A rough strength relational DEMATEL model for analysing the key success factors of hospital service quality

Jagannath Roy; Krishnedu Adhikary; Samarjit Kar; Dragan Pamucar

doi:10.31181/dmame1801121r

Authors

Jagannath Roy Department of Mathematics, National Institute of Technology Durgapur, India
Krishnedu Adhikary Department of Mathematics, National Institute of Technology Durgapur, India
Samarjit Kar Department of Mathematics, National Institute of Technology Durgapur, India
Dragan Pamucar University of defence in Belgrade, Military academy, Department of logistics, Belgrade, Serbia

DOI:

https://doi.org/10.31181/dmame1801121r

Keywords:

Strength-relation analysis, Rough numbers, DEMATEL, HSQ, KSFs

Abstract

Successful management of hospital service quality (HSQ) is increasingly becoming strategic perspective of hospitals to excel in medical care within reasonable prices which is among the customers’/patients’ primary needs. Several key success factors (KSFs) can control the proper HSQ management and make it a complex problem. For these reasons, it is vital to set hospitals’ goals and detect KSFs via customers’ feedback and viewpoints. The preceding researches discussed not much about the effect of internal strength impact on the interdependencies between KSFs of HSQ management. To resolve these issues, a rough strength relational- decision making and trial evaluation laboratory (RSR-DEMATEL) model is developed to analyse the individual priorities of KSF of hospital’s performance measures. The RSR-DEMATEL method reflects completely the internal as well as external total influences between the KSFs. Additionally, the proposed model has intelligence and flexibility in manipulating the inherent uncertainty due to the subjective ang vague information in KSF analysis for managing HSQ. The validity and efficiency of the RSR-DEMATEL model are examined by applying it to a hospital data available in the literature. The result analysis shows that “medical staff with professional abilities” (KSF5) is the most significant KSF in HSQ management, i.e., recruiting more skilled doctors and nurses will eventually increase the performance of hospital medical services. Finally, a comparative analysis is conducted to cross check the obtained results with other two methods from literature.

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References

Abdolvand, N., Albadvi, A., & Ferdowsi, Z. (2008). Assessing readiness for business process reengineering. Business Process Management Journal, 14(4), 497-511.

Andaleeb, S. S. (2001). Service quality perceptions and patient satisfaction: a study of hospitals in a developing country. Social science & medicine, 52(9), 1359-1370.

Babakus, E., & Mangold, W. G. (1992). Adapting the SERVQUAL scale to hospital services: an empirical investigation. Health services research, 26(6), 767.

Bai, C., & Sarkis, J. (2013). A grey-based DEMATEL model for evaluating business process management critical success factors. International Journal of Production Economics, 146(1), 281-292.

Bandara, W., Gable, G. G., & Rosemann, M. (2005). Factors and measures of business process modelling: model building through a multiple case study. European Journal of Information Systems, 14(4), 347-360.

Bowers, M. R., Swan, J. E., & Koehler, W. F. (1993). What attributes determine quality and satisfaction with health care delivery? Health care management review, 19(4), 49-55.

Fontela, E., & Gabus, A. (1976) The DEMATEL observer. Battelle Geneva Research Center, Geneva.

Gigović, L., Pamučar, D., Božanić, D., & Ljubojević, S. (2017). Application of the GIS-DANP-MABAC multi-criteria model for selecting the location of wind farms: A case study of Vojvodina, Serbia. Renewable Energy, 103, 501-521.

Koerner, M. M. (2000). The conceptual domain of service quality for inpatient nursing services. Journal of Business Research, 48(3), 267-283.

Pamučar, D., & Ćirović, G. (2015) The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42(6), 3016-3028.

Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. The Journal of Marketing, 49, 41-50.

Roy, J., Pamučar, D., Adhikary, K., & Kar, S. (2017). A rough strength relational DEMATEL model for analysing the key success factors of hospital service quality. Proceedings of the 1st International Conference on Management, Engineering and Environment (ICMNEE) (pp. 254-279). Belgrade: ECOR (RABEK).

Shieh, J. I., Wu, H. H., & Huang, K. K. (2010). A DEMATEL method in identifying key success factors of hospital service quality. Knowledge-Based Systems, 23(3), 277-282.

Song, W., Ming, X., & Liu, H. C. (2017). Identifying critical risk factors of sustainable supply chain management: A rough strength-relation analysis method. Journal of Cleaner Production, 143, 100-115.

Youssef, F., Nel, D., & Bovaird, T. (1995). Service quality in NHS hospitals. Journal of Management in Medicine, 9(1), 66-74.

Zhai, L. Y., Khoo, L. P., & Zhong, Z. W. (2008). A rough set enhanced fuzzy approach to quality function deployment. The International Journal of Advanced Manufacturing Technology, 37(5), 613-624.

Zhai, L. Y., Khoo, L. P., & Zhong, Z. W. (2009). A rough set based QFD approach to the management of imprecise design information in product development. Advanced Engineering Informatics, 23(2), 222-228.

Zhu, G. N., Hu, J., Qi, J., Gu, C. C., & Peng, J. H. (2015). An integrated AHP and VIKOR for design concept evaluation based on rough number. Advanced Engineering Informatics, 29, 408–418.