Search results

Drawing on prior research on strengths use and job performance, this study aims to investigate how employees’ strengths use for tasks and strengths use for relationships jointly influence role breadth self-efficacy and subsequent job performance, specifically in- and extra-role performances.

To test the assumptions, the authors methodologically performed a polynomial regression with response surface analysis using data collected from multiple time points and sources (i.e. 312 employee–supervisor dyads in Chinese companies).

The results showed that the higher the congruence between strengths use for tasks and strengths use for relationships, the higher the employees’ role breadth self-efficacy. Employees’ role breadth self-efficacy was greater when both strengths use for tasks and strengths use for relationships were high. Furthermore, the congruence between strengths use for tasks and strengths use for relationships had indirect effects on in- and extra-role performances via role breadth self-efficacy.

This study uniquely contributes to the strengths use literature by offering a more nuanced understanding of the consequences of strengths use for tasks and strengths use for relationships in the Chinese context. It highlights the importance of both types of strengths use for improving employee performance in Chinese organizations. Furthermore, this study provides new theoretical insights into the relationship between strengths use and job performance by ascertaining the mediating effect of role breadth self-efficacy.

This paper aims to investigate how manufacturers can foster insights and improvements from real-time data among shop-floor workers by developing organisational “learning-to-learn” capabilities based on both the lean- and action learning principle of learning through problem-solving. Second, the purpose is to extrapolate findings on how action learning can enable the complementarity between lean and industry 4.0.

An insider action research approach is adopted to investigate how manufacturers can enable their shop-floor workers to foster insights and improvements from real-time data at VELUX.

The findings report that enabling shop-floor workers to use real-time data consist of developing three consecutive organisational building blocks of learning-to-learn, learning-to-learn using real-time data and learning-to-learn generating real-time data − and helping others to learn (to learn).

First, the study contributes to theory and practice by demonstrating that a learning-to-learn capability is a core construct for manufacturers seeking to enable shop-floor workers to use real-time data-capturing systems to drive improvement. Second, the study outlines how lean and industry 4.0 complementarity can be enabled by action learning. Moreover, the study allows us to deduce six necessary conditions for enabling shop-floor workers to foster insights and improvements from real-time data.