https://bjopm.org.br/bjopm/issue/feedBrazilian Journal of Operations & Production Management2024-10-05T00:00:00-03:00Editorial Team (BJO&PM)bjopm.journal@gmail.comOpen Journal Systems<div align="justify"> <div class="gmail_default"><span style="color: #000000; font-family: 'comic sans ms', sans-serif;">The Brazilian Journal of Operations & Production Management (BJO&PM), ISSN (Online): 2237-8960, is an international and open-access journal that providing a platform for publishing applied researches. As an open access journal, articles in BJO&PM will always be freely available online and readily accessible. This means that your work will be recognized and can be searched in Google Scholar, Sumários.org, Diadorim and Web of Knowledge. The journal is dedicated towards dissemination of knowledge related to the advancement in scientific research.</span></div> <div class="gmail_default"> </div> <div class="gmail_default"><span style="color: #000000; font-family: 'comic sans ms', sans-serif;">BJO&PM promote and disseminate the knowledge by publishing original research findings, review articles and short communications in the broad field of Engineering. The BJO&PM welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published approximately after acceptance. All articles published in BJO&PM will be peer-reviewed. </span></div> <div class="gmail_default"> </div> <div class="gmail_default">Brazilian Journal of Operations and Production Management (ISSN (Online): 2237-8960) is a Journal of <a href="http://www.abepro.org.br/indexsub.asp?ss=40" target="_blank" rel="noopener"> ABEPRO - Brazilian Association of Production Engineering</a>. BJO&PM mission is to provide an internationally respected stream for original and relevant research.</div> <div class="gmail_default"> </div> <div class="gmail_default"><span style="color: #000000; font-family: 'comic sans ms', sans-serif;">Only articles in English are considered for submission and publication.</span></div> </div>https://bjopm.org.br/bjopm/article/view/2361A model for measuring the quality of public policies in innovation2024-09-03T08:00:29-03:00Paulo Renato Pakespaulopakes@ufscar.brAna Lúcia Vitale Torkomiantorkomia@ufscar.brBrena Bezerra Silvabezerra.brena@yahoo.com.brMiguel Ángel Aires Borrásmaborras@ufscar.brVívian Karina Bianchinivivian.bianchini@unesp.brCarlos do Amaral Razzinocarlos.razzino@unesp.br<p><strong>Goal</strong> : This article presents a model for measuring the quality of public policies on innovation and its validation in a public policy on technology parks (SPTec)</p> <p><strong>Design/methodology/approach</strong>: A survey on the quality of public policy SPTec was carried out. Through descriptive analysis, it was possible to verify the quality of public policy in five determinants of quality. Factor analysis allowed the regrouping of quality attributes into new determinants for SPTec public policy. Finally, the multiple regression analysis allowed us to analyze the dependence relationship between the variables.</p> <p><strong>Results</strong>: The public policy SPTec is immature in terms of process quality, quality of the relation, and quality of the result. In addition, we identified the determinants that should be prioritized in the implementation of SPTec public policy in a possible reformulation. Finally, the attributes of quality that generate the greatest effect in terms of an increase in user satisfaction are shown, as well as those that generate a decrease in satisfaction if they have an increase in their performance.</p> <p><strong>Limitations of the investigation</strong>: Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.</p> <p><strong>Practical implications</strong>: As a limitation, there is the fact that the factor analysis of public policy SPTec can only be generalized at the level of the same. Likewise, the presented model for measuring quality in the public sector requires adaptation for each public policy analyzed.</p> <p><strong>Originality/value</strong>: This article fills a gap regarding the lack of instruments for measuring the quality of public policies in innovation systems.</p>2024-11-20T00:00:00-03:00Copyright (c) 2024 Paulo Renato Pakes, Ana Lúcia Vitale Torkomian, Brena Bezerra Silva, Miguel Ángel Aires Borrás, Vívian Karina Bianchini, Carlos do Amaral Razzinohttps://bjopm.org.br/bjopm/article/view/2253Multi-criteria approach for weights definition of sustainability indicators in the swine supply chain2024-05-13T11:04:19-03:00Silvana Krugersilvana.d@ufms.brFlavio Trojantrojan@utfpr.edu.brAntonio Zaninzanin.antonio@ufms.brMauro Lizotmauro.lizot@unochapeco.edu.brPaulo Afonsopsafonso@dps.uminho.pt<p><strong>Goal:</strong> This study presents a four-steps methodology for the definition of the weights of sustainable indicators in the Swine Supply Chain (SSC) considering the Triple Bottom-Line (TBL) perspective.</p> <p><strong>Design/Methodology/Approach:</strong> The methodology proposed was based on the Bellagio principles that guide the definition of importance levels for TBL criteria. It was applied to the swine supply chain using Saaty’s scale and information obtained from managers of two agribusiness companies, adjusted by the AHP method.</p> <p><strong>Results:</strong> The results showed the relevance of an appropriate definition of the preferences of decision-makers to decide on the best actions towards environmental, economic, and social sustainability.</p> <p><strong>Limitations:</strong> The limitations of the proposed model are mainly its subjective nature. Despite being necessary in multi-criteria methods, it could be a limitation if more quantitative indicators are relevant or demanded. Nevertheless, the proposed methodology also provides a quantitative perspective, as a result of using the Saaty scale.</p> <p><strong>Practical implications:</strong> The definition and application of importance levels within a TBL-based model can help managers to prioritize environmental, social, and/or economic dimensions under a large diversity of alternatives toward more sustainable scenarios. The AHP method used in this work is a hierarchy method, particularly appropriate for defining weights that are essentially compensatory by nature.</p> <p><strong>Originality/value:</strong> The correct definition and weight of the different dimensions, sub-dimensions, and respective indicators is currently one relevant gap in the literature, limiting the design and prioritization of corrective actions in each stage of the SSC and in the different dimensions of the TBL.</p>2024-11-02T00:00:00-03:00Copyright (c) 2024 Silvana Dalmutt Kruger, Flavio Trojan, Antonio Zanin, Mauro Lizot, Paulo Afonsohttps://bjopm.org.br/bjopm/article/view/2166Impact of Industry 4.0 on firms' sustainable development in the GCC economies2024-07-19T14:01:40-03:00Saif Rehmandoctor.saifkhanfg@gmail.comYacoub Haider Hamdany.hamdan@ammanu.edu.joMahwish Sindhumahwish41@gmail.com<p><strong>Goal</strong>: This paper utilizes a practice-based view (PBV) and technology-organization-sustainable framework to create and evaluate a research model. The model examines how industry 4.0 (I4.0) affects sustainable development, focusing on the mediating role of 10R advanced manufacturing capabilities. Furthermore, the study also analyzes the moderating influence of environment dynamism (ED). Sustainable development is assessed based on two key factors - financial performance (FP) and sustainable performance (SP).</p> <p><strong>Design / Methodology / Approach</strong>: The data is collected by surveying upper management in the GCC manufacturing sector through questionnaires. A total of 232 responses were included in the primary analyses. Data analysis was carried out with the help of SPSS 25.0 and SmartPLS 3.2.8. The dependability and path analysis were established using structural equation modeling (SEM).</p> <p><strong>Results</strong>: The results show that I4.0 increases FP, whereas the I4.0-SP relationship is statistically insignificant. However, the I4.0-SP insignificant relationship is moderated by ED. Further, ED also moderates the relationship between I4.0 and 10R advanced manufacturing capabilities, as well as 10R advanced manufacturing capabilities and sustainable development (FP and SP). The 10R capabilities partially mediate the I4.0-FP relationship, whereas the study finds full mediation for the I4.0-SP association.</p> <p><strong>Research limitations:</strong> The study employed Google forms to conveniently collect data from GCC industrial senior management using a cross-section design.</p> <p><strong>Originality / Value:</strong> This study has identified a business model that impacts sustainable development by integrating I4.0 technologies, ED, and 10R. The study findings have significant implications for managers and policymakers.</p>2024-10-05T00:00:00-03:00Copyright (c) 2024 Saif Rehman, Yacoub Haider Hamdan, Mahwish Sindhuhttps://bjopm.org.br/bjopm/article/view/2328Lean Green Tendency2024-07-23T08:10:25-03:00Cláudia Sousa e Silvaclaudia.margarida@ua.ptSara Azevedonaodisponivel@gmail.comMaria Fonsecanaodisponivel@gmail.com<p>Lean philosophy and Green practices have been identified as management approaches that allow organizations to reach better economic and environmental results. Nevertheless, some authors argue that results can be enhanced with the integration of the Lean and Green practices. This synchronous effort has led to the developing a new Lean philosophy branch, the Lean Green.</p> <p><strong>Goal:</strong> This work aims to deepen the Lean Green state of the art, as well as to understand how companies have adopted it.</p> <p><strong>Design / Methodology / Approach: </strong>The methodology was supported by a systematic literature review following three steps: Planning, data collection, data analysis throughout content analysis.</p> <p><strong>Results: </strong>The results showed that Lean Green is still an emerging theme in scientific research, with an increasing trend of publications worldwide in the last six years, adopting distinctive research strategies. Companies' main motivations and barriers to adopting Lean Green were also identified. Finally, were identified the key factors that could help organizations to adopt Lean Green, namely critical implementation factors, facilitator models and tools, and the main results and advantages obtained.</p> <p><strong>Limitations of the investigation: </strong>The main work´s limitation is that it was considered only the Scopus database.</p> <p><strong>Practical implications: </strong>Help companies find solutions that enhance their performance and competitiveness, reduce their environmental impact, and improve their social responsibility.</p> <p><strong>Originality/Value: </strong>The originality of this work is defended by crossing the results at the academic and practical levels. This allows the usefulness of academic research results by bringing them into a practical organizational context.</p>2024-11-20T00:00:00-03:00Copyright (c) 2024 Cláudia Sousa e Silva, Sara Azevedo, Maria Fonsecahttps://bjopm.org.br/bjopm/article/view/2221Benchmarking supply chain collaboration dimensions with insights from resource-based theories2024-05-30T08:01:44-03:00Benitha Mhoka Myambabenitha9@yahoo.comDeus Shattadeus.shatta@nit.ac.tzErick Massamierick.massami@nit.ac.tz<p><strong>Goal</strong>: Despite the increased attention to the role of supply chain collaboration on firm performance, insufficient evidence exists about the relative importance of each dimension of supply chain collaboration on manufacturing competitiveness. The purpose of this study is to examine the influence and relative importance of supply chain collaboration dimensions on manufacturing competitiveness based on resource-based theories.</p> <p><strong>Design/methodology/approach:</strong> This study employs a deductive approach to derive empirical evidence from the responses of 300 officials of manufacturing firms. The PLS-SEM is used to test the significance of conceptual predictions and IPMA is used to benchmark the most important collaborative dimensions. </p> <p><strong>Results</strong>: It is revealed that manufacturing firms capitalize on all supply chain collaboration dimensions. However, customer collaboration and supplier collaboration have a significant and positive direct influence while internal collaboration exhibits a complementary partial mediation effect. Customer collaboration is the most important dimension followed by internal collaboration and supplier collaboration.</p> <p><strong>Limitations of the investigation</strong>: This study employed a cross-section design lacking the longitudinal effect. Nevertheless, the identification, testing and validation of the conceptual model, backed up by an extensive literature review, could assist researchers in developing meaningful comparative studies.</p> <p><strong>Originality/value</strong>: The study applied PLS-SEM and IPMA to reveal the role and relative importance of supply chain collaborative dimensions on manufacturing competitiveness. Managers of manufacturing firms can emulate this knowledge within their settings and be able to compete amid increased competition and supply chain complexity.</p>2024-10-05T00:00:00-03:00Copyright (c) 2024 Benitha Mhoka Myamba, Deus Shatta, Erick Massamihttps://bjopm.org.br/bjopm/article/view/2144Supply Chain Environmental Uncertainty, Competitive Advantage, and Operational Performance in Manufacturing Industry2024-08-07T13:31:47-03:00La Hatanilahatani@uho.ac.idNursaban Rommy nursabansuleman@gmail.comUsmanusmanmogane015@gmail.com<p><strong>Goal:</strong> This study investigates the impact of Supply Chain Environmental Uncertainty (SCEU) on competitive advantage and operational performance in manufacturing companies. The mediating role of competitive advantage and the moderating role of supply chain environmental uncertainty in the relationship between competitive advantage and operational performance were examined.</p> <p><strong>Design/ Methodology/ Approach:</strong> This paper used quantitative approach to confirm the conceptual model. Data was collected through questionnaires from directors/operational managers in 121 large and medium-scale manufacturing companies in Southeast Sulawesi Indonesia. The analysis employs Generalized Structured Component Analysis (GSCA) to test the direct, mediating, and moderating effects of supply chain environmental uncertainty.</p> <p><strong>Results:</strong> The findings demonstrate a significant positive influence of supply chain environmental uncertainty on competitive advantage and operational performance. However, competitive advantage does not significantly affect operational performance. The study reveals that competitive advantage is perfect mediator between supply chain environmental uncertainty and operational performance, while supply chain environmental uncertainty is a moderating predictor between competitive advantage and operational performance.</p> <p><strong>Practical Implications:</strong> The research has implications for manufacturing company managers adapting to supply chain environmental uncertainty through supplier, customer, and technology considerations. It emphasizes the importance of adapting to supply chain environmental uncertainty to enhancing competitive advantage and operational performance in the manufacturing industry. Efforts to improve operational performance and strategically integrate competitive advantage should consider the business environment, including suppliers, customers, and technology.</p> <p><strong>Limitations: </strong>This research is limited to large and medium-scale manufacturing industries, hindering generalization to other industries, particularly small-scale ones. Additionally, researchers can consider additional contextual factors such as supply chain integration, supply chain agility, and total quality management.</p> <p><strong>Originality/Value:</strong> This study expands the theoretical framework of supply chain environmental uncertainty, competitive advantage, and operational performance through empirical testing of a theoretical model. The findings support the proposed model's validity and highlight the mediation role of competitive advantage and supply chain environmental uncertainty, providing a reference for future theory development and model building.</p>2024-10-31T00:00:00-03:00Copyright (c) 2024 La Hatani, Nursaban Rommy , Usman