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1 – 10 of over 4000Jani Koskinen, Sari Knaapi-Junnila, Ari Helin, Minna Marjaana Rantanen and Sami Hyrynsalmi
Data economy is a recent phenomenon, raised by digital transformation and platformisation, which has enabled the concentration of data that can be used in economic purposes…
Abstract
Purpose
Data economy is a recent phenomenon, raised by digital transformation and platformisation, which has enabled the concentration of data that can be used in economic purposes. However, there is a lack of clear procedures and ethical rules on how data economy ecosystems are governed. As a response to the current situation, there has been criticism and demands for the governance of data use to prevent unethical consequences that have already manifested. Thus, ethical governance of the data economy ecosystems is needed. The purpose of this paper is to introduce a new ethical governance model for data economy ecosystems. The proposed model offers a more balanced solution for the current situation where a few global large-scale enterprises dominate the data market and may use oligopolistic power over other stakeholders.
Design/methodology/approach
This is a conceptual article that covers theory-based discourse ethical reflection of data economy ecosystems governance. The study is based on the premise of the discourse ethics where inclusion of all stakeholders is needed for creating a transparent and ethical data economy.
Findings
This article offers self-regulation tool for data economy ecosystems by discourse ethical approach which is designed in the governance model. The model aims to balance data “markets” by offering more transparent, democratic and equal system than currently.
Originality/value
By offering a new ethically justified governance model, we may create a trust structure where rules are visible and all stakeholders are treated fairly.
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Keywords
Tom A.E. Aben, Wendy van der Valk, Jens K. Roehrich and Kostas Selviaridis
Inter-organisational governance is an important enabler for information processing, particularly in relationships undergoing digital transformation (DT) where partners depend on…
Abstract
Purpose
Inter-organisational governance is an important enabler for information processing, particularly in relationships undergoing digital transformation (DT) where partners depend on each other for information in decision-making. Based on information processing theory (IPT), the authors theoretically and empirically investigate how governance mechanisms address information asymmetry (uncertainty and equivocality) arising in capturing, sharing and interpreting information generated by digital technologies.
Design/methodology/approach
IPT is applied to four cases of public–private relationships in the Dutch infrastructure sector that aim to enhance the quantity and quality of information-based decision-making by implementing digital technologies. The investigated relationships are characterised by differing degrees and types of information uncertainty and equivocality. The authors build on rich data sets including archival data, observations, contract documents and interviews.
Findings
Addressing information uncertainty requires invoking contractual control and coordination. Contract clauses should be precise and incentive schemes functional in terms of information requirements. Information equivocality is best addressed by using relational governance. Identifying information requirements and reducing information uncertainty are a prerequisite for the transformation activities that organisations perform to reduce information equivocality.
Practical implications
The study offers insights into the roles of both governance mechanisms in managing information asymmetry in public–private relationships. The study uncovers key activities for gathering, sharing and transforming information when using digital technologies.
Originality/value
This study draws on IPT to study public–private relationships undergoing DT. The study links contractual control and coordination as well as relational governance mechanisms to information-processing activities that organisations deploy to reduce information uncertainty and equivocality.
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Louise Holly, Shannon Thom, Mohamed Elzemety, Beatrice Murage, Kirsten Mathieson and Maria Isabel Iñigo Petralanda
This paper introduces a new set of equity and rights-based principles for health data governance (HDG) and makes the case for their adoption into global, regional and national…
Abstract
Purpose
This paper introduces a new set of equity and rights-based principles for health data governance (HDG) and makes the case for their adoption into global, regional and national policy and practice.
Design/methodology/approach
This paper discusses the need for a unified approach to HDG that maximises the value of data for whole populations. It describes the unique process employed to develop a set of HDG principles. The paper highlights lessons learned from the principle development process and proposes steps to incorporate them into data governance policies and practice.
Findings
More than 200 individuals from 130 organisations contributed to the development of the HDG principles, which are clustered around three interconnected objectives of protecting people, promoting health value and prioritising equity. The principles build on existing norms and guidelines by bringing a human rights and equity lens to HDG.
Practical implications
The principles offer a strong vision for HDG that reaps the public good benefits of health data whilst safeguarding individual rights. They can be used by governments and other actors as a guide for the equitable collection and use of health data. The inclusive model used to develop the principles can be replicated to strengthen future data governance approaches.
Originality/value
The article describes the first bottom-up effort to develop a set of principles for HDG.
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Anca Yallop and Hugues Seraphin
The purpose of this paper is to examine and provide insights into one of the most influential technologies impacting the tourism and hospitality industry over the next five years…
Abstract
Purpose
The purpose of this paper is to examine and provide insights into one of the most influential technologies impacting the tourism and hospitality industry over the next five years, i.e. big data and analytics. It reflects on both opportunities and risks that such technological advances create for both consumers and tourism organisations, highlighting the importance of data governance and processes for effective and ethical data management in both tourism and hospitality.
Design/methodology/approach
This paper is based on a review of academic and industry literature and access to trends data and information from a series of academic and industry databases and reports to examine how big data and analytics shape the future of the industry and the associated risks and opportunities.
Findings
This paper identifies and examines key opportunities and risks posed by the rising technological trend of big data and analytics in tourism and hospitality. While big data is generally regarded as beneficial to tourism and hospitality organisations, there are extensively held ethical, privacy and security concerns about it. Therefore, the paper is making the case for more research on data governance and data ethics in tourism and hospitality and posits that to successfully use data for competitive advantage, tourism and hospitality organisations need to solely expand compliance-based data governance frameworks to frameworks that include more effective privacy and ethics data solutions.
Originality/value
This paper provides useful insights into the use of big data and analytics for both researchers and practitioners and offers new perspectives on the debate on data governance and ethical data management in both tourism and hospitality. Because forecasts from the UNWTO indicate a significant increase in international tourist arrivals (1.8 billion tourist arrivals by 2030), the ways tourism and hospitality organisations manage customers’ data become important.
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Malkiat Thiarai, Sarunkorn Chotvijit and Stephen Jarvis
There is significant national interest in tackling issues surrounding the needs of vulnerable children and adults. This paper aims to argue that much value can be gained from the…
Abstract
Purpose
There is significant national interest in tackling issues surrounding the needs of vulnerable children and adults. This paper aims to argue that much value can be gained from the application of new data-analytic approaches to assist with the care provided to vulnerable children. This paper highlights the ethical and information governance issues raised in the development of a research project that sought to access and analyse children’s social care data.
Design/methodology/approach
The paper documents the process involved in identifying, accessing and using data held in Birmingham City Council’s social care system for collaborative research with a partner organisation. This includes identifying the data, its structure and format; understanding the Data Protection Act 1998 and 2018 (DPA) exemptions that are relevant to ensure that legal obligations are met; data security and access management; the ethical and governance approval process.
Findings
The findings will include approaches to understanding the data, its structure and accessibility tasks involved in addressing ethical and legal obligations and requirements of the ethical and governance processes.
Originality/value
The aim of this research is to highlight the potential use of use new data-analytic techniques to examine the flow of children’s social care data from referral, through the assessment process, to the resulting service provision. Data held by Birmingham City Council are used throughout, and this paper highlights key ethical and information governance issues which were addressed in preparing and conducting the research. The findings provide insight for other data-led studies of a similar nature.
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The purpose of this paper is to survey how research data are governed at repositories in Japan by deductively establishing a governance typology based on the concept of openness…
Abstract
Purpose
The purpose of this paper is to survey how research data are governed at repositories in Japan by deductively establishing a governance typology based on the concept of openness in the context of knowledge commons and empirically assessing the conformity of repositories to each type.
Design/methodology/approach
The fuzzy-set ideal type analysis (FSITA) was adopted. For data collection, a manual assessment was conducted with all Japanese research data repositories registered on re3data.org.
Findings
The typology constructed in this paper consists of three dimensions: openness to resources (here equal to research data), openness to a community and openness to infrastructure provision. This paper found that there is no case where all dimensions are open, and there are several cases where the resources are closed despite research data repositories being positioned as a basis for open science in Japanese science and technology policy.
Originality/value
This is likely the first construction of the typology and application of FSITA to the study of research data governance based on knowledge commons. The findings of this paper provide practitioners insight into how to govern research data at repositories. The typology serves as a first step for future research on knowledge commons, for example, as a criterion of case selection in conducting in-depth case studies.
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Teemu Birkstedt, Matti Minkkinen, Anushree Tandon and Matti Mäntymäki
Following the surge of documents laying out organizations' ethical principles for their use of artificial intelligence (AI), there is a growing demand for translating ethical…
Abstract
Purpose
Following the surge of documents laying out organizations' ethical principles for their use of artificial intelligence (AI), there is a growing demand for translating ethical principles to practice through AI governance (AIG). AIG has emerged as a rapidly growing, yet fragmented, research area. This paper synthesizes the organizational AIG literature by outlining research themes and knowledge gaps as well as putting forward future agendas.
Design/methodology/approach
The authors undertake a systematic literature review on AIG, addressing the current state of its conceptualization and suggesting future directions for AIG scholarship and practice. The review protocol was developed following recommended guidelines for systematic reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).
Findings
The results of the authors’ review confirmed the assumption that AIG is an emerging research topic with few explicit definitions. Moreover, the authors’ review identified four themes in the AIG literature: technology, stakeholders and context, regulation and processes. The central knowledge gaps revealed were the limited understanding of AIG implementation, lack of attention to the AIG context, uncertain effectiveness of ethical principles and regulation, and insufficient operationalization of AIG processes. To address these gaps, the authors present four future AIG agendas: technical, stakeholder and contextual, regulatory, and process. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.
Research limitations/implications
To address the identified knowledge gaps, the authors present the following working definition of AIG: AI governance is a system of rules, practices and processes employed to ensure an organization's use of AI technologies aligns with its strategies, objectives, and values, complete with legal requirements, ethical principles and the requirements set by stakeholders. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.
Practical implications
For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.
Social implications
For society, the authors review elucidates the multitude of stakeholders involved in AI governance activities and complexities related to balancing the needs of different stakeholders.
Originality/value
By delineating the AIG concept and the associated research themes, knowledge gaps and future agendas, the authors review builds a foundation for organizational AIG research, calling for broad contextual investigations and a deep understanding of AIG mechanisms. For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.
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Tina Peeters, Jaap Paauwe and Karina Van De Voorde
The purpose of this paper is to explore the key ingredients that people analytics teams require to contribute to organizational performance. As the information that is currently…
Abstract
Purpose
The purpose of this paper is to explore the key ingredients that people analytics teams require to contribute to organizational performance. As the information that is currently available is fragmented, it is difficult for organizations to understand what it takes to execute people analytics successfully.
Design/methodology/approach
To identify the key ingredients, a narrative literature review was conducted using both traditional people analytics and broader business intelligence literature. The findings were summarized in the People Analytics Effectiveness Wheel.
Findings
The People Analytics Effectiveness Wheel identifies four categories of ingredients that a people analytics team requires to be effective. These are enabling resources, products, stakeholder management and governance structure. Under each category, multiple sub-themes are discussed, such as data and infrastructure; senior management support; and knowledge, skills, abilities and other characteristics (KSAOs) (enablers).
Practical implications
Many organizations are still trying to set up their people analytics teams, and many others are struggling to improve decision-making by using people analytics. For these companies, this paper provides a comprehensive overview of the current literature and describes what it takes to contribute to organizational performance using people analytics.
Originality/value
This paper is designed to provide organizations and researchers with a comprehensive understanding of what it takes to execute people analytics successfully. By using the People Analytics Effectiveness Wheel as a guideline, scholars are now better equipped to research the processes that are required for the ingredients to be truly effective.
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Susanne Leitner-Hanetseder and Othmar M. Lehner
With the help of “self-learning” algorithms and high computing power, companies are transforming Big Data into artificial intelligence (AI)-powered information and gaining…
Abstract
Purpose
With the help of “self-learning” algorithms and high computing power, companies are transforming Big Data into artificial intelligence (AI)-powered information and gaining economic benefits. AI-powered information and Big Data (simply data henceforth) have quickly become some of the most important strategic resources in the global economy. However, their value is not (yet) formally recognized in financial statements, which leads to a growing gap between book and market values and thus limited decision usefulness of the underlying financial statements. The objective of this paper is to identify ways in which the value of data can be reported to improve decision usefulness.
Design/methodology/approach
Based on the authors' experience as both long-term practitioners and theoretical accounting scholars, the authors conceptualize and draw up a potential data value chain and show the transformation from raw Big Data to business-relevant AI-powered information during its process.
Findings
Analyzing current International Financial Reporting Standards (IFRS) regulations and their applicability, the authors show that current regulations are insufficient to provide useful information on the value of data. Following this, the authors propose a Framework for AI-powered Information and Big Data (FAIIBD) Reporting. This framework also provides insights on the (good) governance of data with the purpose of increasing decision usefulness and connecting to existing frameworks even further. In the conclusion, the authors raise questions concerning this framework that may be worthy of discussion in the scholarly community.
Research limitations/implications
Scholars and practitioners alike are invited to follow up on the conceptual framework from many perspectives.
Practical implications
The framework can serve as a guide towards a better understanding of how to recognize and report AI-powered information and by that (a) limit the valuation gap between book and market value and (b) enhance decision usefulness of financial reporting.
Originality/value
This article proposes a conceptual framework in IFRS to regulators to better deal with the value of AI-powered information and improve the good governance of (Big)data.
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Artificial intelligence (AI) reasoning is fuelled by high-quality, detailed behavioural data. These can usually be obtained by the biometrical sensors embedded in smart devices…
Abstract
Purpose
Artificial intelligence (AI) reasoning is fuelled by high-quality, detailed behavioural data. These can usually be obtained by the biometrical sensors embedded in smart devices. The currently used data collecting approach, where data ownership and property rights are taken by the data scientists, designers of a device or a related application, delivers multiple ethical, sociological and governance concerns. In this paper, the author is opening a systemic examination of a data sharing concept in which data producers execute their data property rights.
Design/methodology/approach
Since data sharing concept delivers a substantially different alternative, it needs to be thoroughly examined from multiple perspectives, among them: the ethical, social and feasibility. At this stage, theoretical examination modes in the form of literature analysis and mental model development are being performed.
Findings
Data sharing concepts, framework, mechanisms and swift viability are examined. The author determined that data sharing could lead to virtuous data science by augmenting data producers' capacity to govern their data and regulators' capacity to interact in the process. Truly interdisciplinary research is proposed to follow up on this research.
Research limitations/implications
Since the research proposal is theoretical, the proposal may not provide direct applicative value but is largely focussed on fuelling the research directions.
Practical implications
For the researchers, data sharing concepts will provide an alternative approach and help resolve multiple ethical considerations related to the internet of things (IoT) data collecting approach. For the practitioners in data science, it will provide numerous new challenges, such as distributed data storing, distributed data analysis and intelligent data sharing protocols.
Social implications
Data sharing may post significant implications in research and development. Since ethical, legislative moral and trust-related issues are managed in the negotiation process, data can be shared freely, which in a practical sense expands the data pool for virtuous research in social sciences.
Originality/value
The paper opens new research directions of data sharing concepts and space for a new field of research.
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