Enhancing Job Satisfaction Using an Adaptive Neuro-Fuzzy Inference System by Considering HSEE Factors

Document Type : Original Article

Authors

1 Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

2 Department of Industrial Engineering and Management, Shahrood University of Technology, Shahrood, Iran

3 Industrial Engineering Department, Iran University of Science and Technology, Tehran, Iran

Abstract

Job satisfaction plays a crucial role in enhancing productivity and reveals intriguing insights that impact the operational effectiveness of organizations. Due to the importance of maintenance units, special attention should be paid to their employees. This study employs a machine learning approach to enhance the performance and job satisfaction of maintenance units through the focus on health, safety, environment, and ergonomics (HSEE). A standardized questionnaire is developed for on HSEE data. Within the neural-fuzzy inference network, inputs such as health and safety protocols, environmental data collection, and its reliability is assessed using Cronbach's alpha coefficient. Subsequently, various adaptive neuro fuzzy inference system (ANFIS) models are utilized to predict job satisfaction based factors, and ergonomics are considered, while job satisfaction serves as the output. Following the selection of the optimal model, individual efficiency levels are assessed and scrutinized based on the calculated error. The findings suggest that enhancing employee job satisfaction relies on prioritizing the enhancement of ergonomics and the work environment.

Keywords

Main Subjects

References

Al-Alawi, A.I., Al-Marzooqi, N.Y., Mohammed, Y.F., 2007. Organizational culture and knowledge sharing: critical success factors. J. Knowl. Manag. 11 (2), 22–42. https://doi.org10.1108/13673270710738898
Allscheid, S.P., Cellar, D.F., 1996. An interactive approach to work motivation: the effects of competition, rewards, and goal difficulty on task performance. J. Bus. Psychol. 11 (2), 219–237. https://doi.org/10.1007/BF02193860
Asadzadeh, S. M., Maleki, H., & Tanhaeean, M. (2020). A resilience engineering-based approach to improving service reliability in maintenance organizations. International Journal of System Assurance Engineering and Management, 11, 909-922. https://doi.org/10.1007/s13198-020-01015-5
Asadzadeh, S. M., Tanhaeean, M., & Abdi, N. (2019). Recognizing dissimilarities between resilience engineering and EFQM approaches to ensure safety in hospitals. Human Factors and Ergonomics in Manufacturing & Service Industries, 29(3), 233-252. https://doi.org/10.1002/hfm.20779
Azadeh, A., Asadzadeh, S. M., & Tanhaeean, M. (2017). A consensus-based AHP for improved assessment of resilience engineering in maintenance organizations. Journal of Loss Prevention in the Process Industries, 47, 151-160. https://doi.org/10.1016/j.jlp.2017.02.028
Azadeh, A., Bonab, N. A., Salehi, V., & Zarrin, M. (2015). A unique algorithm for the assessment and improvement of job satisfaction by resilience engineering: Hazardous labs. International Journal of Industrial Ergonomics, 49, 68-77. https://doi.org/10.1016/j.ergon.2015.06.002
Azadeh, A., Ghaderi, S., Anvari, M., Saberi, M., (2007). Performance assessment of electric power generations using an adaptive neural network algorithm. Energy Policy 35 (6), 3155e3166. https://doi.org/10.1016/j.enpol.2006.11.012
Azadeh, A., Roudi, E., & Salehi, V. (2017). Optimum design approach based on integrated macro-ergonomics and resilience engineering in a tile and ceramic factory. Safety science, 96, 62-74. Berry, L.M., Houston, J.P., 1993. Psychology at Work. WCB/McGraw-Hill. https://doi.org/10.1016/j.ssci.2017.02.017
Bozorgi-Amiri, A., Mahmoodian, V., Fahimnia, E., & Saffari, H. (2015). A new memetic algorithm for solving split delivery vehicle routing problem. Management Science Letters, 5(11), 1017-1022. https://doi.org/10.5267/j.msl.2015.8.010
Berry, L.M., Houston, J.P., 1993. Psychology at Work. WCB/McGraw-Hill.
Bozorgi-Amiri, A., Mahmoodian, V., Fahimnia, E., & Saffari, H. (2015). A new memetic algorithm for solving split delivery vehicle routing problem. Management Science Letters, 5(11), 1017-1022. https://doi.org/10.5267/j.msl.2015.8.010
Dylag, A., Jaworek, M., Karwowski, W., Ko_ zusznik, M., Marek, T., 2013. Discrepancy between individual and organizational values: occupational burnout and work engagement among white-collar workers. Int. J. Ind. Ergon. 43 (3), 225–231. https://doi.org/10.1016/j.ergon.2013.01.002
Fay, C.H., Thompson, M.A., 2001. Contextual determinants of reward systems’ success: an exploratory study. Hum. Resour. Manag. 40, 213–226. https://doi.org/10.1002/hrm.1012
Hakanen, J., Schaufeli, W.B., Ahola, K., 2008. The job demands-resources model: a three-year cross-lagged study of burnout, depression, commitment, and work engagement. Work. Stress 22, 224–241. https://doi.org/10.1080/02678370802379432
Hale, A.R., Hovden, J., 1998. Management and culture: the third age of safety. A review of approaches to organizational aspects of safety, health and environment. Occupational Injury: Risk, Prevention Intervention, 129–165. https://doi.org/10.1201/9780203212493-18
Hoboubi, N., Choobineh, A., Kamari Ghanavati, F., Keshavarzi, S., Hosseini, A.A., 2017. The impact of job stress and job satisfaction on workforce productivity in an iranian petrochemical industry. Safety and Health at Work 8, 67–71. https://doi.org/10.1016/j.shaw.2016.07.002
Huang, Y.H., Lee, J., McFadden, A.C., Murphy, L.A., Robertson, M.M., Cheung, J.H., Zohar, D., 2016. Beyond safety outcomes: an investigation of the impact of safety climate on job satisfaction, employee engagement and turnover using social exchange theory as the theoretical framework. Appl. Ergon. 55, 248–257. https://doi.org/10.1016/j.apergo.2015.10.007
Keshavarz, M., Mohammadi, R., 2011. Occupational stress and organizational performance, case study: Iran. Procedia. Soc. Behav. Sci. 30, 390–394. https://doi.org/10.1016/j.sbspro.2011.10.077
Lee, Y., Shin, S., 2010. Job stress evaluation using response surface data mining. Int. J. Ind. Ergon. 40 (4), 379–385. https://doi.org/10.1016/j.ergon.2010.03.003
Loi, R., Ngo, H.Y., Zhang, L., Lau, V.P., 2011. The interaction between leader–member exchange and perceived job security in predicting employee altruism and work performance. J. Occupational Organizational Psychol. 84 (4), 669–685. https://doi.org/10.1348/096317910X510468
Mahapatro, B., 2010. Human Resource Management. New Age, New Delhi
Maqbool, Z., Makhijani, N., Chandrasekhar Pammi, V.S., Dutt, V., 2017. Effects of motivation: rewarding hackers for undetected attacks cause analysts to perform poorly. Hum. Factors 59 (3), 420–431. https://doi.org/10.1177/0018720816681888
Morshedi, A., Nezafati, N., Shokouhyar, S., & Tanhaeean, M. (2023). Proposing a hybrid fuzzy model to consider knowledge management challenges in supply chain: case study. International Journal of Knowledge Management Studies, 14(3), 333-362. https://doi.org/10.1504/IJKMS.2023.132046
Parvin, M. M., & Kabir, M. N. (2011). Factors affecting employee job satisfaction of pharmaceutical sector. Australian journal of business and management research, 1(9), 113. https://doi.org/10.52283/NSWRCA.AJBMR.20110109A13
Reimer, B., Mehler, B., Coughlin, J.F., 2016. Reductions in self-reported stress and anticipatory heart rate with the use of a semi-automated parallel parking system. Appl. Ergon. 52, 120–127. https://doi.org/10.1016/j.apergo.2015.07.008
Ruotsalainen, J. H., Verbeek, J. H., Mariné, A., & Consol, S. (2015). Preventing occupational stress in healthcare workers (Review) summary of findings for the main comparison. Cochrane Database Syst Rev Prev. https://doi.org/10.1002/14651858.CD002892.pub2
Ruotsalainen, J.H., Verbeek, J.H., Marine, A., Serra, C., 2014. Preventing occupational stress in healthcare workers. Cochrane Database Syst. Rev. 11. https://doi.org/10.1002/14651858.CD002892.pub3
Saffari, H., Abbasi, M., & Gheidar-Kheljani, J. (2023). A new model for balancing between asset sharing risk and responsiveness: developing the augmented ɛ-constraint method. International journal of research in industrial engineering, 12(2), 106-128. https://doi.org/10.22105/riej.2023.362292.1338
Saffari, H., Abbasi, M., & Gheidar-Kheljani, J. (2023). A robust, sustainable, resilient, and responsive model for forward/reverse logistics network design with a new approach based on horizontal collaboration. Environment, Development and Sustainability, 1-44. https://doi.org/10.1007/s10668-023-02954-2
Saffari, H., Makui, A., Mahmoodian, V., & Pishvaee, M. S. (2015). Multi-objective robust optimization model for social responsible closed-loop supply chain solved by non-dominated sorting genetic algorithm. Journal of Industrial and Systems Engineering, 8(3), 42-58.https://doi.org/20.1001.1.17358272.2015.8.3.3.6
Salehi, V., & Veitch, B. (2020). Performance optimization of integrated job-driven and resilience factors by means of a quantitative approach. International Journal of Industrial Ergonomics, 78, 102987. https://doi.org/10.1016/j.ergon.2020.102987
Sazvar, Z., Nayeri, S., Mirbagheri, R., Tanhaeean, M., Fallahpour, A., & Wong, K. Y. (2022). A hybrid decision-making framework to manage occupational stress in project-based organizations. Soft Computing, 26(22), 12445-12460. https://doi.org/10.1007/s00500-022-07143-3
Schieman, S., 2013. Job-related resources and the pressures of working life. Soc. Sci. Res. 42, 271–282. https://doi.org/10.1016/j.ssresearch.2012.10.003
Shoorehdeli, M.A., Teshnehlab, M., Sedigh, A.K., Khanesar, M.A., 2009. Identification using ANFIS with intelligent hybrid stable learning algorithm approaches and stability analysis of training methods. Appl. Soft Comput. 9 (2), 833e850. https://doi.org/10.1016/j.asoc.2008.11.001
Tanhaeean, M., Ghaderi, S. F., & Sheikhalishahi, M. (2023). A decision-making framework for optimal maintenance management: An integrated simulation-mathematical programming-expert system approach. Computers & Industrial Engineering, 185, 109671. https://doi.org/10.1016/j.cie.2023.109671
Thompson, E.R., Phua, F.T., 2012. A brief index of affective job satisfaction. Group Org. Manage. 37 (3), 275–307. https://doi.org/10.1177/1059601111434201
Wallgren, L.G., Hanse, J.J., 2007. Job characteristics, motivators and stress among information technology consultants: a structural equation modeling approach. Int. J. Ind. Ergon. 37 (1), 51–59. https://doi.org/10.1016/j.ergon.2006.10.005
Yang, H., 2008. Efficiency wages and subjective performance pay. Econ. Inq. 46, 179–196. https://doi.org/10.1111/j.1465-7295.2007.00069.x
Yozgat, U., Yurtkoru, S., Bilginoglu, E., 2013. Job stress and job performance among employees in public sector in istanbul: examining the moderating role of emotional intelligence. Procedia-Social and Behavioral Sciences 75, 518–524. https://doi.org/10.1016/j.sbspro.2013.04.056
Send comment about this article
CAPTCHA Image

Files

Share

How to cite

Statistics