Producción Científica

The journal of Operations Management Research (OMR) is a rigorous journal that started its publication in 2008. It publishes short, focused research studies that advance both the theory and practice of operations management. Considering the relevant OMR’s contribution to the field of Operations Management in the last years, this study provides an overall assessment of the journal performance by conducting a retrospective review. To elaborate on OMR’s temporal development in terms of publications, authors, affiliated institutions and countries, citation patterns, and conceptual structure, we extract publications from Scopus database for the period 2008–2020. We rely on bibliometric techniques in addition to bibliographic coupling, keyword analysis, and content analysis. 166 documents were analyzed using RStudio, VOSviewer, and Microsoft Excel. Findings emphasize OMR’s steady productivity growth (3.24%). Narrowly, Olhager J. is the most productive authors while Kalchschmidt M. and Stentoft J. are the most influential authors (H-index of 4). Furthermore, USA contributes to the highest number of publications while UK is the most influential country in terms of citations. Cranfield School of Management, UK stands as the top cited university. The analysis of the thematic evolution concludes to three main clusters: “Manufacturing and Supply chain Performance”, “Six Sigma and Lean Management”, and “Reshoring, Backshoring and Offshoring”. This study recommends to further investigate the implications of the fourth industrial revolution and the sequels of COVID-19.

This study aims to analyse the literature regarding the characteristics of Industry 4.0 in the context of operations management. The analysis covers the evolution of publications over time, the countries involved, the most prolific journals, the most cited authors, and the identification of the most frequent words that can generate insights for the research agenda. A total of 235 articles published between 2011 and 2017 were collected through an automated process from the Scopus and Web of Science databases and later analysed using data mining, bibliometric indicators analysis, clusters analysis, networks analysis, and word cloud. The bibliographic analysis explained the interaction between the various concepts and techniques associated with the central theme. These concepts and respective characteristics discussed allow an understanding and the development of agenda with theoretical possibilities to fill current research gaps.

Military innovations have historically driven technological development and industry innovation. This research focuses on Industry 4.0 technologies and their relationship with the development of military applications in the current context. A literature review and a bibliometric study using Bibliometrix evidence the relationship between the multidimensional difficulties in implementing technologies and the scarce research in these fields. Compared to more developed countries, there are wide technological gaps in Latin America, generating a strong technological dependence. Thus, it is concluded that research and innovation in Industry 4.0 and its military applications is a strategic opportunity for Latin America, as it can boost the region’s technological, economic, and social development.

This paper reports a second-order structural equation model composed of four variables: the green attributes before and after an industrial production process, the operating benefits, the commercial benefits, and the economic benefits. The variables are related by means of five hypotheses and are validated statistically with information obtained from 559 responses to a questionnaire applied to the Mexican maquila industry. The model is evaluated using the technique of partial least squares and the results obtained indicate that the green attributes before and after the production process have a direct and positive effect on the obtained benefits, mostly on the operational ones. It is concluded that companies that are focused on increasing their greenness level must monitor and evaluate the existence of green attributes in their production process to guarantee benefits and make fast decisions if required due to deviations.