Search

Introduction—Decision making (DM) is a fundamental responsibility for managers, with significant implications for organizational performance and strategic direction. The increasing complexity of modern business environments, along with the recognition of human reasoning limitations related to cognitive and emotional biases, has led to a heightened interest in harnessing emerging technologies like Artificial Intelligence (AI) to enhance DM processes. However, a notable disparity exists between the potential of AI and its actual adoption within organizations, revealing skepticism and practical challenges associated with integrating AI into complex managerial DM scenarios. This systematic literature review aims to address this gap by examining the factors that influence managers' adoption of AI in DM. Methods—This study adhered to the PRISMA guidelines. Articles from 2010 to 2024 were selected from the Scopus database using specific keywords. Eligible studies were included after rigorous screening and quality assessment using checklist tools. Results—From 202 articles screened, a data synthesis of 16 eligible studies revealed seven major interconnected factors acting as key facilitators or barriers to AI integration within organizations. These factors—Managers' Perceptions of AI, Ethical Factors, Psychological and Individual Factors, Social and Psychosocial Factors, Organizational Factors, External Factors, and Technical and Design Characteristics of AI—were then organized into a complex analytical framework informed by existing theoretical constructs. Discussion—This contribution provides valuable insights into how managers perceive and interact with AI systems, as well as the conditions necessary for successful integration into organizational DM processes. [ABSTRACT FROM AUTHOR]

Purpose: Prior studies on entrepreneurial intention have shown that different orientations exist regarding entrepreneurial engagement: one looking at the growth of a venture (growth-oriented) and the other looking at the maintenance of an entrepreneurial autonomy (independence-oriented). Filling a gap in the literature concerning the reasons why individuals develop different orientations of entrepreneurial intention, this study revolves around achievement goal motivation (mastery, performance and avoidance approaches) and self-regulatory modes (locomotion and assessment), since both are thought to be at the origin and maintenance of an action willingness. Design/methodology/approach: In a sample of 209 undergraduates, we administered a structured questionnaire at the beginning of an elective entrepreneurship education programme. Through a set of hierarchical regressions we examined the specific role of achievement goal motivation and regulatory modes in relation to the two orientations of intention. Findings: Our findings show that, on the one hand, growth-oriented intention is related to a performance approach and both locomotion and assessment regulatory modes. On the other hand, independence-oriented intention is related to an avoidance approach. Research limitations/implications: These results illuminate the theoretical connections between entrepreneurial intention and motivation and provide implications for entrepreneurship education and the relationship between intention and consequent behaviour. Originality/value: This study is among the first to provide an empirical exploration of the motivational and regulatory drivers that lie beneath a growth-oriented and an independent-oriented intention, offering a theoretical explanation about the development of different intentions towards venture creation. Our findings illuminate on the urgency to consider entrepreneurial intention as a multi-dimensional construct if we are to understand the intention-behaviour nexus.