Abstract
Selection of a cloud service provider (CSP) is an important decision for businesses that make long-term investments. Notably, this process is a complex decision that involves assessing multiple criteria where more than one condition jointly may dictate the decision. In addition, the selection decision can be explained with more than one equally effective configuration of conditions. Moreover, the causal configurations for predicting the rejection of a CSP are unique and may not mirror opposites of the causal configurations of the selection of a CSP. Prior studies commonly apply traditional regression-based linear modeling techniques and thus far, these techniques do not fully capture the complexity of CSP selection but rather identify the individual and isolated effects of the conditions. This study fills the gap by proposing a new configuration framework, which posits that CSP selection does not depend on individual conditions, but on their specific configurations. The configurational model has been validated using fuzzy-set qualitative comparative analysis method. The results suggest three configurations to select and reject a CSP in conjunction with the implications to research and practice.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Both individuals and businesses can be the users; however, our focus is the latter.
- 2.
In configurational models, the antecedent factors (i.e., independent variables) explaining a dependent variable are called “conditions” and the dependent variable is called as “outcome variable.”
References
Walther, S., et al.: Exploring subscription renewal intention of operational cloud enterprise systems-a socio-technical approach. In: European Conference on Information Systems. AIS, Utrecht, The Netherlands (2013)
Salim, S.A., et al.: Moving from evaluation to trial: how do SMEs start adopting cloud ERP? Australas. J. Inf. Syst. 19, S219–S254 (2015)
Walther, S., et al.: Exploring organizational level continuance of cloud-based enterprise systems. In: European Conference on Information Systems. AIS, Münster, Germany (2015)
Youssef, A.E.: An integrated MCDM approach for cloud service selection based on TOPSIS and BWM. IEEE Access 8, 71851–71865 (2020)
Kumar, R.R., Mishra, S., Kumar, C.: A novel framework for cloud service evaluation and selection using hybrid MCDM methods. Arab. J. Sci. Eng. 43, 7015–7030 (2018)
Lang, M., Wiesche, M., Krcmar, H.: What are the most important criteria for cloud service provider selection? A Delphi study. In: European Conference on Information Systems (2016)
Sun, L., et al.: Cloud service selection: State-of-the-art and future research directions. J. Netw. Comput. Appl. 45, 134–150 (2014)
Godse, M., Mulik, S.: An approach for selecting software-as-a-service (SaaS) product. In: 2009 IEEE International Conference on Cloud Computing. IEEE (2009)
Rahimi, M., et al.: Toward the efficient service selection approaches in cloud computing. Kybernetes 51(4), 1388–1412 (2022)
Nagahawatta, R., et al.: Security and privacy factors influencing the adoption of cloud computing in Australian SMEs. In: Pacific Asian Conference on Information Systems. AIS, Dubai (2021)
Xu, H., Mahenthiran, S.: Users’ perception of cybersecurity, trust and cloud computing providers’ performance. Inf. Comput. Secur. 29(5), 816–835 (2021)
McKinney, V., Yoon, K., Zahedi, F.M.: The measurement of web-customer satisfaction: an expectation and disconfirmation approach. Inf. Syst. Res. 13(3), 296–315 (2002)
Walther, S., et al.: Should we stay, or should we go? Analyzing continuance of cloud enterprise systems. J. Inf. Technol. Theory Appl. (JITTA) 19(2), 57–88 (2018)
Ragin, C.C.: Redesigning Social Inquiry: Fuzzy Sets and Beyond. University of Chicago Press, Chicago (2008). https://doi.org/10.7208/chicago/9780226702797.001.0001
Pappas, I.O., Mikalef, P., Giannakos, M.N., Kourouthanassis, P.E.: Explaining user experience in mobile gaming applications: an fsQCA approach. Internet Res. 29(2), 293–314 (2019). https://doi.org/10.1108/IntR-12-2017-0479
Benlian, A., Koufaris, M., Hess, T.: Service quality in software-as-a-service: developing the SaaS-qual measure and examining its role in usage continuance. J. Manag. Inf. Syst. 28(3), 85–126 (2011)
Garg, S.K., Versteeg, S., Buyya, R.: SMICloud: a framework for comparing and ranking cloud services. In: 2011 Fourth IEEE International Conference on Utility and Cloud Computing. IEEE (2011)
Sedera, D., Dey, S.: User expertise in contemporary information systems: conceptualization, measurement and application. Inf. Manage. 50(8), 621–637 (2013)
Schneider, S., Sunyaev, A.: Determinant factors of cloud-sourcing decisions: reflecting on the IT outsourcing literature in the era of cloud computing. J. Inf. Technol. 31(1), 1–31 (2016)
Tricomi, G., Merlino, G., Panarello, A., Puliafito, A.: Optimal selection techniques for Cloud service providers. IEEE Access 8, 203591–203618 (2020). https://doi.org/10.1109/ACCESS.2020.3035816
Bharadwaj, A.S.: A resource-based perspective on information technology capability and firm performance: an empirical investigation. MIS Q. 24(1), 169–196 (2000)
Lokuge, S., et al.: Organizational readiness for digital innovation: development and empirical calibration of a construct. Inf. Manage. 56(3), 445–461 (2019)
Wulf, F., Westner, M., Strahringer, S.: Cloud computing adoption: a literature review on what is new and what we still need to address. Commun. Assoc. Inf. Syst. 48(1), 44 (2021)
Song, C.-H., Kim, S.W., Sohn, Y.-W.: Acceptance of public cloud storage services in South Korea: a multi-group analysis. Int. J. Inf. Manage. 51, 102035 (2020)
Shiau, W.-L., Chau, P.Y.: Understanding behavioral intention to use a cloud computing classroom: a multiple model comparison approach. Inf. Manage. 53(3), 355–365 (2016)
Bouranta, N., Chitiris, L., Paravantis, J.: The relationship between internal and external service quality. Int. J. Contemp. Hosp. Manag. 21(3), 275–293 (2009)
Hair, J.F., et al.: Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook. Springer International Publishing, Cham (2021). https://doi.org/10.1007/978-3-030-80519-7
Ragin, C.: User's Guide to Fuzzy-Set/Qualitative Comparative Analysis 3.0. University of California, Department of Sociology, Irvine, California (2018)
Mattke, J., Maier, C., Weitzel, T., Gerow, J.E., Thatcher, J.B.: Qualitative comparative analysis (QCA) in information systems research: status quo, guidelines, and future directions. Commun. Assoc. Inf. Syst. 50, 208–240 (2022). https://doi.org/10.17705/1CAIS.05008
Rasoolimanesh, S.M., et al.: The combined use of symmetric and asymmetric approaches: partial least squares-structural equation modeling and fuzzy-set qualitative comparative analysis. Int. J. Contemp. Hosp. Manag. 33(5), 1571–1592 (2021)
Pappas, I.O., Woodside, A.G.: Fuzzy-set qualitative comparative analysis (fsQCA): guidelines for research practice in information systems and marketing. Int. J. Inf. Manage. 58, 102310 (2021)
Woodside, A.G.: Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory. J. Bus. Res. 66, 463–472 (2013)
Ide, T., Mello, P.A.: QCA in international relations: A review of strengths, pitfalls, and empirical applications. Int. Stud. Rev. 24(1), viac008 (2022). https://doi.org/10.1093/isr/viac008
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix A
Appendix A
The measures of the variables.
Attributes | Measures |
|---|---|
Reliability CR: 0.70 AVE: 0.52 | Most of the times, … 1…. [your provider] operates without failure 2…. [your provider] provides services at the promised time 3…. [your provider] fulfils the obligations to the contract 4…. The services of [your provider] are accurate/error-free |
Performance CR: 0.93 AVE: 0.81 | Most of the times, … 1…. The service response time of [your provider] is quick 2…. The performance of [your provider] is stable 3…. [your provider] meets most of the end-user requirements 4…. The services of [your provider] are available (e.g., no system crash) |
Security CR: 0.89 AVE: 0.67 | 1. As far I know, [your provider] has anti-virus protection 2. As far I know, all data are encrypted in [your provider] 3. As far I know, [your provider] ensures data confidentiality 4. As far I know, [your provider] has secure data centers |
Usability CR: 0.81 AVE: 0.53 | 1. [Your provider] has a simple user-interface for its contents 2. [Your provider] has a simple layout for its contents 3. The services of [your provider] are well organized 4. Overall, using the services of [your provider] is easy |
Reputation CR: 0.89 AVE: 0.73 | 1. I believe that [your provider] has high brand value 2. When it comes to user problems, [your provider] shows a sincere interest in solving them 3. [Your provider] provides support that is tailored to individual needs 4. Overall, I believe that [your provider] has a good reputation |
Pricing CR: 0.81 AVE: 0.51 | 1. The annual subscription cost of [your provider] is high 2. The acquisition cost (i.e., subscription cost) of [your provider] is high 3. The on-going cost of [your provider] is high 4. The financial charges [your provider] are high 5. The cost of using the service of [your provider] is significantly higher than buying and deploying relevant hardware and software by us 6. Overall, [your provider] is expensive |
Service Capability CR: 0.89 AVE: 0.63 | 1. [Your provider] possesses a wealth of technical proficiency in delivering efficient cloud solutions 2. [Your provider] employs industry best practices, leveraging the latest advancements in cloud technology 3. [Your provider] consistently upgrades their capabilities to ensure they are well-equipped to address customers’ dynamic demands of cloud computing 4. [Your provider] exhibits a strong command of cloud processes, enabling them to streamline deployment, management, and monitoring procedures 5. [Your provider] demonstrates a deep understanding of cloud architecture |
CSP Selection CR: 0.91 AVE: 0.77 | 1. We use cloud services from [your provider] in our business operations 2. Our business plans to continue to use cloud services from [your provider] 3. I will recommend [your provider] to others |
Rights and permissions
Copyright information
© 2024 IFIP International Federation for Information Processing
About this paper
Cite this paper
Hossain, M.A., Sabani, A., Lokuge, S., Boo, Y.L., Kaisar, S. (2024). Selection of Cloud Service Providers: A Fuzzy-set Qualitative Comparative Analysis Approach. In: Sharma, S.K., Dwivedi, Y.K., Metri, B., Lal, B., Elbanna, A. (eds) Transfer, Diffusion and Adoption of Next-Generation Digital Technologies. TDIT 2023. IFIP Advances in Information and Communication Technology, vol 699. Springer, Cham. https://doi.org/10.1007/978-3-031-50204-0_35
Download citation
DOI: https://doi.org/10.1007/978-3-031-50204-0_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-50203-3
Online ISBN: 978-3-031-50204-0
eBook Packages: Computer ScienceComputer Science (R0)