Text mining of industry 4.0 job advertisements |
| |
| Institution: | 1. Department of Enterprise Engineering, University of Rome Tor Vergata, Via del Politecnico, 1, 00133, Rome, Italy;2. Department of Civil and Mechanical Engineering, University of Cassino and the Southern Lazio, Via G. Di Biasio, 43, 03043, Cassino FR, Italy;3. School of Business and Management, Lappeenranta University of Technology, Finland;1. Department of Information Science, College of Information, University of North Texas, Denton, TX 76207, United States;2. Faculty of Learning Sciences and Education, Thammasat University, Thailand |
| |
| Abstract: | Since changes in job characteristics in areas such as Industry 4.0 are rapid, fast tool for analysis of job advertisements is needed. Current knowledge about competencies required in Industry 4.0 is scarce. The goal of this paper is to develop a profile of Industry 4.0 job advertisements, using text mining on publicly available job advertisements, which are often used as a channel for collecting relevant information about the required knowledge and skills in rapid-changing industries. We searched website, which publishes job advertisements, related to Industry 4.0, and performed text mining analysis on the data collected from those job advertisements. Analysis of the job advertisements revealed that most of them were for full time entry; associate and mid-senior level management positions and mainly came from the United States and Germany. Text mining analysis resulted in two groups of job profiles. The first group of job profiles was focused solely on the knowledge related to Industry 4.0: cyberphysical systems and the Internet of things for robotized production; and smart production design and production control. The second group of job profiles was focused on more general knowledge areas, which are adapted to Industry 4.0: supply change management, customer satisfaction, and enterprise software. Topic mining was conducted on the extracted phrases generating various multidisciplinary job profiles. Higher educational institutions, human resources professionals, as well as experts that are already employed or aspire to be employed in Industry 4.0 organizations, would benefit from the results of our analysis. |
| |
| Keywords: | Human resource management Text mining Job profiles Big data analytics Industry 4 0 Education Smart factory |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
