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All Journal Ranah Research : Journal of Multidisciplinary Research and Development
Novi Sofia Fitriasari
Universitas Indonesia, Depok, Indonesia
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Transportation Other

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A Socio-Technical Model of Knowledge Sharing and Discovery in Social Fitness Apps among Indonesian Users: A PLS-SEM Approach Tijani Putri Shabrina; Abdurrohhim Syahruromadhon; Dana Indra Sensuse; Sofian Lusa; Novi Sofia Fitriasari; Icha Mailinda
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 8 No. 3 (2026): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v8i3.2094

Abstract

Social fitness applications such as Strava, Nike Run Club, and Garmin Connect have turned exercise tracking into a community-based activity where users exchange tips, experiences, and performance data. However, little is known about what drives users to share and discover knowledge on these platforms. This study proposes and tests a socio-technical model that explains knowledge sharing and discovery behaviour in social fitness apps. The model integrates Social Capital Theory, the Technology Acceptance Model, and the Theory of Planned Behavior. Data was collected from 57 active users of social fitness applications and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that perceived usefulness, structural social capital, and perceived behavioural control significantly influence users’ intentions, while attitude and cognitive social capital do not play a major role. Intention, in turn, strongly predicts actual knowledge sharing and discovery behaviour. These findings suggest that knowledge-related actions in social fitness communities are driven mainly by functional benefits, connectedness within the community, and users’ sense of capability, rather than by evaluative attitudes alone. The study offers a clearer view of how socio-technical factors work together in digital fitness ecosystems and provides a basis for future research on knowledge behaviour in online communities
AI-Driven Knowledge Sharing in the Banking Sector: Challenges and Approaches Nerissa Arviana; Afina Putri Dayanti; Dana Indra Sensuse; Sofian Lusa; Icha Mailinda; Novi Sofia Fitriasari
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 8 No. 4 (2026): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v8i4.2121

Abstract

Digitalization is becoming increasingly relevant for banking, hence the necessity for a practical Knowledge Management (KM) system that can facilitate rapid innovation and ensure proper regulatory compliance. While there is growing recognition of KM as a strategic driver of performance, it is implemented in a fragmented way within financial institutions and limited by technology, organizational and governance barriers. This paper presents a Systematic Literature Review (SLR) following the PRISMA 2020 protocol, aiming to identify, evaluate and synthesize the academic literature published between 2020 and 2025 on the integration of AI and KM in the banking context. Forty primary studies were examined via narrative synthesis to address two research inquiries: the challenges of AI-driven knowledge sharing (RQ1) and AI-based methodologies and best practices that enhance knowledge management processes (RQ2). The findings identify three main challenge domains data and technology infrastructure, organizational and human factors, and governance, security, and ethics constraints and six main solution categories, including NLP, machine learning, knowledge graphs, expert systems, human-AI hybrid collaboration, and ethical AI governance frameworks. These findings lead to the idea that the use of AI improves the accessibility of knowledge, learning and creativity and its efficiency depends on the capacity of the appropriate KM, absorptive capacity and maturity of governance. The study offers a cohesive framework linking AI innovation to organizational knowledge performance within the finance sector.
Co-Authors Abdurrohhim Syahruromadhon Afina Putri Dayanti Dana Indra Sensuse Icha Mailinda Nerissa Arviana Sofian Lusa Tijani Putri Shabrina