General Model for Adequate Cloud Service Selection using Decision Making Methods


  • Ognjen Pantelic Department of Information Systems Faculty of Organizational Sciences, University of Belgrade Jove Ilica 154, 11000 Belgrade, Serbia
  • Ana Pajic Department of Information Systems Faculty of Organizational Sciences, University of Belgrade Jove Ilica 154, 11000 Belgrade, Serbia
  • Ana Nikolic Novomatic Lottery Solutions Djordja Stanojevica 12, 11070 Novi Beograd, Serbia


cloud adoption, general model, IT investments, cloud services, multicriteria methods


Cloud Computing (CC) is a technology that surely brings innovations in today’s business world, more and more companies around the world are widely incorporating this technology into their businesses. From a technical, as well as organizational point of view transferring enterprise IT to the Cloud is a complex task. Various factors have to be taken into consideration in order to make a right choice when moving IT services to the Cloud. The goal of this paper is to identify and to discuss in detail all factors that influence organization’s decision to adopt Cloud. General model for Cloud adoption, introduced in Pantelic et al. [13]a, consists of the key factors driving the organizational benefits when moving to the Cloud. The purpose of the model is to support decision makers in evaluating the benefits, risks and costs of using Cloud Computing. In this paper the general model is extended with two new aggregation methods for harmonization of alternatives rankings in a group decision process. We present the results of two new methods using the method results from previous research [13], as rank inputs, into an aggregate (group) preference. The idea is to find consensus ranking that minimizes disagreement among previous methods results. There were no strong differences between the results of performed methods. The results have shown that Software as a service model and Storage as a service model dominated according to not just arithmetic-mean method, but also to geometric-mean method.


Alexander, M. (2012); Decision-Making Using the Analytic Hierarchy Process (AHP) and MP RO Scripting Language, 2012 The SouthEast SAS Users Group Conference (SESUG), ESUG Inc.

Alfares, H. K.; Duffuaa, S. O.(2008); Determining Aggregate Criteria Weights From Criteria ankings By a Group of Decision Makers, International Journal of Information Technology & Decision Making, 7(4): 769-781.

Buyya, R. et al (2008), Cloud computing: Principles and paradigms, 8: 3-121.

Carbon Disclosure Project 2011, Carbon Disclosure Project Study 2011 Cloud Computing- he IT Solution for the 21st Century, Verdantix, White Paper.

Costa, P.; Migliavacca, M.; Wolf, A. L. (2012); NaaS: Network-as-a-Service in the Cloud,2nd SENIX Workshop on Hot Topics in Management of Internet, Cloud, and Enterprise Networks nd Service, San Jose, CA, USA.

Cruz, Z.; Fernández-Alemán, J.; Toval A. (2015); Security in cloud computing: A mapping tudy, Computer Science and Information Systems, 12(1): 161-184.

Figueira, J.; Greco, S.; Ehrogott, M. (2005),Multiple Criteria Decision Analysis: State of the rt Surveys, Springer Science+Business Media, Inc., 27-406.

Hashizume, K. et al (2013); An analysis of security issues for cloud computing, Journal of nternet Services and Application, 4(5): 1-13.

Kornevs, M.; Minkevica, V.; Holm, M. (2012); Cloud Computing Evaluation Based on Financial etrics, Information Technology and Management Science, 15(1): 87-92.

Mell, P.; Grance, T. 2011, The NIST Definition of Cloud Computing, NIST Special Publication 00-145, National Institute of Standards and Technology Gaithersburg.

Messmer, E. (2013), Gartner: Cloud-based security as a service set to take off, ttp:// -service-set-to-take-off.html, Information Technology and Management Science

Pajic, A.; Pantelic, O.; Stanojevic B. (2014); Representing IT Performance Management as etamodel, International Journal of Computers Communications & Control, 9(6): 758-767.

Pantelic, O.; Pajic, A.; Nikolic, A.; (2016); Analysis of available cloud computing models to upport cloud adoption decision process in an enterprise, Computers Communications and ontrol (ICCCC), 2016 6th International Conference on, IEEE Xplore, e-ISBN:978-1-5090- 735-5, doi: 10.1109/ICCCC.2016.7496751, 135-139.

Patel, K. H. et al (2012); Tradeoffs between performance and security of cryptographic rimitives used in Storage-as-a-Service for cloud computing, Proceedings of the CUBE International nformation Technology Conference, New York, NY, USA.

Patrascu, A.; Patriciu, V. V. (2015); Logging for Cloud Computing Forensic Systems Related ork, International Journal of Computers Communications & Control, 10(2): 222-229.

Sharma, S. (2015), Evolution of as-a-Service Era in Cloud, ttp://Ëœsugamsha/articles/Evolution%20of%20as-a- ervice%20Era%20in%20Cloud.pdf

Simmonds, M. (2009), Information as a service: A smarter way to SOA success, IBM oftware Group, 1-19.

Waschke, M. (2004), IT Management-As-A-Service, CA Technologies, Whitepaper, no. 451.



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