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The purpose of this study is to identify, analyse and model the post-processing barriers of 3D-printed medical models (3DPMM) printed by fused deposition modelling to overcome these barriers for improved operational efficiency in the Indian context.

The methodology used interpretive structural modelling (ISM), cross-impact matrix multiplication applied to classification (MICMAC) analysis and decision-making trial and evaluation laboratory (DEMATEL) to understand the hierarchical and contextual relations among the barriers of the post-processing.

A total of 11 post-processing barriers were identified in this study using ISM, literature review and experts’ input. The MICMAC analysis identified support material removal, surface finishing, cleaning, inspection and issues with quality consistency as significant driving barriers for post-processing. MICMAC also identified linkage barriers as well as dependent barriers. The ISM digraph model was developed using a final reachability matrix, which would help practitioners specifically tackle post-processing barriers. Further, the DEMATEL method allows practitioners to emphasize the causal effects of post-processing barriers and guides them in overcoming these barriers.

There may have been a few post-processing barriers that were overlooked by the Indian experts, which might have been important for other country’s perspective.

The presented ISM model and DEMATEL provide directions for operation managers in planning operational strategies for overcoming post-processing issues in the medical 3D-printing industry. Also, managers may formulate operational strategies based on the driving and dependence power of post-processing barriers as well as the causal effects relationships of the barriers.

This study contributes to identifying, analyzing and modelling the post-processing barriers of 3DPMM through a combined ISM and DEMATEL methodology, which has not yet been reviewed. This study also contributes to decision makers developing suitable strategies to overcome the post-processing barriers for improved operational efficiency.

This study aims to identify 3D-printed medical model (3DPMM) supply chain barriers that affect the supply chain of 3DPMM in the Indian context and investigate the interdependencies between the barriers to establish hierarchical relations between them to improve the supply chain.

The methodology used interpretive structural modeling (ISM) and a decision-making trial and evaluation laboratory (DEMATEL) to identify the hierarchical and contextual relations among the barriers to the 3DPMM supply chain.

A total of 15 3DPMM supply chain barriers were identified in this study. The analysis identified limited materials options, slow production speed, manual post-processing, high-skilled data analyst, design and customization expert and simulation accuracy as the significant driving barriers for the medical models supply chain for hospitals. In addition, the authors identified linkage and dependent barriers. The present study findings would help to improve the 3DPMM supply chain.

There were no experts from other nations, so this study might have missed a few 3DPMM supply chain barriers that would have been significant from another nation’s perspective.

ISM would help practitioners minimize 3DPMM supply chain barriers, while DEMATEL allows practitioners to emphasize the causal effects of 3DPMM supply chain barriers.

This study minimizes the 3DPMM supply chain barriers for medical applications through a hybrid ISM and DEMATEL methodology that has not been investigated in the literature.

The purpose of this paper is to identify and model critical barriers to cloud computing adoption (CCA) in Indian MSMEs by the interpretive structural modeling (ISM) approach.

In this paper, through a literature survey and expert opinions, 14 critical barriers were identified, and the ISM tool was used to establish interrelationship among the identified barriers and to determine the key barriers having high driving power.

After analyzing the barriers, it was found that three barriers, namely, lack of confidentiality (B8), lack of top management support (B3) and lack of sharing and collaboration (B2) were most significant.

The developed model is based on the expert opinions, which may be biased, influencing the final output of the structural model. The research implications of the developed model are to help managers of the organization in the understanding significance of the barriers and to prioritize or eliminate the same for the effective CCA.

This study is for the first time an attempt that has been made to apply the ISM methodology to explore the interdependencies among the critical barriers for Indian MSMEs. This paper will guide the managers at various levels of an organization for effective implementation of the cloud computing practices.

The digital warehouse management system is an emergence that forms a critical part of the transformation of economic structure in Industry 4.0. In the present business scenario, the warehouse management system encounters a messy layout, poor damage control, unsatisfactory order management, lack of visibility and lack of technological interventions. Digital twin (DT) based warehouse system shows the ontology and knowledge graphs for competitive advantage by consolidating and transferring goods directly from an inbound supplier to an outbound customer on short notice and with no or limited storage. There remains a lack of clarity on how the DT can be implemented successfully in warehouse management.

The current literature remains largely unstructured and scattered due to a lack of a systematic approach to integrating the research implications and analysis. This paper probes the conceptualization of the DT with the help of theoretical analysis using the systematic literature analysis method.

The study explores essential concepts such as interoperability and integrability in implementing DT. Further, it analyzes the role of a supply chain control tower (SCCT) in modern supply chain management. A research framework is proposed for practitioners and academicians by incorporating the opportunities and challenges associated with DT implementation. The research findings are mainly threefold: Conceptualization of DT, Featuring SCCT and Exploration of cross-computer platform interfaces, scalability and maintenance strategies.

This study is among the first to analyze and review DT applications in warehouse management. Moreover, the study proposes a theoretical toolbox for the practitioners to successfully implement the DT in warehouse DT-based warehouse management system: A theoretical toolbox for future research and applications.

With the change in climate and increased pollution, there has been a need to reduce environmental carbon emissions. This research aims to develop a framework for reducing environmental carbon footprints to improve business performance.

This study uses Scientific Procedures and Rationales for the Systematic Literature Reviews (SPAR-4-SLR) approach. Articles are searched in the Scopus database using various keywords and their combinations. It resulted in 651 articles initially. After applying different screening criteria, 61 articles were considered for the final study.

This study provided four themes and sub-themes within each category. This research also used theories, methodologies and context (TMC) framework to provide future research questions. This study used the antecedents, decisions and outcomes (ADO) framework for synthesising the findings. The ADO framework will help to achieve carbon neutrality and improve firms' supply chain (SC) performance.

This study provides theoretical implications by highlighting the various theories that can be used in future research. This study also states the practical implications for the achievement of carbon neutrality by the firms.

This study contributes to the literature linking carbon neutrality with business performance.

The study aims to explore the critical approaches adopted by innovative organizations and to build an environment of trust between the multiple stakeholders collaborating for new product development (NPD).

A qualitative research approach is adopted in this study. Fifteen semi-structured interviews were conducted with experts from the wood product industry in Quebec, Canada. These organizations have successfully adopted the latest technological developments and have developed a strong collaboration with their stakeholders.

The study identified eleven strategies for the innovative organizations that included early involvement of the stakeholders in the design process, developing long-term relationships and fostering a transparent environment using Industry 4.0 technologies. A novel framework for using this strategy is presented with three stages of application, namely, planning, enactment and review.

Inter-organizational collaborations in NPD are more successful when imbued with trust. The NPD strategies must allow innovative organizations to achieve a balanced ecosystem in which value created through the adaption of new technology can be thoroughly captured through commercialization on time with no field failure.

The study adds to the body of knowledge in stakeholder theory and NPD research and practice.

Despite the growing awareness of supply chains on industry 4.0 (I4.0) capabilities as the enabler of sustainable performance, little is known about what accelerates this interaction. Prior studies have focused on the ambidexterity dilemma and the need to adopt sustainable inter-organizational governance to drive I4.0 capabilities while achieving sustainable performance. To address these issues, this paper aims to explore the distinct and combined effects of several approaches such as digital business transformation (DBT), organizational ambidexterity (OA) and circular business models (CBMs) on the relationship between I4.0 capabilities and sustainable performance.

Drawing upon a hybrid methodology including structural equation modeling and fuzzy set qualitative comparative analysis, this paper develops and tests a hypothetical model using data collected from 306 organizations in Europe, Asia and Africa.

The study findings lead to several important implications concerning the potential paths linking I4.0 and sustainable performance. Notably, the DBT was found to mediate this relationship by integrating circular principles to devise business models. Moreover, OA was found to substitute the CBMs in developing new sustainable business models and reconcile sustainability.

The study is among the first to analyze the combined effects of OA, DBT and CBMs on the relationship between I4.0 capabilities and sustainable performance at the supply chain level. Moreover, the findings propose several solutions to resolve the sustainability dilemma through I4.0 capabilities, DBT, OA and CBMs.

The study aims to identify the potential drivers of big data analytics (BDA) practices in the supply chain and develop a sustainability evaluation model to evaluate drivers of big data for sustainability development.

The mixed-method approach was applied to assess sustainability dimensions and calculate the score using two phases. In Phase I, the BDA drivers in the e-commerce industry were finalised using the partial least square based structural equation modelling (PLS-SEM) method. In Phase II, a case study in the Indian fashion e-commerce industry was carried out to evaluate sustainability dimensions with respect to drivers of BDA and the sustainability score was calculated using the fuzzy analytical hierarchical process (AHP) method.

The index for economic sustainability (0.220), social sustainability (0.142) and environmental sustainability (0.182) were derived. The higher index value of economic sustainability compared to social sustainability and environmental sustainability signified those drivers of big data bring social and environmental uncertainty along with economic sustainability.

The study will help practitioners promote BDA use for developing environmental/social/economic sustainability in supply chains. Policymakers must ensure whether the integration of BDA practices brings down cost and brings strategic value for ensuring big data success. The study will help managers decide a constant trade-off between the requirement for social, environmental and economic performance.

The study corroborates and adds to the BDA literature by emphasising the positive role of BDA in sustainability development in the supply chain area and highlighting the significant role of different drivers of BDA in sustainability development.