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This study, based on the instrumental approach of the stakeholder theory, examines the firm performance of public and private sector firms in the mandatory corporate social responsibility (CSR) expenditure regime in India. CSR was legislated in India in the year 2014.

The study hypothesizes that firms which fulfill the mandatory CSR expenditure requirement will have a higher firm performance and uses one-way ANOVA and post-hoc test for analysis. Firm performance is examined with respect to firm value and market performance.

The instrumental approach of the stakeholder theory is not supported in the mandatory CSR expenditure regime in India. The public sector firms that comply with the mandatory CSR expenditure requirement have a lower firm performance. Further, the private sector firms that meet the mandatory CSR expenditure criterion do not have a significantly different firm performance than the private sector firms that do not fulfill this criterion.

The study indicates as to why some firms fail to meet the CSR expenditure compliance. It also gives suggestions on how regulators and government agencies can solicit the participation of the Indian firms to undertake CSR initiatives. The study further suggests how firms may reap maximum benefit from the CSR expenditure.

Since CSR expenditure has been made mandatory only in the year 2014 in India, hardly any study has examined firm performance in the mandatory CSR expenditure regime in India.

The aim of this study is to investigate and clarify how the triple helix actors can effectively implement the concepts of Kaizen to navigate and overcome the complex obstacles brought on by the global COVID-19 pandemic.

Through broad literature reviews, nine common parameters under triple helix actor have been recognized. A regression analysis has been done to study how the triple helix actors’ common parameters impact Kaizen implementation in business operations.

The results of this study revealed insightful patterns in the relationships between the common parameters of triple helix actor and the dependent variables. Notably, the results also showed that leadership commitment (LC) emerges as a very significant component, having a big impact on employee engagement as well as organizational performance.

In addition to offering valuable insights, this study has limitations including the potential for response bias in survey data and the focus on a specific set of common parameters, which may not encompass the entirety of factors influencing Kaizen implementation within the triple helix framework during the pandemic.

The originality of this study lies in its comprehensive exploration of the interplay between triple helix actors and Kaizen principles in addressing COVID-19 challenges. By identifying and analyzing nine specific common parameters, the study provides a novel framework for understanding how triple helix actors collaboratively enhance organizational performance and employee engagement during challenging times.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.

The purpose of this paper is to explore the relationship between various risk management strategies and risk management practices in order to design and hence enact a suitable supply chain risk mitigation (RM) plan. Additionally, this study proposes a hierarchical framework to explain the mutual relationship between supply chain risk management (SCRM) practices and strategies by considering the underlying dimensions between them.

An amalgamation of systematic literature analysis (SLA) and correspondence analysis (CA) has been performed to develop the conceptual framework. A real-life case of Indian petroleum supply chain has been considered to validate and explain the proposed model.

The results reveal three underlying dimensions, which associate the relationship between RM strategies. They are, risk adaptability of SC managers with a variance of 34.71%, followed by resource capability of the firm and the degree of sophistication of RM practices, with variances of 27.72 and 20.35%, respectively. Risk avoidance strategy comprises of practices such as supplier evaluation, technology adaption, flexible process and information security. On the other extreme, the risk sharing strategy includes revenue sharing, insurance, collaboration, public–private partnership and so on as essential RM practices.

The study not only focuses on the distinction between RM strategies and practices, which were used interchangeably in the prior literature, but also provides an association between the same by exploring the underlying dimensions. These underlying dimensions perform a crucial role while developing a risk management plan. This study explicitly focuses on the RM step of SCRM process. Pre and post risk mitigation phases of SCRM process, such as risk assessment and risk monitoring, are beyond the scope of the current research.

The paper develops a framework for mapping various RM strategies with their corresponding practices by considering the Indian petroleum supply chain as a viable case study. Various theoretical and business implications are derived in the context of the developing country.

The purpose of this paper is to develop a decision support system (DSS) to assist supply chain (SC) risk managers to select a suitable risk management (RM) strategy and expedite the implementation of corresponding RM enablers. The relationship between RM strategies and RM enablers is explored by identifying the underlying factors between them, which is further used to build the DSS.

The DSS is built by integrating heterogeneous techniques. A systematic review approach is employed to explore both proactive and reactive RM enablers, and they are further mapped to various RM strategies by using correspondence analysis (CA). An in-depth interview is conducted to develop the rules for constructing the decision system. A rule-based fuzzy inference system (FIS) is utilized to counteract the uncertainty involved in the decision variables. The efficacy of the proposed DSS is demonstrated by considering two conjectural scenarios in the case of Indian petroleum SC (IPSC).

The results reveal three primary underlying factors between the risk mitigation strategies viz. SC managers' preparedness to face risk, organization's resource capability to deal with risk and the sophistication of the implementation of the RM enablers; with explained variances of 37%, 29% and 22%, respectively. Risk avoidance strategy comprises of RM enablers such as supplier evaluation, technology adaption, information security, etc. Whereas, the risk-sharing strategy includes revenue sharing, insurance, collaboration, public-private-partnership, etc. as essential RM enablers. The DSS recommends risk-mitigation and risk-sharing as effective RM strategies for the IPSC under the considered scenarios.

This paper develops a decision support framework for recommending an effective risk mitigation strategy and outranking the corresponding enablers. The study explicitly focuses on the risk mitigation step of the supply chain risk management (SCRM) process. Pre- and post-risk mitigation steps of the SCRM process, such as risk assessment and risk monitoring are beyond the scope of this research.

The operational procedure of the proposed DSS is explained by considering a real-life case of petroleum SC in the Indian scenario. The unique contributions of this study are presented as theoretical implications and managerial propositions in the context of a developing country.

An amalgamation of Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) has been performed to develop a decision-making framework for improving the overall performance of the microfinance institutions. A primary survey was conducted to collect real-time data from the heterogeneous stakeholders of microfinance institutions across India. The validation of the proposed framework is performed by comparing the results against the conventional method of Analytical Hierarchy Process (AHP).

This study identifies various dimensions and indicators for measuring the performance of Indian microfinance institutions. Additionally, the ranking and prioritisation of the performance dimensions and indicators is obtained by considering the mutual interrelation between them.

The study indicates that there exists a significant dyadic relationship between financial performance and social performance for improving the overall performance of the microfinance institutions. Governance is found to unidirectionally influence both financial and social performance. Among all the considered dimensions, financial performance of a microfinance institution is the most critical dimension for improving the overall performance. The top five performance indicators of the Indian microfinance institutions are funding source, borrowing and overhead cost, size of the firm, end-use of the money and depth of outreach.

The study was conducted in the context of Indian microfinance institutions; hence the scope of generalisation of the results is limited. This research considers both subjective and objective aspect of the performance dimensions and indicators from the perspective of multiple stakeholders (i.e. firm, society and regulator). The integrated framework is expected to aid in improving overall performance of microfinance institutions by focusing on the most critical (high prioritised) performance indicators.

An integrated DEMATEL-ANP framework is used in the domain of microfinance to assess the performance dimensions. This study is unique in terms of analysing performance of microfinance institutions from the perspective of heterogeneous stakeholders.

The purpose of this paper is to identify various risk and sub-risk drivers that affect the supply chain (SC) performance and to propose a framework to quantify the overall SC risk index by considering the importance of each risk and sub-risk drivers and their mutual interactions.

A hybrid method based on decision-making trial and evaluation laboratory and analytical network process has been proposed to develop the risk quantification framework. A case study of Indian petroleum supply chain (PSC) has been illustrated to explain the proposed method.

The results of this study found that transportation/logistics (delivery system), quality of the petroleum products, crude supply, customer’s order and legal/political regulations are the most significant risk drivers of a typical PSC. It is also found that the Indian PSC possesses a risk score of 34 percent.

The quantification of risk in operational measure provides an unblemished representation of the overall SC risk. Unlike the existing financial measure, it takes complex subjective operational effectiveness like product quality, customer satisfaction, etc., into consideration. Identifying the high-prioritized risks helps the decision and policy makers to merely focus on the most prominent risk drivers, and reduce the impact of overall SC risk. Planning a risk mitigation strategy at a given level of risk is however beyond the scope of this research.

The paper develops a risk quantification framework in the context of a PSC.

This study aims to identify service quality dimensions for logistics service providers (LSPs) and to examine their relationships with customer satisfaction and customer loyalty.

Service quality dimensions are identified from vast literature review. Customers who take services from LSPs were surveyed to collect data on basis of developed survey instrument. Structural Equation Modelling (SEM) is applied to test the proposed research hypotheses.

The study shows that all the five service quality constructs, i.e. “Operational Quality”, “Resource Quality”, “Information Quality”, “Personnel Contact Quality” and “Customization and Innovation Quality” have direct relationship with customer satisfaction. They also have indirect relationship with customer loyalty, implying the full mediation of customer satisfaction.

The results of the study suggest that the logistics service quality (LSQ) can be measured multi-dimensionally. It provides clear implications to LSPs for improvement of service quality. The present research work is expected to be useful for both, logistics service providers and the customer organizations, which take services from LSPs. LSPs can develop strategies to improve their service quality on basis of findings from this study.

The present research will help in extending the existing literature on service quality in context to LSPs.