This study develops a new Contextual Corporate Integrity Score using large language models (LLMs) to measure firms’ integrity culture more accurately. We analyze the unscripted question-and-answer sections of 183,043 quarterly earnings call transcripts from 2008 to 2024, where executives respond spontaneously to analysts. Unlike traditional dictionary-based methods that rely on keyword counts, our approach interprets language in context and identifies genuine integrity-related discourse. The score captures four dimensions of integrity: Accountability (responsibility and governance), Compliance (adherence to laws and rules), Moral Integrity (fairness and ethical conduct), and Honesty (transparency, trust, and truthful communication). These components are combined into an overall integrity measure. We validate the score in two ways. First, the model shows high agreement with human judgments, indicating strong reliability. We also find that over 70
Human Resource Management 4.0 (HRM 4.0) characterises a new generation of people management through a range of advanced technologies collectively referred to as Industry 4.0 technologies (I4Ts). While multiple studies have been published on I4Ts adoption and applications in HRM, these endeavours have largely fallen short of providing a truly comprehensive, cohesive, and systematically articulated understanding of the transformations brought about by I4Ts. Therefore, using an integrative conceptual review of relevant literature, we weave together the current state and promises of the future, identify latent synergies, and illuminate underexplored interstices of HRM 4.0 literature. In so doing, we develop an ‘HRM 4.0 Strategic Framework’. In light of this framework, we also detail the implications of this research and encourage new research that embraces I4T’s strategic potential.
Digital empowerment has emerged as a critical issue in digital transformation research, yet how digital strategy translates into organizational capabilities through intra-firm diffusion processes remains insufficiently understood. Drawing on innovation diffusion theory and the digital strategizing perspective, this study conceptualizes digital empowerment as a three-stage process—digital strategy, digital routinization, and digital capability formation—and examines the role of organizational culture in this process. Employing a sequential explanatory mixed-methods design, the quantitative phase analyzes survey data from 216 manufacturing firms using hierarchical regression. The results confirm that digital strategy positively influences digital capability formation, with digital routinization serving as a critical mediating mechanism. Furthermore, control orientation weakens while flexibility orientation strengthens the routinization–capability relationship. Building on these findings, the qualitative phase conducts focus group interviews with ten senior managers to extend and refine the general model in the AI context. The qualitative evidence reveals that AI strategy functions as both an enabling and a bounding force incorporating governance mechanisms, that AI routinization operates as an iterative, multi-pathway recombination process, and that the binary cultural opposition dissolves into a configurational logic of directed flexibility in which moderate control and flexibility are dynamically balanced rather than mutually exclusive. The study contributes a synthesized model of digital empowerment that bridges general diffusion processes and technology-specific boundary conditions, and offers practical guidance for firms pursuing digital and AI-enabled transformation.
Can a single piece of legislation serve both normative and strategic ends? This article reviews the EU Artificial Intelligence Act as a hybrid instrument through which the European Union pursues a leading role in the global AI race, applying a leadership through governance strategy. It develops the concept as a four-dimensional analytical construct and four enabling conditions. Situating the Act against the competing US and Chinese AI trajectories and governance philosophies, it combines doctrinal legal and policy analysis with comparative and critical perspectives informed by STS and Information Systems scholarship. It discusses how, and under what conditions, a regulatory instrument can simultaneously serve as a governance framework, a strategic tool, and a sociotechnical regime. By conceptualising leadership through governance, it bridges regulatory and sociotechnical scholarship in a timely discussion about law, technology, and strategy, as the Act’s implementation is unfolding and Regulation (EU) 2026/1744 further sharpens the strategic wager.
This study investigates whether online users can distinguish political deepfakes from real videos and whether these perceptions shape their intention to report the content. We conducted an online experiment in which participants viewed deepfake and real videos of two presidential candidates during the early stages of the 2024 US presidential election. Results show that political deepfakes are more likely to be reported than real videos because they are perceived as less believable, suggesting that realism alone does not guarantee credibility. Furthermore, users show better discernment and a stronger intention to report a politically aligned video, a pattern consistent with the possibility that political alignment increases cognitive engagement. Our findings provide empirical evidence on how the heuristic realism of AI-generated videos shapes users’ beliefs and reporting intentions. Using the elaboration likelihood model as an interpretive lens, we offer a possible explanation for why political alignment may narrow the believability-reporting gap in polarized digital environments.
