Call for Papers

CfP special issue on "Data economy in a globalized world: Opportunities and challenges for public and private organizations"

No longer accepting submissions

Guest editors



Because of digitalisation and the intensive use of Information and Communication Technologies (ICT), public and private organisations are generating, collecting and analysing massive amounts of data. For example, it is estimated that the production of data will grow from 33 zettabytes in 2018 to 175 zettabytes by 2025 (European Commission, 2020). These data are generated from multiple data sources, including but not limited to mobile devices, social media platforms, cloud computing facilities, and government infrastructures. In addition, data are increasingly accessible through data-exchange platforms that transcend organizational and even industry boundaries (Beverungen et al., 2022)

The massive availability of data creates several opportunities for public and private organizations. For example, data enable new ways to create and capture value (Fürstenau et al., 2021). Private parties are looking at new business models to monetise data (Loebbecke & Picot, 2015). Public organizations are exploring how to use external data to streamline their tasks: ranging from public service delivery during disasters (Morabito, 2015) to improving transparency of data to monitor circular economy flows in supply chains (Alt, 2021).

The essential role of data for socio-economic activities also poses significant challenges at multiple levels for many organisations. On a strategic level, competing and conflicting goals may arise between organizations sharing data, especially if organizations operate in distinct institutional settings (Aaen, Nielsen, & Carugati, 2021). Regarding governance, organisations must consider an evolving landscape of stringent rules and norms when exchanging, processing, and extracting value from data (Janssen, Brous, Estevez, Barbosa, & Janowski, 2020). On a technical level, data exchanged among multiple actors may result in identity management, privacy, and security concerns (Ishmaev, 2021). To harness these challenges, solutions are likely needed that address strategic, governance and technical aspects.

Further, while prior research emphasises that data are critical for organisations, concerted efforts examining governance in data-centric ecosystems and collaborations between private and public organisations are lacking (Abraham, Schneider, & Vom Brocke, 2019). More broadly, detailed insights and implications of fundamental aspects such as privacy and stakeholder trust in the data economy are needed.

This special issue intends to advance current theoretical and empirical knowledge on organising in the data economy. We are interested in a broad range of contributions using quantitative, qualitative, or mixed research approaches. More specifically, we call for papers that advance our understanding of the impact of data governance, strategies, management, and analytics in organizing in the data economy. We are also interested in the impact of the data-rich environment on privacy, business models, and inter-organisational collaboration.

Central issues and topics

Examples of potential research topics may include but are not limited to the following:

  • Characteristics of data and impacts on data governance
  • Data analytics and organisational change processes
  • Privacy-enhancing business models
  • Data management practices in the new data-rich environment
  • Scaling strategies for data platforms
  • Governance of private-public data-sharing partnerships
  • Data governance models promoting privacy
  • New forms of trust emerging in data-sharing collaborations
  • Reliability and authenticity of datasets
  • Sociotechnical solutions to challenges in the data economy
  • Best practices for data visibility and transparency across platforms and ecosystems
  • Competing tensions and solutions in data-driven collaborations
  • Data sharing in the context of circular economy and sustainability

Submission guidelines

Electronic Markets is a Social Science Citation Index (SSCI)-listed journal (IF 6.017 in 2021) in the area of information systems. We encourage original contributions with a broad range of methodological approaches, including conceptual, qualitative, and quantitative research. Please also consider position papers and case studies for this special issue. All papers should fit the journal scope (for more information, see and will undergo a double-blind peer-review process. All papers must be original, not published, or under review elsewhere. Papers must be submitted via our electronic submission system at The preferred average article length is approximately 10,000 words, excluding references. Instructions, templates and general information are available at You may contact the guest editors if you would like to discuss any aspect of this special issue.

Important deadline

Full articles submissions due: April 01, 2023


Aaen, J., Nielsen, J. A., & Carugati, A. (2021). The dark side of data ecosystems: A longitudinal study of the DAMD project. European Journal of Information Systems, 1-25.

Abraham, R., Schneider, J., & Vom Brocke, J. (2019). Data governance: A conceptual framework, structured review, and research agenda. International Journal of Information Management, 49, 424-438.

Alt, R. (2021). How to organize for AI? An interview with Yao-Hua Tan. Electronic Markets, 31(3), 639–642.

Beverungen, D., Hess, T., Köster, A., & Lehrer, C. (2022). From private digital platforms to public data spaces: Implications for the digital transformation. Electronic Markets, 32(2).

European Commission. (2020). A European strategy for data.

Fürstenau, D., Klein, S., Vogel, A., & Auschra, C. (2021). Multi-sided platform and data-driven care research. Electronic Markets, 31(4), 811–828.

Ishmaev, G. (2021). Sovereignty, privacy, and ethics in blockchain-based identity management systems. Ethics and Information Technology, 23(3), 239-252.

Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., & Janowski, T. (2020). Data governance: Organising data for trustworthy Artificial Intelligence. Government Information Quarterly, 37(3), 101493.

Loebbecke, C., & Picot, A. (2015).Reflections on societal and business model transformation arising from digitisation and big data analytics: A research agenda. The Journal of Strategic Information Systems, 24(3), 149-157.

Morabito, V. (2015). Big data and analytics for government innovation. In Big data and analytics (pp. 23-45): Springer.