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Corporate leadership and environmental, social and governance (ESG) performance are closely intertwined, as effective corporate leadership can facilitate the achievement of strong ESG performance. Thus, the purpose of the study is to investigate the impact of corporate board leadership on the ESG performance of listed firms.

The sample has been taken from the listed firms of the Nifty 500 index spanning the period of 10 years from 2012 to 2022. Dynamic panel data estimations are applied through a fixed effect model.

The findings of this study revealed that board size, board independence and board qualification have a significant positive influence on ESG performance. It is evident that good corporate governance practices can positively influence ESG performance by fostering accountability, transparency and ethical behavior, as well as better integrating ESG considerations into their decision-making processes and ensuring that ESG issues are prioritized at the highest levels of management. Further findings also revealed that chief executive officer (CEO) duality has a significant negative relationship with ESG performance, which goes against the belief of stakeholder theory.

It has practical implications for policymakers, as they can enact new regulations pertaining to the CEO’s position in the organizations to make corporate governance responsible for improved sustainability and ESG performance.

There are very few studies analyzing the impact of corporate board structure on ESG performance related to emerging markets. Thus, this study contributes to that literature by using the methodology GMM panel data for the first time as per our knowledge

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

This study aims to examine the impact of consumer risk appetite, biases (specifically negative recency bias), and the importance of reviews in enhancing information quality. By analyzing these variables, the authors gain insights into their role in enriching the overall information spectrum available to consumers. The findings contribute to a better understanding of how risk appetite, biases and consumer reviews shape the quality of information.

The questionnaire assessed the relationship between dependent and independent variables by asking participants to rate their experiences in relevant scenarios. Variance-based structural equation modeling with the ADANCO program was used to examine the data. ADANCO software is used explicitly for variance-based structural equation modeling. To evaluate research models and test hypotheses, partial least square path modeling is used.

The efficiency of reviews and ratings is greatly influenced by consumer risk appetite. Businesses should focus on clients who are willing to take risks and balance positive and negative feedback. It is essential to comprehend how customers understand reviews. Credibility is increased by taking biases into account and encouraging unbiased criticism. Promoting thorough reviews strengthens influence. Monitoring and making use of these elements improve online reputation and commercial success.

The research has limitations due to the simplicity of the attributes taken into account and the requirement for a larger sample size. Overcoming barriers to promote consistent client feedback is essential, and tailored emails can help with assessment generation. Increased customer participation in writing evaluations can be achieved by removing obstacles and highlighting the advantages of participation.

Businesses and buyers rely on this “organically” generated content as the basis of their promotional strategy and buying decisions. Most of the research is related to consumer reviews, their behavior and the importance of social validation. However, some critical aspects related to this need further investigation.

This paper aims to explain how Web 2.0, social connectedness online, has created incredible new business options. This research’s primary goal is to help businesses use these resources more effectively and perform better.

Variance-based structural equation modeling with the ADANCO program was used to examine the data. ADANCO software is used explicitly for variance-based structural equation modeling. To evaluate research models and test hypotheses, partial least square path modeling is used.

Theories encompassing social support and related approaches to “word of mouth” online, electronic purchasing and virtual communities mediated by technological platforms are the foundational frameworks for this research piece. It then produces a statistical model that enables users to predict how social commerce (s-commerce) building blocks, including forums, communities, ratings and reviews and recommendations, assist businesses in introducing innovative strategies to win in the digital markets. The results necessarily focus on trust, an essential component of e-commerce. Reciprocally, the study reverses engineer’s trust through the constructs of this moment mentioned.

The present study describes the scope of empirical testing and validation of this framework and assists practitioners in further strengthening s-commerce strategy, an emerging and essential platform in the e-commerce industry.

Research highlights the dearth of current analysis in such conceptual domains while generating novel research insights aimed at e-commerce and digital business. From the viewpoint of potential and recurring customers who interact with online communities and product offerings, the study captures the essence of human interactions, often known as trade relationships, online.

The fiscal outlay efficiency matters when the performance-based allocation of funds is made to state governments by the central government in a federal structure of an economy like India. Also the efficiency cannon of public expenditure is a key aspect in the field of public economics. Thus, a study to evaluate the efficiency in fiscal outlay of Indian states has been conducted.

The paper offers a three divisions–based paradigm under Network Data Envelopment Analysis framework to compare the performance of fiscal entities (say Indian state governments) in converting available fiscal resources into desired short-run and long-run growth and development objectives. The network efficiency score has been taken as a measure of the quality of fiscal outlay management that is trifurcated into divisional efficiencies representing budgeting process, fiscal outlay efficiency process and fiscal outlay effectiveness process.

It has been noticed that the states are under performing in achieving short-run growth targets and so the efficiency process division has been identified a major source of fiscal under performance. Suboptimum allocation of fiscal expenditure under various heads within the fiscal resources, as explained under budgeting process, is another major cause of fiscal under performance.

The study purposes a three divisions–based paradigm that takes into account efficiency of a state in (1) planning budget, (2) achieving short-run growth targets and (3) achieving long-run development targets. These three stages are named as budgeting process efficiency, fiscal outlay efficiency and fiscal outlay effectiveness, respectively. Therefore, a new paradigm called BEE paradigm is proposed to evaluate performance of fiscal entities in terms of fiscal outlay efficiency.

In existing literature on measuring efficiency of public expenditure, the public sector outputs have been made as function of fiscal expenditure as input treating the said outlay as an exogenous variable. In present context, the fiscal expenditure has been treated endogenous to the budgeting process. A high inefficiency on account of budgeting process supports this treatment too.

COVID-19 has affected the economies adversely from all sides. The sudden halt in production has impacted both the supply and demand sides. It calls for analysis to quantify the impact of the reduction in economic activity on the economy-wide variables so that appropriate steps can be taken. This study aims to evaluate the sensitivity of various sectors of the Indian economy to this dual shock.

The eight-sector open economy general equilibrium Global Trade Analysis Project (GTAP) model has been simulated to evaluate the sector-specific effects of a fall in economic activity due to COVID-19. This model uses an economy-wide accounting framework to quantify the impact of a shock on the given equilibrium economy and report the post-simulation new equilibrium values.

The empirical results state that welfare for the Indian economy falls to the tune of 7.70% due to output shock. Because of demand–supply linkages, it also impacts the inter- and intra-industry flows, demand for factors of production and imports. There is a momentous fall in the demand for factor endowments from all sectors. Among those, the trade-hotel-transport and manufacturing sectors are in the first two positions from the top. The study recommends an immediate revival of the manufacturing and trade-hotel-transport sectors to get the Indian economy back on track.

The present study has modified the existing GTAP model accounting framework through unemployment and output closures to account for the impact of change in sectoral output due to COVID-19 on the level of employment and other macroeconomic variables.

Conflict, between individuals and groups, in organizations is a common phenomenon and can have varied implication for the employee and the organization. This paper aims to determine whether experiencing interpersonal conflict drives employees to engage in prosocial behavior (prohibitive voice) and antisocial behavior (interpersonal deviance). Using Stressor–Emotion Model, Uncertainty Management Theory and Impression Management Motives, this study examines the relationship and explores competence uncertainty as a mediator and perception of politics as a moderator.

This study uses a cross-sectional design where data collected is from 386 employees working in nine different public sector enterprises in India. Structural equation modeling using SPSS AMOS was used to analyze the hypothesized relationships.

The results show that interpersonal conflict leads to both prohibitive voice behavior and interpersonal deviance. However, the mediating role of competence uncertainty is valid only for the effect of conflict on interpersonal deviance. Also, the perception of politics strengthens the positive relationship between interpersonal conflict and competence uncertainty.

To the best of the authors’ knowledge, this is one of the first empirical studies to have validated prosocial and antisocial work behavior as outcomes of interpersonal conflict. Again, this is one of the first few studies to examine the mechanism through which interpersonal conflict impacts interpersonal deviance.

The deployment of solar photovoltaic (PV) in higher education institutions is beneficial and critical for attaining sustainable campus goals. However, various barriers hamper the adoption of the technology, and unless these challenges are identified, formulating tailor made solutions to boost deployment will be challenging. Thus, this study aimed to identify the barriers to the deployment of PV in the public university sector in South Africa.

A critical review of the literature was conducted to identify the factors that negatively impact PV deployment. By screening the barriers identified from the literature using a conceptual framework, the barriers that were considered relevant to deployment within a university context were selected. Thereafter, the selected barriers and additional barriers recommended by panellists were verified through a three-round Delphi survey. The factors were either accepted or rejected as barriers in the sector based on the factors' mean score and interquartile range values.

The study observed that 12 barriers hamper PV deployment in the public university sector. The findings indicated that the top five barriers were the lack of incentives, lack of green building targets, lack of financial resources, high initial cost, and lack of clear policy direction. However, the study found that deployment was not hindered because there was resistance to change or uncertainty of recouping investment costs. The deployment was also not hindered because there was a lack of demand from electricity end-users or a lack of suitable installation space.

Given the lack of empirical studies on the subject in the region, the present study contributes to the body of knowledge by identifying the significant barriers that impede PV deployment in the public university sector. Furthermore, insight is provided on measures that relevant stakeholders can take to motivate and support universities to deploy the technology further.

This study aims to explore the interrelationships among human-related lean practices, lean production shop floors, process quality, inventory management, operational productivity and business productivity.

This study used a cross-sectional survey approach, and quantitative data were collected from 324 Indian auto-component manufacturing firms. Confirmatory factor analysis was used, followed by structural equation modelling techniques for the conceptual model, which incorporated a complete set of 11 hypotheses.

The results confirmed that human-related lean practices trigger lean production shop floors and improve process quality. Furthermore, the study revealed the positive impact of a lean production shop floor on process quality and inventory management and the positive impact of process quality on both operational and business productivity. Finally, inventory management is of the utmost importance in achieving better operational and business productivity, and operational productivity positively leads to business productivity.

The findings of this study can benefit auto-component manufacturing firms by elucidating the complex relationships between human-related lean practices, lean production shop floors, process quality, inventory management, operational productivity and business productivity. Better knowledge of these relationships will enable firms to enhance efficiency levels, reduce costs and resource wastage and improve their overall performance. This study provides a good understanding of the interplay between lean and quality factors and their influence on inventory management and business performance.