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The aim of this paper is to identify and analyze critical factors/elements influencing standards compliance and their level of influence in a developing country food industry, with specific reference to India.

A total of 13 critical elements were identified and structured using pair‐wise comparisons. Structural and reachability matrices were formed and iterated to yield levels of hierarchical influence of each element. MICMAC analysis was also performed to determine dependency and driving power of these elements.

The analysis brought out a compelling need for “sensitive and responsive” action by developing country governments while competing globally. Food industries in developing countries tend to detour while complying with standards, owing to costs involved in setting up systems and procedures. While a strong surveillance mechanism is the high point of a good compliant system this has to be preceded by supporting measures such as linking of domestic and international markets, consolidation of institutional structures, strengthening of legal/regulatory systems, etc.

Use of interpretative structural modeling (ISM) is inspired by the versatility displayed by this method, as reported by researchers, across a wide spectrum of economic and competitive complexities affecting businesses.

The study is a hitherto unexplored attempt, using interpretative structural modeling, to analyze standards compliance in a developing country's food industry.

The purpose of this paper is to focus on studying the concept of “Smart Organization” and providing a comprehensive framework for the various factors as barriers for the smart organization, identifying and classifying the key criterion of these factors based on their direct and indirect relationships.

In this paper an extensive literature survey and experts’ opinion have been used to identify major barriers of smart organization. These barriers are then modeled using interpretative structural modeling (ISM) methodology. The model so developed has been further improved and an integrated model has been developed using fuzzy-MICMAC.

Various barriers of smart organization have been identified and a structural model has been developed for barriers using the ISM methodology. The critical barriers have been found out by fuzzy-MICMAC analysis. The driver power and dependence graph has been plotted for barriers. The barriers are classified into four categories which are, autonomous, linkage, dependent and independent according to their driver power and dependence. From the ISM model and the integrated model, and from further discussions with the experts, it has been found that the barriers “(B1) organizational structure” and “(B6) Managerial actions” are the two most important barriers, every other barrier is directly or indirectly driven by these.

The basis of developing the ISM model, i.e, the structural self-interaction matrix is based on experts’ opinion, therefore the result may get influenced if there is any biasing in judging the barriers. The future research scope for this paper will be to test the model generated in this paper. The testing of the model can be done by applying structural equation modeling technique, it has the capability of testing the hypothetical model. Further a framework of smart organizations can be created to find out the smartness of different organizations.

The paper can be used by organizations in understanding the barriers in becoming “smart” on the basis of their inter-relationships. This model can help manufacturing organization of North India in understanding the barriers which needs to be worked upon and the inter-relationship among these factors. This model-based study may be helpful in understanding and implementing the practices of smart organization by removing the possible critical barriers.

This is the first study to identify the barriers of smart organizations and to develop a model of these barriers using ISM and fuzzy-MICMAC.

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.

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.

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.

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.

The aim of this paper is to propose a benchmarking model of supplier development (SD) for an Indian gear manufacturing company for its successful adoption and improvement in a continuous basis.

Thirteen SD critical success factors (CSFs) are identified and classified into four categories through extensive literature review and discussion held with managers/senior engineers in different Indian manufacturing companies. The four categories are primary CSFs related to supplier, secondary CSFs related to supplier, CSFs related to manufacturer and CSFs related to both manufacturer and supplier. The interpretative structural modeling (ISM) approach is applied to the Indian gear manufacturing company for developing and analyzing structural framework of CSFs to propose a benchmarking model for SD.

It is concluded that SD adoption should be carried out in four phases sequentially for the Indian gear manufacturing company. The first, second, third and fourth phase should sequentially focus on primary CSFs related to supplier; secondary CSFs related to supplier; CSFs related to manufacturer; and CSFs related to both manufacturer and supplier, respectively. The proposed benchmarking model has four phases (i.e. plan, analyze, implement and measure) and bifurcated into 12 steps to enhance the performance of CSFs.

This paper provides a useful benchmarking model for successful adoption of SD in manufacturing organizations.

This is one of the few studies to develop the relationship of CSFs for SD in general and its application to an Indian gear manufacturing company in particular. A benchmarking model for SD is also proposed having five phases and 12 steps. The findings of the proposed structural framework and benchmarking model for the Indian gear manufacturing company are discussed in detail and will serve as a guideline for successful adoption of SD in manufacturing environment.

The purpose of this paper is to identify and rank different dimensions of strategic orientation and firm’s performance using the approach of interpretive structural modeling.

The study uses interpretative structural modeling and the MICMAC technique to establish a hierarchical relationship among different dimensions of entrepreneurial orientation and manufacturing performance of Indian SMEs.

The final outcome of interpretative structural modeling and the MICMAC analysis revealed a relationship between the variables under study along with the categorization of all in two different categories, depending upon their driving power and dependency, which decision-makers can also use while devising their strategy to improve performance.

To date, to the best of the authors’ knowledge, no significant contribution about such interrelationship was reported; therefore, this study is one of its types to fill this gap.

Co-creating services with the customer has recently appeared as an alternative strategy to achieve competitive advantage. Developing and sustaining a gainful experience requires sharing of knowledge, skills and resources between the firm and its customers. Managing value co-creation throws substantial challenge and difficulties. This study aims to investigate the barriers to customer resource contribution in value co-creation in service industries and find their interrelationships for developing an effective management framework for removal of those barriers.

A systematic literature review led to the identification of 26 barriers, which were further confirmed through expert opinion. The study used interpretative structural modeling (ISM) approach and Matrice d’Impacts croises-multipication applique (MICMAC), for analyzing the contextual relationships and develop a hierarchical model of the barriers.

ISM approach led to the development of a 13-level structural model. The barriers were further classified into autonomous, driver, linkage and dependent barriers using the MICMAC analysis. The framework offers a means to fulfill the expectations of the customers, thus leading to successful integration of the customer in the value creation process. Removal of the barriers has also been discussed.

The framework provides a direction and a tool to meet the expectations of the customers and lead to successful integration of the customer.

The study addresses a gap in the literature for the need of a structured framework for managing the value co-creation process in the service industry

The theory-building around the quality of human resources has received extensive attention in recent years. Numerous quantitative studies discuss and test theories related to total quality management and human resource linkages. The study aims to understand interlinkages of quality and human resources using Interpretative Structural Modeling (ISM) methodology and DEMATEL.

This paper uses ISM methodology to examine the interrelationship between the identified variables and the DEMATEL approach to find cause–effect relationships. An integrated approach helps managers for better total quality management (TQM) implementation. This study further extended using Total Interpretative Structural Modeling (TISM).

The integrated approach of ISM and DEMATEL shows that leadership development, hiring process and training development become most important for TQM implementation. The outcome of ISM shows customer satisfaction and corporate image are depending on other practices, where DEMATEL analysis revealed that eight practices cause and remaining are effective practices.

This research's integrated approach helps the firm identify essential practices, and further interdependency can be developed from cause and effect analysis. The study also provided a novel approach to implementing TQM practices.

The purpose of this paper is to evaluate the interplay of various measures used by different governments around the world in combatting COVID-19.

The research uses the interpretative structural modelling (ISM) for assessing the powerful measures amongst the recognized ones, whereas to establish the cause-and-effect relations amongst the variables, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used. Both approaches utilized in the study aid in the comprehension of the relationship amongst the assessed measures.

According to the ISM model, international support measures have the most important role in reducing the risk of COVID-19. There has also been a suggestion of a relationship between economic and risk measures. Surprisingly, no linkage factor (unstable one) was reported in the research. The study indicates social welfare measures, R&D measures, centralized power and decentralized governance measures and universal healthcare measures as independent factors. The DEMATEL analysis reveals that the net causes are social welfare measures, centralized power and decentralized government, universal health coverage measure and R&D measures, while the net effects are economic measures, green recovery measures, risk measures and international support measures.

The study includes a list of numerous government measures deployed throughout the world to mitigate the risk of COVID-19, as well as the structural links amongst the identified government measures. The Matrice d'Impacts croises-multiplication applique and classment analysis can help the policymakers in understanding measures used in combatting COVID-19 based on their driving and dependence power. These insights may assist them in employing these measures for mitigating the risks associated with COVID-19 or any other similar pandemic situation in the future.

The purpose of this paper is to identify the critical success factors (CSFs) for AI-integrated CRM system for better knowledge management (KM) in organizations to improve business process.

The factors critical for adoption of AI-integrated CRM system for efficient knowledge management are innumerable. The salient factors may be identified by several means. Methods like brainstorming and Delphi have been applied here. Sixteen CSFs have been identified. Then the interrelationship among these 16 factors, levels of their importance and the principal driving factors have been established by interpretative structural modelling (ISM) methodology.

The results show that out of 16 CSFs, leadership support, adequate fund and support of functional area leads are the most important CSFs for AI–CRM–KM integration.

The results show that support of top management is essential for successful adoption of AI-integrated CRM system for better knowledge management to improve the business process.

This paper has taken a novel attempt to identify CSFs for AI-integrated CRM adoption for efficient knowledge management system in organizations for improvement of business process and to establish interrelationship among those CSFs with the help of ISM methodology.

Existing studies suggested that there is a nonlinear relationship between lean production adoption and organizational performance. Lean production adoption is a gradual process, and the application status of lean tools will affect enterprise performance. The existing literature has insufficiently explored the nonlinear relationship of the lean tools application status on operational performance and environmental performance using the same theoretical framework. A combination approach of interpretative structural modeling (ISM) and Bayesian networks was proposed in this paper, which was used to analyze the complex relationship between lean tools application status with operational and environmental performance.

ISM was used to analyze the inter-relationship of 17 lean tools identified from the lean literature and construct the lean tools structure model providing reference for building Bayesian network. By calculating the prior and conditional probabilities within the lean tools and between the lean tools with the operational and environmental performance, a Bayesian simulation model was constructed and used to analyze the performance outcomes under different lean tools application status.

The performance simulation result – representing by the probability of three performance levels as good, average and poor – shows inconsistent changes with the changing of lean tools application status. By comparing the changes of operational performance and environmental performance, it can be found that environmental performance is less sensitive to the change of lean tools application status than operational performance.

Using the integrated ISM–Bayesian network approach, the results indicated a nonlinear relationship between lean tools with operational and environmental performance and provided a reference for the exploration of the nonlinear relationship between lean tools and performance. This research further calls for exploring the S-curve relationship between lean tools and environmental performance.