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The purpose of this study was to examine consumer data acquired by branded prescription drug websites and the ethics of privacy related to the interconnected web of personal information accessed, packaged and resold by tracker technologies.

The research used the DMI Tracker Tool to collect data on the top 17 branded prescription drug websites, with a specific interest in the tracker technologies embedded in those websites. That data was analyzed using Gephi, an open-source data visualization tool, to map the network of trackers embedded in those branded prescription drug websites.

Findings visualize the interconnections between tracker technologies and prescription drug websites that undergird a system of personal data acquisition and programmatic advertising vehicles that serve the interests of prescription drug marketers and Big Tech. Based on the theory of platform ethics, the study demonstrated the presence of a technostructural ecosystem dominated by Big Tech, a system that goes unseen by consumers and serves the interests of advertisers and resellers of consumer data.

The 17 websites used in this study were limited to the top-selling prescription drugs or those with the highest ad expenditures. As such this study is not based on a random sampling of branded prescription drug websites. The popularity of these prescription drugs or the expanse of advertising associated with the drugs makes them appropriate to study the presence of tracking devices that collect data from consumers and serve advertising to them. It is also noted that websites are dynamic spaces, and some trackers within their infrastructures are apt to change over time.

Branded prescription drug information has over the past three decades become part of consumers’ routine search for information regarding what ails them. As drug promotion moved from print to TV and the Web, searching for drug information has become a part of everyday life. The implications of embedded trackers on branded prescription drug websites are the subject of this research.

This study has significant social implications as consumers who are searching for information regarding prescription medications may not want drug companies tracking them in a way that many perceive to be an invasion of privacy. Yet, as the Web is dominated by Big Tech, web developers have little choice but to remain a part of this technostructural ecosystem.

This study sheds light on branded prescription drug websites, exploring the imbalance between the websites under study, Big Tech and consumers who lack awareness of the system that operates backstage.

The purpose of this paper is to explore the concept of data assets and how companies can assetize their data. Using the literature review methodology, the paper first summarizes the conceptual controversies over data assets in the existing literature. Subsequently, the paper defines the concept of data assets. Finally, keywords from the existing research literature are presented visually and a foundational framework for achieving data assetization is proposed.

This paper uses a systematic literature review approach to discuss the conceptual evolution and strategic imperatives of data assets. To establish a robust research methodology, this paper takes into account two main aspects. First, it conducts a comprehensive review of the existing literature on digital technology and data assets, which enables the derivation of an evolutionary path of data assets and the development of a clear and concise definition of the concept. Second, the paper uses Citespace, a widely used software for literature review, to examine the research framework of enterprise data assetization.

The paper offers pivotal insights into the realm of data assets. It highlights the changing perceptions of data assets with digital progression and addresses debates on data asset categorization, value attributes and ownership. The study introduces a definitive concept of data assets as electronically recorded data resources with real or potential value under legal parameters. Moreover, it delineates strategic imperatives for harnessing data assets, presenting a practical framework that charts the stages of “resource readiness, capacity building, and data application”, guiding businesses in optimizing their data throughout its lifecycle.

This paper comprehensively explores the issue of data assets, clarifying controversial concepts and categorizations and bridging gaps in the existing literature. The paper introduces a clear conceptualization of data assets, bridging the gap between academia and practice. In addition, the study proposes a strategic framework for data assetization. This study not only helps to promote a unified understanding among academics and professionals but also helps businesses to understand the process of data assetization.

This study, rooted in affordance-actualization theory and communication theory, aims to critically examine how ChatGPT influences users’ transition from new adopters to loyal advocates within the context of travel decision-making. It incorporates constructs including communication quality, personalization, anthropomorphism, cognitive and emotional trust (ET), loyalty and intention to adopt into a comprehensive model.

This study used quantitative methods to analyze data from 477 respondents, collected online through a self-administered questionnaire by Embrain, a leading market research company in South Korea. Lavaan package within R studio was used for evaluating the measurement model through confirmatory factor analysis and using structural equation modeling to examine the proposed hypotheses.

The findings reveal a pivotal need for enhancing ChatGPT’s communication quality, particularly in terms of accuracy, currency and understandability. Personalization emerges as a key driver for cognitive trust, while anthropomorphism significantly impacts ET. Interestingly, the study unveils that in the context of travel recommendations, users’ trust in ChatGPT predominantly operates at the cognitive level, significantly impacting loyalty and subsequent adoption intentions.

The findings of this research provide valuable insights for improving Generative AI (GenAI) technology and management practices in travel recommendations.

As one of the few empirical research papers in the burgeoning field of GenAI, this study proposes a highly explanatory model for the process from affordance to actualization in the context of using ChatGPT for travel recommendations.

This study aims to analyze the platforming scenario at a Brazilian university as well as the data security process for students and professors.

This research brings an analysis through a qualitative approach of the platformization process in a Brazilian teaching institution.

The results point to a lack of knowledge on the part of teachers regarding data security in the platforming scenario, as well as the lack of effectiveness of institutions in protecting student data.

Within the Brazilian scenario, this research seeks to contribute to the discussion on platformization in view of the gaps and existing demands on this process in the country.

Personal data is a powerful tool. The more someone know about us, the more power they got over us. But who will control the most of our personal data? Does the government and the big tech really care about our personal data? This paper aims to look at data practices, data-related policy making as well as its economic consequences in the context of emerging economies.

Using qualitative methods such as literature review and analysis of numerous government documents, this paper inquires into the dynamics in the use of data by the business sectors, explains how data governance can add value to the business sectors while ensuring customers’ data privacy protection based on the data governance mechanism framework and details what it takes.

Using the case of Indonesian recent development on data privacy regulation, this paper describes the problems and threats to personal data protection. The advent of latest computing and mobile technology is shifting power relations between the governments, the big tech, as well as the end users. To conclude, the strategy and policy recommendations for implementing data privacy protection are also presented.

This paper provides a timely synthesis of data practices in the context of developing countries, particularly in relation to policy making and economic consequences. This paper also identifies and shares several promising future research ideas.

Drawing on expectancy violation theory, this study aims to assess the impact of corporate environmental irresponsibility (CEI) on workplace deviant behaviors (WDB) of Generation Z and Millennials through the mediation of moral outrage.

The data were collected from 328 nonmanagerial employees working in the refinery, petroleum and power distribution companies who have been convicted for committing environmental irresponsibility by a court of law. Multigroup analysis (MGA) was used to estimate the hypothesized relationships.

Results revealed that CEI affects WDBs positively. Moreover, the MGA results demonstrated that the deviant behavior of Generation Z in response to environmental irresponsibility is higher than of the Millennials.

Theoretically, the findings implicate that harming the environment will cost organizational performance through deviant behaviors.

This study provides a new lens for the executive management that eliminating social irresponsibility is more important than incurring sustainability initiatives, especially from the new generation’s perspective.

The originality of this study is that it confirmed the impact of CEI on employees’ deviant behaviors; and extended the scope of expectancy violation theory to the field of human resources.

Purpose: The research determines how the COVID-19 pandemic affected India’s burgeoning education technology sector and how the new normal responded to this advancement worldwide.

Need for Study: India’s education sector saw a boom in Ed-Tech funding during the pandemic. The Indian Education industry adopted technology as a partner and succeeded in being called as the Ed-Tech capital of the world. The country has a strategic edge in online education that, if explored and researched upon, can be deployed for market growth at a global level.

Research Methodology: The researcher prioritised rigorous original quantitative and qualitative methods of investigation on technology applications in educational contexts during COVID-19 pandemic and drew its conclusions after conducting a comprehensive literature review and collecting and analysing the data from numerous journals and published expert articles on the sector.

Findings: The study found that despite the global pandemic, the Ed-Tech industry was an expanding marketplace for start-ups in India. After the pandemic, the market expanded rapidly, and by 2025, it is expected to have quadrupled in size, expenditure, and investment. It is expected that the global e-learning business, which the outbreak of the COVID-19 pandemic has bolstered, will grow to over 400 billion US dollars by 2026.

Practical Implications: The study sets forth the various Ed-Tech categories, outlining their user bases, growth projections, and the innovative technologies employed in developing these products. The research’s long-term investment projections are envisioned to aid consultants in positioning themselves for profitable operations in the era of digital Ed-Tech disruption worldwide.

The deployment of artificial intelligence (AI) technologies in travel and tourism has received much attention in the wake of the pandemic. While societal adoption of AI has accelerated, it also raises some trust challenges. Literature on trust in AI is scant, especially regarding the vulnerabilities faced by different stakeholders to inform policy and practice. This work proposes a framework to understand the use of AI technologies from the perspectives of institutional and the self to understand the formation of trust in the mandated use of AI-based technologies in travelers.

An empirical investigation using partial least squares-structural equation modeling was employed on responses from 209 users. This paper considered factors related to the self (perceptions of self-threat, privacy empowerment, trust propensity) and institution (regulatory protection, corporate privacy responsibility) to understand the formation of trust in AI use for travelers.

Results showed that self-threat, trust propensity and regulatory protection influence trust in users on AI use. Privacy empowerment and corporate responsibility do not.

Insights from the past studies on AI in travel and tourism are limited. This study advances current literature on affordance and reactance theories to provide a better understanding of what makes travelers trust the mandated use of AI technologies. This work also demonstrates the paradoxical effects of self and institution on technologies and their relationship to trust. For practice, this study offers insights for enhancing adoption via developing trust.

Drawing on the mSERVQUAL model and spillover theory, this study aims to examine the mechanism through which food-ordering mobile app service quality influences users’ mobile app satisfaction, food satisfaction and repurchase intentions.

Online surveys were completed by 1,000 customers who used a food-ordering mobile app to order fast food on the day they completed the online survey. Structural equation modelling was then used to examine the proposed mechanism.

Results showed that the effects of food-ordering mobile app service quality on customer satisfaction (i.e. mobile app satisfaction and food satisfaction) and repurchase intention varied widely across service quality dimensions. Mobile app service quality had significant spillover effects on food satisfaction and repurchase intention.

Online food-delivery platforms should find the results insightful to better design their food-ordering mobile app. The findings can also assist restaurateurs and mobile payment companies with supporting the whole online food delivery process.

Rather than examining online food delivery service quality based on the service delivery process in the during-consumption stage or the service outcomes in the post-consumption stage, this study focused on the service quality in the pre-consumption stage to highlight the important role of online food delivery mobile apps. From a longitudinal perspective, this study drew on the associate network theory to explain the spillover effect of mobile app satisfaction in the pre-consumption stage on food satisfaction in the during-consumption stage and repurchase intention in the post-consumption stage.