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Supply chain digitalization (SCD) facilitates a competitive advantage and is equally challenging. A literature analysis reveals that research related to SCD is available, but analysis of key barriers and their interrelations for effective SCD is limited. This paper aims to identify and find out interrelationships among the key barriers affecting SCD in the electronic supply chain (SC).

Interpretive structural modeling (ISM) is used to identify the contextual relationship among the SCD barriers. The model is validated using MICMAC analysis.

The findings of this study have implications at both theoretical and practical levels. The proposed ISM model can help organizations analyze and interpret interrelationships among barriers to SCD. It can lead to better insights and understanding for minimizing the dominant barriers to effective SCD.

This study tries to bridge the gap in identifying and finding the interrelationships among the key barriers to effective SCD in an electronic SC. The result assists practicing managers and academicians in effective decision-making on the SCD process.

The process of supply chain digitalization (SCD) through enterprise and inter-enterprise information systems (EIIS) is a challenging task. Understanding and studying barriers of SCD adopting EIIS are essential for better management of supply chains (SCs) in the long run. This paper analyses the key EIIS adoption barriers affecting the process of SCD.

Fifteen key EIIS barriers of SCD in the context of an electronic SC were identified from existing literature and in consultation with experts from industry and academia. Grey-based decision-making trial and evaluation laboratory (DEMATEL) methodology is used to identify cause–effect relationship and extent of the strength of relationship amongst EIIS barriers. Sensitivity analysis is done to verify the robustness of the study.

EIIS barriers were classified into seven major cause factors and eight effect factors. This study provides a structural framework of key EIIS adoption barriers to decision makers by classifying barriers into cause and effect groups for effective SCD and better management.

This study contributes to SC literature by exploring key EIIS barriers affecting the process of SCD. These findings will also help the practitioners in effective decision making for digitalization.

Supply chain efficiency can be enhanced by integrating the activities in supply chain through digitalization. Advancements in digital technologies has facilitated in designing robust and dynamic supply chain by bringing in efficiency, transparency and reduction in lead times. This research tries to identify and prioritize the customer requirements and design requirements for effective integration of supply chain through digitalization.

The key nine customer requirements and 16 design requirements applicable for an electronics company were shortlisted in consultation with the experts from the company and academia. An integrated analytic network process (ANP) and quality function deployment (QFD) methodology has been applied for prioritizing the customer and design requirements. The relative importance and interdependence of these requirements were identified and a House of Quality (HOQ) is constructed.

The HOQ constructed has prioritized and identified interrelationships among customer requirements and design requirements for effective supply chain digitalization. These findings could be effectively used by managers for planning the objectives on long-term, medium-term and short-term basis.

This study tries to bridge the gap of identifying and prioritizing the design and customer requirements for effective supply chain integration through digitalization. The results could aid practicing managers and academicians in decision-making on supply chain digitalization process.

Meeting the patients' requirements as customers of the health care sector is crucially important as a social responsibility. According to the resource constraints, only an efficient utilisation of health services can provide that purpose. This study aims to develop a quantitative assessment framework for radiology centres as a vital section in healthcare to translate the patients' requirements into service quality specifications. This would help to achieve quality improvement by emphasising the voice of customers.

A literature review is conducted to specify the service quality criteria and the patients' requirements related to healthcare and hospitals. Based on the experts' opinions, these criteria and requirements are later customised for the radiology centres. Moreover, the requirements are categorised into five dimensions of SERVQUAL. The interrelations between service elements are also determined through expert group consensus using Pearson correlation. Afterwards, by applying the QFD method, the relations between the requirements and criteria are explored. Additionally, a customer satisfaction survey is executed in Tehran public hospitals to prioritise these requirements and provide an importance-satisfaction analysis.

Based on the result of the case study, service elements are prioritised for improvement, and practical suggestions are provided using the Delphi technique for quality improvement. In addition, a cause-and-effect diagram is presented to highlight the improvement area and provide enhancement suggestions.

This study is the first empirical attempt to benefit from the VOC in evaluating and enhancing the quality of service delivered to radiology patients. In doing so, the study applies a hybrid approach of QFD and SERVQUAL as well as other tools to highlight the improvement area and provide enhancement suggestions. The findings can be readily used by the practitioners.

The aim of this study is to investigate the factors that influence the readiness to adopt artificial intelligence (AI) tools within Moroccan auditing firms.

A quantitative research design was used, using survey data to examine the influence of perceived usefulness (PU), ease of use (EU) and top management commitment (TMC) on AI adoption readiness (AIAR) in auditing. A conceptual model, drawing from the technology acceptance model (TAM) and supported by findings from previous literature, was proposed. The model was tested using partial least squares – structural equation modelling on data collected from 116 Moroccan respondents.

The study confirmed that PU and TMC do not significantly influence the AIAR in auditing in Morocco, whereas EU is positively and significantly associated to the AIAR.

The study presents findings based on data from a single country, which may limit the broader applicability of the results to other contexts or regions with different regulatory, cultural or economic environments.

The results suggest that TAM is not necessarily adapted to AI adoption within an emerging context like Morocco. The significant role of EU in AIAR suggests that Moroccan firms should prioritize the development and integration of AI tools that are intuitive and user-friendly. AI should be presented not only as a tool for enhancing audit quality but also as a means of reducing workload and improving efficiency. Furthermore, rather than relying solely on top-down mandates, a more decentralized approach to AI adoption could be effective, where individual auditors are empowered to experiment with AI tools and integrate them into their practices. This approach could foster a culture of innovation and gradual adoption, increasing the likelihood of successful AI integration within Moroccan auditing firms.

AI adoption in auditing can promote societal benefits by enhancing transparency, accountability and trust in both public and private sectors. In countries like Morocco, where financial transparency is lacking but vital for stability, AI can help reduce corruption, improve decision-making and foster public trust, ultimately supporting investment and social equity.

This paper offers an original contribution by examining AIAR in Morocco’s auditing sector, focusing on an emerging market and African context. Unlike studies in developed countries, it highlights the unique challenges and opportunities faced by Moroccan auditors, considering factors like PU, EU and TMC. It challenges organizations to assess their readiness and the ability of their employees to effectively integrate AI into their workflows.

The outset of the COVID-19 pandemic caused disruptions of all forms in the supply chain globally for almost two and a half years. This study identifies various challenges in the effective functioning of the existing supply chain during COVID-19. The focus is to see the disruptions impacting the energy storage supply chains.

The procedure entails a thorough analysis of scholarly literature pertaining to various supply chain interruptions, confirmed and verified by experts working in an energy storage company in India. These experts also confirmed the occurrence of more disruptive factors during their interviews and questionnaire survey. Moreover, this process attempts to filter out the relevant causal disruption factors in an energy storage company by using the integrated approach of qualitative and quantitative methodologies.

The results provide practical insights for the company management in planning and devising new strategies to manage supply chain disruptions. Supply chains for companies in other industry sectors can also benefit from the proposed framework and results in making them more robust to counter future disastrous events.

The study provides an easily adaptable decision framework to different industries by closely examining supply chain disruptions and identifying associated causes for building a robust supply chain focused on the energy storage sector. It examines four disruption dimensions and investigates possible outcomes and impacts of disruptions.

This study has two major objectives. First, comprehensively review the literature on transparency in supply chain management. Second, based on a critical analysis of literature, identify the attributes and sub-attributes of supply chain transparency and develop a numerical measure to quantify transparency in supply chains.

A systematic literature review (SLR) was conducted using the PRISMA approach. Utilizing SCOPUS database past eighteen-year papers search resulted in 249 papers to understand major developments in the domain of supply chain transparency. Subsequently, graph theoretic approach is applied to quantify transparency in supply chain and the proposed index is evaluated for case supply chains from pharma and dairy sectors.

It can be concluded from SLR that supply chain transparency research has evolved from merely tracking and tracing of the product towards sustainable development of the whole value chain. The research identifies four major attributes and their sub-attributes that influence transparency in supply chains, which are used to develop transparency index. The proposed index for two sectors helps to understand areas that need immediate attention to improve transparency in the case supply chains.

This paper attempts to understand the development of transparency research in supply chain using the PRISMA approach for SLR. In addition, development of mathematical model to quantify supply chain transparency is a novel attempt that would help benchmark best practices in the industry. Further, transparency index would help to understand specific areas that need attention to improve transparency in supply chains.

The study aims to provide a comprehensive review of digital twin (DT) literature and examine how various industrial sectors utilize the potential of DT.

This study’s systematic literature review (SLR) and bibliometric analysis focus on utilizing DT in the supply chain (SC) and its applications across various industries between 2017 and 2024. The use of DT for information management and risk management in SCM, which have been investigated in many sectors, is the primary focus of this article. The article also examines the various digital technologies used in digital twin literature.

The following are the main conclusions drawn from the research on digital twins and their implementation: Digital twins have been studied to improve visibility, traceability, resilience, risk identification and assessment, information sharing and decision-making in SC of various sectors. According to the literature review, most research was conducted in the manufacturing industry. Also, the integration of DT with digital technologies (like AI, BD, AI, ML and CPS) in SC has been explored less.

A multisectoral examination has been done to identify any needs or requirements and unknown areas of study and make recommendations for future directions for study on the interface between SC and DT.

Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.

An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.

On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.

The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.