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PurposeThe purpose of this paper is to describe how top management teams' expertise in comprehensive and intuitive decision-making contributes to effective improvisational decision-making in times of crisis. Also, improvisational decision-making, as a means for balancing or transcending the dualities of comprehensive and intuitive decision processes, enables the three strategic decision-making processes to coexist and contribute to decision-quality when in crisis.Design/methodology/approachAfter providing a general overview of comprehensive, intuitive and improvisational decision-making and introducing paradox theory, this paper offers a conceptual model of the link between improvisational decision-making and decision quality in crisis situations. Three boundary conditions are discussed: expertise in comprehensive decision-making, expertise in intuitive decision-making and the paradoxical balanced combination of comprehensive and intuitive decision-making. Two brief cases are included to illustrate the theory.FindingsAlthough comprehensive and intuitive decision-making are rooted in distinct information processing approaches with different cognitive demands and at times contradictory logics, they can be combined in unique ways when senior executives improvise decisions in crisis situations.Practical implicationsParticularly in the contexts of crises, it is critical for managers to understand the value of improvisational decision-making and the balanced combination of decision-making tools available to them in order to make rapid and quality decisions. Potential action research interventions are suggested.Originality/valueThis paper offers an integrated model of decision-making, encompassing comprehensive, intuitive and improvisational processes and highlights the combinatory and synergistic nature of these approaches in a crisis.

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Is strategic decision comprehensiveness beneficial for firms? Despite significant empirical attention on this research question, inconsistent findings have prevented strong insights from being formed. To help the field move forward, we address long-standing controversies surrounding whether comprehensiveness is beneficial for firms, and whether environmental dynamism enhances or diminishes its effects. We meta-analyze 37 studies and provide the most definitive evidence possible regarding the strategic value of decision comprehensiveness. Our analyses show (1) that strategic decision comprehensiveness and organizational outcomes are positively related to a meaningful degree when subjective outcome measures are used, and (2) that environmental dynamism does not have a moderating impact on this comprehensiveness–outcomes linkage. Our results indicate that measurement strategies and methodological choices may have primarily driven the effects of strategic decision comprehensiveness reported in the literature. They also suggest that long-standing ideas related to moderating effects of dynamism do not hold. We define an agenda for future research and a roadmap for empirical efforts.

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Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.