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The main objective of this study is to present a compact overview analysis of intellectual property laws, specifically copyright-related provisions applicable to generative artificial intelligence (GenAI) in the Indian context.

The paper adopts a qualitative research methodology that is grounded in secondary sources of information. The data were gathered from the Scopus database for a systematic literature review.

GenAI technology has given rise to numerous questionable issues within the domain of intellectual property that need resolution in the form of policy solutions. Based on the findings of this paper, it can be deduced that Indian copyright laws are not adequate for addressing the rights pertaining to AI and its creations and outputs. Different countries like the United States, European Union and China have approached the regulation and protection of AI-generated content within the realm of copyright law in different ways. The future of law, as it has been established thus far, seems to be on a path of substantial evolution.

The study has implications for policymakers globally as there is a need to create feasible policy solutions that can efficiently safeguard against risks stemming from large language models (LLMs) and other GenAI models, while also promoting innovation, technical advancement and adoption.

The paper discusses the copyright-related issues in GenAI technology in the context of an emerging economy, India.

The data economy, emerging from the current hyper-technological landscape, is a global digital ecosystem where data is gathered, organized and exchanged to create economic value. This paper aims to shed light on the interplay of the different topics involved in the data economy, as found in the literature. The study research provides a comprehensive understanding of the opportunities, challenges and implications of the data economy for businesses, governments, individuals and society at large, while investigating its impact on business value creation, knowledge and digital business transformation.

The authors conducted a literature review that generated a conceptual map of the data economy by analyzing a corpus of research papers through a combination of machine learning algorithms, text mining techniques and a qualitative research approach.

The study findings revealed eight topics that collectively represent the essential features of data economy in the current literature, namely (1) Data Security, (2) Technology Enablers, (3) Business Implications, (4) Social Implications, (5) Political Framework, (6) Legal Enablers, (7) Privacy Concerns and (8) Data Marketplace. The study resulting model may help researchers and practitioners to develop the concept of data economy in a structured way and provide a subset of specific areas that require further research exploration.

Practically, this paper offers managers and marketers valuable insights to comprehend how to manage the opportunities deriving from a constantly changing competitive arena whose value is today also generated by the data economy.

Socially, the authors also reveal insights explaining how the data economy features may be exploited to build a better society.

This is the first paper exploring the data economy opportunity for business value creation from a critical perspective.

This systematic review aimed to identify and categorize applications using Fast Healthcare Interoperability Resources (FHIR) to support activities outside of direct healthcare provision.

A systematic electronic search was performed, and 53 studies were included after the selection process.

The results show that FHIR is being used to support (1) clinical research (i.e. clinical research based on interventional trials, data interoperability to support clinical research and advanced communication services to support clinical research), (2) public health and (3) medical education. Despite the FHIR potential to support activities outside of direct healthcare provision, some barriers were identified, namely difficulties translating the proposed applications to clinical environments or FHIR technical issues that require further developments.

This study provided a broad review of how FHIR is being applied in clinical activities outside of direct clinical care and identified three major domains, that is, clinical research, public health and medical education, being the first and most representative in terms of number of publications.

This study aims to analyze the development of digital market characteristics particularly focusing on how the strategic choices of platforms are not fully reflected in pricing. In addition, the implications for the development of theories of harm are investigated to explore the necessity of a relevant market definition in assessing infringement and evaluating the adequacy of Indonesian competition law.

This study is a legal analysis that uses statutory approaches, cases, comparative law and the development of theories of harm in digital mergers. The case approach is conducted by analyzing three cases decided by the Indonesia Business Competition Supervisory Commission. This approach provides insight into the response of Komisi Pengawas Persaingan Usaha concerning the merger and acquisition cases in the digital era as well as the provision of different analyses in conventional markets. However, competition can be potentially damaged in digital markets and a comparative law approach is taken by analyzing digital merger cases decided by authorities in other countries.

Results reveal that the digital market has created a “relevant market” that is challenging and blurred due to multi-sided network effects and consumer data usage characteristics. Platform-based enterprises’ prices fluctuate due to the digital market’s network effect and consumer data statistics. Smartphone prices depend on the number of apps and consumer data. Neoclassical theory focusing on product markets and location applied in Indonesia must be revised to establish a relevant digital economy market. To evaluate digital mergers, new harm theories are needed. The merger should also protect consumer data. Law Number 27 of 2022 on Personal Data Protection and Government Regulation on the Implementation of Electronic Systems and Transactions protects online consumers, a basic step in due diligence for digital mergers. The Indonesian Government should promptly strengthen the notion of “relevant markets” in the digital economy, which could lead to fair business competition violations like big data control. Notify partners or digital merger participants of the accessibility of sensitive data like transaction history and user location.

The development of digital market characteristics has implications for developing theories of harm in digital markets. Indonesian competition law needs to develop such theories of harm to analyze the potential for anticompetitive digital mergers in the digital economy era.

In the online environment, consumers increasingly feel vulnerable due to firms’ expanding capabilities of collecting and using their data in an unsanctioned manner. Drawing from gossip theory, this research focuses on two key suppressors of consumer vulnerability: transparency and control. Previous studies conceptualize transparency and control from rationalistic approaches that overlook individual experiences and present a unidimensional conceptualization. This research aims to understand how individuals interpret transparency and control concerning privacy vulnerability in the online environment. Additionally, it explores strategic approaches to communicating the value of transparency and control.

An interpretivism paradigm and phenomenology were adopted in the research design. Data were collected through semi-structured interviews with 41 participants, including consumers and experts, and analyzed through thematic analysis.

The findings identify key conceptual dimensions of transparency and control by adapting justice theory. They also reveal that firms can communicate assurance, functional, technical and social values of transparency and control to address consumer vulnerability.

This research makes the following contributions to the data privacy literature. The findings exhibit multidimensional and comprehensive conceptualizations of transparency and control, including user, firm and information perspectives. Additionally, the conceptual framework combines empirical insights from both experiencers and observers to offer an understanding of how transparency and control serve as justice mechanisms to effectively tackle the issue of unsanctioned transmission of personal information and subsequently address vulnerability. Lastly, the findings provide strategic approaches to communicating the value of transparency and control.

This study aims to examine the association between fair value accounting and the cost of corporate bonds, proxied by bond yield spread. In addition, this study explores the moderating role of auditor industry expertise at both the national and the city levels.

This study first examines the effect of the use of fair value on yield spread by estimating firm-level regression model, where fair value is the testing variable and yield spread is the dependent variable. To test the differential impact of the three levels of fair value inputs, this paper divides the fair value measures based on the three-level hierarchy, Level 1, Level 2 and Level 3, and replace them as the test variables in the regression model.

This study finds that the application of fair value accounting is generally associated with a higher bond yield spread, primarily driven by Level 3 estimates. The results also show that national-level auditor industry expertise is associated with lower bond yield spreads for Level 1 and Level 3 fair value inputs, whereas the impact of city-level auditor industry expertise on bondholders is mainly on Level 3 fair value inputs.

The paper innovates by exploring the impact of fair value accounting in a setting that extends beyond financial institutions, the traditional area of focus. Moreover, most prior research considers private debt, whereas this study examines public bonds, for which investors are more likely to rely on financial reporting for their information about a firm. Finally, the study differentiates between city- and national-level industry expertise in examining the role of auditors.

This research has several practical implications. First, firms seeking to raise debt capital should consider involving auditors, with either industry expertise or fair value expertise, due to the roles that auditors play in safeguarding the reliability of fair value measures, particularly for Level 3 measurements. Second, from standard-setting and regulatory perspectives, the study’s findings that fair value accounting is associated with higher bond yield spread cast further doubt on the net benefits of applying a full fair value accounting regime. Third, PCAOB may consider enhancing guidance to auditors on Level 2 fair value inputs, to further enhance audit quality. Finally, creditors can be more cautious in interpretating accounting information based on fair value while viewing the employment of auditor experts as a positive signal.

First, the paper extends research on the role of accounting information in public debt contracting. Second, this study adds to the auditing literature about the impact of industry expertise. Finally, and more generally, this study adds to the ongoing controversy on the application of fair value accounting.

This study aims to investigate the impact of ex-ante regulatory interventions on emerging digital markets related to data sharing and combination practices. Specifically, it evaluates how such interventions influence market contestability by considering data network effects and the economic value of data.

The research uses agent-based modeling and simulations to analyze the dynamics of value generation and market competition related to the regulatory obligations on data sharing and combination practices.

Results show that while the promotion of data sharing through data portability and interoperability has a positive impact on the market, restricting data combination may damage value generation or, at best, have no positive impact even when it is imposed only on those platforms with very large market shares. More generally, the results emphasize the role of regulators in enabling the market through interoperability and service multihoming. Data sharing through portability fosters competition, while the usage of complementary data enhances platform value without necessarily harming the market. Service provider multihoming complements these efforts.

Although agent-based modeling and simulations describe the dynamics of data markets and platform competition, they do not provide accurate forecasts of possible market outcomes.

This paper presents a novel approach to understanding the dynamics of data value generation and the effects of related regulatory interventions. In the absence of real-world data, agent-based modeling provides a means to understand the general dynamics of data markets under different regulatory decisions that have yet to be implemented. This analysis is timely given the emergence of regulatory concerns on how to stimulate a competitive digital market and a shift toward ex-ante regulation, such as the regulatory obligations to large gatekeepers set in the Digital Markets Act.

Data protection is a significant area of law in a country like India, which is digitalising at a fast rate. Recently, India passed comprehensive data protection legislation after discussing several draft data protection frameworks. This paper aims to analyse the provisions of India’s first comprehensive data protection legislation, the Digital Personal Data Protection Act (DPDPA), 2023.

The paper aims to analyse how the DPDPA’s provisions should be interpreted. The methodology involves studying the act’s provisions, identifying shortcomings and suggesting ways of addressing the shortcomings through legal interpretation. The paper interprets DPDPA provisions through a comparative analysis with the proposed American Privacy Rights Act 2024 and EU General Data Protection Regulation. The methodology can be broadly classified as doctrinal and comparative legal research.

The paper makes several recommendations for interpreting the provisions of the DPDPA, which are discussed throughout the paper and summarised in the way forward section.

The analysis of this paper is limited to present-day data protection concerns. In the future, research can assess how the DPDPA can be interpreted to solve the challenges presented by societal and technological progress.

The originality and contribution of the paper are analysis and interpretation of the provisions of the DPDPA that will provide data principals with strong control over personal data and ensure stringent data protection obligations on data fiduciaries.

The study aims to add to the body of knowledge of open source tangible product management (also called open design). The objective is also to develop a guideline for efficient open source tangible product development and adoption.

The exploratory research design using secondary data (like newspapers, magazines, research articles, bogs, papers, etc.) is used to analyze open source tangible product design challenges and enablers. The success stories of Open Source Software projects (OSS) were studied for identification of critical success factors and further their relevancy was tested in the two popular cases of open source drug discovery (malaria and tuberculosis)

Open innovation has become a part of competitive strategy of current businesses. It requires an efficient intellectual property protection regime for its implementation. However, in a market dominated by proprietary benefits, the open source technology development can serve as remedy for innovation needs of neglected sectors. The OSS literature revealed managing two classes of factors, namely technology sponsor level factors and environmental factors for efficiency and effectiveness. The case study analysis in the context of applicability of these OSS critical factors showed their limitations in open source tangible products, and highlighted understanding additional challenges and remedies.

Open source innovation is a collaborative effort involving inputs from various/diverse players, hence monitoring the effort and motivation level of the contributors is a cumbersome task. Only the information that is available online and in print media is taken as research inputs in this work. Also the data taken were from two case studies; a lot more case studies in the open design domain can progress the theory. The implications of this study are far-reaching in the areas where profit motivated proprietary efforts lack in addressing societal need. It provides guidelines for addressing those unmet needs by developing products in a collaborative way without intellectual property hurdles.

The essence of open design is becoming more vital, and there is a pressing need to build theory to support it, which still is elusive and dispersed. The study fills the gap using secondary data and case study approach.

This study aims to evaluate Artificial Intelligence (AI) research in the hospitality industry based on the service AI framework (mechanical-thinking-feeling) and highlight prospective avenues for future inquiry in this growing domain.

This paper conceptualizes timely concepts supported by research spanning multiple domains.

This research introduces a novel classification for the domain of AI hospitality research. This classification encompasses prediction and pattern recognition, computer vision, NLP, behavioral research, and synthetic data generation. Based on this classification, this study identifies and elaborates upon five emerging research topics, each linked to a corresponding set of research questions. These focal points encompass the realms of interpretable AI, controllable AI, AI ethics, collaborative AI, and synthetic data generation.

This viewpoint provides a foundational framework and a directional compass for future research in AI within the hospitality industry. It pushes the industry forward with a balanced approach to leveraging AI to augment human potential and enrich customer experiences. Both the classification and the research agenda would contribute to the body of knowledge that will guide the industry toward a future where technology and human service coalesce to create unparalleled value for all stakeholders.