Although the importance of artificial intelligence (AI) in managerial decision-making has attracted growing attention, understanding of how perceived AI trustworthiness is associated with the adoption of different AI technologies and their perceived impact on decision efficacy (quality, speed, and integrity) remains underexplored. In particular, limited attention has been paid to how ethical conditions are associated with AI adoption and its impact on decision-making. This study examines the relationships among managers’ perceptions of AI trustworthiness, the adoption of predictive AI (PAI) and generative AI (GAI), and perceived decision efficacy. Perceived AI trustworthiness is conceptualized as a multidimensional construct comprising ethics, transparency, and explainability. Using survey data from UK managers analyzed via structural equation modeling, the findings indicate that perceived AI trustworthiness is positively associated with the adoption of both PAI and GAI, which in turn are positively associated with perceived decision efficacy. PAI shows a stronger, more consistent association. Decision complexity weakens the positive association between GAI and perceived decision efficacy but does not moderate the PAI-perceived decision efficacy relationship. To enrich the interpretation, illustrative cases from BYD, Netflix, and HSBC provide contextual insight into how ethical, transparent, and explainable AI practices correspond with managerial AI use and perceived decision-making outcomes. Collectively, the findings suggest that perceived AI trustworthiness is positively associated with responsible AI adoption and higher perceived decision efficacy, while decision complexity is an important boundary condition associated with the perceived efficacy of GAI in managerial decision processes. The findings advance understanding of how perceived AI trustworthiness is associated with the adoption and performance of distinct AI types in managerial decision-making, contributing to debates on responsible AI, managerial accountability, and ethical technology use in organizations.

This research fills a knowledge gap by introducing a new conceptualization of digital transformation through a multidimensional digital transforming capability. It further examines the influence of four cultural types on this capability and its subsequent impact on product innovation. Empirical findings reveal that adhocracy, followed in descending order of influence by clan, market, and hierarchy cultures, is positively related to digital transforming capability, which in turn is positively related to product innovation in terms of new product newness, meaningfulness, and performance. Additionally, new product newness and meaningfulness each positively mediate the effect of digital transforming capability on new product performance.

The knowledge sciences field has long recognized the importance of communities of practice to the flow of knowledge and situational learning. However, the literature and research has focused mainly on communities in formal organizational contexts. This constraint has limited research and exploration and exposed only a small portion of the knowledge of communities of practice. Focusing only on organizational communities of practice further restricts what we have learned about the full range of knowledge capabilities. The Knowledge of Communities provides an inclusive and comprehensive conceptual framework for understanding the spectrum of communities of practice and their relationship to the development of knowledge capital. Presenting a core standpoint that incorporates the variant perspectives of community processes from social sciences, psychology, behavioral sciences, communication and economics, the authors review existing research, identifying areas where additional work is needed, and present the results as a practical field guide for managers that can be utilized for analyzing any community of practice.

This study addresses the interrelationships between strategy-making, organizational preparedness for corporate entrepreneurship (OPCE), selling actions, and the performance of the organization's business-to-business (B2B) salespeople. A survey of B2B salespeople suggests that entrepreneurial strategy-making is positively associated with OPCE, an organization's entrepreneurial sales actions (i.e., creative selling and sales innovativeness), and, ultimately, its sales performance. This research contributes to the nexus of entrepreneurship and sales literature by highlighting the relationships between entrepreneurial strategy-making, OPCE, creative and sales action innovativeness, and B2B sales performance.

Artificial Intelligence (AI) is viewed as having potential for significant economic and social impact. However, its history of boom and bust cycles can make potential adopters wary. A cross-sectional, qualitative study was carried out, with a purposive sample of AI experts from research, development and business functions, to gain a deeper understanding of the adoption process. Technology Readiness Levels were used as a benchmark against which the experts could align their experiences. A model of AI adoption is proposed which embeds an extended version of the People, Processes, Technology lens, incorporating Data. The model suggests that people, process and data readiness are required in addition to technology readiness to achieve long term operational success with AI. The findings further indicate that innovative organizations should build bridges between technical and business functions.

This paper proposes a research agenda for knowledge management research and practice. To do this, it first reviews selected past knowledge management activity, especially that published in KMRP, including descriptions, predictions, initiatives and other research agendas. This merges into a consideration of the current states of knowledge management literature and knowledge management practice, and some issues that need to be taken into account for the future. These are used to synthesise an agenda whose key feature is research on practice, not just research and practice.