SaaS for Automated Job Performance Appraisals Using Service Technologies and Big Data Analytics

In this paper, we present a new SaaS (software as a service) design for employee job performance appraisals, SaaS-JPA. We use IoT and computer systems to collect data related to the daily works of employees. A semantic model is developed to guide the data collection process, facilitate data interpretation and interoperation, and enable big data analysis to make job performance appraisal decisions. We also propose two new performance assessment models: The similarity-based relative performance model and the revenue-based performance model. These performance models are enabled by the service technologies and big data analytics. Finally, we discuss the design of SaaS-JPA.