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The study investigates the influence of managerial discretion over accruals on banks' financial reporting quality. Furthermore, it examines the role of ownership in shaping managerial incentives to manipulate banks’ reporting quality in a developing economy.

The sample includes 37 Indian public- and private-sector banks from the fiscal year 2001–2022. The discretionary LLP (DLLP) is used to examine various managerial incentives and accounting quality. The models are estimated using panel fixed-effect regression and the system generalized method of moments. The results survive several sensitivity checks.

The results exhibit a low quality of financial reporting in public-sector banks, which is evident through the higher use of DLLP for income smoothing and signaling. In contrast, the low-capitalized private-sector banks employ DLLP to manage capital.

The study’s sample size is relatively small and focuses on a single country. Future researchers can investigate other emerging economies to better generalize the findings of this study.

The study highlights the influential role of ownership in shaping managerial incentives in the banking industry. Moreover, the study is of utmost importance for governments, regulators and policymakers in devising policies that reduce agency conflicts and improve financial stability in emerging economies.

The study subscribes to the growing literature on the role of ownership in influencing the banks’ financial reporting quality. To the best of the author’s knowledge, this is one of the limited studies in the context of government-owned vs private-owned banks in an emerging economy.

This paper aims to examine the influence of sustainability reporting on bank performance. Furthermore, this study investigates the impact of the country’s economic development, financial system and crisis in moderating sustainability reporting and bank performance relationship.

The sample consists of 400 listed banks from 19 countries over the 2009–2022 period. Panel fixed-effect regression is applied, and System Generalized Method of Moments is used as robustness to address endogeneity concerns. The results are robust and survive several sensitivity tests.

The results, aligning with legitimacy and agency theories, suggest a negative relationship between sustainability reporting and bank performance. Based on further classifications, results suggest the negative (positive) impact of country’s financial system (economic development) in moderating the sustainability reporting and bank performance nexus. Finally, this study documents the positive influence of sustainability reporting on bank performance during the crisis period. Overall, the findings fail to support the reduced information asymmetry accruing from higher sustainability disclosures in developing and bank-based economies.

This study has important implications for regulators, policymakers and other stakeholders, especially in light of recent banking scandals that have deteriorated stakeholders' faith in financial institutions' reporting quality.

This study extends the scant literature on sustainability reporting in banking from a cost-benefit vantage point. Furthermore, to the best of the author’s knowledge, no previous research has examined the moderating role of the country’s financial structure and crisis in sustainability reporting and bank performance relationship.

This paper aims to examine the impact of announcements related to 77 interventions by 46 listed Indian pharmaceutical firms during COVID-19 on the abnormal returns of the firms. The study also finds the variables which explain cumulative abnormal returns (CARs).

This study uses standard event methodology to compute the abnormal returns of firms announcing pharmaceutical interventions in 2020 and 2021. Besides this, the multilayer perceptron technique is applied to identify the variables that influence the CARs of the sample firms.

The results show the presence of abnormal returns of 0.64% one day before the announcement, indicating information leakage. The multilayer perceptron approach identifies five variables that explain the CARs of the sample companies, which are licensing_age, licensing_size, size, commercialization_age and approval_age.

The study contributes to the efficient market literature by revealing how firm-specific nonfinancial disclosures affect stock prices, especially in times of crisis like pandemics. Prior research focused on determining the effect of COVID-19 variables on abnormal returns. This is the first research to use artificial neural networks to determine which firm-specific variables and pharmaceutical interventions can influence CARs.

The complexity of citizenship behavior in organizations has long been a focus of research. Traditional methodologies have been predominantly used to address this complexity. This paper aims to tackle the problem using a cutting-edge technological tool: business process mining. The objective is to enhance citizenship behaviors by leveraging primary data collected from 326 white-collar employees in the Indian service industry.

The study focuses on two main processes: training and creativity, with the ultimate goal of fostering organizational citizenship behavior (OCB), both in its overall manifestation (OCB-O) and its individual components (OCB-I). Seven different machine learning algorithms were used: artificial neural, behavior, prediction network, linear discriminant classifier, K-nearest neighbor, support vector machine, extreme gradient boosting (XGBoost), random forest and naive Bayes. The approach involved mining the most effective path for predicting the outcome and automating the entire process to enhance efficiency and sustainability.

The study successfully predicted the OCB-O construct, demonstrating the effectiveness of the approach. An optimized path for prediction was identified, highlighting the potential for automation to streamline the process and improve accuracy. These findings suggest that leveraging automation can facilitate the prediction of behavioral constructs, enabling the customization of policies for future employees.

The findings have significant implications for organizations aiming to enhance citizenship behaviors among their employees. By leveraging advanced technological tools such as business process mining and machine learning algorithms, companies can develop more effective strategies for fostering desirable behaviors. Furthermore, the automation of these processes offers the potential to streamline operations, reduce manual effort and improve predictive accuracy.

This study contributes to the existing literature by offering a novel approach to addressing the complexity of citizenship behavior in organizations. By combining business process mining with machine learning techniques, a unique perspective is provided on how technological advancements can be leveraged to enhance organizational outcomes. Moreover, the findings underscore the value of automation in refining existing processes and developing models applicable to future employees, thus improving overall organizational efficiency and effectiveness.

After completing this case study, students will be able to understand the issues firms, brands and influencers face due to sponsorship disclosure regulation and the impact of self-regulation on firms engaging in influencer marketing, explain the challenges regulators face in ensuring compliance in an emerging market, explain Advertising Standard Council of India (ASCI)’s challenges in adopting influencer guidelines from emerged markets and recommend ethical theory (or theories) and strategies to firms engaged in influencer marketing.

This case study centers on Mr Manish Chowdhary, co-founder of WOW Skin Science, who started the beauty and personal care business with his brother Karan Chowdhary in 2015 in Bangalore, India. The company successfully built its brand through influencer marketing but faced challenges after the ASCI implemented new influencer guidelines. On May 31, 2021, he expressed disagreement with ASCI guidelines during an interview with Akansha Nagar from Buzz in Content, particularly the requirement to label every product or service received by influencers as an advertisement. He expressed concern about certain rules, fearing they might harm organic content and reduce viewership and followers. Subsequently, ASCI registered noncompliance cases against the company and communicated with them about complaints regarding influencer guideline violations. In this situation, Manish needed to evaluate his decision on noncompliance with regulation and required an action plan to strategically manage its influencer marketing campaign by incorporating ASCI’s guidelines. Overall, this case study highlights the journey of WOW Skin Science and its challenges with self-regulatory authorities over its influencer marketing strategy in an emerging market. Additionally, students can gain insight into the marketing communication ethics of a startup operating in an emerging market by embodying the protagonist’s role.

This case study is suitable for postgraduate level students pursuing a Master of Business Administration program. The difficulty level ranges from moderate to complex. It fits well into integrated marketing communication and marketing strategy courses. This case study discusses marketing ethics, advertising and promotion regulation.

Teaching notes are available for educators only.

CSS 8: Marketing.

Numerous prior studies highlight the importance of social media adoption (SMA) in nongovernmental organizations (NGOs) in the disaster preparedness phase (DPP). However, in India, social media is underused by NGOs in their attempts to mitigate the adverse impact of the disaster. Therefore, this study aims to seek to empirically investigate the relationship between factors influencing the SMA in NGOs in the DPP in India.

The “Technology-Organization-Environment (TOE)” framework, integrated with organizational creativity (OC), forms the theoretical foundation of this study. Data were collected from 266 respondents representing 120 Indian NGOs using a seven-point Likert scale. To test the hypotheses, this study used a variance-based structural equation modeling technique.

The empirical findings show that relative advantage, organizational readiness (OR), top management support and government support positively influenced the SMA in NGOs during the DPP. However, compatibility and complexity do not affect the SMA. In addition, OC moderates the relationship between OR and SMA in NGOs. These results underscore the need for NGOs to develop an organizational culture that is more forward-thinking and technology oriented.

This study fills an important research gap in the literature by developing a research model designed to improve the SMA in NGOs during the DPP in India. Furthermore, the authors integrated OC into the TOE framework to develop and examine the relationship between factors that impact SMA.

The prevailing conceptualization of information system (IS) capabilities, rooted in the resource-based view (RBV) framework, tends to focus on unique firm resources. In the digital age, as emphasized by dynamic capabilities (DC), resource reconfiguration is critical in maintaining strategic advantage. This paper focuses on big data analytics capabilities (BDAC) from a DC perspective to present a novel conceptualization of BDAC–DC. We examine its effects on product, business model and business process innovation, including the effects of enterprise architecture (EA) on the BDAC business model innovation relationship.

This research presents a novel DC-based BDAC conceptualization, operationalized as a hierarchical construct. A survey-based approach is used for data collection and data analysis is done using partial least squares structural equation modeling (PLS-SEM).

The novel conceptualization and the effects of BDAC DC on BDA sensing-seizing and reconfiguration capacities support BDAC’s functional and evolutionary roleplay. Empirical results confirm the positive effects of BDAC–DC on first-order value targets (innovation) and the moderating effects of EA.

The novel BDAC–DC conceptualization has several implications for BDAC, DC, EA and business value research. Practicing managers must adopt a multifaceted approach to BDAC development by considering non-technical and organizational factors, collaborate with their business counterparts to explore unique big data ideas, initiate proof-of-concept projects to secure support and allocate resources synchronously, considering a multidimensional view of the process, product and business model innovation.

Practicing managers must adopt a multifaceted approach to BDAC development by considering non-technical and organizational factors, collaborate with their business counterparts to explore unique big data ideas, initiate proof-of-concept projects to secure support and allocate resources synchronously, considering a multidimensional view of the process, product and business model innovation for synergistic outcomes.

To the best of our knowledge, this research is the first attempt toward DC-based BDAC conceptualization, empirical validation of first-order effects on various forms of innovation and the often-overlooked role of critical EA capability.

Adopting and implementing robotic technology applications in the library is a significant technological up-gradation today. The purpose of this study was to evaluate selected literature focused mainly on robotics technology applications in the field of libraries and to assess the online social attention to research publications.

The study employed Scientometric and altmetric tools to evaluate the research publications. The bibliographic data of research publications were downloaded from Scopus database and scrutinized one by one and 71 articles were selected which mainly focused on robotic technology in libraries. Altmetric data were collected from the Dimensions.ai database. The analysis was performed using MS Excel, Tableau, Biblioshiny, VOSviewer and SPSS software.

Research on robotic technology in the field of libraries has been experiencing a gradual increase, marked by an annual growth rate of 12.93%. The United States has prominently led the way as the most active participant and collaborator in this advancement. Among the various journals, Library Hi Tech has notably stood out as a significant contributor to this field. However, the research articles have garnered limited social attention and impact. Furthermore, the patterns of authorship collaboration have demonstrated relatively modest levels within the field, and a weak correlation has been observed between the social attention received and the Scopus citation metrics of the publications.

The research needs to be disseminated more through various social media platforms to increase its visibility. Sharing research information through social media can bridge the gap between academia and society. The findings of this study can serve as a valuable reference for researchers and policymakers.

This study presents a Scientometric analysis of the selected published literature on robotics technology applications in the field of libraries, highlighting the progress and development of worldwide research in this area.

In this chapter, the authors argue that technology can be advantageous to children and young people’s mental health. The authors argue that social media platforms can foster social connection, social support and access to important information to support mental health. The authors also highlight the risks, particularly the research which links technology to mental ill-health. The authors argue that the digital curriculum in schools should develop young people’s knowledge of digital literacy, digital citizenship and digital resilience. Finally, the authors explore the potential role that technological applications (apps) can play in supporting children and young people’s mental health. The authors argue that although research is in its infancy, some studies have produced promising results.

In the era of Industry 5.0, understanding the balance between environmental, social, and governance (ESG) and firm performance is crucial for mitigating climate change and enhancing financial outcomes. This paper aims to analyze the effect of ESG disclosure on the financial performance (FP) of renewable and clean energy (RCE) companies, focusing on the combined ESG disclosure and individual E, S, and G disclosure scores.

The study analyzed a panel data sample from 2015–2021, covering 41 RCE companies. By applying the K-means++ clustering technique, the research also explored how firm-specific features influence the relationship between ESG disclosure and FP. The Bloomberg database and audited financial reports were used to gather the data for the study.

The findings indicate that increased ESG disclosure positively influences FP. Further, a significant positive relationship exists between FP and a company’s E and S disclosure. However, firm-specific characteristics significantly influence this relationship. Findings suggest that a company’s commitment to comprehensive ESG efforts enhances financial efficiency rather than increasing costs.

This study adds to the ESG-FP literature by emphasizing global RCE companies, a key player in sustainability. Further, to the best of the author’s knowledge, the study’s uniqueness is attributed to its application of a two-step approach, combining ESG-FP analysis with K-means++ clustering to account for firm-specific characteristics. It also uniquely examines the individual impact of E, S, and G disclosure on the FP of global RCE companies. The findings offer valuable insights for businesses and policymakers in developing strategies that improve profitability while addressing climate change risks.