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Rising energy demand and the quest for achieving climate change targets have been pushing emerging markets like India to bolster the natural gas share in their energy mix. The country has set an aggressive target of increasing natural gas share in the energy mix to 15% by 2030. The purpose of this study is to acknowledge the need for adopting and developing strategies for natural gas business market development to ensure a reliable supply at an affordable price. Hence, this study explores the natural gas market business development strategies and assesses them through cause/effect analysis.

This study proposed an integrated framework based on the Grey concept and Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique to assess and determine the interdependence among the natural gas business market development strategies by cause-and-effect group analysis. The application of Grey theory reduced the uncertainty and subjectivity involved in the decision-making process. Later, sensitivity analysis is also performed to check the robustness of the framework.

The natural gas business market development strategies are identified through a systematic literature search and contributions from industry experts. The findings of this study highlight the importance of developing pipeline and storage infrastructure facilities, ensuring supply security through long-term imports and overseas investment, implementing free-market-based pricing, simplification and standardization of regulatory processes at state and national levels, etc., for the development of the natural gas market development in India.

This study acknowledges the natural gas market development strategies and evaluated them into cause-and-effect groups which are limited to Indian context. All evaluations in the Grey-based DEMATEL method were made in this study based on the decision team inputs which limits the generalization to other geographies. Moreover, the opinions of the experts can be subjective and differ. The selection of the experts is done through non-probability sampling process.

This study could support the government and decision-makers in formulating the appropriate strategies to develop the domestic natural gas market. The cause-and-effect relationships are helpful for the companies, management, government, regulators and other stakeholders to understand the criticality of the causal strategies that must be implemented for developing the favorable natural gas business market scenario.

This study explores and evaluates the strategies that successfully bolster the natural gas business demand in India using Grey-based DEMATEL framework. By focusing on those critical strategies, relevant stakeholders would ensure a reliable natural gas supply at affordable prices.

The purpose of this paper is to explore the phenomenon of collaborative resilience through in-depth case study research in India. This study endeavours to identify and model the critical success factors of collaborative resilience.

Eight critical success factors of collaborative resilience were identified through literature search. Modelling and analysis of these factors was conducted using grey-based DEMATEL method. Data were collected from supply chain experts in Indian industries.

It was found that organizational factors like top management commitment and resilience system design exhibit highest causality on the entire system. Also, co-adaptive transformation and resilience goal alignment are most important for managers. Overall, this research provides a guideline and mechanism to build collaborative resilience in supply chains.

Through the identification of eight critical success factors, this research has related and grounded the concept of collaborative resilience into pre-exiting supply chain practices and concepts. Through rigorous quantitative modelling and analysis of these factors, this research provides a guideline to managers for building collaborative resilience in supply chains.

To the best of the authors’ knowledge, this is the first study that has proposed the concept of collaborative resilience in supply chain and has conducted empirical research on the phenomenon in India.

The purpose of this paper is to recognize and model the enablers of supply chain quality risk management (SCQRM) through an empirical study in the Indian automotive companies.

A systematic literature review was conducted to extract the key enablers of quality management (QM) and risk management in the context of manufacturing supply chains. A grey-based DEMATEL method was employed to identify and model the key enablers of SCQRM.

The results of empirical study showed that the effectiveness of QM and risk management systems for automotive supply chain is driven by a set of common enablers that could be employed for developing dedicated SCQRM systems. The common causal factors in the model such as the involvement of top leaders, inter-firm communication and strategic-level alignment between supply chain members on both these issues clearly state that there is a need for a broader policy at an early stage.

It is crucial for the automotive companies to develop and implement structured systems for SCQRM keeping in view the impact of any unaddressed quality risk on missed production targets, vehicle recalls and safety hazards.

This study ascertains the key enablers of SCQRM with emblematic focus on automotive industry and identifies if there are commonalities in these enablers.

Successful device development brings substantial revenues to medical device manufacturing industries. This paper aims to evaluate factors contributing to the success of medical device development (MDD) using grey DEMATEL (decision-making trial and evaluation laboratory) methodology through an empirical case study.

The factors are identified through literature review and industry experts’ opinions. Grey-based DEMATEL methodology is used to establish the cause-effect relationship among the factors and develop a structured model. Most significant factors contributing to the success of MDD are identified. An empirical case study of an MDD and manufacturing organisation is presented to demonstrate the use of the grey DEMATEL method. Sensitivity analysis is carried out to check robustness of results.

The results of applying the grey DEMATEL methodology to evaluate success factors of MDD show that availability of experts and their experience (SF4) is the most prominent cause factor, and active involvement of stakeholders during all stages of MDD (SF3) and complete elicitation of end-user requirements (SF1) are the most prominent effect factors for successful MDD. A sensitivity analysis confirms the reliability of the initial solution.

The findings will greatly help medical device manufacturers to understand the success factors and develop strategies to conduct successful MDD processes.

In the past, few success factors to MDD have been identified by some researchers, but complex inter-relationships among factors are not analysed. Finding direct and indirect effects of these factors on the success of MDD can be a good future research proposition.

Staffing is one of the most influential human resource (HR) activities and is the primary method of hiring and retaining human resources. Among staffing’s several activities, recruitment and selection are one of the most crucial activities. It is possible to rehire former firm employees using the talent management strategy known as “boomerang recruitment”. The boomerang recruitment trend has tremendously grown because many employees who believe they are qualified for the position now wish to return to their old employers. According to data, boomerang employees can be 50% less expensive than conventional ways of hiring. The purpose of this study is to identify the generic critical factors that play a role in the boomerang hiring process based on the literature review. Next, the objective is to determine the relative weight of each of these factors, rank the candidates, and develop a decision-making model for boomerang recruitment.

This paper focuses on the grey-based multicriteria decision-making (MCDM) methodology for recruiting some of the best candidates out of a few who worked for the organization earlier. The grey theory yields adequate findings despite sparse data or significant factor variability. Like MCDM, the grey methods also incorporate experts' opinions for evaluation. Furthermore, sensitivity analysis is also done to show the robustness of the suggested methodology.

Seven (7) recruitment criteria for boomerang employees were identified and validated based on the opinions of industry experts. Using these recruitment criteria, three candidates emerged as the top three and created a pool out of six. In addition, this study finds that Criteria 1 (C1), the employee's past performance, is the most significant predictor among all other criteria in boomerang hiring.

Since the weights and ratings of attributes and alternatives in MCDM methods are primarily based on expert opinion, a significant difference in expert opinions (caused by differences in their knowledge and qualifications) may impact the values of the grey possibility degree. However, enough attention was taken while selecting the experts for this study regarding their expertise and subject experience.

The proposed method provides the groundwork for HR management. Managers confronted with recruiting employees who want to rejoin may use this model. According to experts, each attribute is not only generic but also crucial. In addition, because these factors apply to all sectors, they are industry-neutral.

To the best of the authors’ knowledge, this is the first study to apply a grey-based MCDM methodology to the boomerang recruitment model. This study also uses an example to explain the computational intricacies associated with such methods. The proposed system may be reproduced for boomerang recruiting in any sector because the framework is universal and replicable. Furthermore, the framework is expandable to include new criteria for different work.

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.

Third-party logistics (3PL) plays a main role in supply chain management and, as a result, has experienced remarkable growth. The demand for 3PL providers has become a main approach for companies to offer better customer service, reduce costs, and gain competitive advantage. This paper identifies important criteria for 3PL provider selection and evaluation, and the purpose of this paper is to select 3PL providers from the viewpoint of firms which were already outsourcing their logistics services.

This study utilized the grey decision-making trial and evaluation laboratory (DEMATEL) method to develop 3PL provider selection criteria. Because human judgments are vague and complicated to depict by accurate numerical values, the grey system theory is used to handle this problem.

The findings revealed the structure and interrelationships between criteria and identified the main criteria for 3PL provider selection. The most important criteria for 3PL provider selection are on time delivery performance, technological capability, financial stability, human resource policies, service quality, and customer service, respectively.

The paper’s results help managers of automotive industries, particularly in developing countries, to outsource logistics activities to 3PL providers effectively and to create a significant competitive advantage.

The main contributions of this paper are twofold. First, this paper proposes an integrated grey DEMATEL method to consider interdependent relationships among the 3PL provider selection criteria. Second, this study is one of the first studies to consider 3PL provider selection in a developing country like Iran.

The objective of the study is to identify and analyse drivers of smart manufacturing using integrated grey-based approaches. The analysis facilitates industry practitioners in the identification of preference of drivers through which smart manufacturing can be implemented. These drivers are explored based on existing literature and expert opinion.

Modern manufacturing firms have been adopting smart manufacturing concepts to sustain in the global competitive landscape. Smart manufacturing incorporates integrated technologies with a flexible workforce to interlink the cyber and physical world. In order to facilitate the effective deployment of smart manufacturing, key drivers need to be analysed. This article presents a study in which 25 drivers of smart manufacturing and 8 criteria are analysed. Integrated grey Technique for Order Preference by Similarity to Ideal Solution (grey TOPSIS) is applied to rank the drivers. The derived ranking is validated using “Complex Proportional Assessment – Grey” (COPRAS-G) approach.

In total, 25 drivers with 8 criteria are being considered and an integrated grey TOPSIS approach is applied. The ranking order of drivers is obtained and further sensitivity analysis is also done.

In the present study, 25 drivers of smart manufacturing are analysed. In the future, additional drivers could be considered.

The study presented has been done with inputs from industry experts, and hence the inferences have practical relevance. Industry practitioners need to focus on these drivers in order to implement smart manufacturing in industry.

The analysis of drivers of smart manufacturing is the original contribution of the authors.

: Sustainability in fast-moving consumer goods (FMCG) supply chains (SC) is receiving greater than ever attention due to the increasing awareness of sustainability challenges such as climate change and labor rights. A definite solution is to integrate sustainable supply chain management (SSCM) practices all through the upstream and downstream entities of SC. This study identified and compared the drivers for the implementation of SSCM practices in Indian FMCG sector.

A methodology based on Grey-Decision Making Trial and Evaluation Laboratory (DEMATEL), a hybrid multiple-criteria decision making (MCDM) technique and sensitivity analysis was used to envisage the complex causal relationships among the identified SSCM drivers and to identify the critical ones.

The results showed that regulatory and legislative pressure, competition pressure and innovativeness dominantly drive the implementation of SSCM practices in the upstream and downstream SC of the FMCG sector.

The study examined levers of sustainability in FMCG supply chains in an emerging market with most of the extant research limited to automotive and electronic supply chains.

This research aims to identify, examine and evaluate barriers to the adoption of digital servitization in manufacturing firms in the case of the Sri Lankan manufacturing sector and analyze the inter-relationships among digital servitization barriers.

Based on the comprehensive literature review, 13 barriers were identified. The grey decision-making trial and evaluation laboratory (grey-DEMATEL) approach was used to uncover and analyze the relationships among barriers in terms of their overall influence and dependencies.

A prominent barrier to the success of adopting digital servitization in the Sri Lankan manufacturing sector is the lack of digital strategy in developing activities related to the design of digital service packages, organizational structures and processes. Supply chain integration is the most influential factor, which plays an important role in developing a competitive advantage by encouraging innovation process capabilities in servitized companies.

Industry practitioners can develop guidelines for adopting digital servitization practices based on the importance and interdependencies of different barriers and thereby prioritize projects within a program of digital servitization adoption in their organizations.

Research studies on barriers to digital servitization are limited to exploratory nature and have adopted mainly the qualitative approach, such as in-depth interviews. No empirical study has investigated the inter-relationships among digital servitization adoption barriers in the manufacturing sector. This study provides a holistic view of different barriers to the adoption of digital servitization in the manufacturing sector as a basis for developing comprehensive digital servitization strategies to manage and leverage complexity in digital transformation.