Call for Papers

Call for short papers (pdf)

More than ever before, technology touches our lives. While humans have always made use of tools, the way in which technology has become an intimate part of our lives is unprecedented. Especially digital technology stands out in how it shapes day-to-day interactions, moral values, relationships, and work. More than ever before we have become dependent on technology which means that we need to figure out how to move forward.
 
These changes are especially relevant for knowledge and knowledge work. The extant literature on the nature of knowledge (Hadjimichael & Tsoukas, 2019), on processes and mechanisms of knowledge sharing (Anthony, 2021; Moser & Deichmann, 2021; Nonaka & von Krogh, 2009; Safadi et al., 2021), and on the technology that is being used to work with and on knowledge (Bailey et al., 2022) testifies to the central role that knowledge and associated processes and boundary conditions play in management research and practice. More recently, scholars have paid increasing attention to the intersection of knowledge and (digital) technology, studying the role of technology in knowledge work and management research (Faraj & Leonardi, 2022; den Hond & Moser, 2023; Orlikowski & Scott, 2008), as well as algorithms (Glaser et al., 2021; Kellogg et al., 2020; Moser et al., 2022; Shrestha et al., 2019) in business and society.
 
Much research on emerging technologies and knowledge work remains deeply rooted in long-established scholarly traditions. The scholarly discourse on digital technology – most notably artificial intelligence (AI) applications in knowledge work – is sharply divided into two camps. Digital technology is either celebrated as the savior of humankind, rescuing us from inevitable decline, or condemned as a path to disaster, eroding human essence and turning us into machines. Clearly, neither view adequately reflects the realities of knowledge and knowledge work.
 
For most knowledge workers, digital technology offers both benefits and drawbacks, although the balance of these varies across individuals, organizations, disciplines, and professions. Cultural, historical, regional, spatial, and other contexts significantly influence the experiences of those who engage in knowledge work and interact with technology. If we are to truly understand the complex processes and boundary conditions of emerging technologies in knowledge work, research must examine both the positive and negative aspects of these tools as they rearrange work and organizing relations. This need is especially acute as Large Language Models (LLMs) compel us to question our fundamental assumptions about the relation between technology and knowledge. New research that problematizes these assumptions can help us reframe our understanding of the antecedents, processes, and implications of technology in knowledge work. This effort may require adopting unconventional frameworks that extend beyond traditional approaches, such as Science and Technology Studies (STS) or pragmatism, to address the deeper questions surrounding the relationship between technology, knowledge, and work.
 
In this sub-theme, we look forward to accepting conceptual and empirical articles that address this conundrum. We particularly look to scholarly work that pays attention to the intersection of different people, technologies, spaces, temporalities for knowledge, and changing relations in the context of knowledge work. The sub-theme intends to stimulate a constructive dialogue around conceptual and empirical research across these and related issues. High-quality, novel contributions in both early and later stages of development are warmly invited. We fully expect to attract novel, risky, and exciting work that can push the boundaries of our current understanding of knowledge and organizations.
 
Some possible questions are listed below, but these are neither complete nor exhaustive (so please feel free to surprise us!):

• How do emerging technologies transform work processes, including the way knowledge is transformed, shared, and created?

• What is the changing role of AI in organizational knowledge sharing?

• How do emerging technologies reconfigure organizational boundaries, and transform organizing and coordinating within and across organizations?

• How do emerging technologies alter power structures inside the organization?

• What is the changing role of knowledge in new organizational forms?

• How do new technologies or new organizational forms shape our social interaction with and around knowledge?

• How does the use of, and exposure to, decision-making by algorithms shape human decision-making and judgment?

• How does AI transform organizational coordination and control?

• What is the dark side of using emerging technologies (e.g., discrimination, biases, algorithmic control, over-monitoring of behavior or performance)?

• With tools such as AI, what are the ethical questions and dilemmas that come to the fore?

• What are the cultural and social entanglements in technology-driven knowledge creation and sharing?

• How are the rhythms of technology and algorithms intertwined with organizational rhythms?

• What are important crossroads between knowledge and knowing, people, and technology? 

References

• Anthony, C. (2021): “When knowledge work and analytical technologies collide: The practices and consequences of black boxing algorithmic technologies.” Administrative Science Quarterly, 66 (4), 1173–1212.

• Bailey, D.E., Faraj, S., Hinds, P.J., Leonardi, P.M., & von Krogh, G. (2022): “We Are All Theorists of Technology Now: A Relational Perspective on Emerging Technology and Organizing.” Organization Science, 33 (1), 1–18.

• den Hond, F., & Moser, C. (2023): “Useful servant or dangerous master? Technology in business and society debates.” Business and Society, 62 (1), 87–116.

• Faraj, S., & Leonardi, P.M. (2022): “Strategic organization in the digital age: Rethinking the concept of technology.” Strategic Organization, 20 (4), 771–785.

• Glaser, V.L., Pollock, N., & D’Adderio, L. (2021): “The biography of an algorithm: Performing algorithmic technologies in organizations.” Organization Theory, 2 (2), https://doi.org/10.1177/26317877211004609.

• Hadjimichael, D., & Tsoukas, H. (2019): “Toward a better understanding of tacit knowledge in organizations: Taking stock and moving forward.” Academy of Management Annals, 13 (2), 672–703.

• Kellogg, K.C., Valentine, M.A., & Christin, A. (2020): “Algorithms at work: The new contested terrain of control.” Academy of Management Annals, 14 (1), 366–410.

• Moser, C., & Deichmann, D. (2021): “Knowledge sharing in two cultures: the moderating effect of national culture on perceived knowledge quality in online communities.” European Journal of Information Systems, 30 (6), 623–641.

• Moser, C., den Hond, F., & Lindebaum, D. (2022): “Morality in the age of artificially intelligent algorithms.” Academy of Management Learning and Education, 21 (1), 139–155.

• Nonaka, I., & von Krogh, G. (2009): “Perspective – Tacit knowledge and knowledge conversion: Controversy and advancement in organizational knowledge creation theory.” Organization Science, 20 (3), 635–652.

• Orlikowski, W.J., & Scott, S.V. (2008): “Sociomateriality: Challenging the Separation of Technology, Work and Organization.” Academy of Management Annals, 2 (1), 433– 474.

• Safadi, H., Johnson, S.L., & Faraj, S. (2021): “Who contributes knowledge? Core-periphery tension in online innovation communities.” Organization Science, 32 (3), 752–775.

Shrestha, Y.R., Ben-Menahem, S.M., & von Krogh, G. (2019): “Organizational decision-making structures in the age of artificial intelligence.” California Management Review, 61 (4), 66–83.