Submission deadline: 1 June 2027
GUEST EDITORS
- Koen Heimeriks, University of Warwick, UK (koen.heimeriks@wbs.ac.uk
- Tomi Laamanen, University of St. Gallen, Switzerland (tomi.laamanen@unisg.ch)
- Mario Schijven, University of Illinois, Urbana-Champaign, USA (schijven@illinois.edu)
- Natalia Vuori, Aalto University, Finland (natalia.vuori@aalto.fi)
- Xena Welch, Erasmus University, The Netherlands (welch@rsm.nl)
JMS EDITOR:
- Lin Cui, Australian National University, Australia (lin.cui@anu.edu.au)
BACKGROUND
Corporate transactions, including mergers, acquisitions, divestitures, alliances, and other deals that reconfigure ownership, firm boundaries, or portfolios of assets and capabilities, are among the most consequential strategic actions firms undertake. They shape organizational trajectories, competitive dynamics, the composition of corporate portfolios, and sources of firms’ sustainable advantages. They are also highly information-intensive processes: Decision-makers must identify opportunities, evaluate prospects, and implement transactions, while investors, analysts, and other market actors interpret their implications under conditions of uncertainty and incomplete information.
Recent advances in artificial intelligence (AI) and related digital infrastructures – including the tools, platforms, and data systems through which transaction-related information is generated, processed, disseminated, and acted upon – are changing these informational conditions (Raisch & Krakowski, 2021; Chalmers, et al., 2026). Leading corporate strategy departments in publicly-listed firms, investment committees at private equity firms as well as financial sponsors, and market intermediaries are increasingly using AI-enabled tools across the transaction lifecycle, from sourcing through implementation (Bain & Company, 2026; McKinsey & Company, 2026). While these tools can expand analytical capacity, accelerate information processing, and support more systematic comparison across opportunities, they may also reshape information asymmetries, increase the codification and diffusion of transaction practices, and introduce new forms of algorithmic bias. Fundamentally, they may lead over time to a redistribution of information processing, judgment, and expertise across managers, algorithms, advisors, and technology providers.
Beyond internal deal processes, digital technologies are also reshaping how corporate transactions are interpreted and contested in capital markets. Natural language processing tools analyse earnings calls, analyst reports, and social media in real time to gauge market sentiment around announcement events; algorithmic trading systems respond to transaction news faster than human analysts; and related digital infrastructures increasingly shape how market participants interpret and strategically respond to transaction-related information. As corporate transactions are increasingly mediated by digital and algorithmic systems, questions of transparency, fairness, regulatory oversight, market stability, and the concentration of deal-making advantages become ever more important. Moreover, these developments may also create recursive dynamics as firms anticipate technologically mediated market reactions and adapt transaction design, timing, and communication accordingly. In other words, these developments critically shape strategic factor markets by virtue of altering information pivotal for decision making by corporate and market actors (e.g., Schijven & Hitt, 2012).
Existing reviews and meta-analyses have synthesized a rich body of research on the processes and outcomes of acquisitions, alliances, and divestitures, including the pre-deal phase (Welch, et al., 2020), collaboration (Gulati, Wohlgezogen & Zhelyazkov, 2012), integration (Graebner, et al., 2017), capability development (Barkema & Schijven, 2008; Wang & Rajagopalan, 2015), and market responses (King, et al., 2021; Ryan-Charleton, Gnyawali & Oliveira, 2022; Lee & Madhavan, 2010). However, much of this work has developed in contexts characterized by human-centred analysis and relatively stable information environments. As these informational conditions change, long-held assumptions about efficiency, evaluation, learning, and market responses require renewed attention and may call for fundamentally new theoretical perspectives. Below, we outline potential research directions and questions that prospective Special Issue submissions could address.
AIMS AND SCOPE OF THE SPECIAL ISSUE
This Special Issue seeks contributions that examine how artificial intelligence, automated information processing, and related digital infrastructures are reshaping the organizational processes surrounding corporate transactions and their interpretation in capital markets. We particularly welcome work that challenges or extends deep-rooted assumptions about efficiency, evaluation, learning, and market responses, and that develops new theory rather than simply applying pre-digital frameworks to technologically mediated settings.
This invites engagement with multiple theoretical traditions, such as the attention-based view, organizational sensemaking, and organizational learning, as well as related work in behavioural strategy, information economics, institutional theory, and impression management, among others.
We invite empirical and conceptual contributions spanning the transaction process. These include the identification and selection of opportunities, where digital tools and data infrastructures reshape screening, sourcing, and imitation; the evaluation and sensemaking that surround transactions, where AI and predictive analytics affect interpretation, narrative formation, and the presumed unpredictability of market reactions; the management, learning, and implementation of transactions, where codification and AI-enabled systems alter due diligence, governance, integration, and capability development; and the communication, strategic influence, and market dynamics through which firms, analysts, investors, and other market actors interpret and respond to transactions in technologically evolving information environments.
We encourage methodological pluralism, including qualitative and process research, archival and event-study designs, experimental work, and mixed-methods approaches, particularly where they connect organizational and market-level dynamics. Submissions should identify how digital technologies change underlying mechanisms or theoretical relationships rather than treating AI adoption as a new contextual variable alone. Literature reviews will not be considered for this Special Issue.
Research questions might include, but are not limited to:
- Identification and Selection of Corporate Transactions
- How do digital tools and AI reshape target identification and screening processes, and do they reduce cognitive blind spots or introduce new forms of algorithmic bias (Welch, et al., 2020; Doshi, et al., 2025)?
- How do analysts, private equity firms, or other intermediaries use technological tools to identify and promote transaction opportunities, and how does this affect competitive dynamics in deal sourcing (Kaul, Nary & Singh, 2018)?
- How do digital platforms and data infrastructures accelerate vicarious learning and imitation among firms, shaping which transactions are pursued and how (Haunschild, 1993; Baum, Li & Usher, 2000)?
- How does the codification of transaction practices in digital tools influence heterogeneity in strategic behaviour or the extent of its standardization (Heimeriks, Schijven & Gates, 2012)?
- How are information asymmetries (Coff, 1999) and trust dynamics (Graebner, 2009; Lumineau, et al., 2023) between target and acquirer or between alliance partners affected by technological mediation?
- Evaluation of and Sensemaking in Corporate Transactions
- How does the use of AI and automated information processing affect the evaluation of corporate transactions, and how does this influence interpretative dynamics and narrative formation (Campbell, Sirmon & Schijven, 2016; Yang, et al., 2023)?
- To what extent do advances in predictive analytics and AI challenge the assumption that market reactions to corporate transactions are inherently unpredictable, and what are the implications for theories of capital market efficiency, strategic behaviour, and firms’ ability to anticipate and shape investor responses (Mirzayev, Vanneste & Testoni, 2025; Schijven & Hitt, 2012; Qu, Kumar & Tong, 2026)?
- How do analysts interpret and evaluate corporate transactions in technologically evolving information environments that increasingly incorporate AI-generated analyses, and under what conditions do they add value versus amplify biases, narratives, strategic framing effects, or hallucinated content (Feldman, Gilson & Villalonga, 2014; Brauer & Wiersema, 2018; Busenbark, Lange & Certo, 2017)?
- Under what conditions do algorithmic trading and real-time data processing amplify herding, misinterpretation, or narrative-driven distortions (Hendershott, Jones & Menkveld, 2011)?
- How do AI and automated information processing affect decision-making across different ownership structures (Foss, et al., 2021; Nary & Kaul, 2023)?
- Management, Learning, and Implementation
- How do digital tools and AI-enabled systems reshape the management of transaction processes, including due diligence, integration, and restructuring (Patel & Morada, 2022)?
- Do technological tools alleviate or exacerbate challenges such as managerial overload and “corporate indigestion,” and how do they affect firms’ ability to sustain acquisition programs (Keil, et al., 2023; Laamanen & Keil, 2008)?
- How does the increasing codification of transaction practices affect organizational learning, the development of capabilities, and the balance between tacit and explicit knowledge (Zollo & Singh, 2004; Maula, Heimeriks & Keil, 2023)?
- How do technological infrastructures change the development of heuristics (Vuori, Laamanen & Zollo, 2023) and do they enable firms to learn from fewer experiences by generating more granular data on individual transactions (March, Sproull & Tamuz, 1991)?
- How does AI reshape the human side of integration, such as employee sensemaking, identity work, emotional responses, and resistance (Vuori, Vuori & Huy, 2018; Drori, Wrzesniewski & Ellis, 2013)?
- Communication, Strategic Influence, and Market Dynamics
- How do firms use digital communication channels, AI, and data analytics to shape how corporate transactions are interpreted? Do these technological developments increase transparency, or do they create new opportunities for obfuscation, impression management, and coordinated influence (Graffin, et al., 2016; Cao, et al., 2023)?
- How do digital infrastructures reshape the roles and influence of analysts and other market actors in the evaluation of corporate transactions? How does this shape the short- versus long-term horizons by which corporate transactions are assessed? (Keum, 2021; Flammer & Ioannou, 2021; DesJardine, Shi & Sun, 2022; DesJardine, Li & Shi, 2025)?
- How do activist investors, short-sellers, and other market actors use technological tools to influence or contest transaction-related narratives (Brauer, Wiersema & Binder, 2023; Shi, Connelly & Cirik, 2018)?
- How do decentralized financial infrastructures and digital trading environments enable new forms of information dissemination, strategic influence, or manipulation around corporate transactions (Isaak, et al., 2025; Lumineau, Wang & Schilke, 2021)?
- How do digitally mediated market reactions feed back into transaction completion, financing, integration, and subsequent strategic actions (Kumar, Dixit & Francis, 2015)?
These questions are illustrative rather than exhaustive. We welcome submissions that address other questions falling within the scope of the Special Issue, and we particularly encourage interdisciplinary work drawing on theories and methods from adjacent fields, including economics, political science, sociology, finance, and law, where they illuminate the organizational and market dimensions of digitally mediated corporate transactions.
SUBMISSION PROCESS AND DEADLINES
- Submission deadline: 1 June 2027
- Submissions should be prepared using the JMS Manuscript Preparation Guidelines (https://journalofmanagementstudies.ac.uk/publish/author-guidance/manuscript-preparation-guidelines/)
- Manuscripts should be submitted using the JMS ScholarOne system (https://mc.manuscriptcentral.com/jmstudies), selecting this Special Issue from the list.
- Articles will be reviewed according to the JMS double-blind review process and are expected to meet the standards of the journal in terms of rigor, contribution, and fit.
- We welcome informal inquiries relating to the Special Issue, proposed topics, and potential fit with the Special Issue objectives; these may be directed to any of the Guest Editors.
SPECIAL ISSUE EVENTS
Information Sessions: The editorial team will host a first information session at SMS 2026 and an online session in Q4 2026 to launch the special issue call. Prospective contributors can receive feedback and ask questions about the call.
Post-submission Workshop: The editorial team will organize a hybrid special online revision workshop in Q4 2027 (exact dates, times, and place TBA). Authors who receive a “revise-and-resubmit” decision on their manuscript will be invited to attend this workshop.
Participation in the workshops does not guarantee acceptance of the paper in the Special Issue and attendance is not a prerequisite for publication.
