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Motivated by the evidence highlighting the role of sentiments and cognitive biases in investors' decision-making, this study examines a novel behavioral finance-based asset pricing model incorporating the prospect theory framework in the Indian equity market. Specifically, the study’s primary objective is to investigate the importance of Prospect Theory Value (PTV) in the cross-sectional pricing of stocks.

The empirical findings rely on data taken from NIFTY 500 and BSE S&P 500 stocks, encompassing daily, weekly and monthly observations. The analysis employs diverse statistical techniques, including Ordinary Least Squares (OLS), Fama–Macbeth Cross-section Regressions, Panel Fixed Effect and Quantile Regression.

The study demonstrates an asymmetric association between PTV and subsequent stock returns. The findings maintain their robustness even when factoring in stock-specific attributes such as market capitalization and book-to-market ratio, market beta and indicators related to lottery-like behavior such as skewness and MAX. This observed pattern persists when analyzing data at various frequencies, including daily, weekly and monthly intervals. Loss aversion behavior dominates among Indian equity investors, contrary to lottery preferences in the US equity market.

As far as the authors are aware, the study is the first to introduce a new behavioral finance-motivated stock return predictor (PTV) in the Indian stock market. The study also marks the pioneering use of a novel method that evaluates the predictability of PTV across various sections of the conditional return distribution using quantile regression.

The study aims to test prospect theory (PT) predictions in the cryptocurrency (CC) market. It proposes a new asset pricing model that explores the potential of prospect theory value (PTV) as a significant predictor of CC returns.

The study comprehensively analyses a large sample set of 1,629 CCs, representing more than 95% of the CC market. The study uses a portfolio analysis approach, employing univariate and bivariate sorting techniques with equal-weighted and value-weighted portfolios. The study also employs ordinary least squares (OLS) regression, panel data methods and quantile regression (QR) to estimate the models.

This study demonstrates an average inverse relationship between PTV and CC returns. However, this relationship exhibits asymmetry across different quantiles, indicating that investor reactions vary based on market conditions. Moreover, PTV provides more robust predictions for smaller CCs characterized by high volatility and illiquidity. Notably, the findings highlight the dominant role of the probability weighting (PW) component in PT for predicting CC behaviors, suggesting a preference for lottery-like characteristics among CC investors.

The study is one of the early studies on CC price dynamics from the PT perspective. The study is the first to apply a QR approach to analyze the cross-section of CCs using a PT-based asset pricing model. The results shed light on CC investors' decision-making processes and risk perception, offering valuable insights to regulators, policymakers and market participants. From a practical perspective, a trading strategy centered around the PTV effect can be implemented.

This study aims to analyze the impact of ethical leadership on organizational citizenship behavior and turnover intention of employees working in the financial sector, considering procedural justice as a mediator.

Data was collected from 306 employees working in the financial sector (banking, insurance and mutual fund) in India. The data was collected in two phases to avoid common method bias by using standardized close-ended questionnaires. Data for this study was assessed using Smart Partial Least Square (PLS) 3.

The results show that ethical leadership is significantly associated with procedural justice, organizational citizenship behavior and turnover intention. Further procedural justice acts as a mediator between ethical leadership and organizational citizenship behavior; also between ethical leadership and turnover intention.

The research contribute in understanding the role of procedural justice as a mediator between ethical leadership and organizational citizenship behavior and turnover intention for the employees working in the financial sector in India.

One of the major challenges for developing countries is the lack of mechanisms for the evaluation of critical success factors (CSFs) of quality initiatives, which hampers the journey toward sustainability. Lean Six Sigma (LSS) has been one of the most widely used initiatives supporting quality improvement with wastes reduction and facilitating sustainability. To expedite LSS and its spread, it is important to evaluate key CSFs. Accordingly, the purpose of this paper is to provide an approach for the evaluation of LSS-CSFs for Indian small and medium enterprises (SMEs).

The paper uses a graph theoretic approach and demonstrates the evaluation of LSS-CSFs by proposing an index. The development of index is illustrated using a set of seven prioritized CSFs based on the literature review paper (Lande et al., 2016).

This study guides about the translation of CSFs in the form of an index (number) and will benefit both researchers and practitioners, who wish to study the role of key CSFs for implementation and audit requirements for sustainability.

Authors remain confined only to Indian SMEs.

LSS possesses the potential to enhance the performance of manufacturing SMEs, but its evaluation is not easy. This attempt for offering a useful evaluation scheme involving CSFs, in the areas of LSS in developing country contexts, is the first. The approach also facilitates both quality audits and benchmarking between different sets of CSFs. The approach is generalizable and can be extended in other areas.

Critical success factors (CSF) for lean six sigma (LSS) using quality 4.0 are not researched so far. This study aims to bridge this gap. It also validates CSF already identified for LSS under conventional technologies.

Empirical research using the questionnaire method is conducted. Construct of the questionnaire is checked using Cronbach’s alpha and responses received are analysed using t-test and exploratory factor analysis.

In total, 20 factors are evaluated for LSS success. It includes 7 factors related to quality 4.0 technologies and 13 related to the conventional set-up. All 7 quality 4.0 related factors were found critical; whereas, under traditional set-up, 11 factors out of 13 were found critical.

The study will help enterprises in the fast and effective adoption of quality 4.0 and seamless integration with LSS. The post-Covid-19 business scenario is expected to be information technology focussed. The findings of this study will be useful in these circumstances. Consultants and practitioners can prioritise their efforts based on newly identified CSF. The new revelation about CSF for LSS in quality 4.0 enriches theory as well.

Developing skills based on newly identified CSF will help people in remaining employable in the era of automation, robotics and artificial intelligence which is otherwise ill-famed for destroying jobs.

CSF for LSS using quality 4.0 is a new contribution. It differentiates CSF established earlier for conventional technologies. Moreover, many CSF are common for LSS and industry 4.0, therefore this study will also help in smoother adoption of industry 4.0/quality 4.0 in organisations.

The study explores the relationship between entrepreneurial cognitive styles, entrepreneurial orientation (EO) and innovation performance (IP) of organizations in northern India. It also investigates how the cognitive styles of entrepreneurs impact their orientation and influence their innovative performance.

A quantitative research design validates the proposed hypotheses. A survey was conducted using simple random and snowball sampling to gain responses from 150 entrepreneurs based in northern India. The structural relationships in the study were examined using ANOVA (Analysis of Variance) which is a statistical method used to assess whether there are significant differences in means amongst groups by comparing the variance.

Data analysis revealed that entrepreneurial cognitive styles significantly and positively impact EO. The innovativeness and proactiveness dimensions of EO affect IP.

Previous researchers have worked independently on cognitive style and EO. The present paper combines the impact of cognitive style and EO on IP to identify the missing links between the three constructs, which need to be added to the existing literature. The authors' findings are valuable for entrepreneurs seeking to identify the key factors contributing to developing effective strategies at the firm level, thereby driving IP. Furthermore, the authors' insights would assist potential entrepreneurs in distinguishing between the different cognitive characteristics that differentiate entrepreneurs from non-entrepreneurs and how they strategically decide based on market situations to enhance IP.

Power quality issues highly affect the secure and economic operations of the power system. Although numerous methodologies are reported in the literature, flexible alternating current transmission system (FACTS) devices play a primary role. However, the FACTS devices require optimal location and sizing to perform the power quality enhancement effectively and in a cost efficient manner. This paper aims to attain the maximum power quality improvements in IEEE 30 and IEEE 57 test bus systems.

This paper contributes the adaptive whale optimization algorithm (AWOA) algorithm to solve the power quality issues under deregulated sector, which enhances available transfer capability, maintains voltage stability, minimizes loss and mitigates congestions.

Through the performance analysis, the convergence of the final fitness of AWOA algorithm is 5 per cent better than artificial bee colony (ABC), 3.79 per cent better than genetic algorithm (GA), 2,081 per cent better than particle swarm optimization (PSO) and fire fly (FF) and 2.56 per cent better than whale optimization algorithm (WOA) algorithms at 400 per cent load condition for IEEE 30 test bus system, and the fitness convergence of AWOA algorithm for IEEE 57 test bus system is 4.44, 4.86, 5.49, 7.52 and 9.66 per cent better than FF, ABC, WOA, PSO and GA, respectively.

This paper presents a technique for minimizing the power quality problems using AWOA algorithm. This is the first work to use WOA-based optimization for the power quality improvements.

The COVID-19 crisis has created enormous strain in global supply chains. The disruption has caused severe shortages of critical items, including personal protective equipment (e.g. face masks), ventilators and diagnostics. The failure of the industry to meet the sudden demand for these necessary items has caused a severe humanitarian crisis. These situations, resulting from the COVID-19, crisis have led to the informal growth of frugal innovation in sustainable global supply chains. This paper aims to provide a detailed overview of drivers of frugal-oriented sustainable global supply chains, following lessons acquired from emerging countries’ attempts to deal with the COVID-19 pandemic.

The authors used a focused group approach to identify the drivers and this paper further validated them using existing literature published in international peer-reviewed journals and reports. The authors adopted total interpretive structural modeling (TISM) to analyze the complex relationships among identified drivers.

The authors present a theoretical framework to explain how the drivers are interlinked. This paper has developed the framework through a synthesis of the TISM modeling and Matrice d’impacts croisés multiplication appliquée á un classment analysis. This paper observed that government financial support, policies and regulations, under the mediating effect of leadership and the moderating effect of national culture and international rules and regulations, has a significant effect on the adoption of emerging technology, volunteering initiatives and values and ethics. Further, emerging technology, volunteering initiative and values and ethics have a significant effect on supply chain talent and frugal engineering. These results provide some useful theoretical insights that may help in further investigating the role of frugal innovations in other contexts.

The authors find that outcomes of the methodical contributions and the resulting managerial insights can be categorized into four levels. Industry and researchers alike can use the study to develop the decision-support systems guiding frugal-oriented sustainable global supply chains amid the COVID-19 pandemic and in recovering them thereafter. Suggestions for future research directions are offered and discussed.

The study aims to develop an in-depth understanding of challenges faced by Indian women professionals during the pandemic and the human resource (HR) initiatives like effective communication, taken by the organizations to mitigate the plight of these professionals.

A mix of two qualitative research methods namely focus groups in-depth and one-to-one in-depth interviews was used. A total of 32 females working with different organizations participated.

The thematic analysis revealed themes related to challenges faced by working women-gendered burnout, mental health issues, increased household responsibilities, job insecurity, work-life conflict, gender inequalities, reduced internal communication and financial independence, domestic violence and exploitation. The major themes that emerged for the organizational initiatives were flexible working hours, equal women representation in response to planning and decision making, driving transformative change for gender equality, paid leaves for family care, caregiving bonus, leadership development seeds, increased female recruitments, transparent communication and counseling sessions.

The study establishes a holistic understanding of the plight of Indian women professionals and the consequent organizational interventions accompanied by transparent communication. It adds rigor to the evolving literature on COVID-19 and enriches the theoretical narrative of policy adaptations by industry practitioners for aligning them with employee needs. This helps in routing the policy design and implementation in light of the challenges faced.

The study presents an in-depth understanding of challenges faced by women employees; and provides a foundation for identifying human resource management (HRM) interventions customized for working females. It also proposes a framework implementable in the recovery phase, deploying critical strategic shifts like reflection, recommitment and re-engagement of the women workforce in order to maximize their efficacy for rapidly evolving organizational priorities.