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STI Policy and Management Journal
Published by Lembaga Ilmu Pengetahuan Indonesia
ISSN : 19079753     EISSN : 25025996     DOI : -
Core Subject :
The STI (Science, Technology and Innovation) Policy and Management is a scientific journal discussing theoretical and practical issues in science and technology policy for economic competitiveness, research and development management and innovation management. The journal welcomes manuscripts from researchers, academics and practitioners in these areas. The Editor accepts articles and book reviews in STI policy and management. Two volumes are published in a year (July and December).
Arjuna Subject : -
Articles 255 Documents
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The Implementation of The SECI Model in Knowledge Management Adoption Within Local Governments to Foster Innovation Andhika, Lesmana Rian
STI Policy and Management Journal Vol 10, No 2 (2025): STI Policy and Management
Publisher : National Research and Innovation Agency, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/STIPM.2025.423

Abstract

This study examines the application of the SECI model of knowledge management (KM) and how it can contribute to innovation. This study uses a qualitative approach to collect data through semi-structured interviews and case studies. Interviews were conducted with 30 predetermined informants: regional leaders, SPBE (Electronic-Based Government System) managers, and employees involved in planning, implementing, and evaluating innovation (Sumedang and Aceh Tenggara Local Government). This research case study was conducted in the Banyuwangi, Aceh Jaya, and Deli Serdang Local Governments. The results of this study indicate that local governments can improve innovation and public services by creating a learning culture that supports innovation through socialization, externalization, combination, and internalization of knowledge. The recommendations of this study include training and socialization on the importance of knowledge management and creating an environment that supports collaboration. In addition, it is important to involve all stakeholders in the knowledge management planning and implementation process.
Technological Innovation, Public Trust, and Policy Strategies For A Sustainable Financial Sector: A Systematic Review Wibisono, Eristian; Nurul, Mochammad
STI Policy and Management Journal Vol 10, No 2 (2025): STI Policy and Management
Publisher : National Research and Innovation Agency, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/STIPM.2025.425

Abstract

This study aims to address a gap in the literature exploring the state of innovation in the financial industry by presenting key findings and insights from such research. Specifically, it addresses research questions related to the experiences and determinants of successful implementation of financial innovation in different countries, the underlying challenges that often arise, and solutions to overcome them. A systematic literature review (SLR) method was used to explore and investigate the research problem by applying three main protocols: scoping the literature, selecting and retrieving the most relevant articles, and critically reviewing the selected articles. The results of the current study indicate that studies related to financial innovation have grown significantly and are published in medium to high-quality literature sources, but much effort is still needed to bring this topic to a more mature stage. A critical review of previous research results in three main propositions contributing to this study. These include factors that facilitate successful financial innovation, overcoming challenges related to public trust, and policy strategies for sustainable financial innovation.
Revisiting the Stimulus, Organism, Response Model in AI-Driven Tourism: A Multi-Path Analysis of Personalization, Perception, and Privacy Hasanuddin, Arnas; Hasanuddin, Achmad Ansari; Hasanuddin, Askari; Baharuddin, Sitti Mujahida
STI Policy and Management Journal Vol 10, No 2 (2025): STI Policy and Management
Publisher : National Research and Innovation Agency, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/STIPM.2025.428

Abstract

This study revisits the Stimulus, Organism, Response (S-O-R) model to examine the psychological mechanisms underlying tourists’ responses to AI-based personalization on digital tourism platforms. Drawing on a sample of 360 Indonesian respondents collected via online survey, the research investigates how AI-driven personalization influences three organismic states perceived value, trust, and privacy concern and how these states affect tourists’ behavioral intentions. Using partial least squares structural equation modeling (PLS-SEM), the results reveal that personalization significantly enhances perceived value and trust, while also reducing privacy concern. Each of these organismic responses, in turn, significantly shapes behavioral intention, confirming the relevance of the extended S-O-R framework in the AI tourism context. Theoretically, the study contributes to tourism literature by integrating both positive and negative psychological reactions into a unified explanatory model, highlighting personalization’s dual role as both functional and ethical stimulus. Practically, the findings offer insights for tourism platforms to design AI services that are not only adaptive and efficient but also transparent and trust-enhancing. Limitations include the study’s cross-sectional design and geographic concentration, pointing to future research directions involving longitudinal analysis, cross-cultural comparisons, and exploration of moderating variables such as digital literacy and cultural norms.
Enhancing Talent Retention Through AI-Driven Employer Branding: The Mediating Role of Recruitment Marketing and The Moderating Effect of AI-Powered Personalization Isrososiawan, Safroni; Azizurrohman, Muhammad; Pramuja, Risky Angga
STI Policy and Management Journal Vol 10, No 2 (2025): STI Policy and Management
Publisher : National Research and Innovation Agency, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/STIPM.2025.414

Abstract

The adoption of artificial intelligence (AI) in human resource management is transforming employer branding, recruitment marketing, and talent retention. This study examines how AI-driven employer branding enhances recruitment marketing effectiveness and improves retention, considering the roles of technological readiness, organizational culture, and strategic HR practices. Using Structural Equation Modeling - Partial Least Squares (SEM-PLS) with data from 312 HR professionals and employees across Indonesia, Taiwan, Malaysia, Singapore, the United States, the United Kingdom, and Germany, the findings confirm that AI-driven employer branding positively influences recruitment marketing and retention. The mediation analysis reveals that recruitment marketing partially mediates this relationship, while the moderation analysis shows that AI-powered personalization strengthens the impact of recruitment marketing on retention. These findings highlight the need for organizations to strategically integrate AI in employer branding and recruitment to improve hiring outcomes. This study advances theoretical insights into AI adoption in HRM by demonstrating its influence on branding strategies. From a managerial perspective, the results emphasize the importance of balancing AI automation with human interaction. Despite its cross-sectional limitations, future research should explore longitudinal impacts and ethical considerations in AI-driven recruitment. Organizations must adopt personalized, data-driven AI solutions to enhance employer branding and retention in the evolving job market
Balancing AI’s Promise and Pressure: A Dual-Process Model of AI Adoption Psychological States, and Employee Performance in Indonesia Asmini, Asmini
STI Policy and Management Journal Vol 10, No 2 (2025): STI Policy and Management
Publisher : National Research and Innovation Agency, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/STIPM.2025.429

Abstract

This study investigates how artificial intelligence (AI) adoption affects employee performance through two competing psychological mechanisms: a positive pathway involving technological self-efficacy and job engagement, and a negative pathway involving perceived job insecurity and AI-induced stress. Drawing on data from 280 Indonesian employees across diverse sectors, the study employs structural equation modeling using SmartPLS to examine the hypothesized relationships. The findings confirm the dual-process model, showing that AI adoption positively influences performance by enhancing confidence in technology use and fostering engagement. However, the results also reveal that AI adoption can trigger job insecurity and psychological stress, which in turn negatively impact employee performance. Both sequential mediations positive and negative are statistically significant, emphasizing the coexistence of opportunity and risk in AI-driven transformation. These results contribute to theory by integrating cognitive-motivational and emotional-threat perspectives within the same framework. Practically, the study highlights the importance of organizational strategies that simultaneously empower employees through digital skill development while mitigating fears and emotional strain associated with technological disruption. The findings are particularly relevant to emerging economies like Indonesia, where rapid AI diffusion is not always matched by institutional protections or workforce readiness. Recommendations for inclusive, human-centered AI implementation are discussed

Page 26 of 26 | Total Record : 255

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