Workforce fatigue model and its relationship with workforce productivity

Abstract

Earlier studies have shown that attention to ergonomic factors such as suitable work design and planning, appropriate workplace design and facilities, and suitable machine and human design can help to boost workforce productivity, enhance work safety, increase nervous and physical well-being and fulfil job satisfaction. Ergonomic studies can assist managers in planning to reduce fatigue and increase workforce productivity. A review of the models of ergonomics shows that there is a need to conduct further research to gain a more comprehensive fatigue model. This research aims to propose a workforce fatigue model and investigate its relationship with workforce productivity, and the relationships among the variables and mediating variables with the physical and nervous abilities. The main research question is whether there is a significant relationship between the workforce fatigue model and workforce productivity. By adding forgetfulness and retraining as dependent variables and several mediating variables, this model enhances its precision and sensitivity. The service companies in Iran contribute 51.5 % to the economy of the country. From this percentage, the telecommunication service industry holds 12.8%. As a case study, the researcher decided to select a few telecommunication companies, which make up the biggest branches of the telecommunication companies of Iran. To achieve the research objectives, initially interviews were conducted with thirty experts in this area. Answers and responses from the questions about the fatigue model and the degree of its impact on productivity were used to test the performance and validity of the model. The interview results were analysed and the degree of effectiveness of each variable on the conceptual model was measured. Accordingly, a point was assigned to each variable. It was decided to include the main variables and mediating variables with the highest point in the final model. Based on the findings from the interviews, questionnaires were designed and distributed among the eligible study workforce of the companies. Four hundred and fifty respondents were selected as the sample size, among eight hundred workers, from whom information required for the analysis of the model was collected. The survey data collected from the respondents were processed using a Chi-Square Test, Kolmogorov-Smimov Z Test, One Sample TTest, and Cronbach’s alpha. The result showed a strong significant relationship (pvalue was less than 5%) between the workforce fatigue model and workforce productivity and this model provides higher efficiency and accuracy in assisting the company managers in their decision making in work planning and design. The findings from the case service companies greatly improve workforce productivity through reducing risks due to fatigue in the work environment.