EVALUATING THE INFLUENCE FACTORS OF THE ELECTRONIC SERVICE QUALITY IN THE BANKING INDUSTRY WITH THE ANP AND FUZZY TOPSIS METHODS

SHAHRAM GILANINIA *

Department of Industrial Management, Islamic Azad University, Rasht Branch, Rasht, Iran.

MOHAMMAD TALEGHANI

Department of Industrial Management, Islamic Azad University, Rasht Branch, Rasht, Iran.

HAMED GHEIBDOUST

Department of Industrial Management, Islamic Azad University, Rasht Branch, Rasht, Iran.

*Author to whom correspondence should be addressed.


Abstract

The purpose of this study is to evaluate the influence factors of electronic service quality (E-SQ) in the banking industry. A combination of Analytic network process (ANP) and Fuzzy-TOSIS methods was used in this study. ANP method was used to obtain the weight of criteria and sub-criteria and the Fuzzy TOPSIS method was used to prioritize four state banks of Rasht city. The data collection tool is ANP and TOPSIS questionnaire. Data collection is from October 2022 to January 2023. In the present study, 19 E-SQ sub-criteria were evaluated in the banking industry, and the Customers' trust sub-criteria was ranked first. Also, among the four studied public banks, Bank A1 was ranked first. Investigating the influence factors of E-SQ in the banking industry will make bank managers more familiar with the influence factors, and managers and policymakers in this area can provide better quality electronic services to bank customers.

Keywords: Electronic services, electronic service quality, banking industry, SERVQUAL, ANP, fuzzy TOPSIS


How to Cite

GILANINIA, S., TALEGHANI, M., & GHEIBDOUST, H. (2022). EVALUATING THE INFLUENCE FACTORS OF THE ELECTRONIC SERVICE QUALITY IN THE BANKING INDUSTRY WITH THE ANP AND FUZZY TOPSIS METHODS. Journal of Global Economics, Management and Business Research, 14(3-4), 39–49. https://doi.org/10.56557/jgembr/2022/v14i38079

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References

Liu D, Bishu RR, Najjar L. Using the analytical hierarchy process as a tool for assessing service quality, Industrial Engineering and Management Systems. 2005;4(2):129-135.

Zadeh LA, Bellman RE. Decision making in a fuzzy environment. Management Science. 1970;17(4):141-164.

Tan Q, Oriade A, Fallon P. Service quality and customer satisfaction in chinese fast food sector: A proposal for cffrserv. Advances in Hospitality and Tourism Research (AHTR). 2014;2(1):30-53.

Lin M, Ling Q, Liu Y, Hu R. The effects of service climate and internal service quality on frontline hotel employees’ service-oriented behaviours, International Journal of Hospitality Management. 2021;97:XXX-XXX.

Ramezanian MR, Gheibdoust H. Prioritization of the influential factors on health care services quality using a hybrid approach based on analytic network process (ANP) and fuzzy TOPSIS in public hospitals. Journal of Hospital. 2017;15:79-93.

Sahney S, Banwet DK and Karunes S. An integrated framework for quality in education: Application of quality function deployment, interpretive structural modelling and path analysis, Total Quality Management & Business Excellence. 2006;17(2):265-285.

Büyüközkan G, Çifçi G. A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in healthcare industry. Expert Systems with Applications. 2012;39(3):2341-2354.

Hamidi N, Gheibdoust, H, Ramezanian MR. Application of network analysis and fuzzy topsis to analyze electronic service quality of health care industry. Journal of Health Administration (JHA). 2014;17:17-28.

Zahedi S, Biniaz J. Evaluation of Electronic Service Quality in Railway Touring Company Raja, Journal of IT Management. 2009;1(1): 65-82.

Mwiya B, Katai M, Bwalya J, Kayekesi M, Kaonga S, kasanda E, Munyonzwe C, Kaulungombe B, Sakala E, Muyenga A, Mwenya D. Examining the effects of electronic service quality on online banking customer satisfaction: Evidence from Zambia. Cogent Business & Management. 2022;9:XXX-XXX.

Luo H. Banking systemic risk estimating of China's banking industry during the COVID-19 pandemic-based on complex network theory, Heliyon. 2022;8:XXX-XXX.

Sáez-Fernández FJ, Picazo-Tadeo, AJ, Jiménez-Hernández I. Performance and risk in the Brazilian banking industry. Heliyon. 2021;7:XXX-XXX.

Nyagadza B, Mazuruse G, Muposhi A, Chuchu T, Makoni T. Kusotera B. Emotions’ influence on customers’ e-banking satisfaction evaluation in e-service failure and e-service recovery circumstances, Social Sciences & Humanities Open. 2022;6:XXX-XXX.

Hosseini M, Abdolvand N, Harandi SR. Two-dimensional analysis of customer behavior in traditional and electronic banking, Digital Business. 2022;2:XXX-XXX.

Zhang Y, Weng G, Zhu N. The relationships between electronic banking adoption and its antecedents: A meta-analytic study of the role of national culture. International Journal of Information Management. 2018;40: 76-87.

Roy P, Shaw K. A fuzzy MCDM decision-making model for m-banking evaluations: comparing several m-banking applications. Journal of Ambient Intelligence and Humanized Computing. 2022;1-23.

Stewart A, Richard M. Towards quality e-service in the public sector: The evolution of web sites in the local public service sector. Managing Service Quality. 2002;15(1):6-23.

Kong M, Jogaratnam G. The influence of culture on perceptions of service employee behavior, Managing Service Quality. 2007; 17(3):275-297.

Luke R, Heyns GJ. An analysis of the quality of public transport in Johannesburg, South Africa using an adapted SERVQUAL model. Transportation Research Procedia. 2020;48: 3562-3576.

Barnes SJ, Vidgen RT. An integrative approach to the assessment of e-commerce quality. J. Electron. Commerce Res. 2002;3(3):114-127.

Parasuraman A, Zeithmal VA, Berry LLA. A conceptual model of service quality and its implication. Journal of Marketing. 1985; (49):41-50.

Sakyi D. A comparative analysis of service quality among ECOWAS seaports. Transportation Research Interdisciplinary Perspectives. 2020;6:1-10.

Stefano NM, Casarotto Filho N, Barichello R, Sohn AP. A fuzzy SERVQUAL based method for evaluated of service quality in the hotel industry. Procedia CIRP. 2015;30:433-438.

Hsu TH, Hung LC, Tang JW. A hybrid ANP evaluation model for electronic service quality, Applied Soft Computing. 2012;12(1):72-81.

Khambhati R, Patel H, Kumar S. A performance evaluation and comparison model for urban public healthcare service Quality (Urbpubhcservqual) By fuzzy TOPSIS Method. Journal of Nonprofit & Public Sector Marketing. 2022;34(3) 291-310.

Mohammad AB. Al-Okaily M, Al-Majali M, Masadeh R. Business intelligence and analytics (BIA) usage in the banking industry sector: An application of the TOE framework. Journal of Open Innovation: Technology, Market, and Complexity. 2022;8:XXX-XXX.

Ariff MSM. Yun LO, Zakuan N, Jusoh A. Examining dimensions of electronic service quality for internet banking services, procedia - Social and behavioral sciences. 2012;65: 854-859.

Salihu A, Metrin H, Hajrizi E, Ahmeti M. The effect of security and ease of use on reducing the problems/deficiencies of electronic banking services. IFAC Papers On Line. 2019;52:159-163.

Ma Q, Pearson JM, Tadisina S. An exploratory study into factors of service quality for application service providers. Information and Management. 2005;42:1067-1080.

Hu YC, Liao PC. Finding critical criteria of evaluating electronic service quality of Internet banking using fuzzy multiple-criteria decision making, Applied Soft Computing. 2011;11:3764-3770.

Chmielarz W, Zborowski M. A hybrid method of assessing individual electronic banking services in 2019. The Case of Poland, Procedia Computer Science. 2020;176:3881-3889.

Akhisar I, Tunay KB, Tunay N. The effects of innovations on bank performance: The case of electronic banking services. Procedia - Social and Behavioral Sciences. 2015;195:369-375.

Safarpour M. Identification and ranking the barriers to adoption and development of electronic banking in Iran. Procedia Economics and Finance. 2016;36:374-380.

Teka BM, McMillan D. Factors affecting bank customers usage of electronic banking in Ethiopia: Application of structural equation modeling (SEM). Cogent Economics & Finance. 2020;8:XXX-XXX.

Cristobal E, Flavian C, Guinaliu M. Perceived e-service quality (PeSQ): Measurement validation and effects on consumer satisfaction and web site loyalty. Managing Service Quality. 2007;17(3):317-340.

Grigoroudis E, Litos C, Moustakis VA, Politis Y, Tsironis L. The assessment of user-perceived web quality: Application of a satisfaction benchmarking approach. European Journal of Operational Research. 2008; 187:1346-1357.

Iwaarden J, Wiele T, Ball L, Millen R. Perceptions about the quality of web sites: A survey amongst students at Northeastern University and Erasmus University, Information and Management. 2004;41: 947-959.

Ladhari R. Developing e-service quality scales: A literature review, Journal of Retailing and Consumer Services. 2010;17:464-477.

Hadwich K, Georgi D, Tuzovic S, Buttner J, Bruhn M. Perceived quality of e-health services: A conceptual scale development of e-health service quality based on the C-OAR-SE approach. International Journal of Pharmaceutical and Healthcare Marketing. 2010;4(2):112-136.

Patsioura F, Kitsiou S, Markos A. Evaluation of Greek public hospital websites, International conference on E-business – ICE-B; 2009.

Bilsel RU, Büyüközkan G, Ruan D. A fuzzy preference-ranking model for a quality evaluation of hospital web sites, International Journal of Intelligent Systems. 2006;21: 1181-1197.

Li YN, Tan KC, Xie M. Measuring web-based service quality, Total Quality Management. 2002;13(5):685-700.

Bedell SE, Agrawal A, Petersen LE. A systematic critique of diabetes on the World Wide Web for patients and their physicians. International Journal of Medical Informatics, 2004;73:687-694.

KianiMavi R, Gheibdoust H, Khanfar AA. Prioritizing strategic factors of creative tourism industry in Iran by analytic network process (ANP). Event Management. 2020;24: 553-565.

KianiMavi R, Gheibdoust H, Khanfar AA, Kiani Mavi N. Ranking factors influencing strategic management of university business incubators with ANP. Management Decision. 2019;57(12):3492-3510.

Saaty TL. Decision making with the analytic network process: Economic, political, social and technological applications with benefits, opportunities, costs and risks, New York. Science Journal. 2006;30(4):362-375.

Zadeh LA. Fuzzy sets. Information and control 1965;8(3):338-353.

Chen SJ, Hwang CL, Beckmann MJ, Krelle W. Fuzzy multiple attribute decision making: Methods and applications, Springer-Verlag New York,. Secaucus, NJ, USA. 1992; 126(2):370-378.

Wang JW, Cheng CH. Huang KC. Fuzzy hierarchical TOPSIS for supplier selection. Applied Soft Computing. 2009;9(1): 377-386.

Büyüközkan G, Ruan D. Evaluating government websites based on a fuzzy multiple criteria decision-making approach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2007; 15(3):321-343.

Sari FO, Bulut C, Pirnar I. Adaptation of hospitality service quality scales for marina services. International Journal of Hospitality Management. 2016;54:95-103.

Parasuraman A, Zeithaml V, Berry L. SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retail. 1988;64(1): 12–40.

Safdari R, Mohammad Zadeh N. Continuous healthcare records: A new step towards providing electronic medical documents, scientific-educative quarterly of medical documents. 2007;7-12.