Exploring Soft Attributes of Leadership within the Market and Social Research Industries in Gauteng Province using Statistical Analysis

Abstract

The purpose of this paper is to identify the soft attributes of leadership within the Market and Social Research Industries in Gauteng Province, South Africa. A two-stage sampling procedure comprising of stratified random sampling and systematic random sampling were used to select a sample of 261 full-time employees for the quantitative phase of the study. An overall Cronbach alpha of 0.982 showed that the results are statistically reliable. The general concept of soft leadership was coined by Prof M.S. Rao who considered the 11Cs characteristics. There are number of other variances of the soft skills in leadership literature and the soft skills concepts fall under the umbrella of Emotional Intelligence (EI). The data was analyzed using different statistical tools in SPSS software. Stepwise regression analysis was used to identify the soft attributes of leadership that drive overall leadership style. The attributes retained in the model clearly show the importance of good leadership practices and also point to the fact that the manager related attributes directly or indirectly influence proper execution of the job by their subordinates. The researcher also used confirmatory factor analysis to test the model that was produced in the exploratory factor analysis. The combination of different statistical analyses produced rich, powerful and complementary set of results that help to understand the drivers of overall leadership. Although the attributes referred to as soft in this paper, they are the most important salient attributes that any leader should have. The paper also lists some qualitative attributes that a leader should have. This is extracted from a DBL awarded paper from School of Business Leadership, University of South Africa entitled A Statistical Model for Employee Satisfaction in the Market and Social Research Industries in Gauteng Province.

Keywords: Leadership, Regression Model, Goodness of Fit, Confirmatory, Soft Attribute

View PDF