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The competitive rivalry, rapid change and high business volatility necessitate inter-organizational collaboration, including the supply chain (SC). This paper develops an interpretive model of the effect of the chief executive officers’ (CEO's) transformational leadership (TL) style on SC collaboration and, consequently, on the firm's performance.

Total interpretive structural modeling (TISM) is adopted to develop a hierarchical model to delineate the association between the elements of TL, SC collaboration and firm performance. Furthermore, the model has been validated statistically.

The TISM analysis results suggest that the TL style elements require maximum attention and are strategic. These elements drive factors of SC collaboration leading to improved firm performance. Therefore, CEO leadership is critical for SC collaboration to effectively affect firm performance.

The TISM framework in this paper preferred the majority approach over the fuzzy one, which requires a much larger data set. However, the bias of the majority approach can be eliminated by having multiple consultations with participants. Further, the development and validation of the paper was limited to manufacturing small and medium enterprises (SMEs) in India. The model can also be tested in large organizations to garner additional insights.

This study uniquely integrates TL and SC collaboration elements to explain firm performance. The TISM framework explains not only the “what” and “how” but also the “why” of theory building. This study also adds methodological value by combining triangulation with the interpretive tool.

In today’s environment, electric vehicles (EVs) industries and services provided to consumers are facing many challenges. The public in large numbers is not adopting Electric Vehicles because of the unavailability of suitable EVs and not getting proper charging infrastructure to the consumers. The purpose of this study and research work is to analyze the condition of this industry, its charging infrastructure and E-government policies. Based on the above analysis, frameworks/models are to be designed to assist organizations in formulating strategies for the EV industry and providing proper infrastructure to the consumer.

The Variables for the EV and EVsCI case study are identified from an exhaustive literature review, stakeholders’ perspectives, experts’ opinions, existing EV policies, future policy blueprints and data available for this industry, applying the Situation Actor Process-Learning Action Performance (SAP-LAP) methodology. After that, the Interpretive Ranking Process (IRP) is integrated with the SAP-LAP approach to develop models.

The rankings of Actors Versus Processes and Actions Versus Performances have been obtained and then models have been developed. These models can serve policymakers in framing and implementing effective policies.

Although the SAP-LAP approach is an innovative approach for identifying variables, however, this approach lacks perfect interactive relationships among the variables. It may lead to imperfect decision-making. To avoid this, the IRP approach is integrated with the SAP-LAP approach which provides more accurate models for analysis and providing recommendations to government and organizations.

The purpose of the study is to comprehend medical service quality, information quality and system quality toward actual use of Tele-Health in rural India. The study further validates the impact of the actual use of Tele-Health on sustainable development, thus providing implications to improve upon the Tele-Health penetration in India.

Data was collected from 326 healthcare practitioners practicing Tele-Health in North Indian states and Structural Equation Modeling was applied to validate the conceptual framework.

The results indicated that medical service quality, information quality and system quality influence Tele-Health behavioral intentions which in turn impact actual use and sustainable development. This research draws upon a conceptual framework to deepen our understanding of Tele-Health by providing an all-inclusive overview.

The massive topography of India with a prime rural populace instills the need for timely healthcare facilities. Tele-Health is a solution to all these problems but is at a nascent stage. Therefore, there is a vital need to study the factors which improve the penetration of Tele-Health in the Indian context. The model that emerged from the study may be validated by other Indian sub-continental countries so that Tele-Health may be implemented hassle-free.

The world is on the verge of entering the deglobalization age, and industrialized economies have ushered it in. However, there is still a scarcity of comprehensive and rigorous studies in this field. This research has tried to analyze the evolution and characteristics of deglobalization research.

The authors have employed bibliometric analysis for examining the existing evidence on accelerating deglobalization thinking based on a thorough analysis of articles published during a roughly 25-year span between 1996 and 2022. This study has used the TISM-P technique to study the relationship among the factors accelerating deglobalization thinking. This research reviews the articles on several dimensions of deglobalization using the “what”, “why”, “how”, “who”, “when” and “where” approaches.

The authors specify the critical factors, policy reforms, approaches and observed characteristics explored in this developing research area.

The authors have analyzed the factors accountable for rising deglobalization thinking and also suggested strategic recommendations based on the findings to minimize the adverse impact of globalization.

Although there is a wealth of literature on globalization, very little study has been done in the field of deglobalization. This is the first substantive review being done in the deglobalization domain. The contemporary research has used the bibliometric approach and the “5W and 1 H” framework to gain a comprehensive understanding of the changing paradigm.

Sustainability is a major challenge for India’s (Bharat’s) coal mining industry. The government has prioritized sustainable growth in the coal mining industry. It is putting forth multifaceted economic, environmental and social efforts to accomplish the Sustainable Development Goals (SDGs). This research aims to identify the factors for sustainable improvements in coal mining operations. Secondly, this study examines the intensity of causal relations among the factors. Thirdly, this study examines whether causal relations exist among the factors to be considered for sustainable improvement in coal mining operations. Lastly, the study aims to understand how the factors ensure sustainable improvement in coal mining operations.

An integrated three-phase methodology was applied to identify the critical factors related to coal mining and explore the contextual relationships among the identified factors. Fifteen critical factors were selected based on the Delphi technique. Subsequently, the fifteen factors were analyzed to determine the contextual and causal relationships using the total interpretive structural modelling (TISM) and DEMATEL methods.

The study identified “Extraction of Coal and Overburden” as the leading factor for sustainable improvement in coal mining operations, because it directly or indirectly influences the overall mining operation, environmental impact and resource utilization. Hence, strict control measures are necessary in “Extraction of Coal and Overburden” to ensure sustainable coal mining. Conversely, “Health Impact” is the lagging factor as it has very low or no impact on the system. Therefore, it requires fewer control mechanisms. Nevertheless, control measures for the remaining factors must be decided on a priority basis.

The proposed structural model can serve as a framework for enhancing sustainability in India’s (Bharat’s) coal mining operations. This framework can also be applied to other developing nations with similar sustainability concerns, providing valuable guidance for sustainable operations.

The current study highlights the significance of logical links and dependencies between several parameters essential to coal mining sustainability. Furthermore, it leads to the development of a well-defined control sequence that identifies the causal linkages between numerous components needed to achieve real progress towards sustainability.

This study aims to identify the strategic factors and their effects on the post-cross-border acquisitions (CBA) technological innovation performance of the acquiring firms. It develops a hierarchical model to examine the interrelationship between identified strategic factors such as strategic flexibility, strategic ambidexterity, environmental dynamism, etc.

This study uses modified total interpretive structural modeling qualitative methodology (m-TISM) to develop a hierarchical model and conducts a Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis to show the interrelationship between strategic factors affects the acquirer’s post-CBA technological innovation performance. It determines the autonomous, dependent, linkage and independent strategic factors. It further uses comparative case analysis to empirically examine the strategic factors in real-time CBA situations.

This study shows the m-TISM-based hierarchical model highlighting the interrelation, level of autonomy, dependence and linkage among strategic factors affecting the acquirer’s post-CBA technological innovation performance. It suggests that strategic factors such as environmental dynamism, R&D competence, innovation capability and technological capability are largely autonomous and have significant driving power, whereas strategic ambidexterity and strategic flexibility are the connecting factors. post-M&A integration is the governing factor for technological innovation performance in CBA.

The strategists and practitioners could evaluate the key strategic factors having significant driving power for strategy formulation and implementing efficient policies. By implementing the m-TISM model acquiring a firm’s post-CBA performance can be enhanced. Future researchers might utilize quantitative methods like regression and structural equation modeling in the CBA context.

This study uses a novel m-TISM and MICMAC approach to identify the driving and dependent factors affecting post-CBA technological innovation performance. It further provides a detailed theoretical and conceptual understanding relating to the philosophy and establishes an interrelation amongst these under-researched strategic factors in CBA.

This research aims to ascertain the various operational maturity challenges faced by the online food ordering and delivery enterprises (OFODE), their nature and their interactive relationships. In particular, this paper aims to (a) identify the most relevant operational maturity challenges faced by the OFODE during the COVID-19 lockdown in Oman, (b) explore and establish any likely structural relationship among these challenges and (c) put them into logical clusters.

Experts helped to reduce the 18 initially identified maturity challenges to 13 most pressing ones. Mutual relationships, dominance of interactions and their classifications were explored using fuzzy interpretive structural modeling (FISM) and fuzzy MICMAC analysis.

The study of situation-specific operational maturity challenges convinced the authors to propose a distinct FISM model that depicts the relationship among these challenges. Keeping commissions and fees reasonable emerges as the challenge which all other challenges seemingly culminate into. One of the most important situation-specific challenges (i.e. customer confidence about infection free delivery) emerges as a linkage challenge which aggravates as well as is aggravated by certain challenges.

Besides enriching literature, the proposed model has implications for practitioners particularly when the similar lethal waves are experienced anywhere. The number of respondents, subjective approach, specific context as well as the geographical area coverage are the key limitations.

To the best of the authors’ knowledge, this study is the first known scientific effort which attempts to model the operational maturity challenges faced by the OFODE during COVID-19 lockdown period. The authors used the FISM modeling approach to forge these interrelated challenges into a structural model.

E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.

Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.

Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.

TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.

The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.

Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.

Given the rising complexities around organizational resilience, this study identifies and explains the critical enablers of developing organizational resilience (OR). It offers logical reasoning into the interactions and interdependencies among the identified elements with the help of a hierarchical model of the antecedents of OR.

This paper deployed a mixed methodology research design. Firstly, critical enablers of OR are identified from the literature review. Second, contextual relationships and interactions between the enablers are examined using modified total interpretive structural modeling to derive a hierarchical model among the antecedents that characterize OR. Lastly, a survey study including industry experts is used to statistically verify the model links.

Developing resilience lies at the intersection of organization science and strategic management, involving the interaction of factors within an organization’s strategic behaviors, organizational practices, and people processes. The study identifies twelve antecedents of OR. The resultant interpretive hierarchical model helped decipher internal relationships among the antecedents. The proposed model helps determine how organizations move through different phases (before, during, and after) of turbulences and how organizational resilience helps overcome negative spirals.

This research is original and refreshing in its attempt to necessitate resilience as a processual characteristic needed to survive, thrive, and transform amidst business tensions. The hierarchical model of antecedents garners a better understanding of how their interactions and interdependencies help organizations enhance their capacity to adapt and build resilience in organizational systems and processes. It answers questions of “what,” “how,” and “why” relevant to theory building in OR.