The Role of Communication Confidence and Professional Credibility in Linking Communication Skill-Development to Workplace Influence

ABSTRACT: Organisations invest heavily in communication skill-development, yet evidence that such investment converts into workplace influence is thin, and the psychological and social mechanisms that might carry the conversion are rarely modelled together. This article develops and validates a serial mediation framework in which skill-development raises communication confidence, confidence is converted into professional credibility as judged by colleagues and supervisors, and credibility in turn produces workplace influence. Drawing on social cognitive theory, source credibility research and the study of influence, the framework yields six hypotheses and a pre-specified, multi-source, three-wave protocol for Kenyan formal-sector organisations. Because the protocol has not yet been fielded, the empirical contribution is a Monte Carlo validation of the planned estimator, anchored on published meta-analytic effect sizes (training effects of d = 0.60 to 0.63; self-efficacy and performance, r = .38). Across 85,800 simulated samples, the test of the serial indirect effect reached 80% power at 150 to 360 respondents, depending on path size and measurement reliability, whereas the test routed through the weakest direct link needed 680 to 1,380. Measurement error at a reliability of .80 shrank indirect effects by about 49%, Monte Carlo intervals covered the attenuated parameter at near-nominal rates (.931 to .963), and the Type I error rate for the serial test was .058 to .066. The article specifies sample-size rules, a rater design and reporting standards, and it argues that skill-development programmes should be judged by the confidence and credibility they generate, not by skill acquisition alone.

KEYWORDS: Communication confidence, Professional credibility, Communication skill-development, Workplace influence, Serial mediation, Monte Carlo simulation, Kenya.

Abbreviations: CFA, confirmatory factor analysis; CI, confidence interval; ICC, intraclass correlation; MC, Monte Carlo; NACOSTI, National Commission for Science, Technology and Innovation; SEM, structural equation modelling; T1–T3, measurement waves.