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This study uses a meta-analysis approach to analyse the impact of applying corporate green accounting practices as vital sustainable development tools on firm performance. This study aims to examine the moderating effects of country-specific variables and characteristics on the association between corporate green accounting and firm performance.

Three databases were used for a meta-analysis of 68 independent studies involving 19,625 subjects conducted over 25 years from 1996 to 2020.

The results show that corporate green accounting positively affects firm performance, but country-specific variables do not moderate this association. The positive association between corporate green accounting and firm performance was enhanced when it was measured in terms of environmental costs. Subgroup analyses revealed that study characteristics are significant source of heterogeneity in the corporate green accounting indicators-firm performance association.

The findings suggest that firms should strategise to integrate environmental costs into their respective financial accounting frameworks, which would help managers justify the contribution of their firms towards environmental protection.

Accessing accurate and timely information on corporate environmental functioning can assist national policymakers in framing appropriate legislation on environmental protection and sustainable development.

Although meta-analysis has been used previously in accounting research (Guthrie and Murthy, 2009; Alcouffe et al., 2019), to the best of the authors’ knowledge, this is the first study to use a meta-analytical technique to examine the impact of corporate green accounting on firm performance.

Considering the swift adoption of innovative sustainability practices in businesses to accomplish sustainable development goals (SDGs), research on corporate sustainability has increased significantly over the years. This research intends to analyze the published literature, emphasizing the existing, emerging and future research directions on achieving the SDGs through corporate sustainability.

This research analyzed the growing trends in corporate sustainability by incorporating 2,038 Scopus articles published between 1999 and 2022 using latent Dirichlet allocation (LDA) topic modeling, bibliometrics and qualitative content analysis techniques. The bibliometric data were analyzed using performance and science mapping. Thereafter, topic modeling and content analysis uncovered the topics included under the corporate sustainability umbrella.

The findings indicate that investigation into corporate sustainability has considerably increased from 2015 to date. Additionally, the majority of studies on corporate sustainability are from the United States of America, the United Kingdom and Germany. Besides, the USA has the most collaboration in terms of co-authorship. S. Schaltegger was considered the most productive author. However, P. Bansal was ranked as the top author based on a co-citation analysis of authors. Further, bibliometric data were evaluated to analyze leading publications, journals and institutions. Besides, keyword co-occurrence analysis, topic modeling and content analysis highlighted the theoretical underpinnings and new patterns and provided directions for further research.

This study demonstrates various existing and emerging themes in corporate sustainability, which have various repercussions for academicians and organizations. This research also examines the lagging themes in the current domain.

Environment, social and governance (ESG) practices and shareholder activism are making significant strides in the decision-making policies and processes for all firms. This study aims to assess the impact of ESG on the dividend payout decisions of firms in India. In addition, it also aims to determine how shareholder activism influences the impact of ESG on dividend distribution decisions.

The authors gather relevant data from 78 non-financial listed Indian firms from 2016 to 2020. This study undertakes longitudinal data analysis, with fixed effects and calculation of robust standard errors. In addition, the slope test is used to examine the effects of the interaction between ESG and shareholder activism.

It is found in the study that not only does ESG positively impact the dividends but also shareholder activism positively impacts the dividend distribution decisions. Surprisingly, the authors see a significant but negative interaction impact of shareholder activism on the positive association of ESG with dividend distribution decisions. In other words, ESG impacts dividend distribution decisions differently at levels of shareholder activism. When shareholder activism is low, ESG positively influences dividend distribution decisions. However, when shareholder activism is high, ESG negatively influences dividend distribution decisions.

This result has significant implications for all the stakeholders, including shareholders. A shareholder expecting a dividend could decide correctly through the current study’s findings. In cases of high shareholder activism, investors may skip picking a stock if investors expect high ESG to influence the dividend distribution decisions favourably. On the contrary, investors may choose a stock if shareholder activism is low and all else remains the same.

Literature has some evidence of the influence of shareholder activism and ESG (in silos) on the dividend distribution decisions in the firms. This study attempts to contribute by bringing forth the interaction effects of shareholder activism and ESG on dividend distribution decisions.

In recent years, instant messaging platforms like WhatsApp have gained substantial popularity in both academic and practical domains. However, despite this growth, there is a lack of a comprehensive overview of the literature in this field. The primary purpose of this study is to bridge this gap by analyzing a substantial dataset of 12,947 articles retrieved from the Dimensions.ai, database spanning from 2011 to March 2023.

To achieve the authors' objective, the authors employ bibliometric analysis techniques. The authors delve into various bibliometric networks, including citation networks, co-citation networks, collaboration networks, keywords and bibliographic couplings. These methods allow for the uncovering of the social and conceptual structures within the academic discourse surrounding WhatsApp.

The authors' analysis reveals several significant findings. Firstly, the authors observe a remarkable and continuous growth in the number of academic studies dedicated to WhatsApp over time. Notably, two prevalent themes emerge: the impact of coronavirus disease 2019 (COVID-19) and the role of WhatsApp in the realm of social media. Furthermore, the authors' study highlights diverse applications of WhatsApp, including its utilization in education and learning, as a communication tool, in medical education, cyberpsychology, security, psychology and behavioral learning.

This paper contributes to the field by offering a comprehensive overview of the scholarly research landscape related to WhatsApp. The findings not only illuminate the burgeoning interest in WhatsApp among researchers but also provide insights into the diverse domains where WhatsApp is making an impact. The analysis of bibliometric networks offers a unique perspective on the social and conceptual structures within this field, shedding light on emerging trends and influential research. This study thus serves as a valuable resource for scholars, practitioners and policymakers seeking to navigate the evolving landscape of WhatsApp research. The study will also be useful for researchers interested in conducting bibliometric analysis using Dimensions.ai, a free database.

This study investigates how human resource training and development (HRTD) shapes workplace spirituality in higher education. It delves into key factors impacting spirituality among academics, such as colleague support and e-learning initiatives. Through analytical tools like percentage analysis and Garret ranking, it divides workplace spirituality in academia, exploring the HR strategies that induce it.

(a) Type of research – Descriptive research (b) Area of research – The present study is taken up by the academicians as a respondent in selected colleges in Salem district. (c) Sampling technique – Simple random method was adopted. (d) Sources of data collection – The study comprises mixed data method that both types of data were adopted. (i) Primary data – Researcher conducted data by selecting a representative sample of the teaching faculties from various institutions employed in higher education in Salem. (ii) Secondary data – It is mostly gathered through content found on websites. (e) Method of data collection – Structured questionnaires were employed in this research to acquire the data needed for the investigation. Every item it is rated through five-point scale of with 1 denoting “Strongly Agree” to “Strongly Disagree,” this includes questions about the job, coworkers, seniors and training. (f) Research tools used – Descriptive statistics, Friedman test and Garret ranking.

Findings highlight the significance of encouraging colleagues, workplace development and online learning in fostering workplace spirituality. Faculty encouragement emerges as the most impactful HR practice, while development initiatives improve the reputation of training for new aspects. Notably, online training significantly affects workplace spirituality, increasing the influence of cultural training.

Implications for future research arise, suggesting potential models for studying workplace spirituality in academia and sparking curiosity about the connection between HR practices and spirituality.

From a practical viewpoint, the study offers actionable insights for authorities to improve workplace spirituality by supporting colleagues and emphasizing growth strategies. It outlines clear steps for organizations to create more spiritually enriching work environments.

Socially, the study advocates for healthier work cultures that impact society's perspective on work–life balance and employee well-being. It promotes positive work environments that benefit both individuals and society.

This paper's originality lies in its focus on how HRTD contributes to workplace spirituality in higher education. It emphasizes supporting colleagues, fostering growth and utilizing e-learning, offering unique insights into spirituality at work. The methodology, using structured questionnaires and statistical analysis among faculty, provides a distinct approach to studying this area.

The new customer churn prediction (CCP) utilizing deep learning is developed in this work. Initially, the data are collected from the WSDM-KKBox’s churn prediction challenge dataset. Here, the time-varying data and the static data are aggregated, and then the statistic features and deep features with the aid of statistical measures and “Visual Geometry Group 16 (VGG16)”, accordingly, and the features are considered as feature 1 and feature 2. Further, both features are forwarded to the weighted feature fusion phase, where the modified exploration of driving training-based optimization (ME-DTBO) is used for attaining the fused features. It is then given to the optimized and ensemble-based dilated deep learning (OEDDL) model, which is “Temporal Context Networks (DTCN), Recurrent Neural Networks (RNN), and Long-Short Term Memory (LSTM)”, where the optimization is performed with the aid of ME-DTBO model. Finally, the predicted outcomes are attained and assimilated over other classical models.

The features are forwarded to the weighted feature fusion phase, where the ME-DTBO is used for attaining the fused features. It is then given to the OEDDL model, which is “DTCN, RNN, and LSTM”, where the optimization is performed with the aid of the ME-DTBO model.

The accuracy of the implemented CCP system was raised by 54.5% of RNN, 56.3% of deep neural network (DNN), 58.1% of LSTM and 60% of RNN + DTCN + LSTM correspondingly when the learning percentage is 55.

The proposed CCP framework using the proposed ME-DTBO and OEDDL is accurate and enhances the prediction performance.

The current research study aims to examine the application feasibility and impact of artificial intelligence (AI) among higher educational institutions (HEIs) in talent acquisitions (TA).

A systematic sampling method was adopted to collect the responses from the 385 staff working across the various levels of management in HEIs in metropolitan cities in India. JAMOVI & SmartPLS 4 were applied to validate the hypothesis by performing the simple percentage analysis and structural equation modelling. The demographic and construct variables considered were adoption, actual usage, perceived usefulness, perceived ease of use and talent management.

The key indicators of perceived usefulness are productivity, perceived ease of use, adaptability, candidate experience with the adoption of AI, frequency in decision-making in its actual usage and career path of development in the HEIs. These are the most influential items impacting the application of AI in TA.

AI has the potential to revolutionize TA in HEIs in the form of enhanced efficiency, improved candidate experience, more objective hiring decisions, talent analytics and risk automation. However, they facilitate resume screening, candidate sourcing, applicant tracking, interviewing and predictive analytics for attrition.

This study attempts to encapsulate the idea of influencer marketing in the food sector and the vital role played by food influencers in shaping the dietary preferences, tastes and decisions of their social media followers and turning them into brand advocates.

An online survey of 383 social media users, utilizing a self-administered questionnaire, was undertaken to validate the proposed research design. The partial least squares structural equation modeling (PLS-SEM) methodology was used to analyze the data and test the relationships between the constructs.

The results confirm the validity and reliability of the research model. The research revealed the positive influence of influencer–follower demographics and attitude congruence on followers’ food choices, which in turn leads to followers’ delight and significantly impacts their brand advocacy. It also depicts how followers’ perceived trust in an influencer mediates the relationship between their similarity with the influencers, their food choices and brand advocacy.

The study proposes a new theoretical framework and empirically tests the effectiveness of influencer marketing in influencing social media users’ food choice behavior and brand advocacy through the medium of followers’ congruence with social media influencers. The findings offer noteworthy theoretical and managerial implications for academicians as well as marketing practitioners.

This study aims to investigate the connection between digital literacy and women’s empowerment in the rural Himachal Pradesh. It explores how improved digital skills contribute to increased empowerment among women with a specific focus on the role of education in enhancing digital literacy.

This study included 250 rural participants who completed structured questionnaires. Analytical tools, including independent-sample t-tests and partial least squares structural equation modeling, were applied to the data to gain insights into the relationship between digital literacy and women’s empowerment.

This study revealed a significant positive link between digital literacy and women’s empowerment in the rural Himachal Pradesh context. Education has emerged as a key factor that influences women’s digital skills and empowerment levels.

This research adds novelty by examining the digital literacy–women’s empowerment nexus in rural Himachal Pradesh and emphasizing the impact of education. The combination of statistical methods offers a robust approach to understanding this relationship and underscores the importance of digital inclusion and education for gender equality and women’s progress.

Regular monitoring of bacteria, especially Escherichia coli, in wastewater is crucial to ensure the maintenance of public health. Amperometric detection proves to be a fast, sensitive and economically viable solution for E. coli enumeration. This paper reported a prototype amperometric sensor based on PANI-ZnO-NiO nanocomposite thin films prepared by sol–gel method and irradiated with gamma ray. The purpose of this study is to investigate the sensor performance of PANI-ZnO-NiO nanocomposite thin films to detect E. coli in water.

The films were varied with different compositions of ZnO and NiO by using the formula PANI-(ZnO)_1-x-(NiO)_x, with x = 0.2, 0.4, 0.6 and 0.8. PANI-ZnO-NiO nanocomposite thin films were characterized by using X-ray diffraction (XRD) and atomic force microscopy (AFM) to study the crystallinity and surface morphology of the films. The sensor performance was conducted using the current–voltage (I-V) measurement by testing the films in clean water and E. coli solution.

XRD diffractograms show the peaks of ZnO (1 0 0) and NiO (1 0 2). AFM analysis shows the surface roughness, and the grain size of PANI-ZnO-NiO thin films decreases when the concentration ratios of NiO increased. I-V curves show the difference in current flow, where the current in E. coli solution is higher than the clean water.

PANI-(ZnO)_1-x-(NiO)_x nanocomposite thin film with the highest concentration of ZnO performed the highest sensitivity among the other concentrations, which can be used to indicate the presence of E. coli bacteria in water.