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Supply chain disruptions can have severe negative consequences on companies. However, studies measuring the financial impacts of supply chain disruptions are largely confined to developed nations and large companies. Therefore, this study aims to analyze the impact of supply chain disruption on small companies in the context of an emerging nation. Further, an attempt has been made to classify supply chain disruptions and measure its impact by its type.

In this research, the event study on 335 supply chain disruption events for a 10 year period starting from 2009 to 2019 has been used.

The results state that the Indian small and medium companies lost −4.49% of shareholder wealth in disruption. The findings also indicate that the financial and environmental disruptions can have severe effect on shareholder wealth as compared to other category.

The study is confined to a developing country. Considering multiple countries can provide comparative results and therefore a global consensus could be achieved.

The outcomes of the results help managers to plan and prioritize supply chain disruptions, regulatory authorities can plug any possible insider trading practices for small companies in the event of supply chain disruptions. Investors can plan and take prudent investing decisions based on the nature of the disruptions.

To the best of the knowledge, this is the first study measuring the supply chain disruption effects on smaller companies in an emerging nation. The study is also novel in incorporating financial disruptions and measuring source wise impact on shareholder wealth.

This research identifies the supply chain performance indices and designs an evaluation framework to assess and compare the Indian petroleum supply chain performance. We presented a case study of three Indian petroleum companies. For this purpose, we identified fifteen performance criteria extracted from previous literature and expert inputs and classified them into four groups.

A fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) method is employed for evaluating the performance of the Indian petroleum supply chain.

The design and evaluation framework suggests that the top three performance measurement criteria, the purity of the products, compliance with environmental laws, and new technology adoption. The result findings also indicate that company C contributes to a maximum satisfaction level of 77%. Simultaneously, companies A and B hold satisfaction levels of 72% and 67%.

The managers should ensure that environmental standards, new technology adoption, and quality are significant concerns in the petroleum supply chain. The managers should follow national and international policies to preserve the environment and ensure safety in operational activities.

This paper makes two contributions in the domain of performance measurement of the petroleum supply chain. First, it identifies the prominent supply chain performance indices. Second, it proposes a model to assess and compare the performance of Indian petroleum companies.

Disruptive technologies can significantly contribute to the sustainability of operations in the petroleum supply chain. The present study aims to identify the prime sustainable dimensions and disruptive technologies implementation in the supply chain of the petroleum industry. The authors used content analysis in the literature and experts input to explore the sustainable dimensions and disruptive technologies in the supply chain.

This study used a hybrid method of hesitant fuzzy set and regret theory to identify the prominent sustainability dimensions and prominent disruptive technologies. This method emphasizes the decision-makers psychological characteristics under uncertain environments.

The result indicates that social responsibility, labor practices, safety and technical standards hold the most prominent sustainable dimensions in the petroleum supply chain. Further, the result also depicts that when consider an equal degree of regret and rejoice, artificial intelligence and big data could significantly enhance operations sustainability in the petroleum industry.

This study considers only 11 sustainable dimensions and 43 sustainable factors, whereas other dimensions and factors could also be considered in future research. The research uses hesitant fussy set and regret set theory to identify the prominent sustainable dimensions and disruptive technologies, whereas other multiple-criteria decision-making (MCDM) techniques can also be used.

To the best of the authors’ knowledge, this is the first paper to explore the sustainable dimensions (environmental, social and economic) and disruptive technologies in the supply chain of the petroleum industry. This research intended to guide the practitioners, policymakers and academicians to emphasize their effort toward sustainable operations supply chain management.

Innovation is a prerequisite for economic and technological growth of any organization. Identifying enablers of innovation can help managers accelerate the process of economic growth. The purpose of this paper is to identify the prominent enablers of innovation in small and medium enterprises (SMEs) that can help overhauling organizations and benefit them economically.

A comprehensive literature review and expert’s opinions have been applied to identify enablers of innovation. A case of automotive component supplier is considered for conducting the research. A coalescence of Grey and DEMATEL methodologies has been incorporated to first rank the enablers of innovation based on their importance and then identify the causal relationship among these enablers by characterizing enablers into causal and effect groups.

A few important enablers, namely, entrepreneur traits, knowledge management, resources for innovation, and linkage capabilities, have been identified as prominent enablers for successful innovation in SMEs.

This paper identifies enablers of innovation in SMEs and the causal relationship between these enablers. The identified enablers and the causal relationship between these enablers will help managers of small organizations in selecting the enablers that need to be focused on, which, in turn, can drive other enablers of innovation, thus saving time and resources of the organizations.

This paper uses a novel Grey–DEMATEL methodology to identify the causal relationship among enablers and also contributes to the literature on innovation by identifying enablers of innovation in SMEs.

Improving work engagement can have significant implications for performance at individual, team and organisational level. The purpose of this paper is to investigate the effects of occupational self efficacy and human resource development (HRD) climate on work engagement among business executives of select business organisations in India. In addition, it aims to attempt to examine the mediating effect of HRD climate on self efficacy and work engagement relationship.

The sample consisted of 150 business executives from both public and private sector manufacturing and service organisations in India. Data were collected through both personal visits and online questionnaires. Correlation and regression analyses were used to test the research hypotheses. Specifically, Baron and Kenny's method was used for testing the hypotheses of mediation.

A significant relationship was found between all variables in the study. All the study hypotheses were supported. HRD climate was found to partially mediate the relationship between occupational self‐efficacy and work engagement. Interestingly, both HRD climate and self‐efficacy affect work engagement both directly and indirectly through influencing the other.

Work engagement requires the workforce that is endorsed with self‐efficacy as dispositional trait. In addition, improving the HRD climate can have significant implications for enhancing the work engagement among Indian business executives.

By investigating the relationship between self‐efficacy, HRD climate and work engagement the present study made an effort to fulfil the gap in academic literature where there is a significant dearth of academic literature on work engagement from developing economies.

The purpose of this paper is to perform organizational team effectiveness analysis and to find out whether decision-making style (DMS) has any association with team effectiveness. Which style most significantly affects the team effectiveness and how this predictive association can be used to improve existing teams as well as to build new effective teams?

The sample includes 231 sample responses of executives from Indian Manufacturing Organizations from both public and private sectors. Two standardized questionnaires are used for data collection. Mainly, SPSS v20.0 was used for data analysis and hypotheses testing. AMOS v20.0 was used for testing the research model based on the supported hypotheses.

Rational DMS is mostly endorsed by the Indian executives. Not all DMSs but rational and avoidant styles independently and interactively are the significant predictors of team effectiveness.

The survey method of data collection, cross-sectional research design and consideration of particular DMSs and team effectiveness frameworks are the main limitations of this study. Theoretical as well as practical implications are vested in the results.

The study bears significant practical implications for the respondents, practitioners, professionals and academicians in the field of team working. Management development and training activities may be directed based on the findings.

The study suggests socially acceptable and practicable decision-making behaviors in organizations. It highlights suggestions for improving team effectiveness (TE). Hence, certain social implications are also there.

The edge in this research over the previous studies is that earlier scholars, who examined member traits’ impact on TE, did not considered DMS as a predictor of TE. Certain researchers appealed for diagnosing the standard variable to measure the member style. This research is, therefore, unique in its kind as it is a pioneering effort to study the DMS in relation to team effectiveness. The focus on sample of Indian manufacturing executives also bears importance. Moreover, unlike other researches, it focuses on DMS rather than the decision-making process itself.

The purpose of this paper is to investigate the interactions among the key factors of supply chain (SC) in the Indian automotive industry. These key factors are helpful to measure supply chain performance (SCP) and to improve the firm’s effectiveness.

In this paper, an interpretive structural modeling with a fuzzy cross-impact matrix multiplication applied to classification-based approach is used to examine the interactions among the key factors of SCP measurement.

The authors have identified the most dominant key factors used for measuring the performance in automotive SC. The results exhibit that the order lead-time and order entry method are the most significant key factors. These key factors have high driving power to measure SCP whereas the post-transaction measure of customer service and customer query time are highly dependent on other factors. Such relationships among the key factors can help a firm’s top management to make essential judgments in order to solve the overall SC problems and provide a better approach to proactively deal with problems.

In this paper, the authors have explored the interactions among the key factors of the SCP in the Indian automotive industry.

This chapter of the book aims to achieve sustainability and productivity in light of the interaction between managers and engineers in a lean and agile supply chain management system in today’s organizations. The main innovation of this chapter is the use of the balanced scorecard (BSC) model and fuzzy analysis network process (FANP) to create a suitable platform for the realization of this interaction between managers and engineers and to identify exactly which expert system is ideal for the main purpose. Indeed, this chapter introduces its readers to the application of strategic management tools such as the BSC accompanied by FANP in the elements of supply chain management where data analysis of lean and agile networks in supply chain management can create a competitive advantage in the organization.

The purpose of this paper is to identify, classify and prioritize supply chain risks faced by Indian micro small and medium manufacturing companies and to develop a comprehensive supply chain risk index.

Primary data has been collected from 354 Indian micro small and medium enterprises on the different supply chain risks faced by them. An extensive literature review followed by expert's interview has been carried out in order to finalize the supply chain risks. A hybrid methodology consists of AHP and Fuzzy TOPSIS is applied for the data analysis. A sensitivity analysis has been done to check the robustness and consistency of the results.

Results depict the importance of supply side and financial side risks faced by manufacturing supply chains, thus adding to the ongoing academic debate on the importance of supply chain finance solutions.

Study is limited to the scope of an emerging market. Generalization of results needs more systematic studies around the world in different supply chains.

Supply chain managers can consider the benchmark framed in this study in order to identify the health of their supply chain and to efficiently employ supply chain risk management strategies.

The current study is novel in developing a supply chain risk index using a hybrid AHP-Fuzzy TOPSIS methodology with a comprehensive list of 26 supply chain risks under 5 categories for an MSME supply chain. To the best of the authors’ knowledge, this is the first study incorporating financial risks in the development of a supply chain risk index.

Companies all over the world have recently started to adopt supply chain finance (SCF) solutions in their supply chains to reduce the payment defaults and simplify the bill settlement process. The purpose of this paper is to identify and prioritize the barriers to adopting SCF in micro, small and medium enterprises.

It employs a three-phase methodology to identify and prioritize the essential barriers to the implementation of SCF. An extensive survey has been carried out in 101 Indian MSMEs in India which identified 37 barriers under six heads in the first phase. Experts’ interview using the Delphi technique has been carried out in the second phase to finalize the barriers. The analytic hierarchy process methodology, with sensitivity analysis for validation, is used in the final stage to prioritize and rank the barriers.

Results show that financial and information technology barriers are prominent in SCF adoption followed by financial challenges. Among specific barriers, the disclosure of sensitive company information to competitor barrier acts as an essential barrier followed by poor technological capability of MSMEs.

The study is limited to SCF adoption of MSMEs in a developing nation. Extensive research is required in order to derive a global trend.

The current research contributes to the stakeholder theory and transaction cost economics. Observations made in the current research can encourage organizations to incorporate stakeholders’ concerns into the adoption of SCF solutions. The study provides a more in-depth view of such challenges and a benchmark, which will help companies to adopt SCF solutions more effortlessly. Moreover, policy makers across the world can explore these serious issues and amend or introduce new policies to facilitate companies’ implementation of supply chain financial solutions.

To the best of the authors’ knowledge, this is the first study which identified and prioritized SCF adoption barriers of MSMEs in a developing nation. This study is also novel in adopting a hybrid analytical hierarchy process-sensitivity analysis for ranking the SCF barriers in an MSME context. SCF studies often emphasize only on the reverse factoring aspect of SCF. The current study considers many innovative aspects of SCF, such as pre-shipment financing, dynamic discounting, inventory financing, collaborative logistics, etc.