Call for Papers

CfP special issue on "AI-enabled information systems: Teaming up with intelligent agents in networked business"

No longer accepting submissions

 

Guest editors

Theme

Artificial Intelligence (AI) technologies promise new ways to solve (existing) problems, resulting in new paths toward business value. While the understanding of what constitutes AI technologies has continued to change over time, machine learning has now become the focus of applied research and practice (Janiesch et al. 2021). Besides AI technologies’ capabilities to outperform humans in certain tasks, it is the “ability to learn and act autonomously [that] makes intelligent technological actors very different from most technologies historically used in organizations” (Bailey et al., 2019, p. 643). Beyond intelligent agents’ capabilities to contribute to work systems, inscrutability issues as technology-implied constraints are particularly salient in research discussions (Berente et al. 2021). Accordingly, the integration of intelligent agents in work systems is calling into question our existing assumptions about networked business.

Motivated by the need to understand intelligent agents’ roles and impacts in networked business, this call for papers focuses on the appropriate design of AI-enabled information systems as well as their accompanying management. This comes with multifaceted and fascinating questions for the IS discourse whose answers take a socio-technical perspective on the changing interaction within organizations (individuals, teams, etc.) and between organizations. Particularly, we call for research on forms of networked business where intelligent and human agents interact for economic purposes within one or among multiple tiers in economic value chains. We are enthusiastic about research that elaborates on the configuration of human-AI teamwork, including associated choices in (inter-) organizational design, work system setups, and customer interaction.

Central issues and topics

This special issue of Electronic Markets will focus on intra- and inter-organizational design as well as managerial, methodological, and operational practices. We welcome research papers that bridge the gap between technological and organizational issues, emphasizing which of AI technologies’ characteristics constitutes the subject of the study. We advocate a deliberate examination of different technology and application contexts. Method-wise, we welcome all established IS research approaches, including design- and behavior-oriented research approaches as well as conceptual papers.

The (non-exclusive) list of topics comprises:

  • Managing AI-enabled work systems
  • Intra-organizational collaboration with AI-enabled agents
  • (Group) Collaboration and value (co-)creation in human-AI teamwork settings
  • Human-AI teamwork’s implications for organizational roles, practices, and structures
  • Efficient and human-centered design of human-AI collaboration
  • Dark side of human-AI collaboration
  • AI technologies’ potential for customer interaction
  • Algorithmic hiring and management
  • Standardization and semantic interoperability of data for AI/by AI
  • AI in interorganizational and cross-industry data platforms/spaces

Submission guidelines

Electronic Markets is a Social Science Citation Index (SSCI)-listed journal (IF 8.5 in 2022) 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 www.electronicmarkets.org/about-em/scope/) and will undergo a double-blind peer-review process. Submissions must be original, not published, or under review elsewhere. They must be submitted via the journal’s submission system (elma.edmgr.com) and comply with the journal's formatting standards. The preferred average article length is approximately 10,000 words, excluding references. Instructions, templates and general information are available at www.electronicmarkets.org/authors/general-information/. If you would like to discuss any aspect of this special issue, you may either contact the guest editors or the Editorial Office.

Important deadlines

Submission deadline: April 30, 2023

References

Bailey, D., Faraj, S., Hinds, P., von Krogh, G., & Leonardi, P. (2019). Special issue of organization science: Emerging technologies and organizing. Organization Science, 30(3), 642-646. https://doi.org/10.1287/orsc.2019.1299

Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Special issue editor’s comments: Managing artificial intelligence. MIS Quarterly, 45(3), 1433-1450. https://www.researchgate.net/publication/352400557_Managing_Artificial_Intelligence

Janiesch, C., Zschech, P., & Heinrich, K. (2021). Machine learning and deep learning. Electronic Markets, 31(3), 685–695. https://doi.org/10.1007/s12525-021-00475-2