Search results

In this paper, the authors examine the relation between cross-listing and the noncompliance with the mandatory corporate social responsibility (CSR) expenditure regulation in India, the first country to legally mandate the CSR expenditure.

The authors apply panel logit and ordinary least square (OLS) regression models to examine the impact of cross-listing on the noncompliance with the mandatory CSR expenditure regulation because panel regression has lesser multicollinearity problems and has the benefit of controlling for individual or time heterogeneity mostly present in cross-section or time series data.

Using a sample of 1,027 listed Indian firms, the authors show that the cross-listed firms are more likely to comply with the mandatory CSR expenditure than non-cross-listed firms. The authors further show that this relation holds only for those firms which are exposed to higher agency problems, for firms affiliated to business groups and for firms operating in high litigation risk industries. Finally, the authors show that cross-listed firms complying with the mandatory CSR expenditure command more valuation premiums.

This study’s results suggest that the noncompliance of the Indian firms with the mandatory CSR expenditure regulation comes down once they cross-list their shares in the US or the UK since such firms have to bond to the stronger corporate governance standards of the listed country. Hence, the authors recommend that merely making the investment in CSR activities mandatory may not serve the purpose and the convergence in corporate governance as well as compliance with the CSR expenditure can be achieved through cross-listing in US and UK markets.

One, the authors analyze the effect of cross-listing on the likelihood and magnitude of noncompliance with the CSR mandate. Two, this study is based in India where CSR expenditure has been made mandatory under the Companies Act, 2013. Using CSR mandate as a natural experiment, the authors have access to a richer data set on CSR in terms of the actual expenditure made by the company on CSR activities and the mandatory amount to be spent in a particular year.

This study sought to determine the role of green human resource management (GHRM) in fostering employees' environmental performance (ENVP). This study aims to advance knowledge related to the role of firms’ GHRM activities in cultivating eco-responsible behaviors among employees, considering green innovation (GI) as a mediator.

For this study, data of 579 respondents were collected from employees working in the manufacturing industry in India. In all, 579 employees from the manufacturing sector in India participated in the study. The proposed model was tested using SMART PLS 3.3.

The findings of this study stated that GHRM was found significantly to predict ENVP in the Indian manufacturing industry, and GI exhibited partial mediation. This study emphasizes that GHRM activities carried out by firms encourage employees to engage in innovation to develop green products and find novel green operation processes to improve firms’ ENVP.

As this study is limited to manufacturing organizations in India, the results of this study cannot be generalized; future studies may examine the proposed model in different contexts to generalize findings.

This study encourages policymakers to devise laws to enable organizations to implement GHRM practices. This study contributes to the existing literature on the environmental aspects of corporate social responsibility and environmental management. This study is one of the few attempts that seek to assess the relationship between GHRM, ENVP and GI in the Indian manufacturing industry. The contribution of this paper is significant to limit GHRM literature, as it empirically investigates the association between GHRM and ENVP.

Although existing literature abounds with actual diversity research, there is scant work on perceived diversity. This research aims to investigate the impact of employees' perception of workplace diversity on job satisfaction and turnover intentions. Further, the research analyses the gender-moderating effect between the hypothesized connection.

Current research work uses a structural equation modeling (SEM) approach to analyze the hypothesized connection with 222 full-time employees working in the Indian service sector.

Study results showed that employees' perception of workplace diversity has a significant negative impact on job satisfaction, while having a significant positive effect on employees' turnover intentions. Moreover, employees' perception of workplace diversity does not vary across gender.

Though research work on perceived diversity is scant and growing at a slow pace, the current study adds to the diversity studies by assessing diversity through employees' perceptions instead of gleaning the actual diversity index.

There is an urgent need to develop climate-smart agrosystems capable of mitigating climate change and adapting to its effects. Conventional agricultural practices prevail in Mauritius, whereby synthetic chemical fertilizers, pesticides and insecticides are used. It should be noted that Mauritius remains a net-food importing developing country of staple food such as cereals and products, roots and tubers, pulses, oil crops, vegetables, fruits and meat (FAO, 2011). In Mauritius, the agricultural sector faces extreme weather conditions like drought or heavy rainfall. Moreover, to increase the crop yields, farmers tend to use 2.5 times the prescribed amount of fertilizers in their fields. These excess fertilizers are washed away during heavy rainfall and contaminate lakes and river waters. By using smart irrigation and fertilization system, a better management of soil water reserves for improved agricultural production can be implemented. Soil Nitrogen, Phosphorus and Potassium (NPK) content, humidity, pH, conductivity and moisture data can be monitored through the cloud platform. The data will be processed at the level of the cloud and an appropriate mix of NPK and irrigation will be used to optimise the growth of the crops. Machine learning algorithms will be used for the control of the land drainage, fertilization and irrigation systems and real time data will be available through a mobile application for the whole system. This will contribute towards the Sustainable Development Goals (SDGs): 2 (Zero Hunger), 11 (Sustainable cities and communities), 12 (Responsible consumption and production) and 15 (Life on Land). With this project, the yield of crops will be boosted, thus reducing the hunger rate (SDG 2). On top of that, this will encourage farmers to collect the waters and reduce fertilizer consumption thereafter sustaining the quality of the soil on which they are cultivating the crops, thereby increasing their yields (SDG 15).

This study aims to focus on understanding the work–family conflict of Indian women engineers through the lens of identity conflict.

Semi-structured interviews conducted with 20 Indian women engineers working in India and abroad of varying ages and work experience helped in understanding the types, sources and coping decisions about work–family conflicts experienced by them. Thematic analysis was conducted to analyse the qualitative data.

The findings reveal that as women engineers negotiate their “engineering” and “woman” identities, work–family conflict manifests as a battle of time and responsibilities, psychological strain and behaviour-based conflict. Furthermore, self-expectations and negative social sanctions play an important role in augmenting the experiences of these conflicts. The results also reveal how women re-strategize their career decisions to conciliate their conflicting identities.

This study furthers the literature on resolving work–family conflict by taking an identity perspective. Recommendations in literature such as work flexibility and part-time work, place the onus on women to increase their capacities to perform different roles better. Examining work–family conflict from an identity perspective allows us to look at the psychological processes underlying the challenges women face in balancing work and home in a male-dominated profession. These give insights into the need to go beyond accommodations in the workplace to redefine gender roles and relations for equal participation of women in the modern workforce.

This study aims to investigate the feasibility of employing a multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation. The formulated objectives are the minimisation of the total allocation cost of the anti-fraud capacities and the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots.

From the literature survey conducted and primary qualitative data gathered from the 17 licenced banks in South Africa on fraud investigators, the suggested fraud investigators are the organisation’s finance department, the internal audit committee, the external risk manager, accountants and forensic accountants. These five human resource capacities were considered for the formulation of the multi-objectives integer programming (MOIP) model. The MOIP model is employed for the optimisation of the employed capacities for cyberfraud mitigation to ensure the effective allocation and utilisation of human resources. Thus, the MOIP model is validated by a genetic algorithm (GA) solver to obtain the Pareto-optimum solution without the violation of the identified constraints.

The formulated objective functions are optimised simultaneously. The Pareto front for the two objectives of the MOIP model comprises the set of optimal solutions, which are not dominated by any other feasible solution. These are the feasible choices, which indicate the suitability of the MOIP to achieve the set objectives.

The results obtained indicate the feasibility of simultaneously achieving the minimisation of the total allocation cost of the anti-fraud capacities, or the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots – or the trade-off between them, if they cannot be reached simultaneously. This study recommends the use of an iterative MOIP framework for decision-makers which may aid decision-making with respect to the allocation and utilisation of human resources.

The originality of this work lies in the development of multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation.

On the basis of the approach-avoidance motivation theory, this study aims to examine the role of information confusion in influencing consumer switching intention among social commerce platforms, with the mediating effect of emotional exhaustion and the moderating role of social overload.

This study applied a multi-method quantitative approach including a survey and two experiments. Data were obtained from consumers on popular social commerce platforms in China. The survey's sample size was 327 respondents, whereas a total of 1,621 consumers participated in the two experiments.

Findings from the survey reveal that information confusion affects switching intention directly and indirectly via emotional exhaustion. Moreover, social overload moderates the emotional exhaustion–switching intention relationship and the indirect impact of information confusion on switching intention. Results of the two experiments further confirm the relationships found in the survey.

This study develops and validates a mediation and moderation model which expectedly serves as a framework to better explain consumer switching intention on social commerce platforms. The study also offers fresh insights into consumer switching intention in the unique context of social commerce in an emerging market (i.e. China), which has been largely ignored in the prior literature.