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The purpose of this paper is to identify and analyze various critical success factors (CSFs) that can facilitate smartphone manufacturing in India. This paper further aims to understand the mutual interactions among these CSFs through identification of the hierarchical relationships among them.

A framework for a smartphone manufacturing system has been developed, wherein the hierarchical inter-relationships between identified CSFs have been presented and interpreted using total interpretive structural modeling (TISM). Cross-impact matrix multiplication applied to classification analysis has been further employed to identify the driving power as well as dependence power of these CSFs.

In the present research, 15 CSFs have been identified through literature review and expert opinions. The hierarchical framework developed using TISM has revealed the inter-dependencies among these CSFs. This research further categorizes CSFs into three clusters. The first cluster comprises of CSFs having high dependence power, the second cluster identifies CSFs having high driving power and the third cluster identifies CSFs which act as linkages between the driver CSFs and dependent CSFs.

This study has implications for both practitioners and academia. It provides a comprehensive list of CSFs that are relevant to develop a smartphone ecosystem in India. In addition, this study will help decision makers to strategically focus on the main drivers of the ecosystem that requires the immediate attention of decision makers. The methodology employed in this study provides a mechanism to conduct an exploratory study by identifying the factors and analyzing their interactions through the development of a hierarchical framework.

The proposed framework developed through qualitative modeling is an effort to understand relevant factors that can promote the smartphone manufacturing ecosystem. This study makes a significant contribution in the literature of smartphone manufacturing, which captures the perspective of different stakeholders.

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.

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.

Supply chain finance (SCF) has become a vital ingredient that fosters growth and provides flexibility to the global supply chain. Thus, it becomes essential to understand the factors that contribute to the success of the supply chain finance ecosystem (SCFE). This study aims to identify the critical success factors (CSFs) for the development of an efficient and effective SCFE. Based on their characteristics, the study intends to classify the factors into constructs and further establish a hierarchical relationship among the CSFs.

The study is based on empirical data collected from 221 respondents based on administered questionnaires. Exploratory factor analysis (EFA) is carried out on 16 selected factors (out of 21 proposed factors) based on the feedback of the experts and the factors were classified into four constructs. The total interpretive structural modeling (TISM) model was developed by identifying and finalizing CSFs of the SCFE. The model developed a hierarchical relationship between the various factors.

The study identified significant CSFs for the efficient and effective SCF ecosystem. Four constructs were developed by analyzing CSFs using the EFA. The finalized 16 CSFs modeled through the TISM and further hierarchical relationship established between the CSFs concludes that governmental policies and sectoral growth are the strongest driving forces and financial attractiveness is the weakest driving force. Based on the CSFs and the constructs identified, it was found that for the success of the SCF ecosystem, the existence of an economic ecosystem provides a facilitating framework for the overall development of the SCFE. Also, the trustworthiness among the partners fosters better relationships and results in financial feasibility and offers business opportunities for all the stakeholders.

This study will help the SCF partners across the globe understand the CSFs that ensure development of mutually beneficial SCF ecosystems and provide flexibility to the supply chain partners. The CSFs would provide insights to the policymakers and the financial intermediaries for providing a conducive environment for the development of a better SCF ecosystem. Also, the buyers and sellers would understand the CSFs that would develop better relationships among them and ultimately help in development of business across the globe.

The study identifies the CSFs for the SCF ecosystem. The study ascertains the significant factors and classifies them into clusters using EFA. Unlike the literature available, the paper develops the hierarchical relationship between the CSFs and develops a model for an efficient and effective SCF ecosystem.

This study aims to “identify”, “analyse” and “categorise” the lean-sustainability enablers for start-ups during the COVID-19 epidemic using total interpretive structural modelling (TISM).

A closed-ended questionnaire was used to collect data in addition to the scheduled interview. The TISM methodology is used to determine how the variables interact, and the matrice d’Impacts croises-multiplication applique´ a classement (MICMAC) method is used to rank and categorise the lean-sustainability enablers.

This study identified ten lean-sustainability enablers for start-ups during the COVID-19 pandemic. The study says that the key factors are leadership and managerial commitment, implementation of employee skills and abilities, strategic need, personnel engagement and financial ability.

The study focused primarily on lean-sustainability characteristics for start-ups.

This research will aid key stakeholders and academics in better understanding the factors that contribute to lean-sustainability in start-ups.

This study proposes the TISM technique for start-ups, which is a novel attempt in the subject of lean-sustainability in this industry.

Traditional supply chain arrangements have failed to keep up with escalating customer demands and breakthrough innovations. The way forward is a flexible yet innovative network that leverages ecosystem partners and digital tools to unlock new agility. The paper aims at identifying and analyzing numerous critical success factors (CSFs) that may improve the efficiency of a digital supply chain.

Twelve CSFs are identified in this paper through an extensive literature survey. Expert opinion has been considered and the hierarchical structure built using total interpretative structural modeling (TISM) which highlights the interdependencies between these CSFs. Cross-impact matrix multiplication (MICMAC) is used to determine the driving and dependence power of each factor.

This study identified 12 CSFs through an extensive literature survey. The ISM model resulted in six different levels beginning from redesign organization at the bottom of the structure. The TISM model explained why redesigning the organization is pivotal to bringing about novel agility in the supply chain. MICMAC analysis confirmed that the following enhanced the success of a digital supply chain: Sales and Operation Planning Strategies, Strategic Sourcing Techniques, Smart Manufacturing Processes and Warehouse Management.

Various other components contributing to the 12 CSFs identified in this paper may be discovered and detailed in future research. Additionally, further research is required to expand the existing technology-based services structural model to a more empirical form.

This study offers a comprehensive but not exhaustive list of CSFs essential to digital supply chain growth. It will enable market experts and leaders to concentrate on key factors leading to tactical decisions and maximum value for firms.

The paper seeks to add to the body of knowledge on real digitally-led supply chain transformation, which is still in its early stages. This study is one of the first, if not the first, to examine success factors critical to the improvement of the performance of the supply chain. It lays the foundation for further research in this field.

The purpose of this paper is to identify and analyze the interactions among different readiness factors for implementing agility in healthcare organization. Total interpretive structural modeling (TISM) based readiness framework for agility has been developed to understand the mutual interactions among the factors and to identify the driving and dependence power of these factors.

The identification of factors is done by TISM approach used for analyzing the mutual interactions between factors. Cross-impact matrix multiplication applied to classification analysis is utilized to find the driving and dependent factors of agile readiness in healthcare.

This paper identifies 12 factors of readiness for change in literature review, which is followed by an expert interview to understand the interconnection of factors and to study interrelationships of factors. The study suggests that factors like environmental scanning, resource availability, innovativeness, cost effectiveness, organizational leadership, training and development are important for implementing/improving the readiness of agility in healthcare organizations.

This research focuses mainly on readiness factors for agility in healthcare sector.

Top management must stress on readiness factors that have a strong driving power for efficient implementation of agility in healthcare. This study helps the managers to take quick decisions, and continuous monitoring of readiness factors would be more beneficial to improve the quality of service, which makes the organization more agile.

In this research, TISM-based readiness for agile framework structural model has been proposed for healthcare organizations, which is a new effort for implementation of agility in healthcare.

Startups across all sectors are affected by the COVID-19 pandemic and are facing a formidable challenge in terms of marketing and operations. Most of the startups have experienced a downturn in demand and supply due to COVID-19 led disturbances in sourcing networks. This paper aims to identify, analyze and categorize the significant risks influencing sourcing operations in startups during the COVID-19 era in India, using the total interpretive structural modeling (TISM) approach.

Eight enablers were identified through literature review and expert opinions from various startups in India. This study adopted the TISM approach to analyze the inter-relationships between the enablers. Multiplication Applied to Classification (MICMAC) analysis was used to rank the sourcing risk enablers and classify them as autonomous, independent, linkage and dependent enablers.

The results indicate “insufficient fund” as the most critical enabler. Network issues and employee flexibility risk were among the other critical enablers that have a high driving power. Supplier risk, quality risk and demand risk were found to have highly dependent on other enablers for implementation.

This study mainly focuses on the sourcing risks in startup operations in India. This study can be extended to many other countries.

This study will help startup industry managers and practitioners understand the interactions of enablers and identify critical enablers to mitigate risks in startup sourcing operations in the COVID-19 era.

The present study identifies the sourcing risk enablers in the COVID-19 era. It is the first attempt to analyze the interrelationship among sourcing risks in startups using the TISM approach.

This paper aims to identify and model barriers to internationalising automotive small and medium-sized enterprises (SMEs) from emerging market perspectives using the interpretive structural modelling (ISM) approach.

In this paper, 13 critical barriers are identified through an exhaustive literature review and the Delphi method. The ISM tool is then used to establish interrelationships among the identified barriers to expose and discuss the key barriers having high-driving power.

It was found that barriers such as trade agreements and export documentation, exchange rates and material inadequacies were relatively less challenging than the other barriers. At the next level, there are barriers such as supply chain, high international quality standards, legal barriers, skilled labour marketing capacity and information and logistics and infrastructure. Finally, barriers such as government policies, entrepreneurial orientation and technology and finance availability posed the most significant challenge for the internationalisation of Indian SMEs. These barriers warrants immediate and considerable attention.

This study developed a model based on experts’ opinions, which may be biased and influence the final model as proposed in this study. This research will help the owners/managers of the SMEs and policymakers identify and understand the significance and relevance of automotive sector barriers while strategizing.

To the best of the authors’ knowledge, this is the first time an attempt has been made to apply ISM methodology to explore the interdependencies among the critical barriers of internationalisation for SMEs of Indian automotive industries. This study will guide the owner–managers management practices to overcome ineffective practices and move towards successful internationalisation.

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.