Forthcoming and Online First Articles

International Journal of Business Performance and Supply Chain Modelling

International Journal of Business Performance and Supply Chain Modelling (IJBPSCM)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Business Performance and Supply Chain Modelling (2 papers in press)

Regular Issues

  • A Systematic Literature Review on the Management of Small Agroindustrial Producers using Artificial Intelligence   Order a copy of this article
    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   Order a copy of this article
    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
     

 

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