Template-Type: ReDIF-Article 1.0 Author-Name: Alexey P. Tyapukhin Author-X-Name-First: Alexey P. Author-X-Name-Last: Tyapukhin Author-Name: Olga N. Zueva Author-X-Name-First: Olga N. Author-X-Name-Last: Zueva Title: Essence and structure of value creation management system Abstract: Research purpose is to create prerequisites for clarifying and supplementing the theory and methodology of designing and forming value creation systems (VCSs) and value creation management systems (VCMS) that ensure effective fulfilment of orders of end consumers of products and/or services. The paper presents the results that have signs of scientific novelty: the classification of tools of enterprise (chain) management system developed; the sequence of object management in the creation of values for the end consumer proposed; the structure of chains and concepts of value creation management have been clarified; the relationship between the goals of consumer and supplier (value creation channel) determined; the classification of management system functions developed; the approach to designing and forming of value creation management system substantiated. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 207-230 Issue: 3 Volume: 15 Year: 2025 Keywords: value; VCS; value creation system; VCMS; value creation management system; goal; objective; principle; approach; method; function. File-URL: http://www.inderscience.com/link.php?id=147076 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:15:y:2025:i:3:p:207-230 Template-Type: ReDIF-Article 1.0 Author-Name: Oumaima Hansali Author-X-Name-First: Oumaima Author-X-Name-Last: Hansali Author-Name: Samah Elrhanimi Author-X-Name-First: Samah Author-X-Name-Last: Elrhanimi Author-Name: Laila El Abbadi Author-X-Name-First: Laila El Author-X-Name-Last: Abbadi Title: Exploring digital supply chain barriers: case study in automotive industry Abstract: Businesses across diverse industries are grappling with the intricacies of an ever-expanding digital economy. The objective of this study is to conduct an examination of the barriers hindering the adoption of digital supply chain (DSC) in the automotive industry. To analyse these barriers, an integrated approach utilising the Best-Worst method (BWM) was employed. By reviewing relevant literature and experts feedback, a total of 26 barriers to the adoption of digitalisation in the automotive supply chain were identified. Subsequently, the BWM was used to determine the relative importance of each barrier. The findings showed that high investment cost and lack of digital skills are the highest-ranked digital supply chain barriers (DSCB) that needs to be overcome on a priority basis. The proposed framework has significant potential to help business managers identify and address the key obstacles that must be overcome for the successful digitalisation of the automotive supply chain. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 255-280 Issue: 3 Volume: 15 Year: 2025 Keywords: SCM; supply chain management; digitisation tools; DSC; digital supply chain; BWM; best-worst method. File-URL: http://www.inderscience.com/link.php?id=147088 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:15:y:2025:i:3:p:255-280 Template-Type: ReDIF-Article 1.0 Author-Name: Vaibhav Misra Author-X-Name-First: Vaibhav Author-X-Name-Last: Misra Author-Name: Smriti Shukla Author-X-Name-First: Smriti Author-X-Name-Last: Shukla Title: The factors influencing the acceptance of drones as delivery option for young consumers Abstract: This study aimed to examine the influence of predictors of drone delivery on young consumers' intention to adopt drones as a medium of delivery in the Indian context. The theoretical framework was developed using a combination of diffusion of innovation theory and perceived risk theory. 230 respondents aged 18-34 years were considered usable for this study. Principal component analysis and multiple regression analyses were used for the analysis. The results showed that relative speed advantage (RSA), performance risk, and delivery risk positively influence the intention to adopt drone delivery, whereas green image negatively influences drone delivery adoption. The limitations of this study are discussed. The present study is one of the first attempts to understand the factors influencing the acceptance of drone delivery in India, which will help to understand the importance of environment-friendly deliveries. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 231-254 Issue: 3 Volume: 15 Year: 2025 Keywords: diffusion of innovation; drone delivery; perceived risk; privacy; performance risk; delivery risk; innovativeness; speedy delivery; environment friendliness. File-URL: http://www.inderscience.com/link.php?id=147093 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:15:y:2025:i:3:p:231-254 Template-Type: ReDIF-Article 1.0 Author-Name: Santonab Chakraborty Author-X-Name-First: Santonab Author-X-Name-Last: Chakraborty Author-Name: Rakesh D. Raut Author-X-Name-First: Rakesh D. Author-X-Name-Last: Raut Author-Name: T.M. Rofin Author-X-Name-First: T.M. Author-X-Name-Last: Rofin Author-Name: Shankar Chakraborty Author-X-Name-First: Shankar Author-X-Name-Last: Chakraborty Title: Solving supplier selection problem in a textile industry using an integrated grey-MABAC method Abstract: Like other industries, selection of suppliers in a textile mill also plays a decisive role by providing right quality of raw materials/components/dyes and chemicals in right quantities at right time and affordable cost, thereby establishing an effective supply chain. Acknowledging supplier selection/evaluation as a multi-criteria decision-making (MCDM) problem, various mathematical tools have been proposed to resolve the issue. In this paper, a grey-based MCDM approach, i.e. grey-multi-attributive border approximation area comparison (G-MABAC) method is proposed for solving a textile supplier selection problem, expressing relative importance of the decision makers, criteria and alternatives using grey numbers. Based on the performance scores, G-MABAC partitions six alternative suppliers into upper approximation (reliable) and lower approximation (unreliable) areas, identifying the relative strengths and weaknesses of each of them. It would act as an intelligent decision support framework in effectively adopting multi-sourcing strategy for enhanced resilience with minimum disruption in the textile supply chain. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 315-337 Issue: 3 Volume: 15 Year: 2025 Keywords: supplier selection; textile industry; grey number; MABAC; multi-attributive border approximation area comparison; ranking. File-URL: http://www.inderscience.com/link.php?id=147103 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:15:y:2025:i:3:p:315-337 Template-Type: ReDIF-Article 1.0 Author-Name: Raja Roy Author-X-Name-First: Raja Author-X-Name-Last: Roy Author-Name: Soma Roychowdhury Author-X-Name-First: Soma Author-X-Name-Last: Roychowdhury Title: Orientation-performance modelling for supply chain organisations ecosystem Abstract: The supply chain issues, and their attributes are derived from the supply chain organisation (SCO) ecosystem. The SCO's strategic and operational issue attributes from the weakness-rationality limits-risk-dissatisfaction (WRRD) model influence the firm's performance, evaluated using pooled confirmatory factor analysis (PCFA) and SEM methods using SCO's orientation-performance modelling. A study of 218 micro and small manufacturing enterprises in Eastern India shows that SCO's orientation-performance model suggests a good fit. Results suggest these industries prioritise rationality over risk issues proactively and use reactive enablers to address dissatisfaction more than weakness issues. Besides strategic-operational, proactive-reactive orientations, risk issues also directly influence the firm's performance, limiting proactive enablers' effectiveness in mitigating risk. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 281-314 Issue: 3 Volume: 15 Year: 2025 Keywords: operational orientation; performance modelling; proactive approach; reactive approach; strategic orientation; SCM; supply chain management; supply chain risk management. File-URL: http://www.inderscience.com/link.php?id=147106 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:15:y:2025:i:3:p:281-314 Template-Type: ReDIF-Article 1.0 Author-Name: Jairo Fuentes Author-X-Name-First: Jairo Author-X-Name-Last: Fuentes Author-Name: Jose Aguilar Author-X-Name-First: Jose Author-X-Name-Last: Aguilar Title: A systematic literature review on the management of small agroindustrial producers using artificial intelligence Abstract: Small agro-industrial producers play a vital role in a country's 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. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 339-363 Issue: 4 Volume: 15 Year: 2025 Keywords: artificial intelligence; agribusiness; small agribusiness production management; SLR; systematic literature review. File-URL: http://www.inderscience.com/link.php?id=150381 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:15:y:2025:i:4:p:339-363 Template-Type: ReDIF-Article 1.0 Author-Name: Pankaj C. Shete Author-X-Name-First: Pankaj C. Author-X-Name-Last: Shete Author-Name: Zulfiquar N. Ansari Author-X-Name-First: Zulfiquar N. Author-X-Name-Last: Ansari Author-Name: Ravi Kant Author-X-Name-First: Ravi Author-X-Name-Last: Kant Title: Ranking the solutions to mitigate sustainable innovation implementation barriers using a BWM-COPRAS approach Abstract: This study aims to prioritise 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 organisational change synchronised 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. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 364-395 Issue: 4 Volume: 15 Year: 2025 Keywords: sustainable supply chain management; sustainable innovation; barriers; solutions; BWM; best-worst method; COPRAS; Complex Proportional Assessment. File-URL: http://www.inderscience.com/link.php?id=150384 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:15:y:2025:i:4:p:364-395 Template-Type: ReDIF-Article 1.0 Author-Name: Twinkle Singh Author-X-Name-First: Twinkle Author-X-Name-Last: Singh Author-Name: Jeanne Poulose Author-X-Name-First: Jeanne Author-X-Name-Last: Poulose Author-Name: Vinod Sharma Author-X-Name-First: Vinod Author-X-Name-Last: Sharma Title: Redefining digital transformation in service supply chain: the missing piece of big data analytics Abstract: The study delves into the transformative role of big data analytics (BDA) 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 analysed 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 BDA, ultimately contributing to the advancement of supply chain management in the service industry. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 396-414 Issue: 4 Volume: 15 Year: 2025 Keywords: digital transformation; service supply chain; supply chain management; BDA; big data analytics; service industry. File-URL: http://www.inderscience.com/link.php?id=150389 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:15:y:2025:i:4:p:396-414 Template-Type: ReDIF-Article 1.0 Author-Name: Zouina Ameur Author-X-Name-First: Zouina Author-X-Name-Last: Ameur Author-Name: Samir Abdelhamid Author-X-Name-First: Samir Author-X-Name-Last: Abdelhamid Title: Decision support tool for the selection and evaluation of suppliers, to optimising the textile raw material supply chain, through programming Abstract: In a developed commercial world, the optimisation of supply chains is a very attractive area of research; and as we know that the optimisation of each link can contribute to the optimisation of the entire supply chain, 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, and in response to the demand of managers of textile companies seeking to improve their market shares, 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 textile companies, 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. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 415-430 Issue: 4 Volume: 15 Year: 2025 Keywords: developed supply chain; optimisation algorithm; selection supplier; evaluation criteria; digitalisation; textile supply chain. File-URL: http://www.inderscience.com/link.php?id=150392 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:15:y:2025:i:4:p:415-430 Template-Type: ReDIF-Article 1.0 Author-Name: Anurup Arora Author-X-Name-First: Anurup Author-X-Name-Last: Arora Author-Name: Saroj Koul Author-X-Name-First: Saroj Author-X-Name-Last: Koul Title: Developing supply chain resilience to counter transboundary crisis: a proposed three-level framework Abstract: There is limited published literature on 'supply chain resilience' (SCR) that deals with abnormal and relatively less frequent events called 'transboundary crisis (TC)'. These disruptive events stretch beyond boundaries and require collaborative efforts at multiple levels to minimise their impact. This research conducts a systematic literature review on TC and its effect on supply chains, particularly COVID-19. Accordingly, a global-national-organisational (GNO) framework is proposed to counter TC threats to global supply chains. Lastly, a 'Q-Framework' to assess organisational-level resilience is presented, providing supply chain practitioners with 48 questions. The Q-Framework offers a ready reckoner for practitioners and researchers to evaluate and plan to build SCR. This work can be extended by adding more strategies to the GNO framework to make it more robust. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 431-458 Issue: 4 Volume: 15 Year: 2025 Keywords: TC; transboundary crisis; SCR; supply chain resilience; supply chain disruption; supply chain risk; framework; COVID-19. File-URL: http://www.inderscience.com/link.php?id=150394 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:15:y:2025:i:4:p:431-458