Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Providing better hospital service quality is one of the major concerns of healthcare industry in the world. Since health services in Turkey are provided in a very competitive environment, for making a better choice, the services delivered by the public and private hospitals should be evaluated according to the viewpoint of stakeholders in terms of satisfaction. In this study, a model proposal is presented based on the concept of Pythagorean fuzzy analytic hierarchy process and Pythagorean fuzzy technique for order preference by similarity to ideal solution method to provide an accurate decision-making process for evaluating the hospital service quality. We study under fuzzy environment to reduce uncertainty and vagueness, and use linguistic variables parameterized by Pythagorean fuzzy numbers. The proposed approach is separated from others with the integration of the methods in a way providing a systematic fuzzy decision-making process. A case study including 32 service quality criteria and two public and one private hospitals in Turkey assessed by 32 evaluators by medical staff, hospital executives, auxiliaries, and patients is performed to demonstrate the applicability and validity of the proposed approach. On conclusion, integrated model produces reliable and suggestive outcomes better representing the vagueness of decision-making process.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Afkham L, Abdi F, Komijan A (2012) Evaluation of service quality by using fuzzy MCDM: a case study in Iranian health-care centers. Manag Sci Lett 2(1):291–300

    Google Scholar 

  • Akdag H, Kalaycı T, Karagöz S, Zülfikar H, Giz D (2014) The evaluation of hospital service quality by fuzzy MCDM. Appl Soft Comput 23:239–248

    Google Scholar 

  • Aktas A, Cebi S, Temiz I (2015) A new evaluation model for service quality of health care systems based on AHP and information axiom. J Intell Fuzzy Syst 28(3):1009–1021

    Google Scholar 

  • Ali M, Raza SA (2017) Service quality perception and customer satisfaction in Islamic banks of Pakistan: the modified SERVQUAL model. Total Qual Manag Bus Excell 28(5–6):559–577

    Google Scholar 

  • Altuntas S, Dereli T, Yilmaz MK (2012) Multi-criteria decision-making methods based weighted SERVQUAL scales to measure perceived service quality in hospitals: a case study from Turkey. Total Qual Manag Bus Excell 23(11–12):1379–1395

    Google Scholar 

  • Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96

    MATH  Google Scholar 

  • Carpitella S, Certa A, Izquierdo J, La Fata CM (2018) A combined multi-criteria approach to support FMECA analyses: a real-world case. Reliab Eng Syst Saf 169:394–402

    Google Scholar 

  • Celik E, Gul M, Gumus AT, Guneri AF (2012) A fuzzy TOPSIS approach based on trapezoidal numbers to material selection problem. J Inf Technol Appl Manag 19(3):19–30

    Google Scholar 

  • Chakravarty A (2011) Evaluation of service quality of hospital outpatient department services. Med J Armed Forces India 67(3):221–224

    Google Scholar 

  • Chang TH (2014) Fuzzy VIKOR method: a case study of the hospital service evaluation in Taiwan. Inf Sci 271:196–212

    Google Scholar 

  • Chen C (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114:1–9

    MATH  Google Scholar 

  • Demir P, Gul M, Guneri AF (2018) Evaluating occupational health and safety service quality by SERVQUAL: a field survey study. Total Qual Manag Bus Excell. https://doi.org/10.1080/14783363.2018.1433029

  • Demirer Ö, Bülbül H (2014) Kamu ve özel hastanelerde hizmet kalitesi, hasta tatmini ve tercihi arasındaki ilişki: Karşılaştırmalı bir analiz. Amme İdaresi Dergisi 47(2):95–119

    Google Scholar 

  • Gul M (2018) Application of Pythagorean fuzzy AHP and VIKOR methods in occupational health and safety risk assessment: the case of a gun and rifle barrel external surface oxidation and colouring unit. Int J Occup Saf Ergon. https://doi.org/10.1080/10803548.2018.1492251

    Article  Google Scholar 

  • Gul M, Ak MF (2018) A comparative outline for quantifying risk ratings in occupational health and safety risk assessment. J Clean Prod 196:653–664

    Google Scholar 

  • Gul M, Guneri AF (2018) Use of FAHP for occupational safety risk assessment: an application in the aluminum extrusion industry. In: Emrouznejad A, Ho W (eds) Fuzzy analytic hierarchy process. Chapman and Hall/CRC, New York, pp 249–271

    Google Scholar 

  • Gul M, Celik E, Aydin N, Gumus AT, Guneri AF (2016) A state of the art literature review of VIKOR and its fuzzy extensions on applications. Appl Soft Comput 46:60–89

    Google Scholar 

  • Gul M, Guneri AF, Nasirli SM (2018) A fuzzy-based model for risk assessment of routes in oil transportation. Int J Environ Sci Technol. https://doi.org/10.1007/s13762-018-2078-z

    Google Scholar 

  • Handayani PW, Hidayanto AN, Sandhyaduhita PI, Ayuningtyas D (2015) Strategic hospital services quality analysis in Indonesia. Expert Syst Appl 42(6):3067–3078

    Google Scholar 

  • Hwang CL, Yoon K (1981) Multiple attribute decision making: methods and applications, a state of the art survey. Springer, New York

    MATH  Google Scholar 

  • Ilbahar E, Karaşan A, Cebi S, Kahraman C (2018) A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Saf Sci 103:124–136

    Google Scholar 

  • Kayapınar S, Erginel N (2017) Designing the airport service with fuzzy QFD based on SERVQUAL integrated with a fuzzy multi-objective decision model. Total Qual Manag Bus Excell. https://doi.org/10.1080/14783363.2017.1371586

    Google Scholar 

  • Kubler S, Robert J, Derigent W, Voisin A, Le Traon Y (2016) A state-of the-art survey & testbed of fuzzy AHP (FAHP) applications. Expert Syst Appl 65:398–422

    Google Scholar 

  • Kutlu AC, Ekmekçioğlu M (2012) Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Expert Syst Appl 39(1):61–67

    Google Scholar 

  • Lee H, Delene LM, Bunda MA, Kim C (2000) Methods of measuring health-care service quality. J Bus Res 48(3):233–246

    Google Scholar 

  • Lin QL, Liu L, Liu HC, Wang DJ (2013) Integrating hierarchical balanced scorecard with fuzzy linguistic for evaluating operating room performance in hospitals. Expert Syst Appl 40(6):1917–1924

    Google Scholar 

  • Lupo T (2013) A fuzzy ServQual based method for reliable measurements of education quality in Italian higher education area. Expert Syst Appl 40(17):7096–7110

    Google Scholar 

  • Lupo T (2016) A fuzzy framework to evaluate service quality in the healthcare industry: an empirical case of public hospital service evaluation in Sicily. Appl Soft Comput 40:468–478

    Google Scholar 

  • Mete S (2018) Assessing occupational risks in pipeline construction using FMEA based AHP-MOORA integrated approach under Pythagorean fuzzy environment. Hum Ecol Risk Assess Int J. https://doi.org/10.1080/10807039.2018.1546115

    Google Scholar 

  • Min H, Mitra A, Oswald S (1997) Competitive benchmarking of health care quality using the analytic hierarchy process: an example from Korean cancer clinics. Socio-econ Plan Sci 31(2):147–159

    Google Scholar 

  • Ministry of Health in Republic of Turkey (2015) Health statistics yearbook 2014. Republic of Turkey Ministry of Health General Directorate of Health Research, Ankara

    Google Scholar 

  • Ministry of Health in Republic of Turkey (2016) Health statistics yearbook 2015. Republic of Turkey Ministry of Health General Directorate of Health Research, Ankara

    Google Scholar 

  • Ministry of Health in Republic of Turkey (2017) Health statistics yearbook 2016. Republic of Turkey Ministry of Health General Directorate of Health Research, Ankara

    Google Scholar 

  • Mohd WRW, Abdullah L (2017) Pythagorean fuzzy analytic hierarchy process to multi-criteria decision making. In: AIP conference proceedings, vol 1905, no 1, p. 040020. AIP Publishing

  • Oz NE, Mete S, Serin F, Gul M (2018) Risk assessment for clearing and grading process of a natural gas pipeline project: an extended TOPSIS model with Pythagorean fuzzy sets for prioritizing hazards. Hum Ecol Risk Assess Int J. https://doi.org/10.1080/10807039.2018.1495057

    Article  Google Scholar 

  • Parasuraman A, Zeithaml VA, Berry LL (1988) Servqual: a multiple-item scale for measuring consumer perc. J Retail 64(1):12

    Google Scholar 

  • Pérez-Domínguez L, Rodríguez-Picón LA, Alvarado-Iniesta A, Luviano Cruz D, Xu Z (2018) MOORA under Pythagorean fuzzy set for multiple criteria decision making. Complexity 2018:1–10

    MATH  Google Scholar 

  • Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48(1):9–26

    MATH  Google Scholar 

  • Samantra C, Datta S, Mahapatra SS (2017) Fuzzy based risk assessment module for metropolitan construction project: an empirical study. Eng Appl Artif Intell 65:449–464

    Google Scholar 

  • Shieh JI, Wu HH, Huang KK (2010) A DEMATEL method in identifying key success factors of hospital service quality. Knowl Based Syst 23(3):277–282

    Google Scholar 

  • Taşkin H, Kahraman ÜA, Kubat C (2015) Evaluation of the hospital service in Turkey using fuzzy decision-making approach. J Intell Manuf. https://doi.org/10.1007/s10845-015-1157-y

  • Teng CI, Ing CK, Chang HY, Chung KP (2007) Development of service quality scale for surgical hospitalization. J Formos Med Assoc 106(6):475–484

    Google Scholar 

  • Tzeng GH, Huang JJ (2011) Multiple attribute decision making: methods and applications. CRC Press, Boca Raton

    MATH  Google Scholar 

  • Wu CR, Chang CW, Lin HL (2008) A fuzzy ANP-based approach to evaluate medical organizational performance. Inf Manag Sci 19(1):53–74

    MATH  Google Scholar 

  • Yager RR (2014) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22(4):958–965

    Google Scholar 

  • Zeng S, Chen J, Li X (2016) A hybrid method for pythagorean fuzzy multiple-criteria decision making. Int J Inf Technol Decis Mak 15(02):403–422

    Google Scholar 

  • Zhang X, Xu Z (2014) Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets. Int J Intell Syst 29(12):1061–1078

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Muhammet Gul.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Communicated by V. Loia.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix: Hospital service quality evaluation questionnaire

Appendix: Hospital service quality evaluation questionnaire

This questionnaire is purely related to an academic research entitled “Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS”, aiming at measuring the healthcare service quality level of hospitals. This survey is divided into two sections to explain how we acquire the weights of criteria and sub-criteria and ratings (performances) of hospitals. The first questionnaire is designed for evaluating the relative importance of hospital service quality criteria. The second questionnaire is for evaluating the ranking order of hospitals with respect to each criterion.

The pairwise comparisons in the evaluation forms of first questionnaire will take a considerable time of you. However, findings of this study will contribute to present a guide for the way of highlighting hospital service quality.

Thank you for your attention. Regards.

1.1 General questions

Hospital name:

Working department:

Expertise area (medical/administrative/auxiliary):

Total time of experience (year):

1.2 First questionnaire

Main criteria evaluation

Pairwise comparison of a criterion versus another one

CLI

VLI

LI

BAI

AI

AAI

HI

VHI

CHI

Certainly low importance

Very low importance

Low importance

Below average importance

Average importance

Above average importance

High importance

Very high importance

Certainly high importance

C1 versus C2

         

C1 versus C3

         

C1 versus C4

         

C1 versus C5

         

C1 versus C6

         

C2 versus C3

         

C2 versus C4

         

C2 versus C5

         

C2 versus C6

         

C3 versus C4

         

C3 versus C5

         

C3 versus C6

         

C4 versus C5

         

C4 versus C6

         

C5 versus C6

         

Sub-criteria evaluation of C1

Pairwise comparison of a criterion versus another one

CLI

VLI

LI

BAI

AI

AAI

HI

VHI

CHI

Certainly low importance

Very low importance

Low importance

Below average importance

Average importance

Above average importance

High importance

Very high importance

Certainly high importance

C11 versus C12

         

C11 versus C13

         

C11 versus C14

         

C12 versus C13

         

C12 versus C14

         

C13 versus C14

         

1.3 Second questionnaire

Linguistic terms: Extremely low (EL), Very little (VL), Little (L), Middle little (ML)

Middle (M), Middle high (MH), Big (B), Very tall (VT), Tremendously high (TH)

Hospital service quality criteria

Hospitals

Hospital 1

Hospital 2

Hospital 3

C11

   

C12

   

C13

   

C14

   

C21

   

C22

   

C23

   

C24

   

C25

   

C26

   

C27

   

C28

   

C31

   

C32

   

C33

   

C34

   

C35

   

C41

   

C42

   

C43

   

C51

   

C52

   

C53

   

C54

   

C55

   

C56

   

C61

   

C62

   

C63

   

C64

   

C65

   

C66

   

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yucesan, M., Gul, M. Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS. Soft Comput 24, 3237–3255 (2020). https://doi.org/10.1007/s00500-019-04084-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-019-04084-2

Keywords

Navigation