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Introduction: As Internet usage increases, so does widespread concern about surveillance and privacy. While most of the research primarily focuses on a particular digital setting, these problems cut beyond national boundaries and impact economies everywhere.

Purpose: This study critically analyses the Data Protection Bill 2019’s effectiveness within the context of surveillance and privacy in India’s digital economy. Investigating critical provisions of the bill, comparing it to international privacy laws and standards, and identifying potential gaps and weaknesses, this study provides insights into the bill’s ability to protect personal data and limit surveillance practices.

Methodology: The chapter is based on secondary sources of data, including academic articles, government reports, and news articles on the topics of surveillance, privacy, and the Data Protection Bill 2019 in India, involving content and critical discourse analyses.

Findings: The Data Protection Bill 2019 evaluation reveals a set of provisions with the overarching intent to safeguard citizens’ privacy worldwide and curtail undue surveillance practices exercised by both governmental bodies and private enterprises. Intricately delineates the entitlements of individuals concerning their data, encompassing vital aspects such as the right to access, rectify, and erase their data, the bill mandates stringent adherence to the principle of explicit consent when collecting and processing personal data.

Nevertheless, a comprehensive analysis also reveals several gaps and constraints inherent in the bill’s framework. One such area is the inclusion of exemptions for governmental entities, an aspect that raises international concerns regarding potential disparities in data protection practices.

The purpose of this paper is to understand how hospitality companies can best explain controversial corporate social responsibility (CSR) activities to consumers who may not agree with the CSR activity. This research explores message framing through emotional and cognitive appeals to influence consumer perceptions of the Gideon Bible in USA hotel rooms. The study uses the theory of deontic justice to measure the impacts of messaging on consumer perceptions of the morality of the Gideon Bible as suicide prevention in hotels and its relation to controversial CSR initiatives.

The study uses an experimental study design via a self-administered survey to analyze participants’ perceptions of the placement of the Gideon Bible in hotel rooms and participants’ attitudes toward CSR initiatives based on deontic justice and religion using different message framing conditions.

Results show that religion was a major determinant of attitude towards the Gideon Bible, but the sentiment analysis also revealed that negative perceptions can be mitigated through message framing via emotional and cognitive appeals. Additionally, the cognitive appeal did impact CSR perceptions, as did identifying as Christian. Moral outrage emerged as a significant moderator for the relationships between message framing, attitudes toward the Gideon Bible and CSR.

This study provides an extension of deontic justice research to examine justice traits in accepting controversial CSR.

This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.

Using three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.

The models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.

This study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.

This study produced a reliable, accurate forecasting model considering risk and competitor behavior.

This paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.

This study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.

The purpose of this study is to examine the differential impact of qualitative and quantitative informational signals within the merger and acquisition (M&A) press releases on deal completion and duration. A significant percentage of deals by emerging market acquirers get abandoned before completion, and those that are completed have a longer duration. The limited information about the operations of acquirers from emerging markets creates suspicion among the stakeholders involved in deal resolution, hindering the completion of deals. Thus, using the signal-feedback paradigm, authors investigate how informational signals in the M&A press release impact the deal resolution.

The study employs content analysis on M&A press releases announced by firms from five emerging economies: Brazil, Russia, India, China and South Africa. The technique is applied based on the exploration-exploitation framework developed by March (1991) to categorize the announced deal motives (qualitative information). Next, the authors identify the percentage of relevant quantitative information disclosed in the press release, following which results are obtained using logistic and ordinary least square regressions.

The study reports that deals with declared exploratory motives take longer to complete. Additionally, deals disclosing higher percentage of quantitative disclosure exhibit lower completion rate and increased deal duration.

This is the first study to provide evidence that familiarity bias impacts deal duration as relative to exploitation deals that are familiar to the stakeholders; exploratory deals take longer to conclude. Further, our analysis indicates that a greater percentage of quantitative disclosure may not always reduce information risk but rather be interpreted negatively in the form of the acquirer’s overconfidence in the deal’s potential.

This paper aims to highlight how the Greek State tried to improve public procurement processes during the outbreak of the COVID-19 pandemic and propose measures that could be implemented in a future force majeure event where the global supply chain will not operate efficiently.

The authors investigated the existing scientific literature. Afterwards, they designed a questionnaire to gather primary data and add value to the current literature.

The research paper results highlight that in future force majeure events, the best way for effective public procurement is to implement central procurement, framework agreements with more than one economic operator and use the newly established Public Buyers Community in the European Union. The questionnaire interviews also highlighted that payment terms could be adjusted to the needs of the suppliers to improve their financial flows, which are disrupted in case of a force majeure event.

One of the limitations of the present case study is that apart from the Greek procurement Laws and policy documents related to the COVID-19 pandemic, only scientific articles written in English were used by the authors in the literature review section.

The findings could benefit public contracting authorities and central procurement bodies when designing their processes in case of a force majeure event like the COVID-19 pandemic. As the public contracting authorities and the procurement officers are more informed about potential ways to improve the public procurement processes, they might apply measures that could facilitate the flexibility of the procurement processes.

The research paper can provide lessons learned to policy makers, when they have to cope with similar challenges in the future.

To the best of the authors' knowledge, no previous scientific article has examined how the Greek State has tried to respond to the supply shortages created during the pandemic. Furthermore, this is the first study in Greece that gathers primary data from public procurement practitioners.

This research analyzes the alignment of story framing between Samarco and news media following the dam disaster in Minas Gerais in November 2015. Drawing on framing theory as the underlying impetus, the study seeks to answer five major questions: RQ1: How did Samarco frame the mining tragedy in the aftermath of the dam collapse? RQ2: How did the news media frame the mining tragedy in the aftermath of the dam collapse? RQ3: Did the frames presented by Samarco and news media coincide? RQ4: Did the frames presented by Samarco and news media contradict? RQ5: What can be observed about the information flow and interaction between news media and the general public on social media? From a methods perspective, the study uses comparative textual analysis and NodeXL social network visualization to analyze the discourse around Samarco and information flow on social media in the aftermath of the tragedy. The results show that, while some social media content served as a forum for expressions of empathy toward survivors, social media content on Twitter mostly delivered a one-sided and positive view of the firm’s actions.

The goal of this work is to evaluate how digital transformation disclosure in corporate news and press releases affects stock prices. We examine American and Chinese companies from the energy and industry sectors for two periods: pre-COVID-19 and during the COVID-19 pandemic.

To estimate the effects of disclosure of information related to digital transformation, we applied the bag-of-words (BOW) method. As the benchmark dictionary, we used Kindermann et al. (2021), with the addition of original dictionaries created via Latent Dirichlet allocation (LDA) analysis. We also employed panel regression analysis and random forest.

For USA energy sector, all aspects of digital transformation were insignificant in pre-COVID-19 period, while sustainability topics became significant during the pandemic. As for the Chinese energy sector, digital strategy implementation was significant in pre-pandemic period, while digital technologies adoption and business model innovation became relevant in COVID-19 period. The results show the greater significance of digital transformation aspects for industrials sectors compared to the energy sector. The result of random forest analysis proves the efficiency of the authors’ dictionary which could be applied in practice. The developed methodology can be considered relevant.

The research contributes to the existing literature in theoretical, empirical and methodological ways. It applies signaling and information asymmetry theories to the financial markets, digital transformation being used as an instrument. The methodological contribution of this article can be described in several ways. Firstly, our data collection process differs from that in previous papers, as the data are gathered “from investor’s point of view”, i.e. we use all public information published by the company. Secondly, in addition to the use of existing dictionaries based on Kindermann et al. (2021), with our own modifications, we apply the original methodology based on LDA analysis. The empirical contribution of this research is the following. Unlike past works, we do not focus on particular technologies (Hong et al., 2023) connected with digital transformation, but try to cover all multi-dimensional aspects of the transformational process and aim to discover the most significant one.

Corporate disclosures are essential because they provide transparent and accurate information about a company's financial health, performance, risks and governance practices. They enable investors to make informed decisions, promote market efficiency and maintain trust in the financial system. This paper uses bibliometrics to identify the intellectual composition of the literature on corporate disclosure.

Based on the bibliometric information of 4,551 articles on corporate disclosure research, the authors conducted citation, keyword co-occurrence, bibliographic coupling and publication analyses to elucidate the leading articles, authors, sources, institutions, countries, themes and topics in the field of corporate disclosure from the 1960s to 2021.

The findings of this review demonstrate that corporate disclosure research is based on four broad themes – the role of disclosure in capital markets, non-financial disclosure, determinants of corporate disclosure and firm risk and intellectual capital disclosure. This review suggests that management should pay attention to the financial and non-financial corporate information that investors, regulators and the government emphasise.

This paper is the first comprehensive bibliometric review on corporate disclosure. It summarises the regulatory shifts, technological changes and industry trends that have influenced corporate disclosure research. Besides identifying broad research themes, the authors performed bibliographic coupling for research on disclosure sources, including annual reports, management forecasts, earnings calls, press releases, the Internet and social media, to reveal the thematic clusters related to these sources.

The purpose of this study was to investigate the factors impacting the intermediating variable of employee engagement toward employee performance in a hybrid working organization in Bangkok, Thailand.

This study uses secondary data analysis and an archival study; the primary data were gathered from 370 employees who are working in a hybrid model environment in a private agricultural machinery company. To construct a new conceptual framework, this study adopted four frameworks from the previous research.

Perceived organizational support and trust and respect in the organization are found to have a significant positive impact on employee engagement. Moreover, there is a significant positive impact of the employee engagement on employee performance in a hybrid working model.

For hybrid work environments, the research focused mainly on the emotional themes of perceived support, trust and respect in the organization. Therefore, there would be many factors that could possibly affect those dependence variables in any environment, which will have to be investigated more in future research. Either in the organization or in the company, many departments and business units operates for the company, but the researcher specifies only the business units or departments that now use the hybrid working model.

This study focuses on a case study of an agricultural machinery company, which likely produces different results than other industries, other industries may produce different results.

Hybrid working models can blur the boundaries between work and personal life, potentially leading to increased stress and burnout. Organizations should prioritize work-life balance and employee well-being by promoting flexible schedules, encouraging breaks and time off, and providing resources for mental health support.

The organization which is operating among a hybrid working model, the increasing of perceived organizational support and trust and respect level, has positively increase the employee engagement toward enhancing the employee performance.

With 43.2 million coronavirus cases and 525,000 deaths in 2022, India ranked second worldwide, after the United States (84.6 million cases and 1 million deaths), according to the latest available June 2022 COVID-19 impact data.

Amid people’s growing mistrust in the government, India’s news media enhanced the nation’s distinguished designation as the world’s largest and most populous democracy. India’s news media inform, educate, empower, and entertain a surging population of 1.4 billion people, which is roughly one-sixth of the world’s people.

Drawing upon the media agendamelding theoretical framework, we conducted a case study research into interplay between two prominent democratic institutions, the media and the government, to analyze the role of the COVID-19 pandemic in redefining India’s networked society.

India’s COVID-19 pandemic aggravated internecine tensions between media and government relating to four key freedom issues: (1) world’s largest COVID-19 lockdown affecting 1.3 billion Indians from March 25, 2020 to August 2020 with extensions and five-phased re-openings, to restrict the spread of COVID-19; (2) Internet shutdowns; (3) media censorship during the 1975–1977 “Emergency”; and (4) unabated murders of journalists in India.

Although the COVID-19 pandemic caused deleterious problems debilitating the tensions between the media and the government, India’s journalists thrived by speaking truth to power. This study delineates key aspects of India’s media agendamelding that explicates how the people of India form their media agendas. India’s news audiences meld media messages from newspapers, television, and social media to form a picture of the issues, insights, and ideas that define their lives and times in the 21st century digital age.