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The purpose of this paper is to identify the intra-organizational factors effective in a successful strategy implementation, measure the interaction intensity, analyze relation patterns among those factors, and lastly, prioritize the factors according to the level of importance and effect in the success of a strategy implementation.

A review of the literature produced 13 key intra-organizational factors involved in successful strategy implementation. The factors were then prioritized and the interaction among them was identified using interpretive structural modelling (ISM). DEMATEL was employed to quantitatively calculate the importance, intensity and effect in the interaction among the factors. Finally, combining both the aforementioned methods an integrated ISM-DEMATEL model was devised through which the factors were prioritized while the importance, intensity and effect of each factor were quantitatively calculated.

Prioritization and establishing relations and interactions among the identified factors by ISM; determining the priority of each factor and their intensity of effect and interaction on a quantitative basis through DEMATEL method and developing the integrated model of ISM-DEMATEL for intra-organizational factors effective in successful strategy implementation.

Due to time limitation, the hybrid model could not be practically applied to any organizations or businesses and in this research, only 12 experts were consulted to construct the model. If the experts involved were increased both quantitatively and qualitatively no doubt the final model would be upheld.

Managers who are involved in strategy implementation or who intend to enter this phase are advised to apply the integrated ISM-DEMATEL model that presented in this paper in order to obtain good perspective about interaction and prioritization among the intra-organizational factors effective in strategy implementation success.

Identification of 13 key intra-organizational factors effective in successful strategy execution, by studying through the literature; prioritization and establishing relations and interactions among the identified factors by ISM; determining the priority of each factor and their intensity of effect and interaction on a quantitative basis through DEMATEL method; developing the integrated model of ISM-DEMATEL for intra-organizational factors effective in successful strategy execution; improving the integrated model through ISM by applying the findings obtained through DEMATEL.

The study aims to identify and analyse complex interrelationships among factors influencing omnichannel retailing adoption in Indian apparel firms.

The study applies an integrated interpretive structural modelling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) approach for understanding the hierarchical and contextual relationship structure among the factors influencing omnichannel retailing adoption.

The integrated ISM–DEMATEL approach identifies that financial commitment is the most crucial factors followed by technological capability, training and development, performance metrics, supportive organisational structure, collaboration and knowledge sharing, offline–online information aggregation and integrated technological platform. Also, the study reveals that financial commitment and supportive organisational structure impact the majority of factors but are affected by only a few factors.

Unlike previous studies, this study suggests an alternate approach to theory building emerging from the various factors that could be considered while developing omnichannel retailing.

Practitioners should pay close attention to leading factors that influence the adoption of omnichannel retailing, namely, financial commitments, supportive organisational structure, technological capability, integrated technological platform and training and development rather than focusing on significant receivers, such as warehouse management and assortment management.

The integrated approach of ISM-DEMATEL offers a hierarchical model and cause–effect relationship among factors influencing omnichannel retailing adoption.

The purpose of this paper is to identify, analyze and model Internet of Things (IoT) enablers essential for the success of Industry 4.0.

IoT enablers for Industry 4.0 are identified from literature and inferable discussions with industry experts. Three different techniques namely, principal component analysis (PCA), interpretive structural modeling (ISM) and decision making trial and evaluation laboratory (DEMATEL) are applied to model IoT enablers. In addition to this, DEMATEL is also applied under two different situations representing the behavioral characteristic of experts involved. These are termed as optimistic (maximum) and pessimistic (minimum).

The integrated approach of PCA-ISM-DEMATEL shows that IoT ecosystem and IoT Big Data are the most influential or driving IoT enablers. These two enablers have been identified as the pillars for Industry 4.0. On the other side, IoT interchangeability, consumer IoT, IoT robustness and IoT interface and network capability have also been identified as the most dependent enablers for Industry 4.0.

The findings enable the industry practitioners to select the most appropriate driving enablers for an effective implementation of Industry 4.0.

The integrated approach-based hierarchical model and cause-effect relationship among IoT enablers are proposed which is a novel initiative for Industry 4.0. Moreover, two different variants of DEMATEL namely, pessimistic and optimistic are applied first time.

This study aims to examine which organisational and other factors can facilitate the adoption of artificial intelligence (AI) in Indian management institutes and their interrelationship.

To determine the factors influencing AI adoption, a synthesis-based examination of the literature was used. The interpretative structural modelling (ISM) method is used to determine the most effective factors among the identified ones and the inter-relationship among the factors, while the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used to analyse the cause-and-effect relationships among the factors in a quantitative manner. The approaches used in the analysis aid in understanding the relationship among the factors affecting AI adoption in management institutes of India.

This study concludes that leadership support plays the most significant role in the adoption of AI in Indian management institutes. The results from the DEMATEL analysis also confirmed the findings from the ISM and Matrice d’ Impacts croises- multiplication applique and classment (MICMAC) analyses. Remarkably, no linkage factor (unstable one) was reported in the research. Leadership support, technological context, financial consideration, organizational context and human resource readiness are reported as independent factors.

This study provides a listing of the important factors affecting the adoption of AI in Indian management institutes with their structural relationships. The findings provide a deeper insight about AI adoption. The study's societal implications include the delivery of better outcomes by Indian management institutes.

According to the authors, this study is a one-of-a-kind effort that involves the synthesis of several validated models and frameworks and uncovers the key elements and their connections in the adoption of AI in Indian management institutes.

This paper aims to study the critical success factors (CSF) of knowledge management (KM) in Iranian urban water and sewage companies (IUWSC) using interpretive structural modeling (ISM)-decision-making trial and evaluation laboratory (DEMATEL) method.

Through the literature review among many key factors of KM success, nine factors were selected as the main factors. After confirming the related indices by industry experts, a questionnaire was distributed among them for determining the relationship between the relevant components. Using ISM-DEMATEL approach, a structural model was formed and then the causal relationship among factors was visualized through a cause-effect relationship diagram.

The analysis of the results showed that among the studied factors, strategies and goals would have the greatest impact on success of KM implementation and senior management support, and teamwork and organizational culture are other CSFs of KM in IUWSC. In the end, the author’s proposed model for implementation of KM was presented based on the results for the status quo of the studied community.

The set of CSFs can act as a guideline for organizations to ensure that basic factors and issues are covered during implementation KM. Moreover, it provides a clue for effective development of KM in a stepwise approach.

This survey is probably the first to provide an integrated view of CSFs for implementation KM in IUWSC. It is hoped to give valuable information to help this business sector to accomplish KM effectively.

Big Data can be utilised for efficient use of resources and to provide better services to the resident in order to enhance the delivery of urban services and create sustainable build environment. However, the adoption of Big Data faces many challenges at the implementation level. Therefore, the purpose of this paper is to identify the challenges towards the efficient application of Big Data in smart cities development and analyse the inter-relationships.

The 14 Big Data challenges are identified through the literature review and validated with the expert’s feedback. After that the inter-relationships among the identified challenges are developed using an integrated approach of fuzzy Interpretive Structural Modelling (fuzzy-ISM) and fuzzy Decision-Making Trial and Evaluation Laboratory (fuzzy-DEMATEL).

Evaluation of interrelationships among the challenges suggests that diverse population in smart cities and lack of infrastructure are the significant challenges that impede the integration of Big Data in the development of smart cities.

This study will enable practitioners, policy planners involved in smart city projects in tackling the challenges in an optimised manner for the hindrance free and accelerated development of smart cities.

This research is an initial effort to develop an interpretive structural model of Big Data challenges for smart cities development which gives a clearer picture of how the identified challenges interact with each other.

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.

Drawing from boundary-spamming knowledge processes and knowledge-based theory, the purpose of this paper is to study enablers of the knowledge management (KM) process using robust multi-criteria decision-making (MCDM) tools like interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) method.

Drawing on the knowledge-based view and through the detailed literature review among different KM success, eight enablers were identified. By using the ISM-DEMATEL approach, a systematic framework was designed, and further cause–effect relationship diagram visualized a causal relationship among the enablers.

The combined approach of ISM-DEMATEL showcase that “knowledge creation” and “knowledge capture” are essential enablers. These two identified enablers have considered being pillars for KM implementation. On the other side, knowledge organization, knowledge application are dependent enablers.

From a practical viewpoint, the findings of this research work enable the industry consultants to identify the most prominent driving enablers for KM implementation. Additionally, it provides a clue for the effective implementation of KM in a systematic approach.

The integrated method depending on the hierarchical model and cause–effect relationship between enablers of the KM process is a novel approach that opens a new research area in this domain. Moreover, this is the first-ever attempt to combine ISM along with DEMATEL to identify enablers of the KM process.

Electricity savings from energy-efficient appliances (EEAs) may have a significant impact on reducing global warming. There are several barriers confronted by EEAs, which have lowered their acceptance rate. The current study aims to identify and highlight key barriers to strengthening domestic sector adoption of EEAs in developing countries.

In the current study, 13 barriers were discovered by an in-depth literature review and the judgement of experts as well. Further, integrated “interpretive structural modeling” (ISM) and “decision-making trial and evaluation laboratory” (DEMATEL) approaches are used to evaluate barriers. The ISM technique is implemented to categorize barriers into distinct hierarchy levels and “cross-impact matrix multiplication applied to classification” (MICMAC) analysis to divide barriers among four clusters “independent, linkage, dependent and autonomous.” Moreover, the DEMATEL methodology is applied to classify the barriers among cause and effect clusters.

The integrated ISM and DEMATEL approach suggests that the topmost influencing barriers to the acceptance of EEAs are the lack of Government policies and initiatives, lack of attractive loan financing and subsidized energy prices.

This study would help researchers, regulators, producers, policymakers and consumers to comprehend the need for additional developments and understand that the adoption of EEAs is a current need. Overall, the results of this study expedite stakeholders with the key barriers that may assist to enhance the acceptance of EEAs within the domestic sector.

An extensive literature survey showed a dearth of studies for the identification, modeling and analysis of barriers collectively. Therefore, the current work used the ISM and DEMATEL approaches to fill the gap and to provide more comprehensive knowledge on barriers related to the acceptance of EEA.

By replacing traditional fossil fuels, renewable energy (RE) has the potential to become an outstanding sustainable energy supply. However, owing to technological, economic, social and legal constraints, RE is still in its early stages of development. Hence, this paper aims to analyze the sustainable development hindrances in the RE supply chain (RESC).

Twenty-three hindrances to the sustainable development of the RE industry were investigated in this research, which included a review of the expert opinion and literature. Then, a mutual relationship between the hindrances by integrating interpretive structural modeling and decision-making trial and evaluation laboratory in fuzzy environment was established. Furthermore, using the cross-impact matrix multiplication applied to a classification analysis, these hindrances were grouped.

The findings show that the important hindrances are “lack of standards for the RESC (H19), lack of entrepreneurship support (H21), lack of incentives/subsidies to encourage RE producers to compete (H30) and lack of governmental support for sustainable supply chain solutions (H31).

This research provides unique insights into the area of sustainability in RESC. To the best of the authors’ knowledge, this is the first paper to analyze the sustainability hindrances in the RESC.