Quality assessment of the contact center while implementation the IP IVR system by using teletraffic theory

Authors

  • Katipa Chezhimbayeva Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev, Kazakhstan https://orcid.org/0000-0002-1661-2226
  • Madina Konyrova Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev, Kazakhstan
  • Saule Kumyzbayeva Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev, Kazakhstan https://orcid.org/0000-0003-3175-2435
  • Elvira Kadylbekkyzy Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev, Kazakhstan https://orcid.org/0000-0003-4059-5996

DOI:

https://doi.org/10.15587/1729-4061.2021.244976

Keywords:

Interactive Voice Response – IVR, service quality, call probability, queueing theory, teletraffic theory, communication systems

Abstract

The paper considers the form of taking into account the specialization of information needs. An analysis of the work of modern call centers has been carried out. The authors noted the effectiveness of using IVR devices, operators, and consultants for differentiated customer service and the need to take feedback into account when forming the revenue stream of applications. The models make it possible to determine the leading indicators of the quality of service for applications arriving at the call center. Formal expressions for descriptions are derived from the input parameters' values and the model's stationary probability. The relationships between the characteristics of the call center that regulate the intensity of incoming and outgoing calls, call processing through 3CXPhone, corporate mail, and social networks were obtained using Global Statistic. The developed methodology for organizing information and reference systems makes it possible to consider modern trends in the development of call centers. The paper presents the results of research using the IP IVR system. The results of calculating service characteristics are given for two different types of calls with mixed order ω=(0.5; 0.7; 0.9). The presented results were obtained by using experimental data of the JSC Kazakhtelecom's call center. For the calculations, the authors used the formulas of the teletraffic theory for a mixed service system. It also assesses the extent of combined service model effects for the contact center's call quality. It is shown that the probability of lost calls depends on the incoming load. The obtained results show that the mixed order for incoming calls servicing affects the probability of service failure.

Supporting Agency

  • The authors of the article express their appreciation to the Department of Telecommunications and Innovative Technologies for the financial support provided in the article's publication. The article was funded by the Telecommunications and Innovative Technologies Department budget in the item

Author Biographies

Katipa Chezhimbayeva, Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev

PhD, Professor

Department of Telecommunications and Innovative Technologies

Madina Konyrova, Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev

Doctorant Student

Department of Telecommunications and Innovative Technologies

Saule Kumyzbayeva, Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev

PhD, Senior Lecturer

Department of Telecommunications and Innovative Technologies

Elvira Kadylbekkyzy, Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev

PhD, Associate Professor

Department of Telecommunications and Innovative Technologies

References

  1. Afolalu, S. A., Ikumapayi, O. M., Abdulkareem, A., Emetere, M. E., Adejumo, O. (2021). A short review on queuing theory as a deterministic tool in sustainable telecommunication system. Materials Today: Proceedings, 44, 2884–2888. doi: https://doi.org/10.1016/j.matpr.2021.01.092
  2. Valverde, M., Ryan, G., Gorjup, M. T. (2007). An Examination of the Quality of Jobs in the Call Center Industry. International Advances in Economic Research, 13 (2), 146–156. doi: https://doi.org/10.1007/s11294-007-9078-y
  3. Khizirova, M. A., Chezhimbayeva, K., Mukhamejanova, A., Manbetova, Z., Ongar, B. (2021). Using of virtual private network technology for signal transmission in corporate networks. News of the National Academy of Sciences of the Republic of Kazakhstan. Series of Geology and Technical Sciences, 3 (447), 100–103. doi: https://doi.org/10.32014/2021.2518-170x.69
  4. Kumyzbayeva, S., Ibragimova, M., Stoyak, V., Apsemetov, A. (2016). Hybrid stand-alone power supply system in conditions of extreme continental climate in Central Asia. 2016 International Conference on Cogeneration, Small Power Plants and District Energy (ICUE). doi: https://doi.org/10.1109/cogen.2016.7728940
  5. Walsh, G., Gouthier, M., Gremler, D. D., Brach, S. (2012). What the eye does not see, the mind cannot reject: Can call center location explain differences in customer evaluations? International Business Review, 21 (5), 957–967. doi: https://doi.org/10.1016/j.ibusrev.2011.11.002
  6. Alcover, C.-M., Chambel, M. J., Estreder, Y. (2020). Monetary incentives, motivational orientation and affective commitment in contact centers. A multilevel mediation model. Journal of Economic Psychology, 81, 102307. doi: https://doi.org/10.1016/j.joep.2020.102307
  7. Chicu, D., Pàmies, M. del M., Ryan, G., Cross, C. (2019). Exploring the influence of the human factor on customer satisfaction in call centres. BRQ Business Research Quarterly, 22 (2), 83–95. doi: https://doi.org/10.1016/j.brq.2018.08.004
  8. Dean, D. H. (2008). What's wrong with IVR self‐service. Managing Service Quality: An International Journal, 18 (6), 594–609. doi: https://doi.org/10.1108/09604520810920086
  9. Bauermeister, J. A., Carballo-Dieguez, A., Giguere, R., Valladares, J., McGowan, I. (2014). Interactive Voice Response System (IVRS): Data Quality Considerations and Lessons Learned During a Microbicide Placebo Adherence Trial With Young Men Who Have Sex With Men. Journal of Adolescent Health, 54 (2), S57–S58. doi: https://doi.org/10.1016/j.jadohealth.2013.10.128
  10. Namestnikov, S. M., Sluzhivyy, M. N., Ukraincev, Yu. D. (2016). Osnovy teorii teletrafika. Ul'yanovsk, 154. Available at: http://tk.ulstu.ru/lib/books/book_tt.pdf
  11. Afolalu, A. S., Adelakun, O. J., Ongbali, S. O., Abioye, A. A., Ajayi, O. O. (2019). Queueing Theory – A Tool for Production Planning in Health Care. Proceedings of the World Congress on Engineering 2019. Available at: http://www.iaeng.org/publication/WCE2019/WCE2019_pp391-396.pdf
  12. Kruger, K., Basson, A. H. (2019). Evaluation of JADE multi-agent system and Erlang holonic control implementations for a manufacturing cell. International Journal of Computer Integrated Manufacturing, 32 (3), 225–240. doi: https://doi.org/10.1080/0951192x.2019.1571231
  13. Atencia, I., Galán–García, J. L., Aguilera–Venegas, G., Rodríguez–Cielos, P., Galán–García, M. Á., Padilla–Domínguez, Y. (2021). A discrete-time queueing system with three different strategies. Journal of Computational and Applied Mathematics, 393, 113486. doi: https://doi.org/10.1016/j.cam.2021.113486

Downloads

Published

2021-12-29

How to Cite

Chezhimbayeva, K., Konyrova, M., Kumyzbayeva, S., & Kadylbekkyzy, E. (2021). Quality assessment of the contact center while implementation the IP IVR system by using teletraffic theory. Eastern-European Journal of Enterprise Technologies, 6(3 (114), 64–71. https://doi.org/10.15587/1729-4061.2021.244976

Issue

Section

Control processes