Producción Científica

Systemic disruptions are becoming more continuous, intense, and persistent. Their effects have a severe impact on the economy in volatile, uncertain, complex, and ambiguous (VUCA) environments that are increasingly transversal to productive sectors and activities. Researchers have intensified their academic production of multiple-criteria decision-making (MCDM) in recent years. This article analyzes the research agenda through a systematic review of scientific articles in the Web of Science Core Collection according to the Journal Citation Report (JCR), both in the Social Sciences Citation Index (SSCI) and in the Science Citation Index Expanded (SCIE). According to the selected search criteria, 909 articles on MCDM published between 1979 and 2022 in Web of Science journals in the business and management categories were located. A bibliometric analysis of the main thematic clusters, the international collaboration networks, and the bibliographic coupling of articles was carried out. In addition, the analysis period is divided into two subperiods (1979-2008 and 2009-2022), establishing 2008 as the threshold, the year of the Global Financial Crisis (GFC), to assess the evolution of the research agenda at the beginning of systemic disruptions. The bibliometric analysis allows the identification of the motor, basic, specialized, and emerging themes of each subperiod. The results show the similarities and differences between the academic debate before and after the GFC. The evidence found allows academics to be guided in their high-impact research in business and management using MCDM methodologies to address contemporary challenges. An important contribution of this study is to detect gaps in the literature, highlighting unclosed gaps and emerging trends in the field of study for journal editors.

Circular economy has emerged as a way to achieve sustainability. Although interest in the subject is growing rapidly, barriers to its implementation are still in place. In this study, a number of barriers are identified and grouped through a content analysis. The present article adopted bibliometric research as a methodological approach. The research method combined bibliometric, networks and content analysis. The sample is composed of 195 articles extracted from the Web of Science Core Collection and Scopus databases. The main barriers identified in the literature were: (i) technological, (ii)policy and regulatory, (iii) financial and economic, (iv) managerial, (v) performance indicators, (vi) customer and (vii) Social. (C) 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 10th CIRP Conference on Industrial Product-Service Systems.

In this study, we examined the extant literature on the dynamic association between oil prices and financial assets with special emphasis on the methodologies for measuring the dependence among oil prices, exchange rates, stock prices, energy markets, and assets related to sustainable finance. We performed a scientometric review of the structure and global trends of the dynamic association among oil prices and financial assets, based on research from 1982 to 2022 (September) using techniques such as the analysis of (i) sources, (ii) authors, (iii) documents, and (iv) cluster analysis. A total of 746 bibliographic records from Scopus and Web of Science databases were analyzed to generate the study’s research data through scientometric networks. The findings indicate that the most promising areas for further research in this field are represented by co-movement, copula, wavelet, dynamic correlation, and volatility analysis. Furthermore, energy markets and assets related to sustainable finance emerge as crucial trends in investigating dynamic co-movements with oil prices. They also suggest a research gap in analyzing by means of machine learning, deep learning, big data, and artificial intelligence for measuring dynamic co-movements among oil prices and assets in financial and energy markets, especially in emerging countries. Thus, these methodologies can be implemented in further research because these methods could more robustly quantify the association among such variables. The analysis provides researchers and practitioners with a comprehensive understanding of the existing literature and research trends on the dynamic association among oil prices and financial assets. It also promotes further studies in this domain. The identification of these relations presents benefits in risk diversification, hedges, speculation, and inflation targeting.