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The authors argue that privacy is integral to the well-being of consumers and an essential component in not only corporate social responsibility (CSR) but what they term uniquely as social media responsibility (SMR). A conceptual framework is proposed that delineates the privacy issues companies should pay attention to in artificial intelligence (AI)-fueled social media environments.

The authors review literature on privacy issues in social media and AI in the academic and practitioner literatures. Based on the review, arguments focus on the need for an SMR framework, proposing responsible use of consumer data that is attentive to consumers' privacy concerns.

Implications from the framework are a path forward for social media companies to treat consumer data more fairly in this new environment. The framework has implications for companies to reduce potential harms to consumers and consider addressing their power and responsibility. With social media and AI transforming consumer behavior so profoundly, there are a variety of short- and long-term social implications.

Since AI tools are becoming integral to social media company activities, this research addresses the changing responsibilities social media companies have in securing consumers' data and enabling consumers the agency to protect their privacy effectively. The authors propose an SMR framework based on CSR research and AI tools employed by social media companies.

In the last two decades, risk reporting has followed a normative and calculative culture rather than the “materiality” of data. Although integrated reporting (IR) has become flooded with extra information, it does not adequately disseminate material information to stakeholders. In addition, the poor tone from the top diminishes creativity. This study aims to investigate how companies creatively address issues of the materiality of risk information in IR and how IR can be aligned with enterprise risk management.

Qualitative research was conducted via interviews with 50 chief risk officers and senior management executives in the Indian and UK insurance markets.

Overall, five institutions were observed to exhibit elements of being early adopters of institutional creativity. This confirmed the present study’s theoretical contribution of five divergent types of early adopters. The motivations for creativity are reflected in the resources available to these institutions.

To the best of the authors’ knowledge, this study provides a new insight into IR from internal mechanisms to deal with issue of materiality.

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors’ behavior.

Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.

This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors’ decision-making. Through thematic analysis, an attribute–consequence–impact framework is proposed that explains different biases leading to individual investors’ irrationality. The study further proposes directions for future research by applying the theory–characteristics–context–methodology framework.

The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.

The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor’s decision-making.

The article aims to investigate how washing practices focused on appeasing sceptics of diversity work in for-profit organizations play out in corporate online communication of diversity and inclusion efforts, and how these enable communication to a wide audience that includes social equity advocates.

Online corporate communication data of diversity and inclusion themes were compiled from the websites of eight Swedish-based multinational corporations. The data included content from the companies’ official websites and annual reports and sustainability reports as well as diversity and inclusion-themed blog posts. A thematic analysis was conducted on the website content.

The study showcases how tensions between conflicting external demands are navigated by keeping the communication open to several interpretations and thereby achieving multivocality. In the studied corporate texts on diversity and inclusion, this is achieved by alternating between elements catering to a business case audience and those that appeal to a social justice audience, with some procedures managing to appease both audiences at the same time.

The article complements previously described forms of washing by introducing an additional type of washing – business case washing – an articulation of the business case rhetoric that characterizes the diversity management discourse. While much has been written about washing to satisfy advocates of social change and equity, washing to appease shareholders and boardroom members, who are focused on profit and economic growth, has received less attention. The article suggests that online corporate communication on diversity and inclusion, by appeasing diverse audiences, can be seen as aspirational talk.

The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as health care, manufacturing, retail, food services, education, media and entertainment, banking and insurance, travel and tourism. Furthermore, the authors discuss the tactics in which information technology is used to implement business strategies to transform businesses and to incentivise the implementation of these technologies in current or future emergency situations.

The review provides the rapidly growing literature on the use of smart technology during the current COVID-19 pandemic.

The 127 empirical articles the authors have identified suggest that 39 forms of smart technologies have been used, ranging from artificial intelligence to computer vision technology. Eight different industries have been identified that are using these technologies, primarily food services and manufacturing. Further, the authors list 40 generalised types of activities that are involved including providing health services, data analysis and communication. To prevent the spread of illness, robots with artificial intelligence are being used to examine patients and give drugs to them. The online execution of teaching practices and simulators have replaced the classroom mode of teaching due to the epidemic. The AI-based Blue-dot algorithm aids in the detection of early warning indications. The AI model detects a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection, sound pressure detection and light level detection. The above and various other applications are listed throughout the paper.

Research is largely delimited to the area of COVID-19-related studies. Also, bias of selective assessment may be present. In Indian context, advanced technology is yet to be harnessed to its full extent. Also, educational system is yet to be upgraded to add these technologies potential benefits on wider basis.

First, leveraging of insights across various industry sectors to battle the global threat, and smart technology is one of the key takeaways in this field. Second, an integrated framework is recommended for policy making in this area. Lastly, the authors recommend that an internet-based repository should be developed, keeping all the ideas, databases, best practices, dashboard and real-time statistical data.

As the COVID-19 is a relatively recent phenomenon, such a comprehensive review does not exist in the extant literature to the best of the authors’ knowledge. The review is rapidly emerging literature on smart technology use during the current COVID-19 pandemic.