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The purpose of this paper is to elucidate the methodology of total interpretive structural modeling (TISM) in order to provide interpretation for direct as well as significant transitive linkages in a directed graph.

This study begins by unfolding the concepts and advantages of TISM. The step-by-step methodology of TISM is exemplified by employing it to analyze the mutual dependence among inhibitors of smartphone manufacturing ecosystem development (SMED). Cross-impact matrix multiplication applied to the classification analysis is also performed to graphically represent these inhibitors based on their driving power and dependence.

This study highlights the significance of TISM over conventional interpretive structural modeling (ISM). The inhibitors of SMED are explored by reviewing existing literature and obtaining experts’ opinions. TISM is employed to classify these inhibitors in order to devise a five-level hierarchical structure based on their driving power and dependence.

This study facilitates decision makers to take required actions to mitigate these inhibitors. Inhibitors (with strong driving power), which occupy the bottom level in the TISM hierarchy, require more attention from top management and effective monitoring of these inhibitors can assist in achieving the organizations’ goals.

By unfolding the benefits of TISM over ISM, this study is an endeavor to develop insights toward utilization of TISM for modeling inhibitors of SMED. This paper elaborates step-by-step procedure to perform TISM and hence makes it simple for researchers to understand its concepts. To the best of the authors’ knowledge, this is the first study that analyzes the inhibitors of SMED by utilizing TISM approach.

The purpose of this paper is to examine the elements of asymmetric motives, i.e., initial cross-border joint venture (CBJV) conditions and relative partner characteristics in emerging nations. The two main objectives of the present research are to identify the elements affecting asymmetric motives in Indian bilateral CBJV and to construct modified total interpretive structural modelling (TISM) for the identified elements of asymmetric motives.

For the current study, the qualitative technique named total interpretive structural modelling was used. The TISM (Sushil, 2012) is a novel extension of interpretive structural modelling (ISM) where ISM helps to understand the “what” and “how” of research (Warfield, 1974) and TISM answers the third question, i.e., “why” in the form of TISM; further checks for the correctness of TISM are given in Sushil (2016). TISM provides a hierarchical model of the elements selected for study and the interpretation of each element by iterative process and also a digraph that systematically depicts the relationship among various elements. TISM is an innovative modelling technique used by researchers in varied fields (Srivastava and Sushil, 2013; Wasuja et al., 2012; Nasim, 2011; Prasad and Suri, 2011). Steps involved in TISM are shown in Figure 1. It uses reachability matrix and partitioning of elements similar to ISM. Also, along with traditional TISM, the modified TISM process was also used where both paired comparisons and transitivity checks were done simultaneously which helped in minimising the redundant comparisons being made in the original process. Furthermore, for identifying the elements of study, SDC Platinum database was used, which was taken from research papers of major journals namely British Journal of Management, Administrative Science Quarterly, Strategic Management Journal, Management Science, Academy of Management Journal and Organization Science (Schilling, 2009). The database included all joint ventures that were formed in India, having India as one of the partner firms during fiscal year April 2000 and March 2010. From these, 361 CBJVs and 76 domestic joint ventures were identified. Although 54 CBJVs were excluded from these, a total number of 307 CBJVs were studied in the current research. Among these 307 CBJVs, 201 were from super-advanced nations (G7), 40 CBJVs from developing nations and 66 CBJVs from other developed nations. As 65 per cent of the CBJVs came from G7 nations (France, Italy, Japan, Canada, Germany, USA and UK), in the current study, we tried to examine Indian CBJVs with G7 partners only for a period of ten years as mentioned above.

The results of the study indicate that asymmetric motives are directly affected by critical activity alignment and interdependency. Thus, we can conclude that critical activity alignment of partners in CBJV is an antecedent of CBJV motive and thereby minimises the number of asymmetric motives. Bottom level variables such as culture difference and relative capital structure are considered as strong drivers of asymmetric motives. Diversification, resource heterogeneity and inter-partner conflict are middle level elements. Effect of these elements on asymmetric motives can only be improved and enhanced when improvement in bottom level variables is found. It has been believed that as the relative capital structure among firm increases, CBJVs’ asymmetric motives also increase, the reason being that as the difference in capital structure occurs, gradual change in bargaining power will also occur.

TISM used in the present study provides valuable insights into the interrelationship between identified elements through a systematic framework. The methodology of TISM used has its implications for researchers, academicians as well for practitioners. Further study also examines driver-dependent relationship among elements of interest, i.e., relative partner characteristics and initial CBJV conditions by using MICMAC analysis, which can be viewed as a significant step in research related to bilateral CBJV.

The purpose of this paper is to develop a model based on the total interpretive structural modeling (TISM) approach for analysis of factors of additive manufacturing (AM) and industry 4.0 (I4.0) integration.

AM integration with I4.0 is attributed due to various reasons such as developing complex shapes with good quality, real-time data analysis, augmented reality and decentralized production. To enable the integration of AM and I4.0, a structural model is to be developed. TISM technique is used as a solution methodology. TISM approach supports establishing a contextual relationship-based structural model to recognize the influential factors. Cross-impact matrix multiplication applied to classification (MICMAC) analysis has been used to validate the TISM model and to explore the driving and dependence power of each factor.

The derived structural model indicated the dominant factors to be focused on. Dominant factors include sensor integration (F9), resolution (F12), small build volumes (F19), internet of things and lead time (F14). MICMAC analysis showed the number of driving, dependent, linkage and autonomous factors as 3, 2, 12 and 3, respectively.

In the present study, 20 factors are considered. In the future, additional factors could be considered based on advancements in I4.0 technologies.

The study has practical relevance as it had been conducted based on inputs from industry practitioners. The industry decision-makers and practitioners may use the developed TISM model to understand the inter-relationship among the factors to take appropriate measures before adoption.

The study on developing a structural model for analysis of factors influencing AM and I4.0 is the original contribution of the authors.

The purpose of this paper is to identify and analyze the interactions among different enablers of total quality management (TQM) and its outcome variables in service sector specific to Indian domestic airline industry. No study has been done regarding the implementation of TQM in Indian domestic aviation sector. To fill this gap interpretive structural modeling (ISM) and total interpretive structural modeling (TISM) based quality framework model has been developed to understand the mutual interactions among the variables and to identify the driving and dependence power of these variables.

An ISM and TISM based approach have been used to study and analyze the interactions between identified variables.

In this research work, a total of 14 variables have been identified based on extensive literature review, brainstorming and experts opining from the Indian airline industry and academia. The result showed that top management commitment, training, continuous improvement, benchmarking, employee involvement and commitment have strong driving power and weak dependence power and are at the lowest level in hierarchy in the ISM and TISM model, while the outcome variables of TQM have low driving power but have high dependence power.

Top management must stress on variables having strong driving power for efficient implementation of TQM. By implementation of TISM model in the Indian airline industry, organizations would become more productive, competitive and would eventually become more profitable.

In this research work, ISM and TISM based quality framework structural model have been proposed for Indian domestic aviation industry which is a new effort in the area of TQM implementation in this sector.

The purpose of this paper is to present a qualitative analysis of the significant factors that influence graduate employability in information technology (IT) sector. This is imperative, given the rising “employability gap” confronted by this sector, especially in context of India. The key factors that influence graduate employability have been drawn from the literature. This research paper aims to conduct a preliminary validation of these predictors of employability and analyse the contextual relationship between them through Total Interpretive Structural Modelling (TISM) technique (Nasim, 2011; Sushil, 2012). This technique is an innovative version of Interpretive Structural Modelling proposed by Warfield (1973).

The antecedents of graduate employability have been identified through qualitative analysis of available literature. Further, TISM has been used to derive a structural model and analyse the contextual relationship among these identified antecedents. The structural model has been derived through in-depth interviews with experts that include senior middle management professionals from reputed IT companies in India. The developed TISM model has been further validated through assessment surveys with a larger set of domain experts to enhance the credibility of the obtained results.

Based on the data collected from the domain experts, eight elements including employability and its seven antecedents were hierarchically modelled into four levels. While all the seven identified factors were endorsed by the industry experts as the drivers of employability, some of the key factors affecting employability emerged to be technical specialties knowledge, technology management skills and communication skills. Furthermore, the developed model has been subsequently validated and accepted based on the results of the assessment surveys conducted with a larger set of domain experts.

The findings are expected to help the graduates seeking jobs in IT and allied sectors and the higher education institutions (HEIs) offering academic programmes in this domain. These findings would enable the graduates to understand the significance of the different knowledge/skill areas that influence their employability and increase the chances of securing job. Also, the HEIs can comprehend the developed model to understand the demands of the employers, the rationale behind it and further align their course curriculum/teaching methodologies in sync with their expectations. The developed model should be put to empirical validation for greater reliability.

The qualitative analysis of the antecedents of graduate employability using TISM technique is an original methodological contribution to the field. Though the TISM technique has been used in research studies across different sectors like e-government (Nasim, 2011), higher education (Prasad and Suri, 2011) and flexible manufacturing systems (Dubey and Ali, 2014), the application of this technique to employability in IT sector in India is a novel contribution.

The purpose of this paper is to develop a total interpretive structural modelling (TSIM) of strategic factors related to performance management in the context of Indian Telecom Service Providers taking dual perspectives in account, i.e. enterprise perspective and subscribers’ perspective.

An evolving performance management framework, i.e. flexible strategy game-card has been taken as the basis to develop the strategic performance management model, where strategic factors have been identified through thematic content analysis and the hierarchical structure of factors has been developed using TISM.

Two total interpretive structural models have been developed, one for enterprise-related strategic factors, and another for subscriber-related strategic factors. These hierarchical structures portray the leading and lagging factors of performance, and showcase that financial performance indicators are the lagging indicators.

This study has implications for both practitioners and academics. For practitioners, it provides an indicative list of strategic factors relevant for Indian telecom companies, which drive better financial results as well as a list of strategic factors that subscribers consider while assessing the performance of telecom operators. For academics, the methodology used provides a mechanism to conduct an exploratory study by identifying the variables of interest and highlighting their interactions through hierarchical structures.

The proposed strategic performance management models developed through qualitative modelling technique is a new effort altogether in the context of Indian telecom operators’. Capturing subscribers’ perspective of firm's performance is neglected in existing performance management literature, and this study makes a contribution in this regard.

The purpose of this paper is to identify the flexible manufacturing system performance variables and analyze the interactions among these variables. Interpretive structural modeling (ISM) has been reported for this but no study has been done regarding the interaction of its variables. Therefore, fuzzy TISM (total ISM) has been applied to deduce the relationship and interactions between the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.

Fuzzy TISM and fuzzy MICMAC analysis have been applied to deduce the relationship and interactions among the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.

In total, 15 variables have been identified from the extensive literature review. The result showed that automation, use of automated material handling, an effect of tool life and rework percentage have high driving power and weak dependence power in the fuzzy TISM model and fuzzy MICMAC analysis. These are also at the lowest level in the hierarchy in the fuzzy TISM model.

Fuzzy TISM model has been suggested for manufacturing industries with fuzzy MICMAC analysis. This proposed approach is a novel attempt to integrate TISM approach with the fuzzy sets. The integration of TISM with fuzzy sets provides flexibility to decision-makers to further understand the level of influences of one criterion over another, which was earlier present only in the form of binary (0, 1) numbers; 0 represents no influence and 1 represents influence.

This study aims to identify and prioritize various growth-accelerating factors in the Indian automotive industry. It further develops a hierarchical model to examine the mutual interactions between the factors, their dependence and their driving power.

This study first identifies the growth-accelerating factors and then uses the modified total interpretive structural modeling (m-TISM) framework, which is an extended version of TISM. It further uses MICMAC analysis to analyze the mutual interrelation between the identified factors.

This study highlights the interrelation amongst the factors using m-TISM model. A hierarchical model shows the level of autonomous, dependence, linkage and independent factors considering the Indian automotive industry. This study also provides the understanding related to the interdependence of growth-accelerating factors.

The government and practitioners could evaluate the growth-accelerating factors which have higher driving power for implementing efficient policies and strategy formulation. By implementing m-TISM model in the Indian automotive industry, auto manufacturers can become more productive and profitable. Future studies could use other methods such as expert opinion to derive the factors, and further model could be verified using structural equation modeling technique.

This study uses a novel m-TISM framework for the analysis of growth-accelerating factors in the context of the Indian automotive industry. It further provides a detailed theoretical and conceptual understanding relating to the philosophy and establishes an interrelation amongst these under-researched growth-accelerating factors.

The study aims to present demand chain management (DCM) modeling of Indian apparel retailers. This will result in a structured model presenting contextual interrelationship among DCM variables so that retailers can proactively manage their demand chain.

The research follows an exploratory research design. It initially involves identification and analysis of influential factors of the implementation of DCM practices through the review of literature. Then, these variables were analyzed using total interpretive structural modeling or TISM followed by a statistical verification and case-based validation of the model.

The major findings of the paper are: top-management commitment and support, information management and supply chain agility in supply chain are the most significant enablers with the highest driving power. The other apparel retail specific significant variables are assortment planning, category management and marketing orientation. The model also indicates that the firms that implement customer-centric DCM practices do well in terms of organizational performance and thereby achieve differential advantage over their competitors.

Because the literature on DCM is still in nascent stage, the study bases itself on interpretive method; that is, TISM of analysis with a limited number of experts. Future studies may consider larger sample with more advanced statistical tools such as structural equation modeling for further validation of the findings.

The novelty of the paper lies in the study of an emerging supply chain philosophy; that is, DCM and its key practices per se. It has rarely been studied from the theory building perspective hitherto. Moreover, TISM-based approach is applied for the first time to study the DCM practices and its drivers vis-à-vis dependents.

In recent years, sustainable issues have gained increasing importance in the higher education sector across the country. To remain competitive, higher education institutions (HEIs) have to engage themselves in providing world-class opportunities for higher education and research so that the beneficiaries may not be at a disadvantage in the international level. However, many HEIs still encounter barriers that can affect their growth. The purpose of this study is to identify and interpret the most significant barriers affecting the growth of HEIs in India and understand the mutual interactions and interdependence among them.

In this study, 12 barriers affecting the growth of HEIs in India were identified and sorted by literature review, and these were validated through discussion with experts. Contextual relationships were drawn between them during brainstorming sessions. A hierarchical, seven-level structural model of these barriers affecting the growth of HEIs was developed by utilizing the total interpretive structural modeling (TISM) approach.

The results of this study showed “lack of climate change research” as the topmost outcome of the model having the highest dependence and lowest driving power. “Facilitator domination over academic experts” occupied the bottom-level input, compared to other barriers of the model, with highest driving power and lowest dependence. Further, Matrice d'Impacts Croisés – Multiplication Appliquée à un Classement (MICMAC) analysis was also performed to categorize the identified barriers for better understanding. Under MICMAC analysis, five barriers were categorized as driver barriers, four barriers as dependent barriers and the rest as linkage barriers, while none as autonomous. A TISM-based model that partitioned the barriers into different levels was developed, showcasing direct and important transitive relations.

The TISM-based model developed in this study may provide a more realistic approach to the problems faced by decision-makers, academicians and top managers in the growth of HEIs in India. Thus, it will provide a roadmap to focus on the most influential barriers and reduce or eliminate them.

The present study identified major barriers that when dealt with can help overcome the effect of other barriers preventing the growth of HEIs in India. It also introduces a model to identify and manage the barriers by understanding the effectiveness of each barrier and minimizing the overall effect in Indian HEIs. Moreover, the analysis of interdependence and interactions studied among these barriers may also help decision-makers, academicians and top managers to find deeper insights, prioritize and rectify them, to re-establish the growth of HEIs and gain a competitive advantage.