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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.

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.

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.

By offering a new ethically justified governance model, we may create a trust structure where rules are visible and all stakeholders are treated fairly.

Data economy is pervasively present in our everyday lives. Still, ordinary laypersons' chances to genuine communication with other stakeholders are scarce. This paper aims to raise awareness about communication patterns in the context of data economy and initiate a dialogue about laypersons' position in data economy ecosystems.

This conceptual paper covers theory-based critical reflection with ethical- and empirical-based remarks. It provides novel perspectives both for research and stakeholder collaboration.

The authors suggest invitational rhetoric and Habermasian discourse as instruments towards understanding partnership between all stakeholders of the data economy to enable laypersons to transfer from subjectivity to the agency.

The authors provide (1) theory-based critical reflection concerning communication patterns in the data economy; (2) both ethical and empirical-based remarks about laypersons' position in data economy and (3) ideas for interdisciplinary research and stakeholder collaboration practices by using invitational rhetoric and rational discourse. By that, this paper suggests taking a closer look at communication practices and ethics alike in the data economy. Moreover, it encourages clear, rational and justified arguments between stakeholders in a respectful and equal environment in the data economy ecosystems.

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.

The data economy mainly relies on the surveillance capitalism business model, enabling companies to monetize their data. The surveillance allows for transforming private human experiences into behavioral data that can be harnessed in the marketing sphere. This study aims to focus on investigating the domain of data economy with the methodological lens of quantitative bibliometric analysis of published literature.

The bibliometric analysis seeks to unravel trends and timelines for the emergence of the data economy, its conceptualization, scientific progression and thematic synergy that could predict the future of the field. A total of 591 data between 2008 and June 2021 were used in the analysis with the Biblioshiny app on the web interfaced and VOSviewer version 1.6.16 to analyze data from Web of Science and Scopus.

This study combined findable, accessible, interoperable and reusable (FAIR) data and data economy and contributed to the literature on big data, information discovery and delivery by shedding light on the conceptual, intellectual and social structure of data economy and demonstrating data relevance as a key strategic asset for companies and academia now and in the future.

Findings from this study provide a steppingstone for researchers who may engage in further empirical and longitudinal studies by employing, for example, a quantitative and systematic review approach. In addition, future research could expand the scope of this study beyond FAIR data and data economy to examine aspects such as theories and show a plausible explanation of several phenomena in the emerging field.

The researchers can use the results of this study as a steppingstone for further empirical and longitudinal studies.

This study confirmed the relevance of data to society and revealed some gaps to be undertaken for the future.

Smart cities require data governance to articulate data sharing and use among relevant stakeholders. Given the lack of a comprehensive examination of this research topic, this study aims to review data governance publications to detect and categorize endeavors backing up data sharing in smart cities.

A systematic literature review was conducted, and 568 academic and professional sources were identified, but finally, only 10 relevant papers were selected.

Results reveal that data governance must be based on well-defined mechanisms, procedures and roles to achieve accountability and responsibility in a multi-actor environment. Moreover, data governance should be adapted to address power imbalances among all interested parties.

The main limitation is the list of sources considered for the literature review. However, this study provides a holistic overview for researchers and professionals willing to know more about smart city data sharing.

This review identifies the data governance approaches supporting data sharing in smart cities, analyzes their data dimension, enhances the state-of-the-art literature on this topic and suggests possible areas for future research.

This study aims to examine the necessity effects of big data analytics capabilities (BDAC) on decision-making performance (DMP), particularly in the public sector.

The authors used the combined methods of partial least square structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) to test the hypothesized relationships.

The findings show that the presence of all three BDAC (infrastructure, management and personnel) is significant and necessary to achieve higher levels of DMP. Specifically, the results revealed big data management capabilities to be of higher necessity to achieve the highest possible DMP. The findings provide public-sector practitioners with insights to support the development of their BDAC.

Time-sensitive domains such as the public sector require insight and quality decision-making to create public value and achieve competitive advantage. This study examined BDAC in light of the combined methods of (PLS-SEM) and NCA to test the hypothesized relationships in the public sector context.

India ranks third in the global startup ecosystem in the world incubating more than 50,000 startups and witnessing 15% YoY growth per year. Being a center of innovation and skilled labor, Indian startups have attracted investments from all over the world. This paper aims at exploring the trends that are driving the growth in the Indian startup ecosystem.

Top 200 startups according to valuation are selected as a sample to find out the major trends in the Indian startup ecosystem. This paper includes surveying the sample startups about the implementation of trends such as big data, crowdfunding and shared economy in their startup and its tangible, as well as intangible impacts on their business. The result of the survey is analyzed to get an overview of the emerging trends in the Indian startup ecosystem.

Major ten emerging trends that drive growth in the Indian startup ecosystem are discovered and the areas where these trends can be leveraged are identified.

This research has contributed toward structuring and documenting the growth driving trends, and it will help the budding entrepreneurs to get familiar with the contemporary trends, pros and cons associated with it and the ways to leverage these trends to build a successful startup.

The purpose of this paper is to analyse the development and evolution of industrial innovation ecosystems of Around-Tongji Knowledge Economy Circle from the three levels mentioned above, focusing on knowledge-producing populations, core populations and service-supporting populations, and to further develop this research framework by combining with the latest developments.

Based on the five-helix theory and economic census statistical data, this paper adopts geographic information system technology and examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji knowledge economy circle.

The knowledge product populations lead the development of industries in Around-Tongji Knowledge Economy Circle. It contributes political capital output for the government. It innovates community cooperation and governance mode, and it improves the natural ecological environment. In the face of the changes and challenges in the development environment, the future development must be recognised from the height of the iterative development of the interaction mode between university knowledge production and economic and social development.

Based on the five-helix theory and economic census statistical data, this paper examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji Knowledge Economy Circle. It further expands the research framework used to develop a synergistic evolution model, which reveals the interactive and synergistic relationship among the populations and the evolution characteristics of the entire industrial innovation ecosystem. This paper also provides useful perspectives for the study of the industrial innovation ecosystem.

Tech startup is the new hope for sustaining economic growth and job creation in a knowledge-based economy. However, research on the entrepreneurial ecosystem (EE) is always constructed upon macro-level analysis and is still very limited to the developed economies. This study aims to tackle those issues by exploring the connections within an EE in an emerging economies context with a micro and meso-level social network approach to unravel the pattern of networks and interactions between each actor in the EE.

This research used multi-layered social network analysis, exploring actors in the ecosystem and their interactions. The authors conducted interviews with startups, support organizations and government agencies. The authors used Atlas.ti software to visualize the network structures.

The authors found that the content of interaction within the EE in the emerging economies differs greatly with EE in the developed economies and they produced distinctive characteristics as follows: lack of a dense network, resource scarcities and structural gaps and weak institutional policies.

The research is based on a case study of tech-based EE in Yogyakarta, Indonesia. Therefore, the authors encourage other researchers to investigate networks and connections in other EEs in emerging economies. This research contributes a conceptual framework to better understand the network of connections in an emerging-economies-based EE.

The research shows grants provision alone cannot contribute to the functioning of EE. The authors argue strategic networks which promote collaboration among actors can reduce holes and structural gaps, as well as resource scarcities in the ecosystem. In addition to that, strong institutional policies and effective policy integration are needed to create a successful EE.

This research promotes the importance of networks, particularly networks between tech startups and strategic organizations to provide resources and support productive entrepreneurship in hopes of sustaining and accelerating tech startup growth within an EE.

The research proposes to add to the existing EE literature by shedding light on governance of EE, as well as exploring network of connection and interaction among actors within the ecosystem. As a result, the study addresses the need for a more micro or operational-level understanding of an EE. Recent calls for EEs literature have also focused on a certain actor’s dynamic function in the ecosystem. By focusing on the role of the government, the research added to the underdeveloped EE literature.