Leadership decision-making: A behavioral reasoning theory analysis
Section snippets
Leadership decision-making and behavioral reasoning theory
A visual representation of the central hypotheses in behavioral reasoning theory is displayed in Fig. 1. In the section that follows, we use this framework to guide our hypotheses about leadership decision-making. Consistent with past theoretical treatments (Ajzen, 1991), we start with the prediction of behavior, given its centrality in behavioral studies.
Participants and procedure
To test the hypotheses in this study, we solicited participation from a representative sample of employers (e.g., company owners, executives, and high-level managers) that have control over their organizations' employment of youth workers. In other words, all participants were employers with direct responsibility for executive-level workforce decisions in their companies. This was ensured through our solicitation methodology, which stated the pre-requisites for participation in the study.
Results
Descriptive statistics and intercorrelations are presented in Table 1. AMOS 4.0.1 with maximum likelihood estimation was used in covariance modeling analyses. We used Anderson and Gerbing's (1988) two-step approach to test the conceptual model. The first step uses confirmatory factor analysis to test the measurement model, while the second step examines hypothesized linkages in the conceptual framework via structural equation modeling (SEM). Finally, to test mediation hypotheses and model
Discussion
This article examined the utility of behavioral reasoning theory in the study of leadership decision-making. The theory was empirically evaluated in the case of executives' decisions to employ youth workforces, which is a serious issue for many leaders in high-risk industries. Results provided support for the theory. First, leaders' intentions were related to behavioral outcomes in this study. This finding supports the notion that managerial intentionality is associated with organizational
Acknowledgement
This research was funded in part by the National Institute for Occupational Safety and Health (U50 OH008107).
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