Abstract
Cloud Computing has become nowadays a significant field of Information and Communication Technology (ICT). Both cloud providers and customers invest time and resources in an endeavor of the former to serve effectively the needs of the latter so as to adopt efficiently such cloud services, based their needs. The decision to adopt cloud services falls within the category of complex and difficult to model real-world problems. Aiming to support the cloud adoption decision process, we propose in this paper an approach based on Fuzzy Cognitive Maps (FCM) which models the parameters that potentially influence such a decision. The construction and analysis of the map is based on factors reported in the relevant literature and the utilization of experts’ opinion. The proposed approach is evaluated through four real-world experimental cases and the suggestions of the model are compared with the customers’ final decisions. The evaluation indicated that the proposed approach is capable of capturing the dynamics behind the interdependencies of the participating factors.
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
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kosko, B.: Fuzzy Thinking. The New Science of Fuzzy Logic. Harper Collins, London
Tsadiras, A.K., Margaritis, K.G.: Cognitive Mapping and the Certainty Neuron Fuzzy Cognitive Maps. Information Sciences 101, 109–130 (1997)
Axelrod, R.: Structure of Decision: The Cognitive Maps of Political Elites. Princeton University Press, Princeton (1976)
Alizadeh, S., Ghazanfari, M., Fathian, M.: Using Data Mining for Learning and Clustering FCM. International Journal of Computational Intelligence 4(2), 118–125 (2008)
Kosko, B.: Fuzzy Cognitive Maps. International Journal of Man-Machine Studies 24, 65–75 (1986)
Taber, W.R., Siegel, M.: Estimation of Expert Weights and Fuzzy Cognitive Maps. In: 1st IEEE International Conference on Neural Networks, vol. 2, pp. 319–325 (1987)
Andreou, A.S., Mateou, N.H., Zombanakis, G.A.: Optimization in Genetically Evolved Fuzzy Cognitive Maps Supporting Decision-Making: The Limit Cycle Case. In: Proceedings of International Conference on Information and Communication Technologies: From Theory to Applications, pp. 377–378 (2004)
Wu, W.-W.: Developing an explorative model for SaaS adoption. Expert Systems with Applications 38, 15057–15064 (2011)
Wu, W.-W.: Mining significant factors affecting the adoption of SaaS using the rough set approach. The Journal of Systems and Software 84, 435–441 (2011)
Mell, P., Grance, T.: The NIST Definition of Cloud Computing. National Institute of Standards and Technology (2009)
Khajeh-Hosseini, A., Greenwood, D., Smith, J.W., Sommerville, I.: The Cloud Adoption Toolkit: supporting cloud adoption decisions in the enterprise. Software: Practice and Experience 42(4), 447–465 (2012)
Kim, W., Kim, S.D., Lee, E., Lee, S.: Adoption issues for cloud computing. In: MoMM 2009, pp. 2–5 (2009)
Wu, W.W., Lan, L.W., Lee, Y.T.: Exploring decisive factors affecting an organization’s SaaS adoption: A case study. International Journal of Information Management 31(6), 556–563 (2011)
Gabus, A., Fontela, E.: World problems, an invitation to further thought within the framework of DEMATEL. BATTELLE Institute, Geneva Research Centre, Geneva, Switzerland (1972)
Mateou, N.H., Andreou, A.S.: A framework for developing intelligent decision support systems using evolutionary fuzzy cognitive maps. Journal of Intelligent and Fuzzy Systems 19(2), 151–170 (2008)
Papageorgiou, E.I., Papandrianos, N.I., Karagianni, G., Kyriazopoulos, G.C., Sfyras, D.: A fuzzy cognitive map based tool for prediction of infectious diseases. In: IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2009, pp. 2094–2099. IEEE (August 2009)
Andreou, A.S., Mateou, N.H., Zombanakis, G.A.: Evolutionary fuzzy cognitive maps: A hybrid system for crisis management and political decision-making. In: Proc. Computational Intelligent for Modeling, Control & Automation CIMCA, Vienna, pp. 732–743 (2003)
Iakovidis, D.K., Papageorgiou, E.: Intuitionistic fuzzy cognitive maps for medical decision making. IEEE Transactions on Information Technology in Biomedicine 15(1), 100–107 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Christoforou, A., Andreou, A.S. (2013). A Cloud Adoption Decision Support Model Based on Fuzzy Cognitive Maps. In: Heidrich, J., Oivo, M., Jedlitschka, A., Baldassarre, M.T. (eds) Product-Focused Software Process Improvement. PROFES 2013. Lecture Notes in Computer Science, vol 7983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39259-7_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-39259-7_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39258-0
Online ISBN: 978-3-642-39259-7
eBook Packages: Computer ScienceComputer Science (R0)