Quality of Work Life (QWL) and Its Impact on the Performance of the Banking Industry in Saudi Arabia

The quality of work life (QWL), job satisfaction, and individual work performance are the lynchpins of organizational performance and sustained business growth (SBG). Numerous researchers have recognized an association between QWL and SBG. Positive QWL dimensions ensure a workforce’s commitment to SBG. Like SERVQUAL, the QWL has several dimensions, and the most common are: (1) job satisfaction, (2) autonomy, (3) physical working environment, (4) remuneration, (5) career growth, (6) collegial relationships, and (7) relationship with management. A career in the banking industry has always been considered a symbol of prestige, prosperity, job security, and job satisfaction. To understand this, we present the WRKLFQUAL model to measure QWL and its impact on job security and satisfaction (JSS) and individual work performance (IWP). The dimensions and subdimensions of WRKLFQUAL are different from the dimensions and subdimensions of SERVQUAL; however, mechanisms measuring service quality and QWL have similar approaches. Accordingly, this study applied gap analysis to find what workforces expected from their work environments, as well as what they have actually experienced. Many researchers have argued that gaps in service quality significantly influence business performance. In this regard, our research found that almost all dimensions of WRKLFQUAL have negative gaps, meaning poor QWL causes job dissatisfaction and hampers IWP. Regression analysis also shows that average gaps have a significant relationship with job satisfaction. Finally, research proves that job security and satisfaction plays a mediating role in average gap scores and individual work performance. This study was carried out with reference to the banking sector’s performance in the Kingdom of Saudi Arabia, as follows. Cronbach’s α score suggests that 95% of the sample is free of error. To apply WRKLFQUAL on the same lines those of SERVQUAL, we developed seven dimensions and 28 subdimensions. Based on these dimensions, seven factors were extracted, all with factor loading between 0.745 and 0.835, confirming that all components had quite a high level of common variance. Accordingly, gaps in QWL, ranging from −0.997 to −1.149, also show that almost all the dimensions and subdimensions need improvements. Carrying this analysis further, we also compared QWL between Saudi and non-Saudi multinational banks and found that the QWL of the Saudi banking system has a slight edge over non-Saudi multinational banks. A correlation among seven predictors, ranging from 0.625 to 0.812, suggests that all seven predictors are highly correlated. Similarly, regression analysis with R 2 0.704 shows that we have a good-fitting model. Hence, we argue that JSS depends on QWL and conclude that negative QWL causes job dissatisfaction and insecurity. We also examined the mediating impact of JSS on QWL and IWP and conclude that the Sobel test, in most cases, provided results higher than 1.98, which is the minimum criterion of having Sobel be significant and effective. Hence, we prove that JSS has a mediating role in QWL and IWP. Finally, we conclude that poor QWL causes job dissatisfaction and eventually reduces organizational efficiency.