Employee preferences as a significant influence on reward mix determination

Abstract

Orientation: The ubiquitous challenging economic climate in South Africa and globally makes it incumbent on South African companies to reconsider their current reward policy and practices if they are to maintain and foster global economic competitiveness. This coupled with the fact that motivation in the workplace has always been a conundrum for managers and human resource practitioners alike. This dilemma becomes an obstacle to organisational effectiveness and hinders competitive advantage when employee morale is low and performance levels decrease. Research purpose: The primary aim of this study was to investigate the influencing factors of employee demographics and motivation type on rewards mix preferences. Motivation for the study: The war for talent is accelerating and the globalization of economies and world markets places pressure on companies to perform well and to maintain optimal performance levels. The workplace in South Africa is not exempt from these pressures and the nature of the workplace is changing every day. Employee engagement dynamics are changing and require deeper insight into what appeals to employees, what motivates them to perform and what will retain good resources. This knowledge would further assist organisations to create reward mix programs that appeal to both extrinsic and intrinsically motivated persons as different motivation types are triggered and stimulated by different types of rewards and adds value by examining the effects of demographical factors (such as age, race/ethnicity and gender) on employees’ perspective of reward mix giving depth to existing insights into what drives whom and at what price. Research design, approach and method: This research followed a quantitative, empirical and descriptive study of reward preferences through the administration of an online questionnaire survey via email. The data was analysed using non-parametric test for variance between dependent and independent variables, factor analysis, ANOVA and MANOVA testing.