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The present study's goal is to analyze the impact of audit quality (AQ) on earnings quality (EQ) using different audit attributes. The study shows empirical evidence from India, considered an emerging market.

The sample selected represents the 376 non-financial firms listed on the Bombay Stock Exchange (BSE). With a 20-year time frame, the authors used the absolute value of discretionary accruals (McNichols, 2002) (DA) as a proxy for EM, which is inversely related to EQ. The authors analyzed data using OLS, fixed effect (FE), 2SLS and Panel-IV estimators.

The authors found that most audit attributes positively affect EQ. In the Indian context, joint auditor (JA), auditor size (A_SIZE), auditor fee (A_FEE) and auditor tenure (A_TENURE) have a negative association with EM indicating high EQ. In contrast, auditor rotation (A_ROTATON) positively affects EM confirming low EQ.

The present study uses Big-4 and its member firms as a proxy of auditor size (A_SIZE); instead, other bases may be taken for it, like the dominant audit firms in a particular industry in sample data, etc. The authors have started audit tenure from the base year, i.e. 2001, which may ignore the association of auditor and auditee just before 2001.

The study findings would enhance policymakers' willingness to prepare appropriate regulations regarding JAs and auditor rotation, which might improve financial market efficiency and reduce financial fraud among Indian corporates.

To the best of the authors' knowledge, this is the first study to incorporate “Joint Auditor” (JA) as a proxy for audit quality in the Indian context, which might significantly contribute to the literature.

Stock return volatility is an important aspect of financial markets which requires specific attention of researchers. This study examines the impact of board structure, board activities and institutional investors on the stock return volatility of the Indian firms.

The author had selected the non-financial companies of the National Stock Exchange (NSE), which form the part of the NSE 500 index. Regression models had been estimated using the system generalised method of moment (GMM) framework designed by Arellano and Bover (1995) and Blundell and Bond (1998) to deal with endogeneity concerns.

The author found that the stock return volatility was affected by the institutional investors, particularly pressure-insensitive (PI) investors. Moreover, this study supported the non-linear relationship between stock return volatility and institutional investors. Unlike developed world, the author found that the independent directors were positively associated with the stock return volatility.

It is important for the investors and regulators to understand that the behaviour of the institutional investors depends on its class and having more independent directors will not ensure containment of the stock return volatility as suggested in previous literature reviews.

Most of the prior studies have used simple standard deviation (SD) to compute stock return volatility. In this study, besides SD, the author used the generalised autoregressive conditional heteroskedasticity (GARCH) model to compute the stock return volatility of the firms.

The author examines the role of board structure and institutional investors in dealing with the agency issues for the Indian firms by taking the data of NSE-500 nonfinancial firms for the period 2010–2019.

The author applies dynamic panel data methodology to deal with endogeneity concerns prevalent in corporate finance variables.

The agency view is consistent with the board size in the context of India. The author observed that the board size has a harmful effect on agency cost. A larger board size may create a coordination problem, or CEO may find it easy to thrust his or her decisions on board. The author also noticed that firms should have sizeable institutional ownership, particularly pressure-insensitive investors, in equity as they can reduce agency-related issues.

This study focuses on one of the largest emerging economies, i.e. India.

The purpose of this paper is to investigate the relationship between dividend policy and the life cycle of firms in India. In addition, this study intends to examine the variation in dividend behaviour over the life cycle of a firm. The study anticipates that a firm's dividend behaviour varies over its life cycle.

To scrutinize the validity of the proposition, the authors classify 1968 non-financial industrial firms listed at Bombay Stock Exchange (BSE) into growth, mature and stagnant firms over the period 2000–20. Additionally, to check the robustness of the results, they use an array of techniques such as analysis of variance, pooled ordinary least squares, fixed effects models and random effects models.

The empirical findings suggest that dividend behaviour varies over a firm's life cycle. Specifically, stagnant firms are paying significantly higher dividends than growth firms. Mature firms are paying significantly higher dividends than growth firms. The results are consistent after controlling the effects of firm's size, profitability, leverage, operating risk, systematic risk and growth opportunities.

The findings are useful for corporate decision makers in establishing an appropriate dividend policy conditional on firms' life cycle stage and for shareholders in making investment decisions.

The relation between dividend policy and firm life cycle has not been examined before in the context of Indian stock market. Thus, this research bridges this gap in the literature.

This paper aims to explore the key factors which influence whistleblowing intentions of teachers working with higher education institutions (HEIs) in India. Both internal and external whistleblowing intentions of the HEI teachers are studied by examining their relative intentions to report a potential wrongdoing to the authorities within the management of the institution and to the external statutory bodies. The reporting intentions of the HEI teachers are measured through the use of three vignettes related to academic frauds. Whistleblowing intentions are proposed to be determined by the individual, organizational and situational factors.

Survey method of descriptive research design has been used to obtain the primary data regarding the individual, organizational and situational variables deemed to influence HEI teachers’ internal and external whistleblowing intentions. A self-administered structured questionnaire is used as survey instrument for primary data collection. The respondents’ internal and external whistleblowing intentions are measured through the use of three vignettes related to academic frauds. Non-parametric tests such as Mann–Whitney U test, Kruskal–Wallis test and Spearman correlations have been used to test the research hypotheses.

The study has found that the HEI teachers are more likely to blow the whistle internally if there is a proper communication channel in their organization for reporting wrongdoings. However, they do not hesitate to blow the whistle externally in the absence of internal reporting channel, especially in those cases of wrongdoings where they perceive the cost of reporting to be high. The high status of the wrongdoer and high costs of reporting discourage the teachers to blow the whistle internally. However, if the wrongdoer holds a very powerful position in the organization, then the teachers prefer to report his wrongdoing to external agencies as they are afraid of the likely negative repercussions of reporting against him internally. In case of serious wrongdoings, the teachers intend to blow the whistle within the organization rather than going to external agencies probably because they do not want to spoil the image of their organization in the external world.

The first limitation is that because of the unavailability of pre-tested vignettes in the context of academic frauds, the study has used three vignettes which have been developed on the basis of few case studies. Second, the results showed the existence of social desirability bias across all the three vignettes. Also, the study has been conducted among teaching professionals; therefore, the findings cannot be generalized to the professionals of other sectors.

The findings of the study may bring awareness to the board of management of HEIs, regarding the importance of whistleblowing in their educational institutions. They should encourage the teachers working with their institutions to report the wrongdoings internally as external reporting may cause damage to their institute’s reputation. Proper reporting mechanisms should be designed and shared with the employees as a part of institutional culture.

The Whistle Blowers Protection Act passed by the Parliament of India in 2011 should be amended to include the private sector employees, especially the teachers working in higher education sector. This will encourage the HEI teachers to report the academic frauds fearlessly which will put a serious check on the growing number of frauds and wrongdoings in the education sector.

Previous research studies have discussed the factors influencing whistleblowing intentions in the context of various non-academic organizations. However, existing research has not adequately provided a better understanding of the influencing factors of whistleblowing intentions in higher education sector. The present paper addresses this gap by empirically examining the key factors which influence HEI teachers’ intentions of blowing the whistle and reporting the wrongdoings occurring in their institutions, in Indian context. An attempt has been made to identify the influencing factors of both internal and external whistleblowing intentions by using three different vignettes related with academic frauds.

This study aims to examine the impact of institutional investors and their classes on the stock return volatility of an emerging market. The paper also determines the moderating role of firm size, crisis and turnover on such relationships.

The study covers nonfinancial companies of the Bombay Stock Exchange-100 index that are listed during the study period. The study uses fixed effects and systematic generalized method of moments estimators to look over the association between institutional investors and firms’ stock return volatility.

The study provides evidence that institutional investors destabilize the Indian stock market. It indicates that institutional investors do not engage in management activities; they earn short-term gains depending on information efficiency. Pressure-insensitive institutional investors have a significant positive relation with stock return volatility, while pressure-sensitive institutional investors do not. The study also reflects that pressure-sensitive institutional investors are underweighted in India, which jointly represents an insignificant nonlinear association between institutional ownership and stocks’ volatility. Furthermore, outcomes reveal that the intersection effect of the crisis, firm size and turnover is positively and significantly related to such relationships.

The outcomes encourage initiatives that keep track of institutional investors in the Indian stock market. To control the destabilizing effect of pressure-insensitive institutional investors, regulators should follow strict regulations on their trading patterns. Moreover, it guides the potential researchers that they should also take into account the impact of other classes of ownership structure or what type of ownership can help in stabilizing or destabilizing the Indian stock market.

Abundant literature studies the relationship between institutional ownership and firm performance in the Indian context. From the standpoint of making management decisions, the return and volatility of stock returns are both different aspects. However, this study examines the effect of institutional ownership and its groups on the volatility of stock return using the panel data estimator, which was previously not discussed in the literature.

This study identifies barriers faced by online e-waste collection platforms in India and proposes a novel approach to manage strategies that contribute towards making such online platforms economically, socially, and environmentally sustainable by mitigating their interacting barriers.

The approach consists of a barrier assessment process and a strategy evaluation and planning process. The barrier assessment process uses multiple criteria decision making (MCDM) based method to evaluate the interactive effects of the barriers to derive their direct and indirect impacts on sustainability. The strategy evaluation and planning process evaluates the overall contribution value of strategies for mitigating interacting barriers and then categorizes them into planning zones based on their contribution and feasibility.

The interaction among the barriers is a significant component of the overall impact of the barriers on sustainability. The most impactful barriers are the lack of dissemination of information, lack of government support, insufficient infrastructure, and awareness and attitude of consumers. Lack of government support is the most influential causal barrier. Lack of information dissemination is a significant causal barrier with the highest overall impact on sustainability. Priority strategies that must be implemented to ensure sustainability include government support, offering higher prices or discounts for giving up e-waste, and increasing information dissemination.

Different from existing approaches for evaluating sustainability strategies, the strategies in this study are identified and evaluated based on their overall contribution towards mitigating interacting barriers to sustainability. The approach is applied in the Indian context to reveal the most influential barriers to the sustainability of online e-waste collection platforms and the most effective strategies for mitigating these barriers. The outcomes of this study contribute to strategy planning for sustainable online e-waste collection platforms in India.

The purpose of this paper is to estimate the relative efficiencies of banks of the Indian domestic banking sector by employing various models of data envelopment analysis (DEA) using the panel data of the recent decade (2008–2017). The paper provides a comparative analysis of these models based on the efficiency outputs. It compares the performance of banks based on their ownership and sizes and studies the decade-long trend of productivity using Malmquist indices.

This paper estimates overall technical, pure technical and scale efficiencies of 21 public sector banks and 17 private banks. It compares the descriptive statistics of efficiency estimates found out through 18 different DEA models and compares them using two non-parametric statistical tests. It studies the difference in efficiencies based on ownership and size by applying the same statistical tests. It employs the Malmquist index method to study the technological and technical progress in the banks’ productivity over the decade of FY 2008–FY 2017.

During FY 2016–2017, only 9 out of 38 banks were overall technically efficient with the whole sample having a mean overall technical inefficiency of 5 percent with scale inefficiency contributing more than pure technical inefficiency. The comparative study ascertains that private sector and public sector banks (PSBs) possess efficiencies that are similar based on super-efficiency slack-based model – variable returns to scale and non-oriented, a model that the authors argue to be the most suitable for the real-life business banking scenarios whereas the private sector banks possess better efficiency than the PSBs. The Malmquist indices prove that private sector banks have a higher increase in productivity based on both technological progress and efficiency improvements whereas PSBs had a loss of efficiency and comparatively less improvement in technology.

This study has a limitation of choosing a single model of inputs and outputs. Improved insights can be drawn by employing more models based on different inputs and outputs. Further, relevance of each input and output can be examined using a regression-based feedback mechanism (Ouenniche and Carrales, 2018). The influence of environmental factors on the efficiencies can be studied using second-stage regression models and the relationship between efficiency scores and financial ratios can be examined.

This study is based on the panel data of the recent decade (2008–2017) and provides insights into the efficiency scenario of the Indian banking industry and how it changed over the past decade, to the leadership of banks, the banking regulators and the policy makers. The comparative analysis of DEA models based on a sample of Indian banks is first of its kind in the Indian context and helps the researchers to select an appropriate model and delve into further research on the same.

Across industries, firms want to adopt data-driven decision-making (DDDM) in various organizational functions. Although DDDM is not a new paradigm, little is known about how to effectively implement DDDM and which problem areas to focus on in these functions. This study aims to enable start-ups to use DDDM in human resources (HR) by studying five HR domains using a narrative inquiry technique and aims to guide managers and HR practitioners in start-ups to enable data-driven decisions in HR.

This study adopts the narrative inquiry technique by conducting semi-structured interviews with HR practitioners and senior members handling HR functions in start-ups. Interview memos are thematically analyzed to identify repeated ideas, concepts or elements that become apparent.

The study findings indicate that start-ups need to have canned operational reports with right attributes in each of these HR domains, which members should use when performing HR tasks. Few metrics, like cost-to-hire in recruitment, distinctly surfaced relatively higher in importance that each start-up, should compute and use in decision-making.

Managers, HR practitioners and information technology implementation teams will be able to consume the findings to effectively design or evaluate HR processes or systems that empower decision-making in a start-up.

Start-ups have a fast-paced culture where creativity, relationships and nimbleness are valued. Prevalent decision models of larger organizations are not suitable in start-ups’ environments. This study, being cognizant of these nuances, takes a fresh approach to guide start-ups adopt DDDM in HR and identify key problem areas where decision-making should be enabled through data.

The purpose of this study is to explore and prioritize the barriers that affect weather index-insurance (WII) adoption among customers by utilizing interpretive structural modelling (ISM) and fuzzy-MICMAC.

This paper utilized the combined approach in two phases. In first phase comprehensive literature study and expert mining method have been performed to identify and validate WII adoption barriers. In second phase, ISM has been utilized to examine the direct relationships among WII adoption barriers in order to develop a structural model. Further, fuzzy-MICMAC method has been utilized to analyse indirect relationships among barriers to explore dependence and driver power.

This study has identified 15 key barriers of WII adoption among customers and developed a structural model based on binary direct relationship using ISM. Later, the outcomes of ISM model have been utilized for analysing the dependence and driver power of each WII adoption barriers in cluster form using fuzzy-MICMAC. The customer awareness related WII adoption barrier are mainly at the top level, WII demand related barriers are in the centre and WII supply related barriers at the bottom level in ISM model.

The findings offered important insights for WII insurers to understand mutual relationships amongst WII adoption barriers and assists in developing strategy to eliminate dominant key barriers in order to enhance their customer base.

Based on best of author's knowledge this paper firstly integrates the ISM fuzzy-MICMAC method into identification and prioritization of barriers that affects WII adoption among customers.