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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.

This study was conducted to analyse the socio-ecological problems faced by the Suhelwa Wildlife Sanctuary and understand its potential and challenges for developing ecotourism following Triple Bottom Line (TBL) principles. The study also benchmarked best ecotourism practices across the globe to create an ecotourism plan that would provide alternative livelihood and help in sustainable management of the area by reducing poverty, dependency on forests and biodiversity protection.

Suhelwa Wildlife Sanctuary was chosen because this area has several socio-ecological crises with limited livelihood options, and there is an urgent need for alternative livelihood opportunities in the form of ecotourism. The study followed an ethnographic approach through observation, participant observation, and semi-structured interviews. Content and thematic analysis was conducted through Atlas Ti9.0 software for data analysis. Subsequently, benchmarking best ecotourism practices through a literature review was done to develop an ecotourism action plan.

The First finding was related to the study area divided into three themes: problems, potential for ecotourism development, and challenges for ecotourism development. The second finding was related to benchmarking best practices and suggesting an action plan.

This work studied an area not sufficiently acknowledged by academicians and policymakers concerning ecotourism development. The work also benchmarks the best practices for ecotourism and proposes a sight-specific ecotourism action plan in accordance with TBL.

In the era of the circular economy, the economic growth of a country is highly dependent on the sustainable performance of the manufacturing sector. In today’s increasingly competitive world, it is important to constantly improve the manufacturing or service industry. Quality with quantity is a main characteristic, which helps a company stay in the competition. Flexibility and responsiveness to customer demands are very important for success. Generally, additional time is needed for setup caused by poor design of equipment. At this point, the terms continuous process improvement and single-minute exchange of dies (SMED) as an approach of lean manufacturing come into play. Lean manufacturing system has been identified as an approach for improving the performance of the process and product.

In this paper, high setup time is considered as major problem in the industry and a major cause and effect for high setup time was found. On the basis of the literature review and experts’ opinions, four categories of barriers, namely method, manpower, machine and tools are identified. In this study, a hybrid approach comprising of the analytic hierarchy process (AHP) and graph theoretic approach (GTA) has been used. First, prioritization of different categories of barriers by AHP has been done, and second, GTA has been applied for finding the barriers' intensity index. Based on this study, machine and manpower barriers have emerged as major hurdles in the high setup time of machine. The proposed framework will help organizations quantify barriers in high setup time in different manufacturing processes, thereby developing effective strategies for sustainable production.

Findings of this research will contribute to ensuring sustainable competitive advantages, but it has some limitations. Development of the permanent matrix equation for barriers of high setup time is complex and lengthy when barriers are more in number. Absolute and relative values considered while quantifying the intensity of barriers are based on experts’ opinions, which may be inconsistent. In spite of these limitations, organizations can use an illustrated approach to quantify the barriers, thereby developing strategies for successful implementation of high setup time for making them sustainable in the global market. Organizations can also benchmark their sustainability preparedness with the best in the industry. As a future scope of study, high setup time can be reduced by using SMDE technology can be further validated through an empirical and case-based approach to generalize the findings.

Authors remain confined only to setup time. The approach is generalizable and can be extended in other areas. As a future scope of study, high setup time can be reduced by using single minute die exchange technology and can be further validated through an empirical and case-based approach to generalize the findings.

The study guides and facilitates researchers and practitioners in using the most appropriate techniques such as AHP and GTA for empirical studies and in developing, modifying and/or reviewing application frameworks for production. It also guides implementation experience regarding high setup time by using advanced techniques such as single point die exchange (SMDE), which can be beneficiary for both developing and developed country contexts. Industries can accelerate implementation by understanding and using most important AHP, GTA and SMDE techniques.

Lean manufacturing system has been identified as an approach for improving the performance of the process and product. A lean manufacturing system is part of corporate culture, like tools and approaches. High setup time can be classified as waste for the company. Reduction in time is a direct way to increase the productivity and profit. Therefore, there is a need to reduce the time by using some new lean methodology. In global industry, different techniques are used for reduction of time.

The importance of entrepreneurship as a force for economic progress and poverty alleviation has grown in recent years. Innovation is at the core of entrepreneurship, whereas entrepreneurship is a tool for innovation. Forbye, social innovation has become a new way of thinking and strategy for solving social problems. Additionally, to study the ever-growing and dynamic space of entrepreneurship followed by an analysis of the actors in the ecosystem, including an emphasis on its outcome and social impact on poverty. Drawing on the insights from the framework of the Theory of Change, the authors present the case of PYXERA Global. Using a qualitative research strategy to create insights from the organisation's activities in over 100 countries, we exhibit the entrepreneurial ecosystem approach followed and implemented by them. Through meticulous interviews, the chapter produces in-depth insights from the strategists and entrepreneurs of the organisation that create a balanced and focused social impact. The study reveals the importance of entrepreneurial training, education, technical skills and gender balance in poverty alleviation. Through collaborations with the private, public and social sectors, the organisation ensures to the creation of an ecosystem that provides technical support and access to skills to develop an entrepreneurial mindset. The Theory of Change undertaken by PYXERA informs how tri-sector partnerships and deep organisational involvement can aid towards sustainable development and poverty alleviation. The findings contribute to the development of an attitude that poverty reduction and community development can be achieved through co-creation, which is possible through entrepreneurship and innovation.

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.