Gaining and sustaining a competitive advantage in a VUCA context characterized by Volatile environments; Uncertain outcomes; Complex operational networks; and Ambiguous decisions has made digital transformation key to effective business management. Dynamic capabilities provide a conceptual foundation that sheds light on digital transformation as a managerial phenomenon. Performing a literature review based on inductive method BIBGT (BIB = Bibliometrics; GT = Grounded Theory), which combines bibliometrics and grounded theory, we propose a process model that sequentially articulates three categories of digital transformation capabilities: digital sensing, digital seizing, and digital transforming. The study’s main contribution lies in distinguishing fifteen sub-capabilities involved in the three categories. Based on this model and discussion of the results, we provide recommendations to managers for successful digital transformations, and elaborate avenues for future research on digital transformation capabilities.

Conversational generative AI-based systems (CGAIS), like ChatGPT, seem capable of taking part in conversations with such fluidity that we may not distinguish them from a human. The global integration of CGAIS, however, bears various risks, including the one of colonizing the social through data. In this article, we are interested in the colonization of a new territory: that of conversations. We therefore investigate the nature of conversations individuals have with these technologies. Following Habermas, the realm of the communicative is what enables to construct a common social world, a lifeworld. Conflating the communicative and the instrumental threatens lifeworld construction and more broadly our democracy. We explore CGAIS technical and conceptual properties, and show that they do not support communicative action. Rather, CGAIS should remain confined to the realm of instrumental action. Yet, as they give the impression to belong to the realm of the communicative, we conceptualize them as colonialist agents. Notably, they are imperialist agents because they are increasingly used for all types of activities at work and in the private and public spheres. This reduces the space for communicative action. In addition, they are derealization agents as they distort conversation, by giving the illusion of communicative action. As a result, they threaten the co-construction of a common lifeworld, that forms the basis of our democratic societies.

People analytics (PA) systems can enable data-driven decision-making but also have been described as surveillance. Falling back on privacy-calculus theory, we are leveraging a scenario-based survey among German employees to explain employees' perceptions of PA deployment in their workplace. We find that analytical capability levels of PA-descriptive, prescriptive, and predictive-do not affect participants' perception of constructs in our theoretical model. Employees' privacy concerns about PA systems are strong enough to erode organizational trust to a level where employees are likely to consider leaving an organization, and risk perceptions outweigh employees' perceived usefulness of PA systems. With different analytical capabilities not impacting perceptions, we interpret these effects as related to the employee's realization that, with PA, managers have access to more information on employee behavior than the employee can get on their own behavior. We find that PA thus has an effect that reverses the traditional asymmetry in which employees generally have more information on their own behavior than their managers. Notably, employees' perceptions of PA and the organization using it are less negative when they are not aware of the information asymmetry. Our study contributes by highlighting implications of PA information asymmetry, as the resulting (unfulfilled) intention to leave can have negative consequences for employees' wellbeing and performance. Further, we contribute theoretically to discussions about transparency of algorithmic systems. In our study, transparency does allow employees to perform an informed privacy calculus, yet they are not given the option to act according to it.

Generative AI (GenAI) holds potential for organizations, offering transformative opportunities while simultaneously raising concerns about its associated risks. Like many emerging technologies, GenAI presents organizations with a significant challenge: navigating uncertainty before making large-scale decisions about which systems to adopt and how to implement and leverage them. Managers cannot rely solely on general knowledge of GenAI; they require insights tailored to their specific organizational context. Drawing on an 18-month study of sandbox experiments conducted within a large international service organization, this paper presents CORE-sandbox experiments as a structured framework for systematically learning about the critical dimensions of uncertainty surrounding GenAI. The framework organizes learning into four key domains: Capabilities, Opportunities, Risks, and Ecosystem. The paper also advances the discourse on organizational learning and dynamic capabilities by demonstrating how in-situ and ex-situ learning cycles reinforce one another and how second and third-order organizational learning emerge under conditions of high uncertainty before GenAI rollout decisions are made.

The rapid and wide proliferation of digital technologies and ‘digital first’ ideology has exposed society to significant risks. While useful or even transformative, these technologies often advance without adequate consideration of their societal implications, leading to potentially degraded resilience in social systems and threats to civic and social values. We explore the social values dilemmas arising from societal digitalization, characterized by the tension between the promises of digital innovation and unintended consequences, which challenge foundational values such as privacy, equity, and democratic participation. By critiquing the dominance of neoliberal market logic in shaping digital infrastructure, we reveal how current trajectories can undermine public institutions and exacerbate societal inequalities. Using examples from the embeddedness of digital infrastructures, mass surveillance, and disinformation, we highlight cascading failures that destabilize critical systems and erode social cohesion. To address these challenges, we trace the origins of the social values dilemma to the neoliberal policies of the 1990s and show how these have evolved into existential societal crises in the 21st century. We advocate for a sociotechnical systems approach that prioritizes participatory governance, ethical design, and long-term evaluation of digital technologies. Collaboration among governments, scientific communities, and civil society is essential to ensure digital advancements align with collective social values, mitigate risks, and foster a resilient digital society. By incorporating diverse stakeholder perspectives and embracing both digital and non-digital alternatives, societies can achieve a balanced approach to digitalization that preserves human agency, civic participation and democratic values.

Academic publishing is dominated by a small group of publishers whose platformization practices are threatening academic institutions and their values. These publishers deploy digital research and publishing platform infrastructures (DRPIs) to capture and transform scientific knowledge production in their private interest. This paper aims at analyzing this shift in the political economy of knowledge production and scholarly communication from expanding use of DRPIs. Using Marx's theory of subsumption, we empirically analyze the case of Elsevier and its DRPI to theorize platform capture of scientific knowledge production. We find that DRPIs, recently reinforced by generative artificial intelligence (GenAI), enable academic publishers to advance from real subsumption to general intellect subsumption, progressively sidelining academics in scientific knowledge production. Through regimes of marketization, appropriation and exploitation, the leading academic publishers impose structural dominance on academics to appropriate their labor, data and intellectual property rights. Despite the Open Science movement, DRPIs enable the private capture of societal wealth at the expense of epistemic communities and societal good. Without strong collective action, we will not be able to envision DRPIs that fit with academic values, nor will we be able to combat the negative outcomes of advancing platform capture on the institution of science.

Adolescents' use of online social networks (OSNs) may contribute to the development of a social skill-theory of mind (ToM). Based on ToM theory and communication insights, we predict both direct and indirect effects of OSNs through smartphone communication. Specifically, we posit that (A) the relationship between the frequency of OSN practices and affective ToM is mediated by adolescents' (a) feedback acquisition and (b) conversation depth in their smartphone communication and (B) the relationship between the frequency of OSN practices and adolescents' cognitive ToM is mediated by smartphone (a) network size and (b) communication frequency. To test such predictions, this study uses a two-phase design, involving two surveys of French teens (N = 562) and a preliminary causal test (N = 303). The resulting analysis confirms the research model across the most popular OSN platforms (Snapchat, Instagram, and TikTok), revealing that the frequency of OSN use contributes to two types of ToM, mediated by smartphone communication. These mediating effects are found to be moderated by gender. In contrast with concerns regarding the dangers of OSNs for young users, our research highlights their potentially constructive value and thus suggests the relevance of a more balanced view.

Artificial Intelligence (AI), particularly Generative Artificial Intelligence (GAI), has profoundly transformed the professional landscape. These technologies present new opportunities to enhance productivity, potentially offsetting the societal risks they pose. This study aims to assess whether GAI contributes to satisfaction at work and whether some of this improvement can be explained by productivity gains, human flourishing and reduced frustration when using GAI. To explore this, we employed the CHAID (Chi-square Automatic Interaction Detection) method and ANOVA analyses to investigate the use of GitHub Copilot by software developers. Our findings show that using GitHub Copilot boosted developers' productivity, their sense of flourishing at work, reduced their frustration and increased their satisfaction.

To improve its economic and environmental performance, Carrefour, a major European retailer, restructured the distribution of logistic flows from its small and medium suppliers by introducing consolidation centers to expand flows and optimize resource sharing. The success of such an innovative supply chain (SC) largely depends on the number of suppliers deciding to adopt it without reverting to the previous SC. This specific context prompted us to propose a multi-agent model to analyze how the success of SC restructuring evolves as a function of delivery costs, information system (IS) integration and assimilation, and institutional pressures. Simulation results show first that, the lower IS integration in both the extant and the new SC, the more firms switch to and stay in the new SC. Second, a high level of IS assimilation in the new SC structure combined with coercive pressures fosters the success of SC restructuring.

The giants of digital capitalism exploit Big Data practices based on the datafication of our behavior, permanent access to these data and their processing by machine learning. We are entrapped in these practices and the related platforms without being fully aware of it. This article proposes a theory of the causal dynamics of this entrapment, represented both by reinforcement loops and synthesized by three propositions. The ideology of technology (Marcuse, 1968) leads to the development of a false consciousness (Heidegger, 1954), which conditions digital entrapment and leads to Faustian bargains. Both the false consciousness, this entrapment and the Faustian bargains are the subject of deleterious and interrelated causal reinforcement loops, providing a plausible explanation for the decline in digital users’ freedoms.

In this paper, we revisit the issue of collaboration with artificial intelligence (AI) to conduct literature reviews and discuss if this should be done and how it could be done. We also call for further reflection on the epistemic values at risk when using certain types of AI tools based on machine learning or generative AI at different stages of the review process, which often require the scope to be redefined and fundamentally follow an iterative process. Although AI tools accelerate search and screening tasks, particularly when there are vast amounts of literature involved, they may compromise quality, especially when it comes to transparency and explainability. Expert systems are less likely to have a negative impact on these tasks. In a broader context, any AI method should preserve researchers’ ability to critically select, analyze, and interpret the literature.

Autonomous driving systems (ADS) operate in an environment that is inherently complex. As these systems may execute a task without the permission of a human agent, they raise major safety and responsibility issues. To identify the relevant issues for information systems, we conducted a critical and scoping review of the literature from many disciplines. The innovative methodology we used combines bibliometrics techniques, grounded theory and a critical conceptual framework to analyse the structure and research themes of the field. Our findings show that there are certain ironies in the way in which responsibility for apparently safe autonomous systems is apportioned. These ironies are interconnected and reveal that there remains significant uncertainty and ambiguity regarding the distribution of responsibility between stakeholders. The ironies draw attention to the challenges of safety and responsibility with ADS and possibly other cyber-physical systems in our increasingly digital world. We make seven recommendations related to (1) value sensitive design and system theory approaches; (2) stakeholders’ interests and interactions; (3) task allocation; (4) deskilling; (5) controllability; (6) responsibility (moral and legal); (7) trust. We suggest five areas for future IS research on ADS. These areas are related to socio-technical systems, critical research, safety, responsibility and trust.

What if reality fundamentally consists in events and processes rather than things? All actions are situated within processes, influenced by a broader set of preceding and concomitant flows of digital information and other actions. This paper offers a process philosophy perspective that sees things as merely constellations of processes. Decisions within these processes, moreover, must usually be made within time constraints. Rather than a view of time, such as in process theories, as being tied to notions of entities, variance, or-at best-the flow of things, process philosophy sees time as duration: tied to consciousness, sensemaking, and free will. While principles for conducting positivist, interpretive, and critical research have been widely discussed in the IS literature, criteria and principles for a process philosophy perspective are lacking. In the context of Bergson and Whitehead's creative evolution process philosophy, this paper proposes a set of five principles for the conduct of process philosophy research in information systems: (1) heterogeneous multiplicity, (2) immanence in a process, (3) experience over abstraction, (4) consciousness in duration, and (5) a relational ontology. We describe these in detail and discuss some potential applications, methodological issues, and related difficulties in the principles' implementation for IS research. We highlight their value for requirements engineering in large-scale projects.