2,617 research outputs found

    Data Trading and Monetization: Challenges and Open Research Directions

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    Traditional data monetization approaches face challenges related to data protection and logistics. In response, digital data marketplaces have emerged as intermediaries simplifying data transactions. Despite the growing establishment and acceptance of digital data marketplaces, significant challenges hinder efficient data trading. As a result, few companies can derive tangible value from their data, leading to missed opportunities in understanding customers, pricing decisions, and fraud prevention. In this paper, we explore both technical and organizational challenges affecting data monetization. Moreover, we identify areas in need of further research, aiming to expand the boundaries of current knowledge by emphasizing where research is currently limited or lacking.Comment: Paper accepted by the International Conference on Future Networks and Distributed Systems (ICFNDS 2023

    Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research

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    This paper reviews the published articles on eTourism in the past 20 years. Using a wide variety of sources, mainly in the tourism literature, this paper comprehensively reviews and analyzes prior studies in the context of Internet applications to Tourism. The paper also projects future developments in eTourism and demonstrates critical changes that will influence the tourism industry structure. A major contribution of this paper is its overview of the research and development efforts that have been endeavoured in the field, and the challenges that tourism researchers are, and will be, facing

    Is Your Organization Ready to Share? A Framework of Beneficial Conditions for Data Sharing

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    In a constantly evolving digital sphere, surmounting organizational boundaries and sharing data offers the opportunity to realize a multitude of mutual benefits, such as advanced analytics and innovative services. Organizations aspire to share data. However, they struggle to identify and establish beneficial conditions for data sharing, and research still offers little support to exploit the potential of data sharing. We apply an exploratory research approach to develop a framework of beneficial conditions for data sharing. By combining ten expert interviews and a systematic literature review, we aggregate 23 characteristics that constitute beneficial conditions into eight categories and apply and validate the framework in a real-world case. Thus, we contribute to research by providing a fundamental understanding of beneficial conditions for data sharing and a compact target picture. Additionally, we enable practitioners to systematically assess an organization’s current condition to set the course toward exploiting the full potential of data sharing

    Mapping the Path to a Health Data Marketplace in Norway: An Exploratory Case Study

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    This Master's thesis explores the complex dynamics of health data in the digital age, focusing on its secure and efficient management and ethical considerations. It investigates the potential of implementing a Health Data Marketplace (HDM) in the Norwegian e-health sector, aiming to construct a seamless health data exchange platform. This study proposes the integration of an existing health data gateway, the Egde Health Gateway (EHG), with the HDM. The research offers an in-depth analysis of existing limitations in health data exchange systems in Norway. It addresses current research gaps in Data Marketplace, Business Models, Gateways, and the Norwegian e-health context. Guided by two central research questions, this thesis delves into identifying essential components required to successfully implement an HDM in Norway and how this marketplace could be established using an existing data platform. Significantly, the thesis underscores the pivotal role of primary stakeholders in the HDM - Platform Operators, Platform Users, and Legal Authorities. The exploration reveals that Platform Operators are vital influencers, fostering collaboration and innovation within the ecosystem, while Platform Users and Legal Authorities ensure the marketplace's innovative and compliance aspects. Additionally, this study identifies essential components for successfully integrating an HDM into an existing health data platform, including Data Standardization, Interoperability, Integration, Security, Trust, and Legal Frameworks, among others. The thesis marks a significant step towards realizing an HDM in the Norwegian e-health sector. It invites future research to broaden stakeholder perspectives, examine economic aspects of the HDM, and delve into ethical considerations and technological innovations. The findings from this exploration serve as a catalyst for leveraging health data effectively, securely, and ethically, contributing to improved healthcare outcomes, research, and innovation in Norway and beyond

    Mapping the Path to a Health Data Marketplace in Norway: An Exploratory Case Study

    Get PDF
    This Master's thesis explores the complex dynamics of health data in the digital age, focusing on its secure and efficient management and ethical considerations. It investigates the potential of implementing a Health Data Marketplace (HDM) in the Norwegian e-health sector, aiming to construct a seamless health data exchange platform. This study proposes the integration of an existing health data gateway, the Egde Health Gateway (EHG), with the HDM. The research offers an in-depth analysis of existing limitations in health data exchange systems in Norway. It addresses current research gaps in Data Marketplace, Business Models, Gateways, and the Norwegian e-health context. Guided by two central research questions, this thesis delves into identifying essential components required to successfully implement an HDM in Norway and how this marketplace could be established using an existing data platform. Significantly, the thesis underscores the pivotal role of primary stakeholders in the HDM - Platform Operators, Platform Users, and Legal Authorities. The exploration reveals that Platform Operators are vital influencers, fostering collaboration and innovation within the ecosystem, while Platform Users and Legal Authorities ensure the marketplace's innovative and compliance aspects. Additionally, this study identifies essential components for successfully integrating an HDM into an existing health data platform, including Data Standardization, Interoperability, Integration, Security, Trust, and Legal Frameworks, among others. The thesis marks a significant step towards realizing an HDM in the Norwegian e-health sector. It invites future research to broaden stakeholder perspectives, examine economic aspects of the HDM, and delve into ethical considerations and technological innovations. The findings from this exploration serve as a catalyst for leveraging health data effectively, securely, and ethically, contributing to improved healthcare outcomes, research, and innovation in Norway and beyon

    Revealing the Landscape of Privacy-Enhancing Technologies in the Context of Data Markets for the IoT: A Systematic Literature Review

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    IoT data markets in public and private institutions have become increasingly relevant in recent years because of their potential to improve data availability and unlock new business models. However, exchanging data in markets bears considerable challenges related to disclosing sensitive information. Despite considerable research focused on different aspects of privacy-enhancing data markets for the IoT, none of the solutions proposed so far seems to find a practical adoption. Thus, this study aims to organize the state-of-the-art solutions, analyze and scope the technologies that have been suggested in this context, and structure the remaining challenges to determine areas where future research is required. To accomplish this goal, we conducted a systematic literature review on privacy enhancement in data markets for the IoT, covering 50 publications dated up to July 2020, and provided updates with 24 publications dated up to May 2022. Our results indicate that most research in this area has emerged only recently, and no IoT data market architecture has established itself as canonical. Existing solutions frequently lack the required combination of anonymization and secure computation technologies. Furthermore, there is no consensus on the appropriate use of blockchain technology for IoT data markets and a low degree of leveraging existing libraries or reusing generic data market architectures. We also identified significant challenges remaining, such as the copy problem and the recursive enforcement problem that-while solutions have been suggested to some extent-are often not sufficiently addressed in proposed designs. We conclude that privacy-enhancing technologies need further improvements to positively impact data markets so that, ultimately, the value of data is preserved through data scarcity and users' privacy and businesses-critical information are protected.Comment: 49 pages, 17 figures, 11 table

    The art of online arbitrage: essential practices for third-party sellers

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    The topic of arbitrage is an essential concept in the financial world. It involves taking advantage of price discrepancies for an asset or security across different markets. The emerging third-party retail and online e-commerce arbitrage sellers industry is growing and becoming a popular income source for many individuals. While there is various research on arbitrage and its impact on the economy, there is scant literature on third-party retail e-commerce arbitrage selling. The goal of this research is to build upon existing scholarly work by examining optimal methods, tactics, and obstacles encountered by e-commerce arbitrage sellers who operate through third-party retail platforms. A phenomenological methodology was employed to capture the firsthand experiences of seasoned professionals in the field. Twelve third-party e-commerce sellers who met inclusion criteria were interviewed and asked 11 interview questions designed to elicit detailed and nuanced answers. Thematic analysis was employed to code and categorize the interview data. Forty-nine overarching themes were identified and condensed to create the ACES Framework, which can be used as a guide for success in third-party retail e-commerce arbitrage selling
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