Empirical Evaluation of Operational and Relational Determinants on Customer Satisfaction in Disaster Recovery Outsourcing: An IPA and Regression Approach
AUTHORS
E. Rajh,Ekonomski Institut, Zagreb, Croatia
Piri Suncana,Ekonomski Institut, Zagreb, Croatia
ABSTRACT
In today’s digital ecosystem, where operational continuity is increasingly threatened by cyberattacks, data loss, and infrastructure failures, Disaster Recovery Outsourcing (DRO) has become a vital strategy for enterprises seeking to safeguard critical systems and data. This study aims to identify and analyze the key factors influencing customer satisfaction in DRO services. A structured quantitative approach was employed, involving a validated survey instrument distributed to 198 respondents across finance, healthcare, IT services, and manufacturing sectors—industries with high reliance on information resilience. The analytical framework integrated Importance-Performance Analysis (IPA) and multiple regression modeling to evaluate perceived importance and satisfaction across various service attributes. The findings reveal that customer satisfaction in DRO is not determined solely by technical service delivery—such as Recovery Time Objective (RTO) and Recovery Point Objective (RPO)—but is significantly influenced by relational dimensions, including communication effectiveness, responsiveness, and trust. IPA results identified critical service gaps in service pricing, data backup timeliness, and RPO performance. These attributes were rated highly important but underperforming, placing them in the “Concentrate Here” quadrant. Regression analysis confirmed that relational quality is the most influential predictor of overall satisfaction (β = 0.49), followed by technical service quality (β = 0.38) and economic perception (β = 0.22), with the model explaining 72.3% of the variance. The study concludes that a multidimensional approach that balances technical reliability, economic fairness, and human-centric service design is essential to improving satisfaction and retention in disaster recovery outsourcing relationships. Strategic recommendations are provided for enhancing service transparency, adaptability, and customer engagement.
KEYWORDS
Disaster recovery outsourcing, Customer satisfaction, Importance-Performance Analysis (IPA), Recovery Time Objective (RTO), Recovery Point Objective (RPO), Technical service quality, IT service management
REFERENCES
[1] A. Reis, C. Fraga, and A. J. Gouveia, “Cloud computing adoption as IT strategy in organizations: A short systematic review,” Procedia Computer Science, vol.256, pp.122–129, (2024). DOI:10.1016/j.procs.2025.02.104(CrossRef)(Google Scholar)
[2] J. Jarvelainen, “IT incidents and business impacts: Validating a framework for continuity management in information systems,” International Journal of Information Management, vol.33, no.3, pp.583–590, (2013). DOI:10.1016/j.ijinfomgt.2013.03.001(CrossRef)(Google Scholar)
[3] X. Xu, M. Tang, and Y. Tian, “QoS-guaranteed resource provisioning for cloud-based MapReduce in dynamical environments,” Future Generation Computer Systems, vol.78, pp.18–30, (2017). DOI:10.1016/j.future.2017.08.005(CrossRef)(Google Scholar)
[4] F. L. Lizarelli, L. Osiro, G. M. Ganga, G. H. Mendes, and G. R. Paz, “Integration of SERVQUAL, analytical Kano, and QFD using fuzzy approaches to support improvement decisions in an entrepreneurial education service,” Applied Soft Computing, vol.112, p.107786, (2021). DOI:10.1016/j.asoc.2021.107786(CrossRef)(Google Scholar)
[5] W. J. Kettinger, S. Park, and J. Smith, “Understanding the consequences of information systems service quality on IS service reuse,” Information & Management, vol.46, no.6, pp.335–341, (2009). DOI:10.1016/j.im.2009.03.004(CrossRef)(Google Scholar)
[6] D. M. Kesa, “Ensuring resilience: Integrating IT disaster recovery planning and business continuity for sustainable information technology operations,” World Journal of Advanced Research and Reviews, vol.18, no.3, pp.970–992, (2023). DOI:10.30574/wjarr.2023.18.3.1166(CrossRef)(Google Scholar)
[7] A. Z. Abualkishik, A. A. Alwan, and Y. Gulzar, “Disaster recovery in cloud computing systems: An overview,” International Journal of Advanced Computer Science and Applications (IJACSA), vol.11, no.9, (2020). DOI:10.14569/IJACSA.2020.0110984(CrossRef)(Google Scholar)
[8] S. Thekdi, U. Tatar, J. Santos, and S. Chatterjee, “Disaster risk and artificial intelligence: A framework to characterize conceptual synergies and future opportunities,” Risk Analysis, vol.43, no.8, pp.1641–1656, (2023). DOI:10.1111/risa.14038(CrossRef)(Google Scholar)
[9] J. J. Liou, H. Wang, C. Hsu, and S. Yin, “A hybrid model for selection of an outsourcing provider,” Applied Mathematical Modelling, vol.35, no.10, pp.5121–5133, (2011). DOI:10.1016/j.apm.2011.04.020(CrossRef)(Google Scholar)
[10] M. C. Lacity, S. A. Khan, and L. P. Willcocks, “A review of the IT outsourcing literature: Insights for practice,” The Journal of Strategic Information Systems, vol.18, no.3, pp.130–146, (2009). DOI:10.1016/j.jsis.2009.06.002(CrossRef)(Google Scholar)
[11] Q. Duan, “Cloud service performance evaluation: Status, challenges, and opportunities – a survey from the system modeling perspective,” Digital Communications and Networks, vol.3, no.2, pp.101–111, (2017). DOI:10.1016/j.dcan.2016.12.002(CrossRef)(Google Scholar)
[12] R. Mechler, “Reviewing estimates of the economic efficiency of disaster risk management: Opportunities and limitations of using risk-based cost–benefit analysis,” Natural Hazards, vol.81, pp.2121–2147, (2016). DOI:10.1007/s11069-016-2170-y(CrossRef)(Google Scholar)
[13] A. Guerrero, O. Bodin, D. Nohrstedt, R. Plummer, J. Baird, and R. Summers, “Collaboration and individual performance during disaster response,” Global Environmental Change, vol.82, p.102729, (2023). DOI:10.1016/j.gloenvcha.2023.102729(CrossRef)(Google Scholar)
[14] L. Wang, P. Hu, X. Kong, W. Ouyang, B. Li, H. Xu, and T. Shao, “Microservice architecture recovery based on intra-service and inter-service features,” Journal of Systems and Software, vol.204, p.111754, (2023). DOI:10.1016/j.jss.2023.111754(CrossRef)(Google Scholar)
[15] S. Abbasi, Ç. Sıcakyüz, E. D. Santibanez Gonzalez, and P. Ghasemi, “A systematic literature review of logistics services outsourcing,” Heliyon, vol.10, no.13, e33374, 2024. DOI:10.1016/j.heliyon.2024.e33374(CrossRef)(Google Scholar)
[16] T. A. E. Aben, W. van der Valk, J. K. Roehrich, and K. Selviaridis, “Managing information asymmetry in public–private relationships undergoing a digital transformation: The role of contractual and relational governance,” International Journal of Operations & Production Management, vol.41, no.7, pp.1145–1191, 2021. DOI:10.1108/IJOPM-09-2020-0675(CrossRef)(Google Scholar)
[17] S. Jones, Z. Irani, U. Sivarajah, et al., “Risks and rewards of cloud computing in the UK public sector: A reflection on three organisational case studies,” Information Systems Frontiers, vol.21, pp.359–382, (2019). DOI:10.1007/s10796-017-9756-0(CrossRef)(Google Scholar)
[18] B. Baatartogtokh, W. S. Dunbar, and D. Van Zyl, “The state of outsourcing in the Canadian mining industry,” Resources Policy, vol.59, pp.184–191, (2018). DOI:10.1016/j.resourpol.2018.06.014(CrossRef)(Google Scholar)
[19] S. Sengupta and K. Annervaz, “Multi-site data distribution for disaster recovery—A planning framework,” Future Generation Computer Systems, vol.41, pp.53–64, (2014). DOI:10.1016/j.future.2014.07.007(CrossRef)(Google Scholar)
[20] M. L. Finucane, J. Acosta, A. Wicker, and K. Whipkey, “Short-term solutions to a long-term challenge: Rethinking disaster recovery planning to reduce vulnerabilities and inequities,” International Journal of Environmental Research and Public Health, vol.17, no.2, p.482, (2020). DOI:10.3390/ijerph17020482(CrossRef)(Google Scholar)
[21] A. Maria, L. Lily, C. Augusto, and E. J. Eric, “Sustainability and resilience organizational capabilities to enhance business continuity management: A literature review,” Sustainability, vol.13, no.15, p.8196, (2020). DOI:10.3390/su13158196(CrossRef)(Google Scholar)