Cloud-Based Tools Adoption and Digital Workload as Predictors of Knowledge Sharing Behavior - Kovács, Eszter; El-Sayed, Mona (Future of Work and Digital Management Journal, 2024)
This study aimed to examine the predictive roles of cloud-based tools adoption and digital workload on knowledge sharing behavior among knowledge workers in Egypt. A correlational descriptive research design was used, involving 400 employees selected through stratified random sampling based on Morgan and Krejcie’s sample size table. Participants completed three validated instruments measuring knowledge sharing behavior, cloud-based tools adoption, and digital workload. Data were analyzed using SPSS version 27. Descriptive statistics were calculated, followed by Pearson correlation to examine the relationships between the dependent variable and each independent variable. A multiple linear regression analysis was conducted to assess the joint and individual predictive power of the two independent variables on knowledge sharing behavior. Pearson correlation results showed a strong positive relationship between cloud-based tools adoption and knowledge sharing behavior (r = .61, p < .001), and a moderate negative relationship between digital workload and knowledge sharing behavior (r = –.39, p < .001). Multiple linear regression indicated that both cloud-based tools adoption (B = 0.52, β = .58, t = 10.34, p < .001) and digital workload (B = –0.29, β = –.31, t = –6.97, p < .001) were significant predictors of knowledge sharing behavior. The overall model was statistically significant (F(2, 397) = 155.42, p < .001), with an R² of .44, explaining 44% of the variance in the dependent variable. The findings demonstrate that cloud-based tools adoption facilitates, while digital workload inhibits, knowledge sharing behavior in digital work environments. These results highlight the importance of balancing technological integration with workload management to foster effective knowledge exchange in organizations undergoing digital transformation.