The impact of decision-making styles (effectuation logic and causation logic) on firm performance: a meta-analysis

Purpose As two essential styles of firm decision-making, the relationships among effectuation logic, causation logic and firm performance are unclear. It is helpful to deepen the understanding of reasoning theory and the process of decision-making. The purpose of this paper is to explore the relationship between effectuation logic, causation logic and firm performance. Design/methodology/approach Based on 31 independent empirical studies (including 11,600 samples) published by predecessors, meta-analysis is used to systematically integrate the impact of two decision-making styles on firm performance and explore the potential factors affecting their relationship. Findings The results show a positive correlation between two decision-making styles and firm performance and the influence of effectuation decision-making style in firm performance is slightly stronger. However, the application environment is different: in the emerging market, the causation decision-making style is more effective for firm performance management. When the firm chooses the effectuation decision-making style, it is more effective for performance management in the emerging market. In addition, the industry type, firm performance evaluation tools, national development level and firm scale and firm age can significantly moderate the impact of two decision-making styles on firm performance. Research limitations/implications Both decision-making logics are possible ways for firm to success. Still, the future needs to dig deeper into the black box that can unlock the decision-making styles to achieve firm performance or competitive advantage based on other factors of the decision-behavior-outcome business model, more longitudinal data and experiments. Originality/value To the best of the authors' knowledge, this is the first study to explore the impact of decision-making styles (effectuation logic and causation logic) on firm performance using a meta-analysis.