Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben
Telecommunication Systems
Erschienen in: Telecommunication Systems 1/2019

13.10.2018

Evaluating the impact of service quality on the dynamics of customer satisfaction in the telecommunication industry of Jorhat, Assam

verfasst von: Syed Abou Iltaf Hussain, Debasish Baruah, Bapi Dutta, Uttam Kumar Mandal, Sankar Prasad Mondal, Thuleswar Nath

Erschienen in: Telecommunication Systems | Ausgabe 1/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Service quality acts as an antecedent to customer satisfaction (CS). Evaluation of service quality in an enterprise is vital to improve productivity and increase CS. Usually, it is difficult to rate service quality due to the presence of vagueness in the available information as well as impreciseness in the physical nature of the problem. The comprehensive intention of this paper is to present a robust modified SERVQUAL based multi-criteria decision making (MCDM) method to evaluate the quality of service and its interaction with the dynamics of CS. The proposed evaluation model is a hybrid model, which integrates three popular tools of decision making at the different stage. At first stage, service quality assessment SERVQUAL with the statistical tool has employed to identify appropriate factors affecting the service quality of the telecommunication network. In the next stage, to find the appropriate weight of the different factors in the evaluation process, fuzzy Rasch method is utilized. The final stage involves the selection of the service provider with the most contented customer based on fuzzy MCDM method. Moreover, a new risk minimizing evaluative model is proposed for the study. The strength of the proposed approach is its practical applicability and ability to provide solution under partial or lack of quantitative information. The proposed model is applied for evaluating the service quality of the telecommunication industry of Jorhat, Assam with respect to 256 participants on 15 criteria. Finally, sensitivity analysis is conducted to evaluate the robustness of the proposed approach.
Vorheriger Artikel Approximate expressions of packet error probability, throughput and delay for cognitive radio networks using fixed and adaptive transmit power
Nächster Artikel Optimal routing and one hop routing for D2D communications in the presence of mutual interference

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Awasthi, A., Chauhan, S. S., Omrani, H., & Panahi, A. (2011). A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality. Computers & Industrial Engineering, 61(3), 637–646.CrossRef
2.
Al-Aali, A., Khurshid, M. A., Nasir, N. M., & Al-Aali, H. (2011). Measuring the service quality of mobile phone companies in Saudi Arabia. King Saud University Journal-Administrative Sciences, 22(2), 43–55.
3.
Ali, A. (2017). Service quality and customers’ satisfaction level in telecommunication sector: A comparative study of Kingdom of Saudi Arabia & India. International Journal of Applied Business and Economic Research, 15(25), 521–527.
4.
5.
Yadav, R. K., & Dabhade, N. (2013). Impact of services quality on customer satisfaction of mobile users—A case study of Airtel. International Journal of Innovative Researcher & Studies, 2(5), 139–163.
6.
Chaudhary, A., & Uprety, I. (2013). Identification of telecom service quality dimensions in India with fuzzy analysis. Global Journal of Management and Business Studies, 3(5), 467–474.
7.
Chaudhary, A., & Uprety, I. (2016). Analysis of telecom service quality factors with analytic hierarchy process and fuzzy extent analysis: A case of public sector unit. International Journal of Business and Systems Research, 10(2–4), 162–185.CrossRef
8.
Baruah, D., Nath, T., & Bora, D. (2015). Impact of service quality dimensions on customer satisfaction in telecom sector. International Journal of Engineering Trends and Technology (IJETT), 27(2), 111–117.CrossRef
9.
Grnroos, C. (1990). Service management and marketing: Managing the moments of truth in service competition. New York: Jossey-Bass.
10.
Hirmukhe, J. (2012). Measuring internal customers’ perception on service quality using SERVQUAL in administrative services. International Journal of Scientific and Research Publications, 2(3), 1–6.
11.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). Servqual: A multiple-item scale for measuring consumer perc. Journal of Retailing, 64(1), 12–40.
12.
Liou, J. J., Yen, L., & Tzeng, G. H. (2010). Using decision rules to achieve mass customization of airline services. European Journal of Operational Research, 205(3), 680–686.CrossRef
13.
Khan, M. A. (2010). An empirical assessment of service quality of cellular mobile telephone operators in Pakistan. Asian Social Science, 6(10), 164–177.CrossRef
14.
Dalvi, P. K., Khandge, S. K., Deomore, A., Bankar, A., & Kanade, V. A. (2016). Analysis of customer churn prediction in telecom industry using decision trees and logistic regression. In Symposium on colossal data analysis and networking (CDAN) (pp. 1–4). IEEE. https://​doi.​org/​10.​1109/​cdan.​2016.​7570883.
15.
16.
Oghojafor, B. E. A., Mesike, G. C., Omoera, C. I., & Bakare, R. D. (2012). Modelling telecom customer attrition using logistic regression. African Journal of Marketing Management, 4(3), 110–117.
17.
Garín Muñoz, T., Perez Amaral, T., Gijón, C., & López, R. (2012). Customer satisfaction of mobile-internet users: An empirical approximation for the case of Spain. Journal of Reviews on Global Economics, 2, 442–454.
18.
19.
Upal, M. (2008). Telecommunication service gap: Call center service quality perception and satisfaction. Communications of the IBIMA, 3, 18–27.
20.
Loke, S. P., Taiwo, A. A., Salim, H. M., Downe, A. G., & Petronas, U. T. (2011). Service quality and customer satisfaction in a telecommunication service provider. International Conference on Financial Management and Economics, 11, 24–29.
21.
Arokiasamy, A. R. A. (2013). The impact of customer satisfaction on customer loyalty and intentions to switch in the banking sector in Malaysia. The Journal of Commerce, 5(1), 14.
22.
Gunarathne, U. W. H. D. P. (2014). Relationship between service quality and customer satisfaction in Sri Lankan hotel industry. International Journal of Scientific and Research Publications, 4(11), 1–7.
23.
Sivanesan, R. (2013). A comparative study on subscribers attitude and perception of BSNL and AIRTEL services in Kanyakumari district. International Journal of Commerce, Business and Management, 2(2), 95–104.
24.
Zhao, L., Chen, Y., & Schaffner, D. W. (2001). Comparison of logistic regression and linear regression in modeling percentage data. Applied and Environmental Microbiology, 67(5), 2129–2135.CrossRef
25.
Gasiea, Y., Emsley, M., & Mikhailov, L. (2010). Rural telecommunications infrastructure selection using the analytic network process. Journal of Telecommunications and Information Technology, 2, 15–29.
26.
Oh, Y., Suh, E. H., Hong, J., & Hwang, H. (2009). A feasibility test model for new telecom service development using MCDM method: A case study of video telephone service in Korea. Expert Systems with Applications, 36(3), 6375–6388.CrossRef
27.
Jyh-Fu Jeng, D., & Bailey, T. (2012). Assessing customer retention strategies in mobile telecommunications: Hybrid MCDM approach. Management Decision, 50(9), 1570–1595.CrossRef
28.
Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17(4), B-141.CrossRef
29.
Cagdac Arslan, M., Catay, B., & Budak, E. (2004). A decision support system for machine tool selection. Journal of Manufacturing Technology Management, 15(1), 101–109.CrossRef
30.
Tabucanon, M. T. (1988). Multiple criteria decision making in industry (Vol. 8). Amsterdam: Elsevier Science Ltd.
31.
Chen, S. J., & Hwang, C. L. (1992). Lecture notes in economics and mathematical systems. Berlin: Springer.
32.
Miller, G. A. (1956). The magic number seven plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 91–97.CrossRef
33.
Olson, D. L. (1996). Decision aids for selection problems. Berlin: Springer.CrossRef
34.
Sun, S. (2002). Assessing computer numerical control machines using data envelopment analysis. International Journal of Production Research, 40(9), 2011–2039.CrossRef
35.
Badi, I., Abdulshahed, A., & Shetwan, A. (2018). A case study of supplier selection for steelmaking company in Libya by using combinative distance-based assessemnt (CODAS) model. Decision Making: Applications in Management and Engineering, 1(1), 1–12.
36.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–356.CrossRef
37.
Molinari, F. (2016). A new criterion of choice between generalized triangular fuzzy numbers. Fuzzy Sets and Systems, 296, 51–69.CrossRef
38.
Van Broekhoven, E., & De Baets, B. (2006). Fast and accurate center of gravity defuzzification of fuzzy system outputs defined on trapezoidal fuzzy partitions. Fuzzy Sets and Systems, 157(7), 904–918.CrossRef
39.
Linacre, J. M. (1994). Likert or Rasch?, Rasch Measurement. Transactions, 8(2), 356.
40.
Lubiano, M. A., Salas, A., de Sáa, S. D. L. R., Montenegro, M., & Gil, M. Á. (2017). An empirical analysis of the coherence between fuzzy rating scale-and Likert scale-based responses to questionnaires. In M. B. Ferraro, P. Giordani, B. Vantaggi, M. Gagolewski, M. Ángeles Gil, P. Grzegorzewski & O. Hryniewicz (Eds.), Soft methods for data science (Vol. 456, pp. 329–337). Cham: Springer.CrossRef
41.
Meads, D. M., & Bentall, R. P. (2008). Rasch analysis and item reduction of the hypomanic personality scale. Personality and Individual Differences, 44(8), 1772–1783.CrossRef
42.
43.
Wampold, B. E. (1999). The promising advantages of Rasch. Rasch Measurement Transactions, 13(2), 695.
44.
Wright, B. D., & Masters, G. N. (1982). 1982: Rating scale analysis. Chicago: MESA Press.
45.
Wright, B., & Stone, M. (1979). Best test design. Chicago, IL: MESA Press.
46.
Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43(4), 561–573.CrossRef
47.
48.
Huang, J. H., & Peng, K. H. (2012). Fuzzy Rasch model in TOPSIS: A new approach for generating fuzzy numbers to assess the competitiveness of the tourism industries in Asian countries. Tourism Management, 33(2), 456–465.CrossRef
49.
Fisher, W. P., Jr., & Luce, R. D. (1995). Fuzzy truth and the Rasch model. Rasch Measurement Transactions, 9(3), 442.
50.
Kahraman, C., Onar, S. C., & Oztaysi, B. (2015). Fuzzy multicriteria decision-making: A literature review. International Journal of Computational Intelligence Systems, 8(4), 637–666.CrossRef
51.
Doumpos, M., & Zopounidis, C. (2002). Multicriteria decision aid classification methods (Vol. 73). Berlin: Springer.
52.
Mahdipoor, H. R. (2006). Flow pattern recognition in tray columns with MADM (multiple attribute decision making) method. Computers & Chemical Engineering, 30(6–7), 1197–1200.CrossRef
53.
Shanian, A., & Savadogo, O. (2006). A material selection model based on the concept of multiple attribute decision making. Materials and Design, 27(4), 329–337.CrossRef
54.
Cicek, K., & Celik, M. (2010). Multiple attribute decision-making solution to material selection problem based on modified fuzzy axiomatic design-model selection interface algorithm. Materials and Design, 31(4), 2129–2133.CrossRef
55.
Chauhan, A., & Vaish, R. (2012). Magnetic material selection using multiple attribute decision making approach. Materials and Design, 1980–2015(36), 1–5.CrossRef
56.
Mandal, U. K., Kulavi, S., & Hussain, S. A. I. (2017). A hybrid approach of AHP-cross entropy model to select bearing material under MCDM environment. In International conference on future trends and challenges in mechanical engineering (FTCME).
57.
Weber, C. A., Current, J. R., & Benton, W. C. (1991). Vendor selection criteria and methods. European Journal of Operational Research, 50(1), 2–18.CrossRef
58.
Degraeve, Z., Labro, E., & Roodhooft, F. (2000). An evaluation of vendor selection models from a total cost of ownership perspective. European Journal of Operational Research, 125(1), 34–58.CrossRef
59.
De Boer, L., Labro, E., & Morlacchi, P. (2001). A review of methods supporting supplier selection. European Journal of Purchasing & Supply Management, 7(2), 75–89.CrossRef
60.
Ho, W., Xu, X., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1), 16–24.CrossRef
61.
62.
Vasiljević, M., Fazlollahtabar, H., Stević, Ž., & Vesković, S. (2018). A rough multicriteria approach for evaluation of supplier criteria in automotive industry. Decision Making: Applications in Management and Engineering, 1(1), 82–96.
63.
Bojanić, D., Kovač, M., Bojanic, M., & Ristic, V. (2018). Multi-criteria decision making in defensive operation of guided anti-tank missile battery: An example of hybrid model fuzzy AHP-MABAC. Decision Making: Applications in Management and Engineering, 1(1), 51–66.
64.
Daim, T. U., Bhatla, A., & Mansour, M. (2013). Site selection for a data centre—A multi-criteria decision-making model. International Journal of Sustainable Engineering, 6(1), 10–22.CrossRef
65.
Elsheikh, R. F. A. (2017). Multi-criteria decision making in hotel site selection. International Journal of Engineering Science Invention, 6, 15–18.CrossRef
66.
Roy, J., Adhikary, K., Kar, S., & Pamucar, D. (2018). A rough strength relational DEMATEL model for analysing the key success factors of hospital service quality. Decision Making: Applications in Management and Engineering, 1(1), 121–142.
67.
Chatterjee, P., Mondal, S., Boral, S., Banerjee, A., & Chakraborty, S. (2017). A novel hybrid method for non-traditional machining process selection using factor relationship and multi-attributive border approximation method. Facta Universitatis, Series: Mechanical Engineering, 15(3), 439–456.CrossRef
68.
Xu, Z. (2007). Intuitionistic fuzzy aggregation operators. IEEE Transactions on Fuzzy Systems, 15(6), 1179–1187.CrossRef
69.
70.
Kharat, M. G., Kamble, S. J., Raut, R. D., Kamble, S. S., & Dhume, S. M. (2016). Modeling landfill site selection using an integrated fuzzy MCDM approach. Modeling Earth Systems and Environment, 2(2), 53.CrossRef
71.
Kuo, Y. C., Lu, S. T., Tzeng, G. H., Lin, Y. C., & Huang, Y. S. (2013). Using fuzzy integral approach to enhance site selection assessment—A case study of the optoelectronics industry. Procedia Computer Science, 17, 306–313.CrossRef
72.
Chen, V. Y., Lien, H. P., Liu, C. H., Liou, J. J., Tzeng, G. H., & Yang, L. S. (2011). Fuzzy MCDM approach for selecting the best environment-watershed plan. Applied Soft Computing, 11(1), 265–275.CrossRef
73.
74.
Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 140, 1–55.
75.
Xu, Z. S. (2007). Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision making. Control and Decision, 22(2), 215–219.
76.
Xu, Z. S., & Jian, C. H. E. N. (2007). Approach to group decision making based on interval-valued intuitionistic judgment matrices. Systems Engineering-Theory & Practice, 27(4), 126–133.CrossRef
77.
78.
Hämäläinen, R. P., & Karjalainen, R. (1992). Decision support for risk analysis in energy policy. European Journal of Operational Research, 56(2), 172–183.CrossRef
79.
Slovic, P. (1987). Perception of risk. Science, 236(4799), 280–285.CrossRef
80.
Yurdakul, M., & Ic, Y. T. (2009). Application of correlation test to criteria selection for multi criteria decision making (MCDM) models. The International Journal of Advanced Manufacturing Technology, 40(3–4), 403–412.CrossRef
81.
Burgess, T. F. (2001). A general introduction to the design of questionnaires for survey research. Information system services (pp. 1–27). Leeds: University of Leeds.
82.
Bolarinwa, O. A. (2015). Principles and methods of validity and reliability testing of questionnaires used in social and health science researches. Nigerian Postgraduate Medical Journal, 22(4), 195.CrossRef
83.
84.
Agarwal, B. L. (1988). Basic statistics. New York: Wiley Eastern Limited.
85.
Yang, Z., Fang, K. T., & Kotz, S. (2007). On the Student’s t-distribution and the t-statistic. Journal of Multivariate Analysis, 98(6), 1293–1304.CrossRef
86.
Sayfi, P., & Nikbakht, M. (2016). Identification and ranking green supplier selection criteria using one-sample T-test and FANP methods: A case study for petrochemical industry. Journal of Modern Processes in Manufacturing and Production, 5(1), 53–67.
87.
Bestetti, R. B., Couto, L. B., Restini, C. B., Faria, M., Jr., & Romão, G. S. (2017). Assessment test before the reporting phase of tutorial session in problem-based learning. Advances in Medical Education and Practice, 8, 181.CrossRef
88.
Deoskar, A. A. (2009). A study of mobile services from customer’s perspective. Ph.D. Thesis in computer management under Faculty of Management, University of Pune.
89.
Ayhan, M. B. (2013). A Fuzzy AHP approach for supplier selection problem: A case study in a gear-motor company. International Journal of Managing Value and Supply Chains, 4(3), 11–23.CrossRef
90.
Gal, T. (1986). Shadow prices and sensitivity analysis in linear programming under degeneracy. OR Spektrum, 8, 59–71.CrossRef
91.
Jansen, B., De Jong, J. J., Roos, C., & Terlaky, T. (1997). Sensitivity analysis in linear programming: Just be careful! European Journal of Operational Research, 101(1), 15–28.CrossRef
92.
Lin, C. J., & Wen, U. P. (2003). Sensitivity analysis of the optimal assignment. European Journal of Operational Research, 149(1), 35–46.CrossRef
93.
Hussain, S. A. I., Mandal, U. K., & Mondal, S. P. (2018). Decision maker priority index and degree of vagueness coupled decision making method: A synergistic approach. International Journal of Fuzzy Systems, 20(5), 1551–1566.CrossRef
94.
Awasthi, A., Chauhan, S. S., & Goyal, S. K. (2010). A fuzzy multicriteria approach for evaluating environmental performance of suppliers. International Journal of Production Economics, 126(2), 370–378.CrossRef
95.
Awasthi, A., & Kannan, G. (2016). Green supplier development program selection using NGT and VIKOR under fuzzy environment. Computers & Industrial Engineering, 91, 100–108.CrossRef
96.
Turanoglu Bekar, E., Cakmakci, M., & Kahraman, C. (2016). Fuzzy COPRAS method for performance measurement in total productive maintenance: A comparative analysis. Journal of Business Economics and Management, 17(5), 663–684.CrossRef
97.
Akkaya, G., Turanoğlu, B., & Öztaş, S. (2015). An integrated fuzzy AHP and fuzzy MOORA approach to the problem of industrial engineering sector choosing. Expert Systems with Applications, 42(24), 9565–9573.CrossRef
98.
Önüt, S., Kara, S. S., & Işik, E. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Systems with Applications, 36(2), 3887–3895.CrossRef
99.
Büyüközkan, G., & Çifçi, G. (2012). A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Systems with Applications, 39(3), 3000–3011.CrossRef
100.
Kumar, M., Tat Kee, F., & Taap Manshor, A. (2009). Determining the relative importance of critical factors in delivering service quality of banks: An application of dominance analysis in SERVQUAL model. Managing Service Quality: An International Journal, 19(2), 211–228.CrossRef
101.
Wilson, A., Zeithaml, V. A., Bitner, M. J., & Gremler, D. D. (2012). Services marketing: Integrating customer focus across the firm (2nd ed.). McGraw Hill.
Metadaten
Titel
Evaluating the impact of service quality on the dynamics of customer satisfaction in the telecommunication industry of Jorhat, Assam
verfasst von
Syed Abou Iltaf Hussain
Debasish Baruah
Bapi Dutta
Uttam Kumar Mandal
Sankar Prasad Mondal
Thuleswar Nath
Publikationsdatum
13.10.2018
Verlag
Springer US
Erschienen in
Telecommunication Systems / Ausgabe 1/2019
Print ISSN: 1018-4864
Elektronische ISSN: 1572-9451
DOI
https://doi.org/10.1007/s11235-018-0514-5

Weitere Artikel der Ausgabe 1/2019

Telecommunication Systems 1/2019 Zur Ausgabe

OriginalPaper

Optimal routing and one hop routing for D2D communications in the presence of mutual interference

OriginalPaper

Zero-rating Internet platforms formation: a game theoretic analysis

OriginalPaper

Coordinate-based addressing for MANET

OriginalPaper

A rapid anti-collision algorithm with class parting and optimal frames length in RFID systems

OriginalPaper

Approximate expressions of packet error probability, throughput and delay for cognitive radio networks using fixed and adaptive transmit power

OriginalPaper

Joint remote radio heads and baseband units pool resource scheduling for delay-aware traffic in cloud radio access networks