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Factors Influencing Sustainable Supplier Selection: Evidence from Palm Oil Refining and Oleochemical Manufacturing Industry Vijayakumaran, Suresh Anand; Abdul Rahim, Suzari; Ahmi, Aidi; Abdul Rahman, Nor Aida; Mazlan, Ahmad Uzair
International Journal of Supply Chain Management Vol 9, No 1 (2020): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (340.665 KB)

Abstract

This study focuses on the sustainable supplier selection in Malaysia palm oil refining and oleochemical manufacturing industry. A sustainable supply chain could lead to smoothness in the long run and thus ensure higher excellence and productivity. It is important to have suppliers that adapt to the sustainability nature of the organisation in order for the entire supply chain to be productive. The independent variables which have been used for this study are the unit price, CSR engagement, and environmental competencies. The leading theory used to support this study is the triple bottom line theory and backed by the resource dependency theory and stakeholder’s theory. This study was aided by surveying 151 respondents who are directly from palm oil refining and oleochemical manufacturing sector, which is the population for this study. After using the statistical tools to analyse the data retrieved from the questionnaires, it has been inferred that the unit price, quality, and environmental competencies have a significant effect on the dependent variable whereas CSR Engagement does not have a significant relationship. This study highlights the implication in the form of theoretical and social perspectives. It concludes with the limitation and the future recommendation of sustainable supplier selection in Malaysia palm oil refining and oleochemical manufacturing industry.
The Impact of Employee Job Satisfaction on Dynamic Capability: The Mediating Role of Turnover Intention Irawati, Marsha Ayunita; Hartarini, Yovita Mumpuni; Khayatun, Siti; Ahmi, Aidi
JDM (Jurnal Dinamika Manajemen) Vol 15, No 1 (2024): March 2024
Publisher : Department of Management, Faculty of Economics and Business, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jdm.v15i1.49018

Abstract

This study aims to analyze three concepts, employee job satisfaction, dynamic capability, and turnover intention, without separating these three concepts by analyzing the effect of employee job satisfaction on dynamic capability and turnover intention as mediation. This research is correlative quantitative research with a cross-sectional approach for employees in Indonesia and uses SEM-PLS to analyze the data. The study results show that employee satisfaction has a negative and significant effect on turnover intention, and turnover intention has a negative and significant effect on dynamic capability; including the mediation variable in this study shows that turnover intention could mediate between employee satisfaction and dynamic capabilities. From the result, this research could be a starting point for developing flexible work program strategies and measures, as well as the implications in the changing business environment, especially in the digital era or situations that cause rapid changes quickly, like urgent situations or even uncertainty and contribute to further research discussing these three concepts.
Leveraging Bibliometrics and AI: Empowering Islamic Studies Scholars to Uncover Emerging Topics and Navigate Diverse Perspectives Ahmi, Aidi
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2024: Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/iseth.5355

Abstract

This study explores the transformative role of bibliometrics and artificial intelligence (AI) in advancing Islamic studies. It highlights how these tools enhance Islamic knowledge's preservation, analysis, and dissemination while fostering intellectual and economic growth aligned with Islamic principles. The paper also examines the synergy between bibliometrics and AI and their collective potential to revolutionize the study of Islamic texts and traditions. A qualitative approach was employed, synthesizing existing literature and case studies to analyze the applications of bibliometrics and AI in Islamic studies. Bibliometric analysis was used to trace research trends and identify gaps in Islamic scholarship. At the same time, the review of AI applications focused on tools such as natural language processing, semantic analysis, and digitization techniques. Challenges such as the lack of digitized Islamic texts, the underrepresentation of Muslim scholars, and ethical concerns in AI applications were critically assessed. The findings reveal that bibliometrics provides valuable insights into the intellectual landscape of Islamic studies, while AI enhances accessibility, efficiency, and precision in text analysis and heritage preservation. These technologies enable data-driven decision-making, interdisciplinary collaboration, and global dissemination of Islamic knowledge. The study identifies practical challenges and proposes solutions, such as targeted investments, training programs, and ethical frameworks, to maximize the potential of these tools. This study underscores the importance of integrating bibliometrics and AI into Islamic studies to preserve heritage, promote innovation, and address contemporary challenges. Proposing actionable recommendations offers a roadmap for scholars, industry leaders, and policymakers to responsibly embrace these technologies and ensure equitable access to their benefits. This work contributes to the growing discourse on technology's role in shaping the future of Islamic scholarship.