Managerial Competencies, Self Efficacy, and Job Performance : A Path Analytic Approach

2016 ◽  
Vol 9 (10) ◽  
pp. 7
Author(s):  
Sethumadhavan Lakshminarayanan ◽  
Yogesh P. Pai ◽  
Badrinarayan Srirangam Ramaprasad
2016 ◽  
Vol 48 (8) ◽  
pp. 423-430 ◽  
Author(s):  
Sethumadhavan Lakshminarayanan ◽  
Yogesh P. Pai ◽  
Badrinarayan Srirangam Ramaprasad

Purpose The purpose of this paper is to adopt a gap analytic approach to identify competency needs and further estimate the strength of such managerial competencies in predicting job performance. Design/methodology/approach A structured questionnaire was administered on 106 managers from 18 pharmaceutical companies in Maharashtra, India to capture their self-perceptions on importance of competencies, current expertise levels and job performance. Further, relative competence metric, t-test and multiple regression analysis was employed for data analysis. Findings Results indicate incongruence in perceptions of managers for current expertise and importance across four managerial competencies, i.e., analytic skills, self-management, relationship management and goal and action management. Further, gap analysis and relative competence metric reveals negative gaps among managers for competency dimensions pertaining to quantitative ability, adaptability, influence co-workers, change management skills and planning and task execution. Furthermore, self-management competencies are found to wield maximum influence on the self-perceptions of job performance followed closely by relationship management and analytic skills. Originality/value To the best knowledge of the authors, no study exists from pharmaceutical sector in India on managerial competencies and its impact on job performance. Also, authors have not come across any study in India that captures the competency needs through gap analysis and relative competence metric. This study attempts to fill both the aforementioned gaps in literature.


2019 ◽  
Author(s):  
Amanda Kay Montoya ◽  
Andrew F. Hayes

Researchers interested in testing mediation often use designs where participants are measured on a dependent variable Y and a mediator M in both of two different circumstances. The dominant approach to assessing mediation in such a design, proposed by Judd, Kenny, and McClelland (2001), relies on a series of hypothesis tests about components of the mediation model and is not based on an estimate of or formal inference about the indirect effect. In this paper we recast Judd et al.’s approach in the path-analytic framework that is now commonly used in between-participant mediation analysis. By so doing, it is apparent how to estimate the indirect effect of a within-participant manipulation on some outcome through a mediator as the product of paths of influence. This path analytic approach eliminates the need for discrete hypothesis tests about components of the model to support a claim of mediation, as Judd et al’s method requires, because it relies only on an inference about the product of paths— the indirect effect. We generalize methods of inference for the indirect effect widely used in between-participant designs to this within-participant version of mediation analysis, including bootstrap confidence intervals and Monte Carlo confidence intervals. Using this path analytic approach, we extend the method to models with multiple mediators operating in parallel and serially and discuss the comparison of indirect effects in these more complex models. We offer macros and code for SPSS, SAS, and Mplus that conduct these analyses.


2021 ◽  
pp. 232948842110239
Author(s):  
Masaki Matsunaga

Digital transformation provokes a great deal of uncertainty among employees. To gain insights into how employees manage the uncertainty driven by digital transformation and also how leaders can support them, this study has drawn on the theory of communication and uncertainty management (TCUM), which posits that the impact of uncertainty varies by how individuals appraise it and social support enhances positive appraisal. Based on those tenets, the current study advanced the following hypotheses: (a) uncertainty has direct and indirect negative effects on employees’ appraisal of digital transformation, self-efficacy, and job performance; (b) in contrast, direct supervisors’ transformational leadership has direct and indirect positive effects on appraisal, self-efficacy, and job performance; and also (c) transformational leadership moderates the impact of uncertainty. SEM with 4-wave time-separated data ( N = 873 employee-supervisor dyads in Japan) found support for these hypotheses. The obtained findings are discussed with reference to TCUM, transformational leadership, and other relevant literature.


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