This study aims to (1) compare the strategic performance of decision-making approaches based on effectuation and causation under varying levels of environmental complexity and volatility; (2) assess the consistency of their outcomes; and (3) evaluate the performance of both strategies across the Pre- and Post-Chasm phases of innovation diffusion. The research employed an NKC model with strategic decision components N = 10 and internal coupling (K) values of 2 and 5 representing the two strategies respectively under simulation scenarios with complexity values C = 1, 7, 9 and volatility values co = –0.1, –0.7, –0.9, conducting 100 time steps and 100 Monte Carlo replications per strategy in each scenario. The findings reveal that the effectuation strategy consistently outperforms causation across all complexity levels, with statistically significant differences in average fitness (***p < 0.001) and corresponding performance gaps (? = +0.025, +0.014, and +0.019, respectively). While both strategies yielded comparable outcomes during the Pre-Chasm phase (p > 0.05), effectuation exhibited superior performance across all scenarios in the Post-Chasm phase (? = +0.030, +0.017, and +0.022). Moreover, the variance in fitness decreased over time, converging to a narrow range (? 0.002–0.003), suggesting enhanced long-term stability. A key insight is that the effectuation strategy can reduce early-stage volatility and foster long-term strategic stability. The emergence of strategic inflection points, evidenced by mean fitness trajectories and variance levels, underscores the importance of detecting critical market transition signals to enable timely and appropriate strategic adaptation.