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In the scope of the immense growth of corporate frauds and scandals, reporting unethical practices could be considered as an important mechanism to control them and ultimately improve organizational quality. To this end, this study proposes the conceptual framework comprising the enablers impacting employees' tendencies and behaviors to reporting misdemeanor in the workplace.

Systematic review of literature has been carried out. To understand the complexities among various enablers and to analyze their driving power and contingencies, a modified total interpretive structural modeling (TISM) approach has been adopted.

The findings indicate that enablers such as moral identity (MI) and job satisfaction (JS) having higher driving power (come at the bottom of the hierarchy) are relatively more important. Furthermore, perceived personal cost (PC), moral courage (MC), self-efficacy (SE) and anger have high dependent power of factors. Finally, the paper provides two paths that can lead to whistleblower's ethical decision.

A conceptual framework delivered in this paper requires to test against the field data. However, the conceptual understanding of driving enablers paves the way to top management in recruiting and hiring people in the workplace.

This study represents the first attempt to apply TISM for whistleblowing phenomenon. It provides a comprehensive conceptual framework in order to address the relative importance of various individual enablers in developing reporting tendencies against misdemeanors.

This study aims to focus on justice perceptions as the operating mechanism for leadership to impact whistle-blowing intention (WBI). Consequently, it aimed to test the mediating role of justice perception through which ethical leadership (EL) and servant leadership (SL) lead to WBI.

Data were gathered from 136 employees of IT companies in India through a questionnaire survey to test the proposed relationships.

The analysis showed that both EL and SL predict employees’ WBI via justice as the mediating mechanism.

Formal and informal mechanisms by leaders should focus on ensuring that justice is not only done but also perceived by their subordinates in such a way that just being an ethical or servant leader by itself might not result in pro-social behavior like whistle-blowing.

Many studies have shown the effect of SL and EL on outcomes like whistle-blowing; however, this study comprises that justice perception might play a critical mediating role through which both leadership styles impact normative/prosocial behavior like whistleblowing. Understanding the role of leadership and justice perception can offer valuable insights into one’s WBI and tendencies, thus increasing the amount of variance in the WBI that researchers can explain.

Systemic risk has been a cause of concern for the bank regulatory authorities worldwide since the global financial crisis. This study aims to identify systemically important banks (SIBs) in India by using SRISK to measure the expected capital shortfall of banks in a systemic event. The sample size comprises a balanced data set of 31 listed Indian commercial banks from 2006 to 2019.

In this study, the authors have used SRISK to identify banks that have a maximum contribution to the systemic risk of the Indian banking sector. Leverage, size and long-run marginal expected shortfall (LRMES) are used to compute SRISK. Forward-looking LRMES is computed using the GJR-GARCH-dynamic conditional correlation methodology for early prediction of a bank’s contribution to systemic risk.

This study finds that public sector banks are more vulnerable to macroeconomic shocks owing to their capital inadequacy vis-à-vis the private sector banks. This study also emphasizes that size should not be used as a standalone factor to assess the systemic importance of a bank.

Systemic risk has attracted a lot of research interest; however, it is largely limited to the developed nations. This paper fills an important research gap in banking literature about the identification of SIBs in an emerging economy, India. As SRISK uses both balance sheet and market-based information, it can be used to complement the existing methodology used by the Reserve Bank of India to identify SIBs.

The purpose of study to this article is to analyze the Rayleigh wave propagation in an isotropic dry sandy thermoelastic half-space. Various wave characteristics, i.e wave velocity, penetration depth and temperature have been derived and represented graphically. The generalized secular equation and classical dispersion equation of Rayleigh wave is obtained in a compact form.

The present article deals with the propagation of Rayleigh surface wave in a homogeneous, dry sandy thermoelastic half-space. The dispersion equation for the proposed model is derived in closed form and computed analytically. The velocity of Rayleigh surface wave is discussed through graphs. Phase velocity and penetration depth of generated quasi P, quasi SH wave, and thermal mode wave is computed mathematically and analyzed graphically. To illustrate the analytical developments, some particular cases are deliberated, which agrees with the classical equation of Rayleigh waves.

The dispersion equation of Rayleigh waves in the presence of thermal conductivity for a dry sandy thermoelastic medium has been derived. The dry sandiness parameter plays an effective role in thermoelastic media, especially with respect to the reference temperature for η = 0.6,0.8,1. The significant difference in η changes a lot in thermal parameters that are obvious from graphs. The penetration depth and phase velocity for generated quasi-wave is deduced due to the propagation of Rayleigh wave. The generalized secular equation and classical dispersion equation of Rayleigh wave is obtained in a compact form.

Rayleigh surface wave propagation in dry sandy thermoelastic medium has not been attempted so far. In the present investigation, the propagation of Rayleigh waves in dry sandy thermoelastic half-space has been considered. This study will find its applications in the design of surface acoustic wave devices, earthquake engineering structural mechanics and damages in the characterization of materials.

This paper aims to investigate the impact of corporate governance mechanisms and the environmental, social and governance (ESG) disclosure score on bank performance and financial stability. Further, this paper analyses how this relationship varies over the different ownership structures.

The paper uses a sample of 41 Indian banks (including both public sector and private sector banks) over the period ranging from 2008 to 2020. The data is analyzed in both static and dynamic frameworks using panel regression and system generalized methods of moments.

The results indicate that the frequency of board meetings has a negative influence on the performance of the banks. Gender diversity reveals both linear and non-linear relationships with bank performance. In the sample of public sector banks, the board size and promoters’ ownership have a significant negative effect on the bank's performance. In private sector banks, CEO duality adversely affects performance. Further, the results indicate that ESG disclosure score is positively linked with the profitability of banks.

This paper provides a comprehensive analysis of the impact of corporate governance mechanisms and ESG disclosure scores on bank performance and stability in the context of the Indian economy. To the best of the authors’ knowledge, there has been no empirical investigation or study that has been conducted in this respect.

This paper explores a new type of housing in India and resulting urban dynamics in Nagpur, a Grade A city in the Indian state of Maharashtra. The accelerating urban growth rate led to a dynamic housing market to accommodate the on-going migration. A new housing typology can be identified as clusters of residential towers, developed as gated communities and marketed as first-class neighbourhoods for emerging higher income groups. This research is a timely effort to address the occurring challenges of future urban patterns produced by this housing typology in India. Various urban qualities are needed to foster sustainable urbanism. Housing patterns have a major impact on how urban environments work efficiently, how they accommodate different user groups and how city images, perceptions and thus lifestyles are affected. The paper investigates these new urban sites in relation to their socio-spatial interactions and the resulting production of urban qualities to foster a new understanding of this particular housing typology and its impact on urbanism in India. Analysing through the lens of three major urban qualities of urban efficiency, diversity and identity the study identifies the complex socio-spatial dynamics fostered by vertical gated communities in Nagpur city. The paper concludes with an outlook on the distinctive roles of architects and urban designers to develop synergies between this urban typology and its surroundings

This study aims to investigate the effects of peers on corporate payout policies in one of the largest emerging markets – India. It also examines the motives for mimicking payout decisions.

The sample is composed of 3,024 non-financial and non-government firms listed on the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) for the period 1995 to 2020. To encounter the endogeneity problem, the instrumental variable technique based on peer firms' idiosyncratic risk is used to estimate the effects of peers on firms' payout policy. To define peer reference groups, the authors use the basic industry classification of the firms.

The results indicate a significant positive impact of peers on firms' dividend policies in India. A firm with all dividend-paying peers is more likely to declare dividends than the one with no dividend-paying peers. Further, peer effects are found to be more pronounced amongst larger and older firms, thus supporting the rivalry theory of mimicking.

To the best of the authors' knowledge, the present study is the first of its kind that attempts to understand peer effects on payout decisions in an emerging market India, that offers a unique institutional setting. Moreover, the authors extend the existing literature by investigating the peer effects on a firm's payout policies considering various firm-level characteristics, such as growth opportunity, cash holding, financial constraint and profitability, which previous studies have not taken into consideration. These results provide additional insights into the heterogeneity and motives behind peer effects.

The purpose of this study is to investigate the dynamics of capital structure for businesses in China and India. Whether and how they adjust their capital structures to witness the trade-off behaviour in the light of different macro-level factors.

Firms listed on the National Stock Exchange and Shanghai Stock Exchange over the period of 2009-2018 are used for the study. System generalized method of moments proposed by Blundell and Bond (1998) is deployed due to the use of dynamic short panel data.

Indian firms revert to their target leverage ratios at a higher rate as compared to Chinese firms (30 and 20 per cent, respectively). Further, the inflation rate, bond market and stock market development are significant factors impacting leverage in the case of India, whereas bond market development significantly impacts leverage in the case of China. These results are robust across various definitions of leverage and other firm and institutional control variables.

This study has implications for various stakeholders. The study highlights that development in financial markets and economy impact the financing decisions and should be a cause for concern for the financial managers and policymakers. Thus, managers can use the findings of the study if they desire to maintain their target capital structures for better firm valuation and the policymakers can support them in achieving the same. Even, the investors can make informed investment decisions considering macro-level factors impacting firms’ financing choices.

It is believed to be the first piece of research effort to consider the novel paradigm of the macro-level factors impacting the target leverage to estimate the adjustment speed. Secondly, it is a pioneering study, which attempts to compare the trade-off behaviour of the top two emerging economies of the world.

In today's fast developing era, the volume of data is increasing day by day. The traditional methods are lagging for efficiently managing the huge amount of data. The adoption of machine learning techniques helps in efficient management of data and draws relevant patterns from that data. The main aim of this research paper is to provide brief information about the proposed adoption of machine learning techniques in different sectors of manufacturing supply chain.

This research paper has done rigorous systematic literature review of adoption of machine learning techniques in manufacturing supply chain from year 2015 to 2023. Out of 511 papers, 74 papers are shortlisted for detailed analysis.

The papers are subcategorised into 8 sections which helps in scrutinizing the work done in manufacturing supply chain. This paper helps in finding out the contribution of application of machine learning techniques in manufacturing field mostly in automotive sector.

The research is limited to papers published from year 2015 to year 2023. The limitation of the current research that book chapters, unpublished work, white papers and conference papers are not considered for study. Only English language articles and review papers are studied in brief. This study helps in adoption of machine learning techniques in manufacturing supply chain.

This study is one of the few studies which investigate machine learning techniques in manufacturing sector and supply chain through systematic literature survey.

1. A comprehensive understanding of Machine Learning techniques is presented.

2. The state of art of adoption of Machine Learning techniques are investigated.

3. The methodology of (SLR) is proposed.

4. An innovative study of Machine Learning techniques in manufacturing supply chain.

A comprehensive understanding of Machine Learning techniques is presented.

The state of art of adoption of Machine Learning techniques are investigated.

The methodology of (SLR) is proposed.

An innovative study of Machine Learning techniques in manufacturing supply chain.

The global economy has witnessed an exponential increase in cross-border acquisitions (CBAs) by emerging market companies (EMCs), demanding a relook at their internationalization strategy. The purpose of the study is to investigate whether the announcement of CBAs by EMCs creates value for the equity-holders of acquiring firms and identify factors affecting the valuation of acquiring companies.

The paper investigates the announcement impact of CBAs of CNX Nifty 500 Indian and SSE 380 Chinese companies. The event study analysis of 553 Indian and 125 Chinese acquisitions supports the contention that CBAs are indeed a strategic choice of EMCs for value creation.

CBAs generate positive and statistically significant abnormal returns for shareholders of both Indian and Chinese acquirers. The markets, however, differ in terms of their motivations; country-level factors have been observed to exert significant influence on the returns of Indian acquirers. Indian companies experience larger value creation on acquiring firms established in developed, institutionally closer and/or economically distant markets. The findings support the asset-seeking motive of Indian companies.

The research work contributes to the evolving stream of CBAs literature with a focus on the globalization strategies of EMCs. The present study is a modest attempt to lay the foundation for a new theoretical framework (asset-seeking perspective) of overseas acquisitions from emerging economies. The existing studies on emerging economies have emphasized, in isolation, either Indian CBAs or international acquisitions by Chinese firms. Being so, the study is unique and original in the sense that it is a comparative study of India and China.