Improving Inclusivity of Digitalization for Employees in Emerging Countries Using Gamification

Behl, Abhishek; Pereira, Vijay; Sindhwani, Rahul; Bhardwaj, Shikha; Papa, Armando; Hassan, Yusuf

Abstract

Digitalization has transformed businesses, especially during the ongoing pandemic. Firms have gradually moved to digital ecosystems and e-marketplaces. Digital transformation (DT) has helped firms improve profit margins, better engage customers, improve productivity, and reduce any functional and operational lags. While some firms have strategically transformed themselves in the digital space, others have adopted technology in an unstructured way. As a result, these firms’ employees have been exposed to sets of new technologies. While some have adopted them based on their past experience, others have perceived them as challenges and have resisted change. This brings us to an important question of whether the DT is inclusive. In this article, the hedonic motivation system adoption model (HMSAM) and flow theory were used to investigate the inclusivity of DT and to propose a modified HMSAM model. As part of in their respective firms’ DT process, employees are exposed to a gamified environment. This article collected data from retail sector employees based in an emerging nation and tested hypotheses using structured equation modeling.

Citation

Behl, A., Pereira, V., Sindhwani, R., Bhardwaj, S., Papa, A., & Hassan, Y. (2024). Improving Inclusivity of Digitalization for Employees in Emerging Countries Using Gamification. IEEE Transactions on Engineering Management, 1-15. https://doi.org/10.1109/TEM.2022.3216553

• Journal Article Type: Article
• Acceptance Date: Oct 17, 2022
• Online Publication Date: Nov 7, 2022
• Publication Date: 2024
• Deposit Date: Jun 24, 2024
• Journal: IEEE Transactions on Engineering Management
• Print ISSN: 0018-9391
• Electronic ISSN: 1558-0040
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• Pages: 1-15
• DOI: https://doi.org/10.1109/TEM.2022.3216553
• Public URL: https://keele-repository.worktribe.com/output/855851