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The purpose of this paper is to identify the critical factors influencing the cloud computing adoption (CCA) in the manufacturing micro, small and medium enterprises (MSMEs) by employing a decision-making trial and evaluation laboratory (DEMATEL) methodology.

Through literature review and expert opinions, 30 significant factors were identified, and then a DEMATEL approach was applied for exploring the cause–effect relationship between the factors.

The results of study highlighted that five factors, namely, “hardware scalability and standardisation”, “cost (subscription fees, maintenance cost and implementation cost (CS1)”, “innovation”, “installation and up gradation (CS28)”, and “quality of service” were the most significant factors influencing the CCA in the case sector.

The DEMATEL model was developed by considering expert inputs, and these inputs could be biased which can influence the reliability of the model. This study guides the organisational managers, cloud service providers and governmental organisations in formulating the new policies/strategies or modifying the existing ones for the effective CCA in the case sector.

For the first time. interdependency between the critical factors influencing CCA was discussed by employing the DEMATEL approach in the Indian manufacturing MSMEs context.

The purpose of this paper is to identify and model the evaluation criteria for the selection of third-party logistics service provider (3PLSP) by an interpretive structural modelling (ISM) approach in the pharmaceutical sector.

Delphi technique was used for identifying the most significant criteria, and the ISM method was employed for developing the interrelationship among the criteria. Also, the critical criteria for having high influential power were identified by using the Matrice d’Impacts Croisés Multiplication Appliqués à un Classement analysis.

The most significant factors, namely, capability of robust supply network/distribution network, quality certification and health safety, service quality and environmental quality certifications, were found to have a high driving power, and these factors demand the maximum attention of the decision makers.

As the ISM approach is a qualitative tool, the expert opinions were used for developing the structural model, and the judgments of the experts could be biased influencing the reliability of the model. The developed hierarchical concept is proposed to help the executives, decision and policy makers in formulating the strategies and the evaluation of sustainable 3PLSP.

It is an original research highlighting the association between the sustainable 3PLSP evaluation criteria by employing ISM tool in the pharmaceutical industry. This paper will guide the managers in understanding the importance of the evaluation criteria for the efficient selection of 3PLSP.

This study aims to identify and analyse critical barriers to cloud manufacturing (CM) adoption for achieving sustainability amongst manufacturing micro, small and medium-sized enterprises (MSMEs) in an emerging economy.

Initially, through a literature survey and expert inputs, this study identified and finalized 21 critical barriers to CM adoption, which were further analysed by employing a hybrid multiple criteria decision-making (MCDM) approach. In this approach, the best–worst method (BWM) was used to rank the identified barriers. However, to analyse the interrelation amongst these barriers and classify them into the cause-effect group, the decision-making trial and evaluation laboratory (DEMATEL) method was employed. Furthermore, the study recommended various strategies that can help overcome high-priority barriers and enhance CM adoption within firms.

The results of the study show that organizational, legal and economic barriers are the high-priority barriers that need to be addressed to enhance CM adoption.

The findings of the study will help managers and decision-makers in manufacturing MSMEs develop effective strategies and policies to enhance CM adoption.

Notably, this investigation is one of the preliminary research activities to explore the sustainability aspect of CM adoption amongst MSMEs in an emerging economy.

Textile and Apparel (T&A) sector significantly influences socio-economic and environmental dimensions of the sustainability. The purpose of this paper is proposed to establish the interrelationship among the critical barriers to the sustainable development of T&A supply chains by using a multi-criteria decision-making approach and to obtain a ranking of the barriers.

In the present investigation through literature review and from expert opinions, 14 significant challenges to the sustainable growth of T&A sector have identified. For establishing the interrelationship and for developing a structural model of the identified challenges, interpretive structural modelling (ISM) methodology is employed.

The results of the investigation revealed that lack of effective governmental policies (B8), poor infrastructure (B4), lack of effective level of integration (B6), low foreign investment (B13) and demonetization (B12) are the top most significant challenges.

The model development based on the expert inputs from the industry and academia, these inputs could be biased influencing the accuracy of the model. Also, inclusion more factors for the analysis will improve the reliability of the model.

This research is intended to guide the policy and decision makers for improving overall the growth of the T&A supply chain.

The purpose of this study is to determine the significant factors affecting the adoption of Cloud of Things (CoT) by Indian small and medium-sized enterprises, using exploratory and confirmatory factor analysis.

Significant factors that impact CoT implementation were identified through a detailed literature survey. A conceptual framework and hypotheses were proposed for linking the significant factors so identified, namely, cost saving, relative advantage, sharing and collaboration, reliability, security and privacy, technical issues and adoption intention. The data were collected from 270 Indian SMEs using an online survey. Structural equation modelling (SEM) was used to test the proposed model.

It was observed that factors such as “sharing and collaboration”, “cost saving” and “relative advantage” had a positive influence on CoT adoption. Findings of the study also supported the hypothesis that “security and privacy” were the prime concerns for CoT adoption.

Sample coverage across different geographical areas with qualitative data can be helpful. The SEM methodology is only capable of verifying linear relationships; to counter this, a hybrid approach with tools such as artificial neural network and multiple linear regression can be used.

This study intends to guide the managers of SMEs, cloud service providers and regulatory organisations for formulating an effective strategy to adopt CoT. It may be noted that CoT is the prime building block of Industry 4.0 and SMEs will benefit from government support for the same.

This paper highlights the influence of factors on the adoption intention of CoT with a focus on the SMEs of a developing country like India.

Cloud technology is extremely critical for the continuing progress of Industry 4.0 and it helps in pooling centralized information for the business. Further, it offers a platform for collaboration for improving the performance of the industry. This paper aims to investigate the factors affecting the implementation of cloud technology for boosting Industry 4.0 adoption in micro, small and medium enterprises (MSMEs) of the manufacturing sector.

A total of 14 enablers were considered for the case study which were obtained from the literature survey and shortlisted by the experts of the domain (academia and industries). The interpretive structural modelling (ISM) approach has been used as a methodology for exploring the relationships between the enablers. Matrices impact croises multiplication applique and classment (MICMAC) analysis has been carried out for the validation of the developed structural model. MICMAC analysis helps to identify driving power and dependency potential of all considered enablers.

The results of the investigation indicate that three factors, namely, system integration, project management and competitive pressure, were significant. These factors drive all other considered factors in the implementation process.

The opinions of the experts from the industry and academia were analyzed for the development of the hierarchical model and these inputs could be biased. This investigation intends to help the decision makers in the effective adoption of the cloud and Industry 4.0 technologies and for the formulation of the efficient implementation policies.

The present study aims to focus on cloud technology as well as Industry 4.0 in the context of manufacturing MSMEs and none of the previous investigations analyzed the enablers that influence the adoption of cloud technology for boosting Industry 4.0, especially using the ISM approach.

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 reduction of food wastage at every stage of a fresh produce supply chain helps in achieving balance among all three dimensions (social, ecological and economic) of the sustainability and helps in stimulating the growth and development in the agricultural domain. The purpose of this paper is to address the causal factors of post-harvesting losses (PHLs) occurring in the transportation phase.

Through exhaustive literature survey and expert opinions, 12 crucial barriers to sustainable transportation of fruits and vegetables (F&V) are identified. The interpretive structural modeling (ISM) methodology, a multi-criteria decision-making (MCDM) approach, is employed for developing a structural model of the identified barriers.

The results of the analysis highlighted that two factors, namely, the non-availability of refrigerated vehicles, and excessive loading on the vehicles, are the most significant barriers to sustainable transportation which are found to have the highest driving power.

The results of the present research are applicable to the F&V supply chains only. The established interrelation among the identified factors depends on the judgments given by the experts which could be biased. The developed ISM model is intended to guide the policy and decision makers for formulating the policies for the performance improvement of the fresh produce value chain.

It is the first research of its kind focusing on the model development of critical factors causing PHLs in the transportation phase of the agricultural fresh produce supply chain using MCDM process.

The purpose of this paper is to analyse proposed cloud computing integration (CCI) and external integration (EI) effects on the relationship between the integration of supply chain and business performance of the organisation in the Indian context.

A two-stage, structural equation modelling (SEM) and artificial neural network (ANN) methodology are employed for the analysis, and for verifying the robustness of the developed model sensitivity analysis is performed.

The results of SEM revealed that out of 14 hypotheses, 12 hypotheses were supported. Furthermore output of SEM was used as input for the ANN model and the results highlighted that production flexibility is an essential factor for operational business performance (OBP) followed by customer integration, supplier integration, product quality, internal integration and on-time delivery (OD).

This study focussed on the emerging economies context and cannot be applied to all the countries, and there could be other derived variables from the real factors. This investigation is intended to guide various policy and decision makers of the case domain.

This study has introduced new factors such as CCI, EI and organisational business performance.

This study aims to develop effective digitization strategies that can assist in enhancing the adoption of digital technologies among manufacturing micro, small and medium enterprises of an emerging economy.

Initially, through a literature survey and by using the Delphi approach that comprises continuous inputs from the team of experts, this study devised 10 key digitization strategies, which were further analysed using a hybrid multi-criteria decision-making approach. This approach helped to develop a hierarchical structure representing mutual interrelation among identified strategies and the cause-effect relation. Also, the strength of interdependence among identified strategies was explored.

Results of the study show that digitization strategies, namely, “development of strategic roadmap”, “effective change management”, “training and education” and “‘participation in knowledge sharing platforms” are the most significant ones.

The outcomes of the study will help decision makers and policymakers of manufacturing micro, small and medium enterprises (MSMEs) in devising effective policies and strategies to enhance digital technology adoption within the firm.

Notably, this research is one of the preliminary investigations to explore the digitization strategies for the manufacturing sector of an emerging economy.