Effectual learning toward causal competence –a POMDP model of decision-making sequences

Abstract

Effectuation is often viewed as more preferable to causation for managing uncertainty. Introducing process theory’s perspective on sequencing, we challenge this view by arguing that entrepreneurs navigate better under uncertainty by interpolating between decision logics. We show that the rate of dynamic switching between decision logics (causal versus effectual) increases as entrepreneurs approach the plunge decision. To unpack the evolution of entrepreneurs’ decision-making sequences in the lead-up to new venture creation, we conducted 3 studies. From a sample of 389 decision events identified from the narratives of 30 successful entrepreneurs, in Study 1, we derive model parameters for a partially observable Markov decision process (POMDP) solution. In Study 2, we analyse the decision-making pattern where effectual logics predominate up until the ‘plunge’ decision and proceeds recursively until that plunge decision results in a ‘go’ or ‘abandon’ decision. Finally, in Study 3, we examine the conditions under which the rate of switching between decision logics becomes more dynamic. We conclude by exploring possible explanations for these findings in the qualitative data.