Article Per Year (5 Year)
p-Index From 2021 - 2026
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All Journal Journal of Management and Business Innovation (JOMBINOV)
Andrias U. T. Anabuni
Kupang State Polytechnic
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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An Integrated Innovation DiffusionTrust-Building Framework for Understanding Mobile Payment Adoption in Indonesia’s Cross-Border Regions Klaasvakumok J. Kamuri; Andrias U. T. Anabuni
Journal of Management and Business Innovation Journal of Management and Business Innovation (JOMBINOV): Volume 01, No 01, December 2025
Publisher : CV. Vocezmi Learnov

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65792/jombinov.v1i01.30

Abstract

Mobile payment adoption in Indonesia has expanded rapidly; however, its diffusion in cross-border regions remains limited due to infrastructural inadequacies, heightened cross-border transaction risks, and low levels of trust in digital financial platforms. These regions—marked by high population mobility, informal economic activity, and uncertain regulatory oversight—create a unique context in which conventional technology adoption models may not fully capture user behaviour. This study introduces an integrated framework that combines Innovation Diffusion Theory and Trust-Building Theory to investigate how mobility, customization, security, and reputation shape trust and influence mobile payment adoption in Indonesia’s international border areas. The framework further examines the role of trust in mitigating perceived risk and strengthening continuance usage intention, while also assessing gender as a moderating variable. Data were obtained from 225 mobile payment users residing in major border gateways between Indonesia and Malaysia, Timor-Leste, and Papua New Guinea. Using partial least squares structural equation modelling (PLS-SEM), the results indicate that security, customization, and reputation significantly enhance trust, whereas mobility does not exert a meaningful effect within the border context. Trust substantially increases continuance usage intention and reduces perceived risk; however, perceived risk does not significantly influence continuance intention. Gender is also found to have no moderating effect on any of the hypothesized relationships. This study contributes to the mobile payment literature by providing a contextualized understanding of user behaviour in high-risk, infrastructure-constrained environments. It also offers practical implications for policymakers and fintech providers aiming to expand digital financial inclusion and strengthen trust-based payment ecosystems in Indonesia’s cross-border regions.
Artificial Intelligence and the Ethical Boundaries of Managerial Judgment: Insights from a Systematic Literature Review Irience R. A. Manongga; Andrias U. T. Anabuni
Journal of Management and Business Innovation Journal of Management and Business Innovation (JOMBINOV): Volume 02, No 01, March 2026
Publisher : CV. Vocezmi Learnov

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65792/jombinov.v2i01.33

Abstract

This research aims to systematically analyze the utilization of Artificial Intelligence (AI) in various Human Resource Management (HRM) functions, evaluate the theoretical foundations used in previous studies, summarize key empirical findings, and identify research gaps and emerging ethical-managerial implications. The research uses a Systematic Literature Review (SLR) design with a PRISMA approach. Data was collected from the Scopus, Web of Science, and Google Scholar databases for reputable journal articles published between 2015 and 2025. The selection process was conducted through the stages of identification, screening, and eligibility based on strict inclusion and exclusion criteria, resulting in 52 articles that were analyzed using thematic analysis and conceptual synthesis. Theoretically, this research enriches the technology-based HRM literature by presenting a typology of AI utilization in HRM functions and revealing the limitations of the theoretical framework, which is still partial and fragmented in previous studies. The research findings have strategic implications for practitioners and policymakers in ethically, responsibly, and sustainably integrating AI into HRM practices, particularly in the context of recruitment and selection, performance analytics, talent management, and data-driven HR decision-making. The limitations of this study lie in its reliance on secondary data sources and the dominance of studies focused on developed country contexts. This situation opens opportunities for further research that is empirical, longitudinal, and contextual, particularly in developing countries.
Co-Authors Irience R. A. Manongga Klaasvakumok J. Kamuri