Accurate Outcome Performance Screening in Strategic Management

Firm’s operating contexts and asymmetric perspectives of success versus failure outcomes are two essential features typically absent in research on firms’ implemented strategies. The study here describes and provides examples of formal case-based models (i.e., constructing algorithms) of firms’ implemented strategies within several of 81 potential context (task environments) configurations—large versus small, service versus production orientation, low versus high competitive intensity, low versus high technological turbulence, and ambiguous settings for each. The study applies the tenets of complexity theory (e.g., equifinality, causal asymmetry, and single causal insufficiency). The study proposes a meso-theory and empirical testing position for solving “the crucial problem in strategic management” (Powell et al. Strategic Manage J. 32(13):1370, 2011)—firm heterogeneity—why firms adopt different strategies and structures, why heterogeneity persists, and why competitors perform differently. A workable solution is to identify/describe implemented executive capability strategies that identify firms in alternative specific task environments which are consistently accurate in predicting success (or failure) of all firms for specific implemented capabilities/context configuration. The study shows how researchers can perform “statistical sameness testing” and avoid the telling weaknesses and “corrupt practices” of symmetric tests such as multiple regression analysis (Hubbard, 2015) including null hypothesis significance testing (NHST). The study includes testing the research issues using survey responses of 405 CEO and chief marketing officers in 405 Hungarian firms. The study describes algorithms indicating success cases (firms) as well as failure cases via deductive, inductive, and abductive fuzzy set logic of capabilities in contexts solutions.