Mobile Computing as a Catalyst for Retail Supply Chain Collaboration: Insights from Ilorin, Nigeria

Objectives: This study explores how mobile computing technologies such as smartphones, online platforms, and mobile payment systems, shape supply chain collaboration among fast-moving consumer goods (FMCG) retailers in Ilorin, Kwara State, Nigeria. The aim was to determine whether these technologies contribute equally to collaboration outcomes and to highlight the contextual factors that may influence their effectiveness. Methods: A quantitative approach method was adopted, with data collected through structured surveys and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 3.0. The measurement model demonstrated strong reliability and validity, with factor loadings above 0.70, Cronbach’s alpha and composite reliability exceeding 0.70, and average variance extracted (AVE) scores above 0.50. Discriminant validity was confirmed using both the Fornell-Larcker criterion and the heterotrait-monotrait (HTMT) ratio. Results: The findings of the research revealed mixed results. That is, it revealed that online platforms significantly enhance supply chain collaboration, improving communication, coordination, and efficiency. In contrast, mobile payment systems showed a significant but negative relationship, while smartphones had no meaningful effect. These results suggest that adoption alone is insufficient; effective integration strategies and supportive infrastructure are critical to realizing the benefits of mobile technologies. Conclusions: This study provides empirical evidence from an emerging market context, showing that not all mobile technologies contribute equally to collaboration. It underscores the importance of strategic deployment, investment in infrastructure, and training to maximize digital transformation benefits. Future research should investigate barriers to mobile payment integration and explore strategies for leveraging smartphones more effectively, while encouraging retailers to capitalize on the proven advantages of online platforms.

Mobile computing, supply chain collaboration, online platforms, mobile payment systems, smartphones, emerging markets

1. Alfian, G., Ijaz, M. F., Syafrudin, M., Syaekhoni, M. A., Fitriyani, N. L., & Rhee, J. (2019). Customer behavior analysis using real-time data processing: A case study of digital signage-based online stores. Asia Pacific Journal of Marketing and Logistics, 31(1), 265–290. https://doi.org/10.1108/APJML-06-2017-0111 [Google Scholar] [Crossref]

2. Attaran, M. (2020). Digital technology enablers and their implications for supply chain management. Supply Chain Forum: An International Journal, 21(3), 158–172. [Google Scholar] [Crossref]

3. https://doi.org/10.1080/16258312.2020.1816361 [Google Scholar] [Crossref]

4. Awa, H. O., Ojiabo, O. U., & Emecheta, B. C. (2015). Integrating TAM, TPB and TOE frameworks and expanding their characteristic constructs for e-commerce adoption by SMEs. Journal of Science & Technology Policy Management, 6(1), 76–94. https://doi.org/10.1108/JSTPM-04-2014-0012 [Google Scholar] [Crossref]

5. Awara, N. F., Udoh, E. G., & Anyadighibe, J. A. (2018). Information technology tools and supply chain performance of online retailers in Calabar metropolis, Cross River State, Nigeria. Global Journal of Social Sciences, 17(1), 55–67. https://doi.org/10.4314/gjss.v17i1.5 [Google Scholar] [Crossref]

6. Beck, T., Pamuk, H., Ramrattan, R., & Uras, B. R. (2018). Payment instruments, finance and development. Journal of Development Economics, 133, 162–186. [Google Scholar] [Crossref]

7. https://doi.org/10.1016/j.jdeveco.2018.01.001 [Google Scholar] [Crossref]

8. Bhandari, R. (2014). Impact of technology on logistics and supply chain management. IOSR Journal of Business and Management, 17(2), 19–24. https://doi.org/10.9790/487X-17221924 [Google Scholar] [Crossref]

9. Bouwer, L. (2017). Innovation management theory evolution map. SSRN. [Google Scholar] [Crossref]

10. https://doi.org/10.2139/ssrn.3222848 [Google Scholar] [Crossref]

11. Burchardt, C., & Maisch, B. (2019). Digitalisation needs a cultural change—Agility and open innovation will drive the digital transformation. Procedia CIRP, 84, 112–117. [Google Scholar] [Crossref]

12. https://doi.org/10.1016/j.procir.2019.04.250 [Google Scholar] [Crossref]

13. Chae, H.-C., Koh, E. C., & Park, K. O. (2018). Information technology capability and firm performance: Role of industry. Information & Management, 55(5), 525–546. [Google Scholar] [Crossref]

14. https://doi.org/10.1016/j.im.2017.10.001 [Google Scholar] [Crossref]

15. De Vass, T. (2018). The “Internet of Things” enabled supply chain integration and performance: A mixed method investigation of the Australian retail industry (Doctoral dissertation, Victoria University). [Google Scholar] [Crossref]

16. Enahoro, M. A., & Olawade, D. B. (2021). GSM and the Nigerian economy: The journey from 2004 to 2019. International Journal of Economics and Finance, 13(7), 69–78. [Google Scholar] [Crossref]

17. https://doi.org/10.5539/ijef.v13n7p69 [Google Scholar] [Crossref]

18. Farr-Wharton, G., Choi, J. H. J., & Foth, M. (2014). Food talks back: Exploring the role of mobile applications in reducing domestic food wastage. In Proceedings of the 26th Australian Computer-Human Interaction Conference on Designing Futures: The Future of Design (pp. 352–361). ACM. https://doi.org/10.1145/2686612.2686665 [Google Scholar] [Crossref]

19. Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104 [Google Scholar] [Crossref]

20. Ganbold, O., Matsui, Y., & Rotaru, K. (2021). Effect of information technology-enabled supply chain integration on firm’s operational performance. Journal of Enterprise Information Management, 34(3), 948–989. https://doi.org/10.1108/JEIM-06-2019-0180 [Google Scholar] [Crossref]

21. Godwin-Jones, R. (2008). Mobile-computing trends: Lighter, faster, smarter. Language Learning & Technology, 12(3), 3–9. [Google Scholar] [Crossref]

22. Guan, Y. (2023). Consumer behavior analysis and marketing strategy optimization in the digital media environment. Industrial Engineering and Innovation Management, 6(10), 87–94. [Google Scholar] [Crossref]

23. Habjan, A., Andriopoulos, C., & Gotsi, M. (2014). The role of GPS-enabled information in transforming operational decision making: An exploratory study. European Journal of Information Systems, 23(4), 481–502. https://doi.org/10.1057/ejis.2013.15 [Google Scholar] [Crossref]

24. Hald, K. S., & Coslugeanu, P. (2022). The preliminary supply chain lessons of the COVID-19 disruption—What is the role of digital technologies? Operations Management Research, 15(1), 282–297. https://doi.org/10.1007/s12063-021-00222-3 [Google Scholar] [Crossref]

25. Hanelt, A., Bohnsack, R., Marz, D., & Antunes Marante, C. (2021). A systematic review of the literature on digital transformation: Insights and implications for strategy and organizational change. Journal of Management Studies, 58(5), 1159–1197. https://doi.org/10.1111/joms.12639 [Google Scholar] [Crossref]

26. Helal, A. A., Haskell, B., Carter, J. L., Brice, R., Woelk, D., & Rusinkiewicz, M. (2006). Any time, anywhere computing: Mobile computing concepts and technology. Springer. [Google Scholar] [Crossref]

27. Henseler, J., Ringle, C. M., & Sarstedt, J. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8 [Google Scholar] [Crossref]

28. Hole, Y., Pawar, M. S., & Khedkar, E. B. (2019). Omni channel retailing: An opportunity and challenges in the Indian market. Journal of Physics: Conference Series, 1362(1), 012121. https://doi.org/10.1088/1742-6596/1362/1/012121 [Google Scholar] [Crossref]

29. Huang, S., Potter, A., & Eyers, D. (2020). Social media in operations and supply chain management: State-of-the-art and research directions. International Journal of Production Research, 58(6), 1893–1925. https://doi.org/10.1080/00207543.2019.1636329 [Google Scholar] [Crossref]

30. Ivanov, D., Dolgui, A., & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829–846. https://doi.org/10.1080/00207543.2018.1488100 [Google Scholar] [Crossref]

31. Jiang, W. (2019). An intelligent supply chain information collaboration model based on internet of things and big data. IEEE Access, 7, 58324–58335. https://doi.org/10.1109/ACCESS.2019.2914450 [Google Scholar] [Crossref]

32. Kilay, A. L., Simamora, B. H., & Putra, D. P. (2022). The influence of e-payment and e-commerce services on supply chain performance: Implications of open innovation and solutions for the digitalization of Indonesia’s MSMEs. Journal of Open Innovation: Technology, Market, and Complexity, 8(3), 119. https://doi.org/10.3390/joitmc8030119 [Google Scholar] [Crossref]

33. Kraus, S., Jones, P., Kailer, N., Weinmann, A., Chaparro-Banegas, N., & Roig-Tierno, N. (2021). Digital transformation: An overview of the current state of the art of research. Sage Open, 11(3), 21582440211047576. https://doi.org/10.1177/21582440211047576 [Google Scholar] [Crossref]

34. Lal, M., Shukla, C., & Tarangini. (2018). Study of effectiveness of POS data in managing supply chain. Industrial Engineering Journal, 11(10), 1–9. [Google Scholar] [Crossref]

35. Li, G., Yang, H., Sun, L., & Sohal, A. S. (2009). The impact of IT implementation on supply chain integration and performance. International Journal of Production Economics, 120(1), 125–138. https://doi.org/10.1016/j.ijpe.2008.07.021 [Google Scholar] [Crossref]

36. Lin, S. Y., Cheng, X., Zhang, J., Yannam, J. S., Barnes, A. J., Koch, J. R., ... & Xue, H. (2023). Social media data mining of antitobacco campaign messages: Machine learning analysis of Facebook posts. Journal of Medical Internet Research, 25, e42863. https://doi.org/10.2196/42863 [Google Scholar] [Crossref]

37. Makudza, F., Mugarisanwa, C., & Siziba, S. (2020). The effect of social media on consumer purchase behaviour in the mobile telephony industry in Zimbabwe. Dutch Journal of Finance and Management, 4(2), em0065. https://doi.org/10.29333/djfm/8444 [Google Scholar] [Crossref]

38. Markoska, K., Ivanochko, I., & Gregus, M. (2017). Mobile banking services—Business information management with mobile payments. In Agile Information Business: Exploring Managerial Implications (pp. 125–175). Springer. https://doi.org/10.1007/978-981-10-5036-8_7 [Google Scholar] [Crossref]

39. Mashayekhy, Y., Babaei, A., Yuan, X. M., & Xue, A. (2022). Impact of Internet of Things (IoT) on inventory management: A literature survey. Logistics, 6(2), 33. [Google Scholar] [Crossref]

40. https://doi.org/10.3390/logistics6020033 [Google Scholar] [Crossref]

41. Moyo, T., Proches, C. G., Mutambara, E., & Singh, U. G. (2022). The nexus between Twitter as a social blog and social capital in corporate reputation behaviour for the Zimbabwe telecommunications industry. Gender and Behaviour, 20(1), 18827–18851. [Google Scholar] [Crossref]

42. Ndurura, N. (2020). The significance of social media as a marketing tool. International Journal of Business and Environmental Studies, 7(1), 12–26. [Google Scholar] [Crossref]

43. Ojo, A. J., & Ajayi, A. P. (2024). Integration of the supply chain and its impact on performance among retailers in Ilorin Metropolis, Nigeria. Journal of Innovations, 75(6), 1124–1132. [Google Scholar] [Crossref]

44. Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform revolution: How networked markets are transforming the economy, and how to make them work for you. W. W. Norton & Company. [Google Scholar] [Crossref]

45. Pattnaik, P. K., & Mall, R. (2015). Fundamentals of mobile computing. PHI Learning Pvt. Ltd. [Google Scholar] [Crossref]

46. Raji, M. A., Olodo, H. B., Oke, T. T., Addy, W. A., Ofodile, O. C., & Oyewole, A. T. (2024). Real-time data analytics in retail: A review of USA and global practices. GSC Advanced Research and Reviews, 18(3), 59–65. https://doi.org/10.30574/gscarr.2024.18.3.059 [Google Scholar] [Crossref]

47. Ramanathan, U., Subramanian, N., & Parrot, G. (2018). The role of social media in retail network operations and marketing to enhance customer satisfaction. International Journal of Operations & Production Management, 37(1), 105–123. https://doi.org/10.1108/IJOPM-03-2016-0150 [Google Scholar] [Crossref]

48. Rishi, N., & Tiwari, M. (2024). Navigating the dynamics of online consumer behaviour: Insights for e-commerce strategies in India and globally. International Journal of Innovative Research in Technology and Science, 12(2), 453–463. [Google Scholar] [Crossref]

49. Rogers, D. L. (2016). The digital transformation playbook: Rethink your business for the digital age. Columbia University Press. [Google Scholar] [Crossref]

50. Saengchai, S., & Jermsittiparsert, K. (2019). Improving sustainability performance through Internet of Things capability in Thailand: Mediating role of IoT-enabled supply chain integration. International Journal of Supply Chain Management, 8(5), 572–584. [Google Scholar] [Crossref]

51. Satyanarayanan, M. (2011). Mobile computing: The next decade. ACM SIGMOBILE Mobile Computing and Communications Review, 15(2), 2–10. https://doi.org/10.1145/1924281.1924283 [Google Scholar] [Crossref]

52. Shankar, V., Kalyanam, K., Setia, P., Golmohammadi, A., Tirunillai, S., Douglass, T., & Waddoups, R. (2021). How technology is changing retail. Journal of Retailing, 97(1), 13–27. [Google Scholar] [Crossref]

53. https://doi.org/10.1016/j.jretai.2020.10.006 [Google Scholar] [Crossref]

54. Tarigan, Z., Jiputra, J., & Siagian, H. (2021). The effect of supply chain practices on retailer performance with information technology as a moderating variable. International Journal of Data and Network Science, 5(1), 47–54. https://doi.org/10.5267/j.ijdns.2020.9.004 [Google Scholar] [Crossref]

55. Tiwari, S. (2021). Supply chain integration and Industry 4.0: A systematic literature review. Benchmarking: An International Journal, 28(3), 990–1030. https://doi.org/10.1108/BIJ-08-2020-0419 [Google Scholar] [Crossref]

56. Waheed, A., Zhang, Q., Farrukh, M., & Khan, S. Z. (2021). Effect of mobile social apps on consumer’s purchase attitude: Role of trust and technological factors in developing nations. Sage Open, 11(2), 21582440211006714. https://doi.org/10.1177/21582440211006714 [Google Scholar] [Crossref]

57. Zafar, B., & Younis, M. (2020). Social media influence on consumer behavior: Insights from supermarket shoppers in Lahore. Journal of Business and Economic Options, 3(2), 65–71. [Google Scholar] [Crossref]

58. Zu, Q., Sarkis, J., & Lai, K. H. (2013). Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. Journal of Purchasing and Supply Management, 19(2), 106–117. https://doi.org/10.1016/j.pursup.2012.11.001 [Google Scholar] [Crossref]

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