Cognitive biases' influence on employees' product creativity and product performance: evidences from Italian manufacturing technology firms

Abstract

Purpose

This paper aims to empirically investigate how cognitive biases influence employees' product creativity (EPC) and related product performance. In particular, the paper primarily studies (1) the direct effect of employees' implicit creativity – based on five cognitive biases – and explicit creativity on EPC; and (2) the mediating role of coworkers' heuristic transfer between shared leadership and EPC.

Design/methodology/approach

Data have been obtained from big Italian manufacturing technology firms through a series of online questionnaires that resulted in 555 answers from R&D employees and their direct managers, who are, respectively, involved and responsible for the proposal of manufacturing technology products. The developed four theoretical hypotheses have been tested through correlation analysis, hierarchical regression, mediation analysis and structured equation modelling.

Findings

Cognitive biases positively influence EPC in manufacturing technology firms, leading to positive product performance. In particular, implicit creative personality better predicts EPC than explicit creative personality; whilst, shared leadership leads to a cognitive convergence among co-workers through the spread of heuristics that positively influence EPC.

Originality/value

The originality of this work lies in having: (1) investigated the influence of cognitive biases in creativity, (2) hypothesized and proved that co-workers' heuristic transfer mediates the relationship between shared leadership and EPC; (3) conducted the first specific study on employees' creativity in manufacturing technology firms; and (4) first implemented the implicit creative personality measurement, apart from those who conceptualized it.

Citation

Cristofaro, M., Leoni, L. and Giardino, P.L. (2022), "Cognitive biases' influence on employees' product creativity and product performance: evidences from Italian manufacturing technology firms", Journal of Manufacturing Technology Management, Vol. 33 No. 4, pp. 675-695. https://doi.org/10.1108/JMTM-10-2020-0414