Skip to main content
Log in

A knowledge-based exploratory framework to study quality of Italian mobile telecommunication services

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

A novel two-step knowledge-based exploratory framework is proposed in this paper for studying quality of Italian mobile telecommunication services (MTSs). Particularly, the Delphi technique is initially considered to finalize an overall quality structure of MTSs features, indicators and drivers, herein described on the basis of a comprehensive review of the fundamental references for the field, and also to select the key elements with reference to the Italian context. At the second step, selected key elements are prioritized via the analytic hierarchical process method according to viewpoints of the fundamental stakeholders for the sector. Furthermore, possible uncertainty and ambiguity of involved experts at this step of the study are addressed via a linguistic comparison scale represented by fuzzy numbers. Results of the first step revealed that the quality structure of Italian MTSs includes 15 key indicators with reference to four key MTSs quality features and seven key drivers. On the other hand, results of the second step pointed out that tangible aspects represents the fundamental key MTSs quality feature, whereas network population coverage, price of data services, and internet network performance represent the crucial key indicators. In addition, technological resources and technological innovation as well as informational resources constitute the most important key quality drivers of Italian MTSs. Obtained results may be of interest for MTSs managers and decision makers as well researchers of the field offering important suggestions as to how to evaluate and improve quality of MTSs.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. AGCOM Annual Report. (2015). http://www.agcom.it/annual-report.

  2. Ahn, J.-H., Han, S.-P., & Lee, Y.-S. (2006). Customer churn analysis: Churn determinants and mediation effects of partial defection in the Korean mobile telecommunications service industry. Telecommunications Policy, 30(10–11), 552–568.

    Article  Google Scholar 

  3. Ansari, A., Kheirabadi, A., Ghalamkari, S., & Khanjari, A. R. (2013). Investigation the relationship among mobile value-added services quality, customer satisfaction and the continuance intention: Case study, Hamrah Avval operator. International Journal of Information Science and Management, 11, 67–84.

    Google Scholar 

  4. Keramati, A., & Ardabili, S. M. S. (2011). Churn analysis for an Iranian mobile operator. Telecommunications Policy, 35(4), 344–356.

    Article  Google Scholar 

  5. Kim, J., Lee, D.-J., & Ahn, J. (2006). A dynamic competition analysis on the Korean mobile phone market using competitive diffusion model. Computers and Industrial Engineering, 51(1), 174–182.

    Article  Google Scholar 

  6. Kirkwood, G. W. (1997). Strategic decision making. Belmont: Duxbury Press.

    Google Scholar 

  7. Volberda, H. W., Van Den Bosch, F. A. J., & Heij, C. V. (2013). Management innovation: Management as fertile ground for innovation. European Management Review, 10(1), 1–15.

    Article  Google Scholar 

  8. Ambastha, A., & Momaya, K. (2004). Competitiveness of firms: Review of theory, frameworks, and models. Singapore Management Review, 26(1), 45–61.

    Google Scholar 

  9. Subramanian, N., Gunasekaran, A., Yu, J., Cheng, J., & Ning, K. (2014). Customer satisfaction and competitiveness in the Chinese E-retailing: Structural equation modeling (SEM) approach to identify the role of quality factors. Expert Systems with Applications, 41(1), 69–80.

    Article  Google Scholar 

  10. Crouch, G. I., & Ritchie, J. R. (1999). Tourism, competitiveness, and societal prosperity. Journal of Business Research, 44(3), 137–152.

    Article  Google Scholar 

  11. Tan, F. B., & Chou, J. P. C. (2008). The relationship between mobile service quality, perceived technology compatibility, and users’ perceived playfulness in the context of mobile information and entertainment services. International Journal of Human–Computer Interaction, 24(7), 649–671.

    Article  Google Scholar 

  12. Charles, V., & Zegarra, L. F. (2014). Measuring regional competitiveness through data envelopment analysis: A peruvian case. Expert Systems with Applications, 41(11), 5371–5381.

    Article  Google Scholar 

  13. Chikán, A. (2008). National and firm competitiveness: A general research model. Competitiveness Review: An International Business Journal incorporating Journal of Global Competitiveness, 18(1/2), 20–28.

    Article  Google Scholar 

  14. Pace, R. W., & Stephan, E. G. (1996). Paradigms of competitiveness. Competitiveness Review: An International Business Journal Incorporating Journal of Global Competitiveness, 6(1), 8–13.

    Article  Google Scholar 

  15. Waheeduzzaman, A. N. M., & Ryans, J. K, Jr. (1996). Definition, perspectives, and understanding of international competitiveness: A quest for a common ground. Competitiveness Review, 6(2), 7–26.

    Article  Google Scholar 

  16. OECD/DAC. (2010). Glossary of key terms in evaluation and results based management. Retrieved June 1, 2015, from http://www.oecd.org/development/peerreviewsofdacmembers/2754804.pdf.

  17. Telecom Italia Report. (2015). http://www.telecomitalia.com/content/dam/telecomitalia/it/archivio/documenti/Investitori/Bilanci_di_esercizio/2015/Relazione-finanziaria-annuale2015.pdf.

  18. ETSI TS 102 250-1 V2.2.1. (2011–2004). Speech and multimedia transmission quality.

  19. ITU X.36 Accuracy and dependability performance values for public data networks when providing international packet-switched services.

  20. ITU X.135 Speed of service (delay and throughput) performance values for public data networks when providing international packet-switched services.

  21. ITU X.137 Availability performance values for public data networks when providing international packet-switched services.

  22. ITU X.138 Measurement of performance values for public data networks when providing international packet-switched services.

  23. ITU X.140 General Quality of service parameters for communication via public data networks.

  24. WIND Sustainability Report. (2014). http://www.sostenibilitawind.com/docs/bilancio_2014.pdf.

  25. TIM Sustainability Report. (2014). http://www.telecomitalia.com/content/dam/telecomitalia/it/archivio/documenti/Sostenibilita/Report_di_sostenibilita/2014/Bilancio-Sostenibilita%CC%80-2014-ITA.pdf.

  26. Vodafone Sustainability Report. (2014). http://v2.vodafone.it/portal/resources/media/Documents/corporate/Vodafone_Foundation_Bilancio_Sostenibilita_2015_Ridotto_new.pdf.

  27. Eshghi, A., Haughton, D., & Topi, H. (2007). Determinants of customer loyalty in the wireless telecommunications industry. Telecommunications Policy, 31(2), 93–106.

    Article  Google Scholar 

  28. Lee, J., Lee, J., & Feick, F. (2001). The impact of the switchingcosts on the customer satisfaction-loyalty link: Mobile phone service in France. Journal of Services Marketing, 15(1), 35–48.

    Article  Google Scholar 

  29. Taha, A., Jahed, D. H., Ahmad, M. N. & Zakaria H. (2013). Antecedents of customer satisfaction in mobile commerce: A systematic literature review. In International conference on research and innovation in information systems (ICRIIS). Kuala Lumpur, 27–28 Nov. 2013. pp. 554–558. ISSN: 2324-8149.

  30. Yang, K. C. C. (2005). Exploring factors affecting the adoption of mobile commerce in Singapore. Telematics and Informatics, 22, 257–277.

    Article  Google Scholar 

  31. Tsang, M., Ho, S. C., & Liang, T. P. (2004). Consumer attitudes toward mobile advertising: An empirical study. International Journal of Electronic Commerce, 8(3), 65–78.

    Google Scholar 

  32. ISO 9001:2015. Quality management system.

  33. BS OHSAS 18001: 2007. Occupational health and safety management systems—Requirements.

  34. ISO 14001:2015. Environmental management system.

  35. ISO 26000:2010. Guidance on social responsibility.

  36. Lam, P. L., & Shiu, A. (2010). Economic growth, telecommunications development and productivity growth of the telecommunications sector: Evidence around the world. Telecommunications Policy, 34(4), 185–199.

    Article  Google Scholar 

  37. Urda, J., & Loch, C. H. (2013). Social preferences and emotions as regulators of behavior in processes. Journal of Operations Management, 31(1), 6–23.

    Article  Google Scholar 

  38. Paulrajan, R., & Rajkumar, H. (2011). Service quality and customers preference of cellular mobile service providers. Journal of Technology Management & Innovation, 6(1), 38–45.

  39. Suárez, D., García-Mariñoso, B., & Santos, I. (2016). Satisfaction of business customers with mobile phone and internet services in Spain. Telecommunications Policy, 40(1), 52–61.

    Article  Google Scholar 

  40. Karjaluoto, H., Jayawardhena, C., Leppäniemi, M., & Pihlström, M. (2013). How value and trust influence loyalty in wireless telecommunications industry. Telecommunications Policy, 36(8), 636–649.

    Article  Google Scholar 

  41. Pagani, M. (2004). Determinants of adoption of third generation mobile multimedia services. Journal of Interactive Marketing, 18(3), 46–59.

    Article  Google Scholar 

  42. Haque, A., Rahman, S., & Rahman, M. (2010). Factors determinants the choice of mobile service providers: Structural equation modeling approach on Bangladeshi consumers. Business and Economics Research Journal, 1(3), 17–34.

    Google Scholar 

  43. ISO 50001:2011—Energy management system.

  44. AGCOM Resolution #417/01/CONS. Guidelines on communications to customers of the services offered. http://www.agcom.it/documents/10179/538499/Delibera+417-01-CONS/0c12c63b-cae9-454e-b426-4f278d3c5c7e?version=1.0&targetExtension=pdf.

  45. Carlson, C., Hyvönen, K., Repo, P. & Walden, P. (2005) Adoption of mobile services across different technologies. In 18th Bled eConference eIntegration in Action. Bled, Slovenia, June 6–8, 2005.

  46. Gijón, C., Garín-Muñoz, T., Pérez-Amaral, T., & López-Zorzano, R. (2013). Satisfaction of individual mobile phone users in Spain. Telecommunications Policy, 37(10), 940–954.

    Article  Google Scholar 

  47. Seth, A., Momaya, K., & Gupta, H. (2005). E-service delivery in cellular mobile communication: Some challenges and issues. Global Journal of e-Business and Knowledge Management, 2(2), 30–42.

    Google Scholar 

  48. Shih, Y. W. (2011). Facilitators and benefits of using mobile entertainment services. International Journal of Mobile Communications, 9(5), 458–476.

    Article  Google Scholar 

  49. Turel, O., & Serenko, A. (2006). Satisfaction with mobile services in Canada: An empirical investigation. Telecommunications Policy, 30(3), 314–331.

    Article  Google Scholar 

  50. SA 8000: 2008. International standard on social accountability.

  51. Lo, C. K. Y., Pagell, M., Fan, D., Wiengarten, F., & Yeung, A. C. L. (2014). OHSAS 18001 certification and operating performance: The role of complexity and coupling. Journal of Operations Management, 32(5), 268–280.

    Article  Google Scholar 

  52. Ward, M. R., & Zheng, S. (2016). Mobile telecommunications service and economic growth: Evidence from China. Telecommunications Policy, 40(2–3), 89–101.

    Article  Google Scholar 

  53. AGCOM Resolution #244/08/CSP. Instructions on quality of internet access services. http://www.agcom.it/documents/10179/539047/Delibera+244-08-CSP/ec82324a-f2a4-4b0e-8109-b53b7e8e9fce?version=1.0&targetExtension=pdf.

  54. Gerpott, T. J., Rams, W., & Schindler, A. (2001). Customer retention, loyalty, and satisfaction in the German mobile cellular telecommunications market. Telecommunications Policy, 25(4), 249–269.

    Article  Google Scholar 

  55. Hafeez, S., & Hasnu, S. (2010). Customer satisfaction for cellular phones in Pakistan: A case study of Mobilink. Business and Economics Research Journal, 1(3), 35–44.

    Google Scholar 

  56. Liu, C. M. (2000). The effects of promotional activities on brand decision in the cellular telephone industry. The Journal of Product and Brand Management, 11(1), 42–51.

    Article  Google Scholar 

  57. Woodru, R. B. (1997). Customer value: The next source for competitive advantage. Journal of the Academy of Marketing Science, 25, 139–153.

    Article  Google Scholar 

  58. AGCOM Resolution # 645/14/CONS. Regulation for protecting consumers in respect of agreements. http://www.agcom.it/documents/10179/1609860/Delibera+645-14-CONS/0f7075e2-b38c-4bad-a104-309eb92d34e7?version=1.5.

  59. Linstone, H. A., & Turoff, M. (2002). The Delphi method: Techniques and applications. Reading, MA: Addison-Wesley.

    Google Scholar 

  60. Van Laarhoven, P. J. M., & Pedrycz, W. (1983). A fuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems, 11, 229–241.

    Article  Google Scholar 

  61. Adler, M., & Ziglio, E. (1996). Gazing into the oracle: The Delphi method and its application to social policy and public health. London: Kingsley.

    Google Scholar 

  62. Hsu, C., & Sandford, B. (2007). The Delphi technique: Making sense of consensus. Practical Assessment, Research & Evaluation, 12, 1–8.

    Google Scholar 

  63. McKenna, H. P. (1994). The Delphi technique: A worthwhile research approach for nursing? Journal of Advanced Nursing, 19, 1221–1225.

    Article  Google Scholar 

  64. Alvarez, S., Carballo-Penela, A., Mateo-Mantecon, I., & Rubio, A. (2016). Strengths–Weaknesses–Opportunities–Threats analysis of carbon footprint indicator and derived recommendations. Journal of Cleaner Production, 121, 238–247.

    Article  Google Scholar 

  65. Mbakwe, A. C., Saka, A. A., Choi, K., & Lee, Y.-J. (2016). Alternative method of highway traffic safety analysis for developing countries using Delphi technique and Bayesian network. Accident Analysis and Prevention, 93(1), 135–146.

    Article  Google Scholar 

  66. Ormshaw, M. J., Kokko, S. P., Villberg, J., & Kannas, L. (2016). The desired learning outcomes of school-based nutrition/physical activity health education: A health literacy constructed Delphi survey of Finnish experts. Health Education, 116(4), 372–394.

    Article  Google Scholar 

  67. Hinckeldeyn, J., Dekkers, R., & Kreutzfeldt, J. (2015). Productivity of product design and engineering processes unexplored territory for production management techniques? International Journal of Operations & Production Management, 35(4), 458–486.

    Article  Google Scholar 

  68. Delbari, S. A., Ng, S. I., Aziz, Y. A., & Ho, J. A. (2016). An investigation of key competitiveness indicators and drivers of full-service airlines using Delphi and AHP techniques. Journal of Air Transport Management, 52, 23–34.

    Article  Google Scholar 

  69. Sinclair, J. B., Oyebode, J. R., & Owens, R. G. (2016). Consensus views on advance care planning for dementia: A Delphi study. Health and Social Care in the Community, 24(2), 165–174.

    Article  Google Scholar 

  70. Henning, J. I. F., & Jordaan, H. (2016). Determinants of financial sustainability for farm credit applications: A Delphi study. Sustainability (Switzerland), 8(1), 1–15.

    Google Scholar 

  71. Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28, 563–575.

    Article  Google Scholar 

  72. Vaidya, O. S., & Kumar, S. (2006). Analytic hierarchy process: An overview of applications. European Journal of Operational Research, 169(1), 1–29.

    Article  Google Scholar 

  73. Subramanian, N., & Ramanathan, R. (2012). A review of applications of analytic hierarchy process in operations management. International Journal of Production Economics, 138(2), 215–241.

    Article  Google Scholar 

  74. Ferdous, R., Khan, F., Sadiq, R., Amyotte, P., & Veitch, B. (2012). Handling and updating uncertain information in bow-tie analysis. Journal of Loss Prevention in the Process Industries, 25, 8–12.

    Article  Google Scholar 

  75. Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukias, A., & Vincke, P. (2000). Evaluation models: A critical perspective. Boston: Kluwer.

    Book  Google Scholar 

  76. Ishizaka, A. (2014). Comparison of fuzzy logic, AHP, FAHP and hybrid fuzzy AHP for new supplier selection and its performance analysis. International Journal of Integrated Supply Management, 9(1–2), 1–22.

    Article  Google Scholar 

  77. Leung, L. C., & Cao, D. (2000). On consistency and ranking of alternatives in fuzzy AHP. European Journal of Operational Research, 124(1), 102–113.

    Article  Google Scholar 

  78. Ayağ, Z. (2005). A fuzzy AHP-based simulation approach to concept evaluation in a NPD environment. IIE Transactions, 37(9), 827–842.

    Article  Google Scholar 

  79. Büyüközkan, G., & Çifçi, G. (2012). A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in health care industry. Expert Systems with Applications, 39, 2341–2354.

    Article  Google Scholar 

  80. Klir, G. J., & Yuan, B. (1999). Fuzzy sets and fuzzy logic, theory and applications. Upper Saddle River, NJ: Prentice Hall PTR.

    Google Scholar 

  81. Kulak, O., & Kahraman, C. (2005). Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic hierarchy process. Information Sciences, 170(2), 191–210.

    Article  Google Scholar 

  82. Zadeh, L. A. (1965). Fuzzy set. Information and Control, 8(3), 338–353.

    Article  Google Scholar 

  83. Dura’n, O., & Aguilo, J. (2008). Computer-aided machine-tool selection based on a fuzzy-AHP approach. Expert Systems with Applications, 34, 1787–1794.

    Article  Google Scholar 

  84. Kahraman, C., Ertay, T., & Büyüközkan, G. (2006). A fuzzy optimization model for QFD planning process using analytic network approach. European Journal of Operational Research, 171(2), 390–411.

    Article  Google Scholar 

  85. Promentilla, M. A. B., Furuichi, T., Ishii, K., & Tanikawa, N. (2008). A fuzzy analytic network process for multi-criteria evaluation of contaminated site remedial countermeasures. Journal of Environmental Management, 88, 479–495.

    Article  Google Scholar 

  86. Kubler, S., Robert, J., Derigent, W., Voisin, A., & Le Traon, Y. (2016). A state-of the-art survey and testbed of fuzzy AHP (FAHP) applications. Expert Systems With Applications, 65, 398–422.

    Article  Google Scholar 

  87. Basak, I., & Saaty, T. (1993). Group decision making using the analytic hierarchy process. Mathematical and Computer Modelling, 17(4–5), 101–109.

    Article  Google Scholar 

  88. Chang, D.-Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655.

    Article  Google Scholar 

  89. Csutora, R., & Buckley, J. J. (2001). Fuzzy hierarchical analysis: The lambda-max method. Fuzzy Sets and Systems, 120(2), 181–195.

    Article  Google Scholar 

  90. Lee, A. R. (1999). Application of modified fuzzy AHP method to analyze bolting sequence of structural joints, UMI dissertation services. A. Bell & Howell Company.

  91. Powell, C. (2003). The Delphi technique: Myths and realities. Journal of Advanced Nursing, 41, 376–382.

    Article  Google Scholar 

  92. Hasson, F., Keeney, S., & McKenna, H. (2000). Research guidelines for the Delphi survey technique. Journal of Advanced Nursing, 32, 1008–1015.

    Google Scholar 

  93. Murphy, M. K., Black, N. A., Lamping, D. L., McKee, C. M., Sanderson, C. F., Askham, J., et al. (1998). Consensus development methods, and their use in clinical guideline development. Health Technology Assessment, 2(i–iv), 1–88.

    Google Scholar 

  94. Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1, 83–98.

    Article  Google Scholar 

  95. Gow, F. (1979). CETA and Vocational Education Administrator’ perceptions of procedures for the implementation and operation of jointly delivered programs in Virginia (Unpublished doctoral dissertation). Virginia Polytechnic Institute and State University, USA.

  96. Jaeger, R. M., & Busch, J. C. (1984). The effects of a Delphi modification of the Angoff-Jaeger standard-setting procedure on standards recommended for the national teacher examinations. Paper presented at the annual meeting of the National Council on Measurement in Education, New Orleans, LA.

  97. Tersine, R. J., & Riggs, W. E. (1976). Models: Decision tools for management. Journal of Systems Management, 27(10), 30–34.

  98. McGaw, B., Browne, R. K., & Rees, P. (1976). Delphi in education: Review and assessment. Australian Journal of Education, 20(1), 59–76.

    Article  Google Scholar 

  99. Fish, L. S., & Osborn, J. L. (1992). Therapists’ views of family life: A Delphi study. Family Relations, 41(4), 409–416.

  100. De Meyrick, J. (2003). The Delphi method and health research. Health education, 103(1), 7–16.

    Article  Google Scholar 

  101. Taylor, R. E., Judd, L. L., Witt, S. F., & Moutinho, L. (1989). Delphi method applied to tourism. In Tourism marketing and management handbook (pp. 95–98).

  102. Velasquez, M., & Hester, P. T. (2013). An analysis of multi-criteria decision making methods. International Journal of Operations Research, 10(2), 56–66.

    Google Scholar 

  103. Saaty, T. L. (1999). Fundamentals of the analytical network process. In Proceedings of ISAHP 1999, Kobe, Japan, August 12–14, pp. 48–63.

  104. Sarkis, J., & Sundarraj, R. P. (2005). Evaluation of enterprise information technologies: A decision model for high-level consideration of strategic and operational issues. IEEE Transactions on Systems, Man., and Cybernetics-Part C: Applications and Reviews, 36(2), 260–273.

  105. Roohnavazfar, M., Houshmand, M., Zarandi, R. N., & Mirsalim, M. (2014). Optimization of design parameters of a limited angle torque motor using analytical hierarchy process and axiomatic design theory. Production & Manufacturing Research, 2(1), 400–414.

    Google Scholar 

  106. Gavade, R. K. (2014). Multi-criteria decision making: An overview of different selection problems and methods. International Journal of Computer Science and Information Technologies, 5(4), 5643–5646.

    Google Scholar 

  107. Triantaphyllou, E., & Mann, S. H. (1995). Using the analytic hierarchy process for decision making in engineering applications: Some challenges. International Journal of Industrial Engineering: Applications and Practice, 2(1), 35–44.

    Google Scholar 

  108. Wang, Y. M., & Luo, Y. (2009). On rank reversal in decision analysis. Mathematical and Computer Modelling, 49(5), 1221–1229.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Toni Lupo.

Appendices

Appendix A

In this section, obtained matrices of evaluating rating of key drivers resulting from the FAHP analysis are reported (Table 9).

Appendix B

See Fig. 5.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lupo, T., Delbari, S.A. A knowledge-based exploratory framework to study quality of Italian mobile telecommunication services. Telecommun Syst 68, 129–144 (2018). https://doi.org/10.1007/s11235-017-0380-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-017-0380-6

Keywords

Navigation