International Journal of Business Performance and Supply Chain Modelling (4 papers in press)

Regular Issues

• A Systematic Literature Review on the Management of Small Agroindustrial Producers using Artificial Intelligence  
  by Jairo Fuentes, Jose Aguilar 
  Abstract: Small agro-industrial producers play a vital role in a countrys economic and social advancement. Artificial intelligence (AI) builds knowledge models that allow agro-industrial producers to make decisions about production chains to achieve high levels of performance and competitiveness. The objective of this work is to perform a systematic literature review on the use of AI for the management of small agro-industrial productions. Seven scientific digital libraries and a search methodology based on research questions, inclusion, and exclusion criteria, among other aspects, were used to investigate the use of AI for the management of small agribusinesses. An analysis of 62 articles was performed to assess the strengths and limitations of using AI in Small Agribusiness Production Management, as well as to identify the primary challenges and opportunities. Among the limitations found are the low investment in new technologies, and the rejection of changes and innovative business models.
  Keywords: Artificial Intelligence; Agribusiness; Small Agribusiness Production Management; systematic literature review.
  DOI: 10.1504/IJBPSCM.2025.10071147
   
  
• Ranking the Solutions to Mitigate Sustainable Innovation Implementation Barriers using a BWM-COPRAS Approach  
  by Pankaj Shete, Zulfiquar Ansari, Ravi Kant 
  Abstract: This study aims to prioritize the solutions for effectively minimising the barriers to sustainable innovation implementation. Based on the literature review and discussion with an expert panel, barriers and solutions to overcome these barriers are identified. The best-worst method (BWM) is used to compute each barrier's relative weights, and the Complex Proportional Assessment method (COPRAS) is used to prioritise and select the most effective solution. The suggested framework is numerically illustrated by applying it to a manufacturing organisation. The findings show that organizational change synchronized with innovative technological change is the top-ranked solution. In addition, sensitivity analysis is performed to check the robustness of the proposed BWM-COPRAS framework. This study will help policymakers better understand the obstacles that obstruct the effective implementation of sustainable innovation in manufacturing organisations. It will also aid the decision-makers in tackling the barriers through systematic implementation of the solutions.
  Keywords: Sustainable supply chain management; Sustainable innovation; Barriers; Solutions; BWM; COPRAS.
  DOI: 10.1504/IJBPSCM.2025.10071480
   
  
• Redefining Digital Transformation in Service Supply Chain: the Missing Piece of Big Data Analytics  
  by Twinkle Singh, Jeanne Poulose, Vinod Sharma 
  Abstract: The study delves into the transformative role of big data analytics in supply chain management within the service industry, employing the PRISMA framework to systematically review literature published between 2011 and 2024. A comprehensive search across multiple databases identified 286 relevant studies, which were meticulously analyzed through bibliometric techniques. Keyword and network analyses, conducted using VOSViewer, revealed critical research linkages, prominent technologies, and thematic patterns within the domain. The findings underscore the pivotal role of technology integration in enhancing the efficiency of service supply chains, with a particular emphasis on emerging technologies such as blockchain, artificial intelligence, and machine learning. By highlighting the interconnectedness of authors, identifying key themes through keyword analysis, and uncovering research patterns through frequency analysis, the study provides valuable insights into the integration of big data analytics, ultimately contributing to the advancement of supply chain management in the service industry.
  Keywords: Digital Transformation; Service Supply Chain; Supply Chaina Management; Big Data Analytics; Service Industry.
  DOI: 10.1504/IJBPSCM.2025.10072510
   
  
• Decision Support Tool for the Selection and Evaluation of Suppliers, to Optimising the Textile Raw Material Supply Chain, through Programming  
  by Zouina Ameur, Samir Abdelhamid 
  Abstract: The optimisation of supply chains is a very attractive area of research for researchers active in this very broad field, our study aims to propose an evaluation approach which will serve as an IT decision support tool, innovated to optimise the operation of evaluation and selection of a best supplier during a comparison of offers...; The program proposed translates the algorithm which summarises the sequence of steps present in an operation of evaluation of offers based on three criteria considered the most important for the supply of cotton by the managers of companies active in the textile industry, it responds with the best choice with reliable information and in a very limited time and above all by avoiding calculation errors as in traditional cases.
  Keywords: Developed Supply chain; optimisation algorithm; selection supplier; evaluation criteria; digitalisation; textile supply chain.
  DOI: 10.1504/IJBPSCM.2025.10072917