Capturing heterogeneities in orchestrating resources for accurately forecasting high (separately low) project management performance

Olajumoke A. Awe, Arch G. Woodside, Sridhar Nerur and Edmund Prater

International Journal of Production Economics, 2020, vol. 224, issue C

Abstract: Applying complexity theory tenets, the study here contributes an asymmetric modeling perspective for examining resources orchestrations that indicate high (separately low) project management performance (PMP) accurately. Complexity theory tenets include recognizing that the causal conditions resulting in high PMP have different conditions (i.e., ingredients) typically than the causal conditions resulting in low PMP—adopting this perspective supports the usefulness of asymmetric point or interval estimation rather than the currently pervasive symmetric approach to theory construction and empirical modeling of variable directional relationships (VDR). This study constructs a general model and specific configurational propositions that include social capital, processes, and knowledge management effectiveness as causal conditions indicating case outcomes of high and separately low PMP. Using survey data, the study includes examining propositions and models empirically on the causal conditions for completed projects (n = 302, USA sample of executives in product and service industrial firms). The findings support the perspective that high (as well as low) PMP depends on resource orchestration (configurational) antecedent conditions. The findings serve to support the general proposition that applications of complexity theory in project management research respond effectively in building in the requisite variety for deep understanding and accurate forecasting of performance outcomes. This study includes contributions to theory and empirical research that support the perspective that separate sets of resource orchestrations of alternative complex antecedents (rather than a VDR, symmetric, net effects perspective) forecast high (low) project management performances accurately.

Keywords: Algorithms; Configurations; Knowledge management effectiveness; Performance; Project management; Social capital (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:224:y:2020:i:c:s0925527319303901

DOI: 10.1016/j.ijpe.2019.107556

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