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The purpose of this paper is to investigate the impact of mandatory corporate social responsibility (CSR) expenditure on the firm’s financial performance in the aftermath of insertion of Section 135 in the Companies Act, 2013 for Indian listed companies.

The paper uses independent sample t-test, one-way ANOVA, fixed effect panel regression model and principal component analysis on a data set of 153 non-financial companies listed in BSE-500 companies for a period of 2015–2019.

The empirical results of the paper suggest that the mandatory CSR expenditure negatively impacts the company’s profitability.

The study has important implications for regulators and listed companies. Firstly, the mandatory CSR expenditure acts as a burden onto the on-going activities of the firms. CSR activities, therefore, should be integrated with the existing skillsets and expertise of the firms. Secondly, the government can encourage CSR activities by making the expenditure tax deductible. Moreover, the Schedule VII list of activities has a scope to become more inclusive rather than the present exhaustive list.

The paper highlights the gap in the expectation and actualisation of the CSR mandate by studying the recent data of the sample companies of the BSE-500 index. The paper adds to the CSR literature in the emerging market context.

This paper aims to introduce recently an unregulated unsupervised algorithm focused on voice activity detection by data clustering maximum margin, i.e. support vector machine. The algorithm for clustering K-mean used to solve speech behaviour detection issues was later applied, the application, therefore, did not permit the identification of voice detection. This is critical in demands for speech recognition.

Here, the authors find a voice activity detection detector based on a report provided by a K-mean algorithm that permits sliding window detection of voice and noise. However, first, it needs an initial detection pause. The machine initialized by the algorithm will work on health-care infrastructure and provides a platform for health-care professionals to detect the clear voice of patients.

Timely usage discussion on many histories of NOISEX-92 var reveals the average non-speech and the average signal-to-noise ratios hit concentrations which are higher than modern voice activity detection.

Research work is original.

Corporate governance; General management; Strategy

Post Graduate/MBA

Tata Group is a conglomerate having 29 listed companies with consolidated revenues of $103bn in FY2016. On October 24, 2016, Cyrus Mistry, chairman of the group has been replaced in an unceremonious way from this job, in a boardroom coup, without being given any opportunity to explain his case. This news arrived in the media between October 2016 and December 2016 and wide and public debates took place on the corporate governance practices of Tata Group. Mistry’s ouster was attributed to non-performance, unethical practices and non-compliance to Tata culture. This case presents the Tata Group performance before Mistry, at the ouster of Mistry, the major trouble points and the corporate governance activities that took place in this saga at Tata Group. The real losers in this battle were the investors who lost $12bn between October 2016 and December 2016. Many of Tata Group companies’ stocks plunged.

The students will learn corporate governance, know how a non-listed company control and govern listed entities, know the way performance of a chairman of a company has been evaluated and learn how ethical and cultural issues impact the performance of chairman of a listed company.

Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS: 11: Strategy

This study aims to re-examine the relationship between financial accessibility and performance of micro, small and medium enterprises (MSMEs) in developing countries using a large database.

This study uses cross-sectional firm-level data from the World Bank Enterprises Survey database collected under Wave II from 2006 to 2019. Controlled for firm level and country level factors, OLS and instrumental variable regressions have been used for analysis. Firm performance has been measured in terms of labour productivity.

The study observes a positive association between access to finance and MSME performance measured in terms of sales and value-added per worker. Along with firm characteristics (like size, age and managerial experience), country’s development level, institutional quality (i.e. corruption and regulations) and economic openness also impact MSMEs’ productivity.

Strengthening the financial system to allow the financial sector to meet the requirements of MSME finance is very important. Better access to external finance will enable MSMEs to invest in upgrading technology and expanding operations, thus improves their labour productivity. As the MSME sector is vulnerable to economic shocks, policies facilitating their access to formal credit during crises could strengthen resilience.

Credit constraint to MSMEs is a multi-stakeholder problem. It requires a coordinated approach from MSME owners, financial institutions and policymakers to address it and enhance the credit flow to the MSME sector. Timely research inputs from academia, research institutions and think tanks may help assess MSMEs promotion policies and their revision if needed.

To the best of the authors’ knowledge, this is the first study that examines the effect of access to finance on the labour productivity of MSMEs in developing countries. Given the mixed results in the recent past between access to finance and firm performance, it highlights the critical role of financial accessibility in improving their labour productivity and thus enabling MSMEs to realise their full potential in developing countries.

Introduction: Commercial banks play a vital role in the global economy, facilitating economic growth and providing essential financial services. As key intermediaries between savers and borrowers, these institutions operate in a dynamic and complex environment characterised by various risk factors that can significantly impact their profitability and overall stability. Understanding the interconnected relationships between credit risk, interest rate risk, liquidity risk, and profitability is crucial for effective risk management strategies and the development of appropriate regulatory frameworks.

Purpose: Commercial banks play a critical role in the global economy by facilitating economic growth and providing financial services. This study examines the interconnected relationships between credit risk, interest rate risk, liquidity risk, and profitability in commercial banking.

Methodology: The sample consists of licenced scheduled commercial banks on the Bombay Stock Exchange (BSE) from 2015 to 2022. Using the Smart PLS-SEM 3.0 path analysis technique, the study evaluates the combined influence of these risk factors on profitability and provides evidence-based recommendations for risk management strategies.

Findings: The findings can assist banks in enhancing their risk management practices, and regulators in developing appropriate regulatory frameworks. By understanding the key risk factors and their impact on profitability, banks and regulators can mitigate risks, enhance transparency, and promote stability within the banking sector.

Significance/value: The value of this study lies in its focus on the interconnectedness of risk factors, profitability, and the potential implications for decision-making, risk management strategies, regulatory frameworks, and the overall stability of the commercial banking sector.

The present study aims to examine whether leisure time posts shared on WhatsApp status drive to travel and tourism consumption among users.

In this study, discriminant analysis was employed to test hypotheses and identify essential factors.

The study indicated that the eight most contributing factors are expressing happiness, planning leisure time, views and comments, attractiveness, inquiring about places, preferring to post, nice way of expression and relax. These factors came from the latent variables of attitude, motivation and self-expression. Overall, the main influencing factors are internal (attitude and motivation), followed by an external factor i.e. self-expression. Additionally, the findings indicated that these significantly and positively impact travel and tourism consumption.

The discriminators identified in the study would guide tour and travel agencies and the agencies' managers on how best to adopt WhatsApp and WhatsApp's status application to influence aspiring travelers.

This study enlarges the existing literature by integrating three factors, attitude, motivation and self-expression, into a model to influence the behavioral outcomes of aspirational travelers using WhatsApp status.

The current study employs text mining and sentiment analysis to identify core banking service attributes and customer sentiment in online user-generated reviews. Additionally, the study explains customer satisfaction based on the identified predictors.

A total of 32,217 customer reviews were collected across 29 top banks on bankbazaar.com posted from 2014 to 2021. In total three conceptual models were developed and evaluated employing regression analysis.

The study revealed that all variables were found to be statistically significant and affect customer satisfaction in their respective models except the interest rate.

The study is confined to the geographical representation of its subjects' i.e. Indian customers. A cross-cultural and socioeconomic background analysis of banking customers in different countries may help to better generalize the findings.

The study makes essential theoretical and managerial contributions to the existing literature on services, particularly the banking sector.

This paper is unique in nature that focuses on banking customer satisfaction from online reviews and ratings using text mining and sentiment analysis.

The purpose of this paper is to evaluate the relationship between bankers’ perspectives and their pro-green banking behaviors (i.e. intentions). Specifically, how do bankers’ perspectives on environmental concerns, environmental normative structure and green technology affect their intentions toward G-banking activities?

A theoretical framework of the theory of bounded rational planned behavior (TBRPB) as its foundation was established. Using measurement scales to measure different aspects of environmental concern, environmental normative structure, green technology, attitudes, perceived behavioral control and subjective norms, a survey instrument was developed to examine the various associations implied by the model of TBRPB. Data were collected from the bankers of selected commercial banks in Bangladesh following the random sampling procedure. The data were analyzed using the partial least square structural equation modeling technique.

Findings indicate that all of the predictors appear to be robust in predicting the G-banking intention of the sampled bankers in Bangladesh. The results also show that attitudes, subjective norms and perceived behavioral control have significant mediating effects toward bankers’ bounded rational G-banking intention.

There are a few limitations in the study. First, the study considers environmental concerns as an antecedent of the attitude of bankers toward G-banking activities. Future studies can explore other variables related to environmental problems to study G-banking adoption and practices. Second, this study only considers the private conventional bankers as respondents to the survey to assess G-baking intention. In the future, other types of bankers, such as Islamic bankers and public banks’ bankers could be included in the survey to explore G-banking practices. Finally, this research has been done in a developing country-context.

In this study, environmental concerns of bankers appeared to be highly significant predictors to influence their attitudes toward bounded rational G-banking intention. Similarly, the social normative structure also appears to be a robust antecedent of subjective norms to influence bounded rational G-banking intention of respondent bankers. Finally, green technology or bakers’ personal and skill-related ability to control bounded rational G-banking intention also appeared to be a strongly significant predictor of green banking activities. All this evidence implies that respondent bankers in the sample responded positively to provide their positive intention toward G-banking activities based on their environmental concern.

Important social implication of the current study is G-banking practices can help reduce carbon emissions and other pollutants which would enrich overall environmental sustainability and ecological conditions.

Few studies are directed on G-banking perspective in Bangladesh. This research is one of the empirical studies which will certainly add values for the clients, institutions and policymakers in banking paradigm.