:10.1016/j.compedu.2012.03.016
25. Escobar-Rodriguez T., Carvajal-Truzillo E. Online purchasing tickets for low cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism managemen,. Elsevier. 2014;43:70–88. https://doi.org/10.1016/j.tourman.2014.01.017
26. Gunawan H., Sinaga B.L., Purnomo Y.S. Assessment of the Readiness of Micro, Small and Medium Enterprises in Using E-Money Using the Unified Theory of Acceptance and Use of Technology (UTAUT) Method. Procedia Computer Science, 2019, 161 (6), 316-323. DOI:10.1016/j.procs.2019.11.129
27. Tarhini A., El-Masri M., Ali M., Serrano A. Factors affecting the adoption of e-learning systems in Qatar and USA: Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Information Technology & People. 2016;29(4):830–49. DOI: 10.1108/ITP-02-2014-0034.
28. Tusyanah T., Wahyudin A., Khafid M. Analyzing Factors Affecting the Behavioral Intention to Use e-Wallet with the UTAUT Model with Experience as Moderating Variable. Journal of Economic Education. 2021;10(1). DOI 10.15294/jeec.v9i2.44824
29. Omotayo F., Dahunsi O. Factors Affecting Adoption of Point of Sale Terminals by Business Organisations in Nigeria. International Journal of Academic Research in Business and Social Sciences. 2015;5(10):115–137. Available at: https://econpapers.repec.org/RePEc:hur:ijarbs:v:5:y:2015:i:10:p:115-137
30. Alqahtani H., Kavakli M., Sheikh N.U. Analysis of the Technology Acceptance Theoretical Model in Examining Users’ Behavioural Intention to Use an Augmented Reality App (IMAPCampus). International Journal of Engineering and Management Research. 2018;8(5). https://doi.org/10.31033/ijemr.8.5.6
31. Audet É.C., Levine S.L., Metin E., et al. Zooming their way through university: which Big 5 traits facilitated students’ adjustment to online courses during the COVID-19 pandemic. Personality and Individual Differences. 2021;180:110969. doi: 10.1016/j.paid.2021.110969
32. Gonzales G.G., Gonzales R.R. Introducing IWB to preservice mathematics teachers: an evaluation using the TPACK framework. Cypriot Journal of Educational Sciences. 2021;16:436–450. doi: 10.18844/cjes.v16i2.5619
33. Halili S.H., Sulaiman H. Factors influencing the rural students’ acceptance of using ICT for educational purposes. Kasetsart Journal of Social Sciences. 2019;40:574–579. https://doi.org/10.1016/j.kjss.2017.12.022
34. Kalavani A., Kazerani M., Shekofteh M. Acceptance of Evidence based medicine (EBM) databases by Iranian medical residents using unified theory of acceptance and use of technology (UTAUT). Health Policy and Technology. 2018;7(3). DOI:10.1016/j.hlpt.2018.06.005
35. Szopiński T., Bachnik K. Student evaluation of online learning during the COVID-19 pandemic. Technological Forecasting and Social Change. 2022;174. https://doi.org/10.1016/j.techfore.2021.121203Getrights and content
36. Šumak B., Šorgo A. The acceptance and use of interactive whiteboards among teachers: Differences in UTAUT determinants between pre-and post-adopters. Computers in Human Behavior. 2016;64:602–620. https://doi.org/10.1016/j.chb.2016.07.037
37. Suki N.M., Suki N.M. Determining students’ behavioral intention to use animation and storytelling applying the UTAUT model: The moderating roles of gender and experience level. The International Journal of Management Education. 2017;15(3):528–538. https://doi.org/10.1016/j.ijme.2017.10.002
38. Kim E.-J., Kim J.J., Han S.-H. Understanding student acceptance of online learning systems in higher education: application of social psychology theories with consideration of user innovativeness. Sustainability. 2021; 13:896. DOI: 10.3390/su13020896
39. Li C., Lalani F. The COVID-19 Pandemic Has Changed Education Forever. This Is How. World Economic Forum, 2020. Available at: https://www.weforum.org/agenda/2020/04/coronavirus-education-global-covid19-online-digital-learning
40. Pham L.T., Dau T.K.T. Online learning readiness and online learning system success in Vietnamese higher education. The International Journal of Information and Learning Technology. 2022;39:147–165. DOI: 10.1108/IJILT-03-2021-0044
41. Sangeeta M.A., Tandon U. Factors influencing adoption of online teaching by school teachers: a study during COVID-19 pandemic. Journal of Public Affairs. 2021;21:2503. DOI: 10.1002/pa.2503
42. Qiao P., Zhu X., Guo Y., et al. The Development and Adoption of Online Learning in Pre- and Post-COVID-19: Combination of Technological System Evolution Theory and Unified Theory of Acceptance and Use of Technology. Journal of Risk and Financial Management. 2021;14(4). Available at: https://eprints.qut.edu.au/234033/
43. Raza S.A., Qazi W., KhanK. A., Salam J. Social isolation and acceptance of the Learning Management System (LMS) in the time of COVID-19 pandemic: an expansion of the UTAUT Model. Journal of Educational Computing Research. 2021;59:183–208. DOI: 10.1177/0735633120960421
44. Sudono F.S., Adiwijaya M., Siagian H. The influence of perceived security and perceived enjoyment on intention to use with attitude towards use as intervening variable on mobile payment customer in Surabaya. Petra International Journal of Business Studies. 2020;3:37–46. DOI: 10.9744/ijbs.3.1.37-46
45. Vlachopoulos D. Covid-19: threat or opportunity for online education? Higher Learning Research Communications. 2020;10:16–19. DOI: 10.18870/hlrc.v10i1.1179
46. Septiani R., Handayani P. W., Azzahro F. Factors that affecting behavioral intention in online transportation service: case study of GO-JEK. Procedia Computing Science.2017;124:504–512. DOI: 10.1016/j.procs.2017.12.183
47. Yates A., Starke, L., Egerton B., Flueggen F. High school students’ experience of online learning during Covid-19: the influence of technology and pedagogy. Technology, Pedagogy and Education. 2021;30:59–73. DOI: 10.1080/1475939X.2020.1854337
48. Marikyan D., Papagiannidis S. Technology Acceptance Model: A Review in the book Theory Hub Book: UK, 2024. Available at: https://open.ncl.ac.uk/theories/1/technology-acceptance-model/
49. Venkatesh V., Michael G., Davis G.B., Davis F.D. User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly. 2003;27(3):425-478. https://doi.org/10.2307/30036540
50. Martins C., Oliveira T., Popovič A. Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management. 2014;34(1):1–13. https://doi.org/10.1016/j.ijinfomgt.2013.06.002
51. Thomas M.A.; Oliveira T, Faria M., Popovic A. Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM. International Journal of Information Management. 2014;34(5):689–703. DOI: 10.1016/j.ijinfomgt.2014.06.004
52. Oney E., Guven G.O., Rizvi W.H. The determinants of electronic payment systems usage from consumers’ perspective. Economic Research, Taylor & Francis Journals, 2017, vol. 30(1), 394-415. DOI: 10.1080/1331677X.2017.1305791
53. Tosuntas S.B., Karadag E., Sevil O-O. The factors affecting Acceptance and Use of interactive whiteboard within the scope of FATIH project: A structural equation model based on the Unified Theory of Acceptance and Use of Technology. Computers & Education. 2012; 81. DOI:10.1016/j.compedu.2014.10.009
54. Chiemeke S., Evwiekpaefe A. A Conceptual framework of a modified unified theory of acceptance and use of technology (UTAUT) Model with Nigerian factors in E-commerce adoption. Educational Research. 2011;2(12):1719–1726.
55. Dwivedi Y.K., et al. Impact of COVID-19 Pandemic on Information Management Research and Practice: Transforming Education, Work and Life. International Journal of Information Management. 2020;55, Article ID: 102211. https://doi.org/10.1016/j.ijinfomgt.2020.102211
56. Wislon A., Laskey N. Internet based marketing research: A serious alternative to traditional research methods? Marketing Intelligence & Planning. 2003;21(2):79–84. DOI:10.1108/02634500310465380
57. Lebo M.P, Odigbo B.E, Iheanacho M.J.U. Career development and University Teachers’ Performance in Nigeria. Solid State Technology. 2021;64(2):8242–8252. Available at: https://solidstatetechnology.us/index.php/JSST/article/view/11270
58. White H., Nteli F. Internet Banking in the UK: Why Are There Not More Customers? Journal of Financial Services Marketing. 2004;9:49–56. https://doi.org/10.1057/palgrave.fsm.4770140
59. Klopper H. B., Petzer D., Ismail Z., et al. Marketing: Fresh perspectives. Cape Town: Pearson, South Africa. 2006.
60. Bryman, A. Social research methods. 2nd Edition, Oxford University Press, New York, 2004, 592.
61. Odigbo B.E.; Etuk A.E., Akpam V.A. Social Marketing-Mix Elements and Drug Abuse Demarketing In Nigerian Universities. Turkish Journal of Computer and Mathematics Education . 2020;12(14):241–276.
62. Ghauri P. N., Grønhaug K. Research Methods in Business Studies: A Practical Guide. London: Pearson Education; 2005
63. Suh B., Han I. Effect of Trust on Customer Acceptance of Internet Banking. Electronic Commerce Research and Application., 2002;1:247–263. https://doi.org/10.1016/S1567-4223(02)00017-0
64. Wang Y-S., Wang Y-M., Lin H.H., Tang T-I.. Determinants of user acceptance of internet banking: an empirical study. International Journal of Service Industry Management. 2003;14(5):501–519.
65. Oliveira T., Thomas M., Baptista G., Campos, F. Mobile Payment: Understanding the Determinants of Customer Adoption and Intention to Recommend the Technology. Computers in Human Behavior. 2016;61:404–414. https://doi.org/10.1016/j.chb.2016.03.030
Рецензия
Для цитирования:
Околи М., Одигбо Б., Нзекву Д. Факторы, влияющие на принятие покупателями Нигерии электронных точек продаж (E-POS). Экономика и природопользование на Севере. Economy and nature management in the North. 2025;(2):25-43. https://doi.org/10.25587/2587-8778-2025-2-25-43
For citation:
Okoli M., Odigbo B.E., Nzekwu D.N. Factors influencing adoption of electronic point of sales (E-POS) by shoppers in Nigeria. Economy and nature management in the North. 2025;(2):25-43. https://doi.org/10.25587/2587-8778-2025-2-25-43