Author:
Koncar Philipp,Helic Denis
Abstract
Abstract
Employee satisfaction impacts the efficiency of businesses as well as the lives of employees spending substantial amounts of their time at work. As such, employee satisfaction attracts a lot of attention from researchers. In particular, a lot of effort has been previously devoted to the question of how to positively influence employee satisfaction, for example, through granting benefits. In this paper, we start by empirically exploring a novel dataset comprising two million online employer reviews. Notably, we focus on the analysis of the influencing factors for employee satisfaction. In addition, we leverage our empirical insights to predict employee satisfaction and to assess the predictive strengths of individual factors. We train multiple prediction models and achieve accurate prediction performance (ROC AUC of best model $$=0.89$$
=
0.89
). We find that the number of benefits received and employment status of reviewers are most predictive, while employee position has less predictive strengths for employee satisfaction. Our work complements existing studies and sheds light on the influencing factors for employee satisfaction expressed in online employer reviews. Employers may use these insights, for example, to correct for biases when assessing their reviews.
Publisher
Springer International Publishing
Reference61 articles.
1. Artz, B.: Fringe benefits and job satisfaction. Int. J. Manpower (2010)
2. Aydogdu, S., Asikgil, B.: An empirical study of the relationship among job satisfaction, organizational commitment and turnover intention. Int. Rev. Manage. Mark. 1(3), 43 (2011)
3. Barbosa, J.L., Moura, R.S., Santos, R.L.d.S.: Predicting Portuguese steam review helpfulness using artificial neural networks. In: Proceedings of the 22nd Brazilian Symposium on Multimedia and the Web, pp. 287–293. ACM (2016)
4. Blood, M.R.: Work values and job satisfaction. J. Appl. Psychol. 53(6), 456 (1969)
5. Brown, S.P., Peterson, R.A.: Antecedents and consequences of salesperson job satisfaction: meta-analysis and assessment of causal effects. J. Mark. Res. 30(1), 63–77 (1993)
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献