Benchmarking the Interactions among Green and Sustainable Vendor Selection Attributes

Purpose The purpose of this paper is to report a study on the application of interpretative structural modelling (ISM) integrated with multi-criteria decision-making (MCDM) techniques for enabling the sustainability supplier selection. Design/methodology/approach In this paper, two approaches of hybrid MCDM methods are followed and the selection of sustainable supplier was based on the comparative results obtained from both the methods. The first hybrid approach is ISM – analytic network process (ANP) – ELimination and Et Choice Translating REality (ELECTRE II) and the second hybrid approach is ISM – ANP – Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). ISM was used to identify the inter relationship between the criteria. Inter-relationship of criteria obtained from ISM will serve as an input for ANP. The weights obtained from ANP will be used in ELECTRE II and VIKOR. ELECTRE II is an outranking method, whereas VIKOR is a compromise ranking method; comparison of both the methods was carried out in this study. Findings In this study, two modules ISM–ANP – ELECTRE and ISM–ANP – VIKOR were compared for the problem of sustainable supplier selection. ELECTRE results with a single solution showed that Supplier 2 can be selected as the best supplier; VIKOR result shows that Supplier 1 and Supplier 2 can be selected as the best suppliers. Originality/value The selection of sustainable supplier considering the interrelationship of criteria using ISM and ranking the alternatives using compromise and outranking techniques was found to be original and novel contribution of the author.

PurposeSecurity and safety have remained important concerns for mankind since ancient times. In the context of railways, however, the threat perceptions to safety and security have increased significantly lately. In view of this, the Indian Railways requires an effective and efficient security management system. The purpose of this paper is to propose an integrated approach to help develop the Indian railway security system (IRSS) by successively reducing the complexity of the system through a series of studies.Design/methodology/approachThe relevant elements of the complex system of Indian Railways have been identified. The framework in which the elements exist and interact with each other has been clearly established using the interpretive structural modelling (ISM) technique. The output of ISM is further reduced in complexity by having different policy option profiles. A comparison of different option profiles has been done by a multi-criteria decision-making technique, the analytic hierarchy process (AHP), by choosing suitable criteria for comparison.FindingsThe following elements need to be pursued as the key objectives for making IRSS: protection of passengers, protection of property, modernisation, manpower enhancement, multi-skilling of staff, latest technology and enhanced legal powers.Research limitations/implicationsThe present research can be extended in many important ways. Interpretive structural models for different contextual relationships can be developed and used for formulating and implementing customised security policy. Policy elements and the ISM structure obtained in this research can be utilised for the system dynamic modelling of IRSS. A pilot study can be done to implement the recommendations made in this study.Practical implicationsThe ISM model developed can be implemented as a policy tool in enhancing the railway’s security. Some of the policy elements proposed appear to be consistent with the strategic direction being undertaken in the railway security in the country.Social implicationsSecurity is an important concern for mankind and social civilisations. The results have significant welfare implications in India and the rest of the world.Originality/valueThe present study is one of the first approaches in a series of studies in railway security in India. The results of this study can be extended to other security scenarios with similar needs.

Purpose – The purpose of this paper is to highlight the application of Interpretive Structural Modeling (ISM) to analyze the barriers in implementation of Total Productive Maintenance (TPM). TPM is explained in brief with emphasis on maintenance programs to improve quality of products, reliability of processes and reduction in cost. Barriers in implementation of TPM are also discussed. Concept of ISM and steps in developing ISM are described in detail. The authors then illustrate the research methodology which involves applying ISM to analyze barriers in TPM. Design/methodology/approach – The paper starts off by describing the concepts of TPM and ISM. Barriers in implementation of TPM are discussed. It explains ISM as a methodology to understand the underlying interrelationship among the inhibiting factors. The authors draw up an action plan to carry out research on the usage of ISM to study the TPM inhibitors, to develop an integrated model to establish the relationship among the different TPM inhibiting factors and to suggest action plan to mitigate these factors. Findings – Interpretive Structural Modeling (ISM) can be used to analyze the driving and dependence power of the variables inhibiting implementation of TPM. The barriers to implement TPM are described with detailed explanation. The complexity of the problem and the degree of interconnection among the variables can be found out. This will help Managers take action on mitigating the barriers. Practical implications – By analyzing the interrelationships among the barriers and their strengths, management can chalk out the strategy to implement TPM in an organization. Management will become aware of the barriers which have the maximum influence and then can act accordingly to mitigate these barriers. This will help in implementing TPM faster and in an organized manner. Originality/value – Many authors have used ISM to study various issues. A couple of authors have used ISM to determine barriers in implementation of TPM. The authors feel that most of the papers describe ISM in brief making it slightly difficult for readers to understand. This paper aims to explain elaborately step-by-step on how to develop an ISM making it easier for researchers to understand the ISM concept. Even though there are papers on TPM and difficulties in implementation of TPM, this paper explains the barriers in implementing TPM based on the experience of the corresponding author having worked in the refinery industry.

This paper aims to identify resilient supplier selection criteria in the desalination supply chain and analyze the interactions between them. We identify 89 criteria from the literature. In the second step, nineteen main criteria were identified based on the literature. Two different multi-criteria decision-making techniques, i.e. interpretive structural modeling (ISM) and fuzzy decision-making testing and evaluation laboratory (fuzzy-DEMATEL), were used to identify driving criteria. Furthermore, standard criteria from each technique, their hierarchies and inter-relationships have been established. The criteria modeling using ISM and Fuzzy-DEMATEL shows that the most influential/driving criteria are management, financial status, and culture. On the other hand, five criteria viz. service, quality, relationship building, adaptive capacity, and responsiveness were commonly identified as the most dependent resilient supplier selection criteria in the desalination supply chain across two different modeling techniques. The findings allow decision-makers to select the desired and drop undesired criteria to select resilient suppliers in desalination. The most common driving criteria can be given high priority over others and can significantly improve the resilient supplier selection. MCDM-based hierarchical models and a causal diagram for resilient supplier selection criteria depicting contextual inter-relationships have been proposed. The main novelty of this research is to identify and modeling resilient supplier selection criteria. Also, multi-criteria decision-making techniques have not been used in desalination supply chain.

PurposeThis research paper aims to analyze the critical barriers to implementing digitalization in the Indian construction industry as Indian construction companies are lagging in the implementation of digital technologies in the work environment.Design/methodology/approachIn this research paper, a qualitative research approach is adopted, and multiple detailed interviews are conducted with industry and academic experts. Further, multi-criteria decision-making (MCDM) techniques are used to finalize the prioritization among various alternatives. The fuzzy-decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) and interpretive structural modeling (ISM) techniques are employed to find the exact relationship among the identified alternatives.FindingsThis study identifies 14 critical barriers from an extensive literature review and multiple interviews with industry professionals, and further driving and critical barriers are identified.Research limitations/implicationsIn this research paper, an exploratory study with a limited number of respondents from a large Indian construction company is carried out. Further, a detailed longitudinal analysis can be done to assess the subjectivity of the participants with more advanced statistical tools. However, this research discusses several points pertaining to the implementation of digitalization in the construction industry. The research further identifies the critical barriers to digitalization in the Indian construction industry.Practical implicationsThe finding of the study has two-pronged implications. First, it provides a road-map to the construction industry by highlighting the engagement of top management as the key focus area for successful digitalization. Second, the finding also shows similarity of the digitalization process to the adoption of process improvement techniques like lean and total quality management (TQM), wherein the top management plays a crucial role in ushering in the implementation of a disruptive change.Originality/valueThe research is unique in two ways. First, this is one of the very few attempts to understand digitalization in the Indian context. Second, the research also demonstrates that the combination of fuzzy DEMATEL and ISM techniques can be successfully employed in the emerging field of construction digitalization research.

Purpose Sustainability is a very important factor to be considered in the supply chain (SC) of any industry. Agricultural industry needs to be addressed even more importantly with the tools of sustainability as it concerns the life of millions. This paper explores the critical barriers (CBs) in the sustainable supply chains (SSCs) of makhana industry located in the northern part of India and seeks to design a model for the researchers and the managers who want to work in this industry. Design/methodology/approach Initially, the CBs were identified with the help of an extensive literature review of sustainability in SCs for agri-industry and discussion with makhana industry experts (consisting of managers and senior managers) and academicians (consisting of professors and research scholars). The study uses the multi-criteria decision-making (MCDM) technique, namely interpretive structural modeling (ISM) and fuzzy ISM to develop the model. The study finally validates the model using Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis. Findings The obtained results indicate that, in the SSC of makhana industry, the role of “Lack of adoption of organic agricultural management techniques” (CB2), “Lack of modern techniques (CB4)”, “Multiple intermediaries” (CB5), “Weak socio-economic conditions” (CB7) and “Lack of proper knowledge” (CB1) are very significant. These barriers are needed to be addressed first as they have the highest driving power and other barriers are directly driven by these CBs. Research limitations/implications The paper has included seven experts, and the interrelationship between CBs has been developed on the basis of their knowledge and discussion, so the results may be a little bias. Moreover, the paper has obtained the results using the ISM and fuzzy ISM by considering ten CBs; the researchers can explore this research by including more CBs and validate the results using other MCDM techniques like fuzzy-decision making trial and evaluation laboratory (DEMATEL), fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Best Worst Method (BWM). Originality/value This study is unique as per industry point of view and may help the researchers and managers to explore the field of makhana.

PurposeThe purpose of this study is to explore and prioritize the barriers that affect weather index-insurance (WII) adoption among customers by utilizing interpretive structural modelling (ISM) and fuzzy-MICMAC.Design/methodology/approachThis paper utilized the combined approach in two phases. In first phase comprehensive literature study and expert mining method have been performed to identify and validate WII adoption barriers. In second phase, ISM has been utilized to examine the direct relationships among WII adoption barriers in order to develop a structural model. Further, fuzzy-MICMAC method has been utilized to analyse indirect relationships among barriers to explore dependence and driver power.FindingsThis study has identified 15 key barriers of WII adoption among customers and developed a structural model based on binary direct relationship using ISM. Later, the outcomes of ISM model have been utilized for analysing the dependence and driver power of each WII adoption barriers in cluster form using fuzzy-MICMAC. The customer awareness related WII adoption barrier are mainly at the top level, WII demand related barriers are in the centre and WII supply related barriers at the bottom level in ISM model.Practical implicationsThe findings offered important insights for WII insurers to understand mutual relationships amongst WII adoption barriers and assists in developing strategy to eliminate dominant key barriers in order to enhance their customer base.Originality/valueBased on best of author's knowledge this paper firstly integrates the ISM fuzzy-MICMAC method into identification and prioritization of barriers that affects WII adoption among customers.

PurposeThere is a concern in literature about the critical elements of lean enterprise (LE) that can be represented as pillars of lean enterprise excellence. However, existing frameworks proposed on LE excellence are very few. The purpose of this paper is to develop a relationship model among the pillars of a proposed framework of LE excellence in Indian manufacturing industry by Jasti et al. (2020) with the help of interpretive structural modelling (ISM) and structural equation modelling (SEM).Design/methodology/approachThe ISM is constructed on two exemplary cases of lean operations from two Indian manufacturing organisations. These cases were selected based on the implementation of lean practices in respective organisations. The two manufacturing organisations which implemented lean practices at different levels were selected as contenders for constructing ISM. The relationships among pillars and constructs of LE framework are obtained from ISM, and later subjected to statistical testing for model fit by using SEM. The input to SEM was the respondent's data collected in a previous study.FindingsThe outcome of the present study revealed that the successful implementation of LE framework requires an appropriate strategy along with top management commitment to get a complete benefits of LE. The study has proposed a strategy to implement the proposed LE framework in Indian manufacturing industry. This study has revealed that ISM developed based on the focal company that implemented lean practices effectively is statistically fit for LE framework.Research limitations/implicationsThe study has established paired relationships among lean pillars for an effective implementation of LE framework. The investigation was started by collecting opinions of experts to perform the appropriate interpretations subsequently. However, the expert judgements can be qualitative in nature and prone to bias and impact the final outcome. To overcome these a large-scale empirical survey is suggested to provide a better catch for interactions in LEs.Practical implicationsThis study helps in providing concrete practical implications to both academic researchers as well as industry professionals. The practitioners normally focus on finding readymade strategies for implementing LE in the organizations. The comprehensiveness of the present work helps the practitioners in implementing LE strategy with ease. The study revealed that management commitment and leadership is driving force but needs strategic implementation methodology for successful implementation.Social implicationsManufacturing industries across the world have been struggling to understand and implement LE strategy effectively. Most of the governments across the world are supporting and motivating various industry practitioners to implement LE strategy by providing financial assistance for conducting training programmes. However, many organizations across the world were not able to implement LE strategy successfully. The present study provides a strategy to implement LE framework effectively in an organization.Originality/valueThe study offers a unique approach for analysing the underlying relationships among pillars of LE for effective management. Researchers can use the results of this study for developing frameworks in various domains of LE.

PurposeThe purpose of this paper is to identify and build a hierarchy of the factors influencing competitiveness of electronics manufacturing industry (EMI) at the industry level and apply the interpretive structural modeling, fuzzy Matriced’ Impacts Croisés Multiplication Appliquée á UN Classement (i.e. the cross-impact matrix multiplication applied to classification; MICMAC) and analytic hierarchy process (AHP) approaches. These factors have been explained with respect to managerial and government policymakers’ standpoint in Indian context.Design/methodology/approachThis study presents a hierarchy and weight-based model that demonstrates mutual relationships among the significant factors of competitiveness of the Indian EMI.FindingsThis study covers a wide variety of factors that form the bedrock of the competitiveness of the EMI. Interpretive structural modeling and fuzzy MICMAC are used to cluster the influential factors of competitiveness considering the driving and dependence power. AHP is used to rank the factors on the basis of weights. Results show that the “government role” and “foreign exchange market” have a significantly high driving power. On the other hand, the “capital resource availability” and “productivity measures” come at the top of the interpretive structural modeling hierarchy, implying high dependence power.Research limitations/implicationsThe study has strong practical implications for both the manufacturers and the policymakers. The manufacturers need to focus on the factors of competitiveness to improve performance, and at the same time, the government should come forward to build a suitable environment for business in light of the huge demand and frame suitable policies.Practical implicationsThe lackluster performance of the industry is because of the existing electronics policies and environmental conditions. The proposed interpretive structural modeling and fuzzy MICMAC and AHP frameworks suggest a better understanding of the key factors and their mutual relationship to analyze competitiveness of the electronics manufacturing industry in view of the Indian Government’s “Make in India” initiatives.Originality/valueThis paper contributes to the industry level competitiveness and dynamics of multi-factors approach and utilize the ISM–fuzzy MICMAC and AHP management decision tool in the identification and ranking of factors that influence the competitiveness of the EMI in the country.

Safety issues in the dairy industry have attracted greater attention in recent years, and the public have showed an intensive concern regarding safety failure in the dairy supply chain. Since the dairy industry is closely associated with humans and fulfills basic necessities, it is necessary to explore safety failure factors (SFFs) affecting the supply chain of the dairy industry. This paper aims to explore the SFFs of the dairy supply chain using an interpretive structural modeling technique (ISM) and Matrice d’Impacts Croises Multiplication Appliques a un Classement (MICMAC) analysis in a Pakistani context. A total of twenty-five failure factors have been identified through literature reviews and the opinion of an expert team, including managerial and technical experts from the dairy industry, as well as academics. Interpretive structural modeling (ISM) is applied to analyze the mutual interaction among barriers and to develop a structural model. The MICMAC technique is used to identify the importance of SFFs based on their driving and dependence power. The results of this study will help decision-makers in the dairy industry to plan their supply chain activities more effectively and efficiently by managing the identified barriers.

Background: Today, despite the complex environment of businesses, the development of strategic thinking has become one of the important factors in gaining a sustainable competitive advantage in organizations; so that its application by managers leads to increased organizational performance and improved competitive conditions. Objectives: This investigation focused on determining the strategic cognition model used in Iran’s health industry. Methods: This study adopts a mixed-methods (qualitative-quantitative) approach with an applied research objective. The target population includes all health industry experts in Iran. The research process began with a comprehensive literature review, followed by in-depth interviews with 17 seasoned professionals to qualitatively identify and validate the key drivers of strategic thinking in Iran’s healthcare sector. Subsequently, a quantitative phase was implemented, during which expert surveys were used to construct the structural self- interaction matrix (SSIM). Following the interpretive structural modeling (ISM) methodology, the initial and final reachability matrices were derived, enabling the classification of research components and the development of the structural model. Additionally, MICMAC analysis was performed to evaluate variable dependence and penetration. Results: All the components and codes of this research are summarized within the framework of four main factors: Obstacles, national infrastructures, scientific insight, and foresight. After obtaining these results, and in order to quantitatively verify and achieve the structural- interpretive model, the main components of the research were tested using the structural-interpretive modeling method, and finally, the final model of the research was extracted. Conclusions: It is suggested that managers and all trustees of the health industry analyze the competitive and political-legal environment of their industry and organization as a first step. Using trend analysis and maintaining a forward-looking vision can help managers better understand the future environment.

Incorporating polarity of relationships in ISM and TISM for theory building in information and organization management

PurposeIn Industry 4.0, different technologies are used to improve the efficiency and reduce the downtime of the processes in the organization. It can be achieved by using predictive maintenance (PdM) technique to avoid the sudden breakdowns in the industry. It is important to implement digital twin (DT) for PdM. DT for PdM is in the nascent stage. This study is focused on the identification of determinants of the DT for PdM for real-life implementation.Design/methodology/approachThis study has focused on the determinants of DTs for predictive maintenance for implementation. To analyse these determinants, multi-criteria decision-making (MCDM) techniques were used by applying Decision-Making Trail and Evaluation Laboratory (DEMATEL) and interpretive structural modelling (ISM) approaches.FindingsIn this study, 13 determinants were found out through the literature survey. These determinants were classified into cause and effect in the DEMATEL approach. Similarly, ISM methodology was applied to these determinants to categorized determinants into different levels. DEMATEL and ISM results were compared, and it was found that real-time analysis, decision-making, self-monitoring and diagnosis are the most important.Practical implicationsThis study is useful for the academic researcher as well as the industrialist to implement DT in PdM. Therefore, it can be implemented in real-life application by considering the important determinants.Originality/valueThis is one of the first studies that represent the investigation of DT for PdM using the DEMATEL and ISM approaches.

Cold supply chain (CSC) is a process that involves temperature-controlled activities ranging from the acquisition of raw materials and down to the end consumers. A sustainable cold chain supplier is the one that incorporates sustainable practices in its complete cycle of operations. This is to ensure keeping the products from going to waste, especially in the case of a developing country. To identify the driving factors towards the sustainable cold chain supplier, this study utilizes the interpretive structural modelling (ISM) approach in the first phase. Fifteen various sustainability factors were analyzed and the “utilization of renewable resources” factor concluded to be the most important driving factor. By implementing renewable resources, a supplier can be able to convert its manufacturing processes and services to sustainable assets. The second phase of this study conducts the selection of cold chain suppliers in the context of Pakistan. For this purpose, fuzzy VIKOR, a multi-criteria decision-making (MCDM) technique is incorporated to analyze eight suppliers based on fifteen distinct criteria. The results concluded Mitchell foods to be the most economically, environmentally and socially sustainable suppliers in the context of Pakistan. This study recommends providing business-friendly incentives to suppliers like Mitchells and new investors who tend to keep their operations sustainable by adopting renewable resources. Furthermore, the relaxation of taxes and creating job employability by working with sustainable suppliers can contribute positively towards economic growth and the overall society. The study holds novelty in the area of cold chain supplier selection for Pakistan by utilizing a novel approach in the form of ISM and fuzzy VIKOR techniques, thus forming a major application of this research study.

SMEs did not have enough ability to invest in development of new products and entering of new markets. Therefore, they try to achieve something through R&D Alliances, such as unique technology, resources, power of synergy, and the ability to reduce the gap between market leaders. However, the scope and characteristics of R&D alliance result in management complexity and difficulty that are higher than business management. The relevant researches in the past only use the fragment analysis, no systematic methods and systems thinking perspective to think about the complexity of R&D Alliance issues. Therefore, this study try to build a composite methodology that can completely reveal the complex causal relationship between the key success factors (KSF) in R&D alliance. This study aims to discuss the complexity of the KSFs in R&D alliance, using the system theory to integrate decision making trial and evaluation laboratory (DEMATEL), interpretative structural modelling (ISM) and analytical network process (ANP) into a composite methodology. Between the KSFs, it reveals the strength and direction of interaction, hierarchy structure, degree of relative importance, and the causal loop map enhancement that is beneficial to help managers use systems thinking for complex issues. Key words: R&D alliance, key success factor, decision making trial and evaluation laboratory (DEMATEL), Interpretative Structural Modelling (ISM), analytical network process (ANP).