Adopting the Supply Chain Operations Reference (SCOR) model, this study aims at investigating the impact of big data (volume, velocity, variety, veracity, and value) on supply chain performance through the mediating role of supply chain management (plan, source, make, deliver, and return) assuming four hypotheses. Data were collected using a questionnaire from managers of food processing companies. The results showed that big data affected supply chain management significantly and positively, which in turn affected supply chain performance significantly and positively. In addition, big data exerted a significant and positive impact on supply chain performance. Based on these links, it was found that supply chain management mediated significantly the effect of big data on supply chain performance. The study contributes to the literature showing that big data plays a pivotal role in improving supply chain performance and supply chain performance from the SCOR model perspective is critical for the relationship between these two constructs.

This study aims at investigating the effect of digital HRM practices on employee motivation and hence employee job performance, or in other words, the mediating role of employee motivation between digital HRM practices and employee job performance. Two digital HRM practices were used in this study: digital training and digital performance appraisal. Collecting data using a valid and reliable questionnaire from employees at industrial companies, the results show that digital training had significant effects on both employee motivation and job performance, digital performance appraisal had significant effects on employee motivation and performance appraisal, and employee motivation exerted a significant effect on job performance. Consequently, it was approved that employee motivation partially mediated the effect of digital HRM practices on job performance. It was concluded that skilled employees who are aware of their performance level are motivated to show higher levels of job performance. Theoretically, the study called scholars to carry out further results to examine the effects of other HRM practices on job performance through employee motivation. Empirically, organizations are requested to conduct training sessions and assess employee performance using digital means.

The purpose of this research is to look into the drivers that influence whether or not users will use e-training. The research identified six elements that influence e-training intention to use: perceived ease of use (PEU), computer and internet self-efficacy (CIS), perceived usefulness (PUS), interaction (INT), technical support (TEC), and management support (MGS). Data were collected using a questionnaire distributed to a sample consisting of employees in private universities to test six hypotheses related to these factors. The results showed that four of these factors, i.e., perceived ease of use (PEU), computer and internet self-efficacy (CIS), perceived usefulness (PUS), and technical support (TEC) are key drivers of e-training intention to use. Results are discussed and conclusion is reported.