The European Union has converted domestic climate ambition into a form of global regulatory power through the European Union Emissions Trading System (EU ETS), the Carbon Border Adjustment Mechanism (CBAM), and the European Union Deforestation Regulation (EUDR). This qualitative literature review examines whether that emerging Brussels-centred carbon order can remain environmentally effective and politically legitimate when its adjustment costs are disproportionately borne by developing economies. Drawing on journal literature published mainly since 2020, the article synthesizes scholarship on global carbon politics, the Brussels Effect, carbon leakage, border adjustment, deforestation-free supply chains, climate justice, and the right to development. It finds that EU instruments can stimulate cleaner production and improve supply-chain transparency, but also transmit measurement, reporting, verification, traceability, certification, and financing costs down value chains in regressive ways. These effects can operate as non-tariff barriers even when the measures pursue legitimate environmental objectives and are formally imposed on EU importers. Palm oil illustrates the problem clearly: although palm oil is not a CBAM commodity, EUDR and related European sustainability rules can exclude smallholders whose environmental performance may be acceptable but whose land records, geolocation data, or chain-of-custody systems remain incomplete. The article argues that durable global carbon governance requires more than unilateral diffusion of European rules. It proposes an inclusive compact based on co-design, differentiated obligations, recognition of equivalent policies, revenue recycling, technology transfer, smallholder-centred traceability, and accessible review mechanisms. Climate leadership will command followers only when decarbonization is aligned with distributive justice and credible development pathways.
Loso Judijanto· Journal on Political Science...· 0 citations
Green data centers have become a central concern in computing infrastructure management as organizations pursue energy efficiency alongside environmental sustainability. In this study, an attempt is made to conduct a bibliometric analysis to investigate the intellectual structure, research trends, key contributors, and emerging themes in green data center and computing energy efficiency scholarship. The data were collected from the Scopus database using keywords “green data center”, “green computing”, and “energy efficiency” and analyzed using VOSviewer to conduct co-occurrence analysis, citation analysis, co-authorship analysis, institutional collaboration analysis, and country collaboration mapping. The results show that green computing, energy efficiency, and data centers form the core themes linked with cloud computing, virtual machine consolidation, cooling systems, and renewable energy integration. Based on citation analysis, key contributions such as energy-aware resource allocation heuristics, dynamic virtual machine consolidation algorithms, and thermal-aware cooling strategies significantly influence the field. The collaboration analysis demonstrates that the United States, China, India, and the United Kingdom serve as major contributors to the global research network, supported by a small group of highly prolific scholars, while institutional affiliation reporting across the field remains fragmented and generically labeled. Furthermore, thematic evolution indicates a transition from infrastructure-level cooling and consolidation concerns toward machine-learning-driven scheduling and carbon-aware resource management. This study contributes by providing comprehensive mapping of green data center research development and identifying critical research gaps for future scholarship, particularly in integrating renewable energy with intelligent workload orchestration.
Loso Judijanto, Tina Isnaeni, Rani Eka Arini· West Science Social and Huma...· 0 citations
Human capital has become a fundamental concept in explaining economic development, organizational competitiveness, innovation capability, and sustainable growth. However, the evolution of research themes, intellectual structures, and emerging directions within human capital studies remains fragmented across different disciplines. This study aims to examine the development and research landscape of human capital through a bibliometric analysis approach. Data were collected from the Scopus database using relevant search terms related to human capital, and the retrieved publications were analyzed using bibliometric techniques, including performance analysis, citation analysis, co-authorship analysis, keyword co-occurrence analysis, and thematic evolution mapping. The findings reveal that human capital research has experienced significant growth and has developed into a multidisciplinary field involving economics, management, entrepreneurship, education, innovation, and sustainability. The citation analysis identifies influential studies focusing on entrepreneurship, psychological capital, strategic management, and sustainable competitive advantage, while the keyword analysis demonstrates a transition from traditional themes such as education, employment, and productivity toward emerging themes including innovation, intellectual capital, social capital, and sustainable development. Furthermore, collaboration analysis highlights the dominant contribution of institutions and countries from North America, Europe, and Asia in shaping global human capital research. This study contributes to the literature by providing a comprehensive understanding of the intellectual evolution of human capital research and identifying future research opportunities related to digital capabilities, green human capital, and adaptive workforce development.
Loso Judijanto, Paramita Andiani, Ilham Akbar Bunyamin· West Science Journal Economi...· 0 citations
With the rise of importance of digital platform use, social media interaction and online consumer activities in decision-making and brand perception processes, Electronic Word-of-Mouth (e-WOM) becomes one of the active fields for scholarly investigations. In order to study the intellectual structure, research development and trends in e-WOM literature, the present study used a bibliometric analysis method. The data was gathered from academic database entries of scientific publications and were analyzed using bibliometric methods, such as citation analysis, co-authorship analysis, keyword co-occurrence analysis, thematic mapping and trends analysis. It was found out that the research on e-WOM was gradually shifting from the issues of consumer motivation, online reviews, and credibility of information towards more general issues like social media, user generated content, purchase intention, brand image and digital consumer behavior. Citation analysis allows identifying fundamental research papers that shaped this field to a great extent, especially in terms of e-WOM adoption, credibility and consumer involvement in it. The cooperation analysis shows that despite the global development of e-WOM research, the fragmentation of authorship, institutionality and inter-country collaboration still exists. Additionally, the thematic evolution proves that modern researches in the area of e-WOM is gradually shifting towards the issues of digital platforms, social media marketing, sentiment analysis and data-driven consumer insights. The present study provides a comprehensive look into the evolution and knowledge base of e-WOM research and defines the possible directions of future research related to artificial intelligence, influencer communication, recommendation algorithms and digital trust.
Loso Judijanto, S. Sari, Tina Isnaeni· West Science Journal Economi...· 0 citations
The rapid advancement of artificial intelligence (AI) has transformed decision-making processes across various domains by enabling data-driven insights, predictive capabilities, and intelligent automation. This study aims to examine the development, intellectual structure, and emerging trends of research on AI-based decision analytics through a bibliometric analysis approach. Data were collected from the Scopus database using relevant search terms related to artificial intelligence and decision analytics. The study applies bibliometric techniques, including performance analysis, citation analysis, co-authorship analysis, keyword co-occurrence analysis, thematic evolution analysis, and density visualization using VOSviewer. The findings indicate that artificial intelligence, machine learning, deep learning, and clinical decision support systems represent the dominant research themes shaping this field. Highly cited studies demonstrate increasing scholarly attention toward ethical considerations, explainability, transparency, and trust in AI-driven decision systems. The collaboration analysis reveals that research development is supported by extensive international networks, with countries such as Germany, the United States, India, and China serving as influential contributors. Furthermore, the temporal analysis indicates a shift from algorithm-focused research toward human-centered and responsible AI applications. This study contributes to the literature by providing a comprehensive mapping of AI-based decision analytics research and identifying future directions related to explainable AI, trustworthy decision systems, and interdisciplinary applications across healthcare, business, and other complex decision environments.
Loso Judijanto, Hanifah Nurul Muthmainah· West Science Information Sys...· 0 citations
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