Abstract
The popularity of cloud computing has been growing among enterprises since its inception. It is an emerging technology which promises competitive advantages, significant cost savings, enhanced business processes and services, and various other benefits. The aim of this paper is to propose a decision modelling using Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) for the factors that have impact in SMEs cloud computing adoption process.
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Baltussen R, Niessen L (2006) Priority setting of health interventions: the need for multi-criteria decision analysis. Cost Eff Resour Allocat 4(1):14
Bolloju N (2001) Aggregation of analytic hierarchy process models based on similarities in decision makers’ preferences. Eur J Oper Res 128(3):499–508
Cameron TA, DeShazo J (2010) Differential attention to attributes in utility-theoretic choice models. J Choice Model 3(3):73–115
Clemen R, Reilly T (2013) Making hard decisions with DecisionTools. Cengage Learn, Boston
de Lautour H, Dalbeth N, Taylor W (2014) Development of preliminary remission criteria for Gout using Delphi and 1000Minds consensus exercises. Wiley-Blackwell, Hoboken
Dillman DA, Smyth JD, Christian LM (2014) Internet, phone, mail, and mixed-mode surveys: the tailored design method. Wiley, Hoboken
Doumpos M, Marinakis Y, Marinaki M, Zopounidis C (2009) An evolutionary approach to construction of outranking models for multicriteria classification: the case of the ELECTRE TRI method. Eur J Oper Res 199(2):496–505
Drummond MF, Sculpher MJ, Torrance GW, O’Brien BJ, Stoddart GL (2005) Methods for the economic evaluation of health care programmes. OUP Catalogue, Oxford
Edwards W (1977) How to use multiattribute utility measurement for social decisionmaking. IEEE Trans Syst Man Cybern 7(5):326–340
Edwards W, Barron FH (1994) SMARTS and SMARTER: improved simple methods for multiattribute utility measurement. Organ Behav Hum Decis Process 60(3):306–325
El-Gazzar RF (2014) A literature review on cloud computing adoption issues in enterprises. Springer, Berlin
Forman EH, Selly MA (2001) Decision by objectives: how to convince others that you are right. World Scientific, Singapore
Godse M, Mulik S (2009) An approach for selecting software-as-a-service (SaaS) product. IEEE, USA
Han S-M, Hassan MM, Yoon C-W, Huh E-N (2009) Efficient service recommendation system for cloud computing market. ACM, New York
Hansen P, Ombler F (2008) A new method for scoring additive multi-attribute value models using pairwise rankings of alternatives. J Multi-Criteria Decis Anal 15(3–4):87–107
Hastie R, Dawes RM (2010) Rational choice in an uncertain world: the psychology of judgment and decision making. Sage, Thousand Oaks
Hussain FK, Hussain OK (2011) Towards multi-criteria cloud service selection. IEEE, USA
KPMG (2013) The cloud takes shape. KPMG, New York
Landon EL (1971) Order bias, the ideal rating, and the semantic differential. J Market Res 8:375–378
Li A, Yang X, Kandula S, Zhang M (2010) CloudCmp: comparing public cloud providers. ACM, New York
Marston S, Li Z, Bandyopadhyay S, Zhang J, Ghalsasi A (2011) Cloud computing—the business perspective. Decis Support Syst 51(1):176–189
Martin-Collado D, Byrne T, Amer P, Santos B, Axford M, Pryce J (2015) Analyzing the heterogeneity of farmers’ preferences for improvements in dairy cow traits using farmer typologies. J Dairy Sci 98:4148–4161
Moshkovich HM, Mechitov AI, Olson DL (2002) Ordinal judgments in multiattribute decision analysis. Eur J Oper Res 137(3):625–641
Nielsen H, Amer P, Byrne T (2014) Approaches to formulating practical breeding objectives for animal production systems. Acta Agric Scand A: Anim Sci 64(1):2–12
Oliveira T, Martins MF (2011) Literature review of information technology adoption models at firm level. Electron J Inf Syst Eval 14(1):110–121
Ombler F, Hansen P (2012) 1000Minds software
Perreault WD (1975) Controlling order-effect bias. Publ Opin Q 39:544–551
Raghavarao D, Wiley JB, Chitturi P (2010) Choice-based conjoint analysis: models and designs. CRC Press, Boca Raton
Ryan M, Gerard K (2003) Using discrete choice experiments to value health care programmes: current practice and future research reflections. Appl Health Econ Health Policy 2(1):55–64
Saaty TL (2008) Decision making with the analytic hierarchy process. Int J Serv Sci 1(1):83–98
Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48(1):9–26
Sullivan T (2012) Using MCDA (multi-criteria decision analysis) to prioritise publicly-funded health care, University of Otago, Dunedin
Timmermans J, Stahl BC, Ikonen V, Bozdag E (2010) The ethics of cloud computing: a conceptual review
Venters W, Whitley EA (2012) A critical review of cloud computing: researching desires and realities. J Inf Technol 27(3):179–197
Von Winterfeldt D, Edwards W (1986) Decision analysis and behavioral research. Cambridge University Press, Cambridge
Wu Y, Cegielski CG, Hazen BT, Hall DJ (2013) Cloud computing in support of supply chain information system infrastructure: understanding when to go to the cloud. J Suppl Chain Manage 49(3):25–41
Yang H, Tate M (2012) A descriptive literature review and classification of cloud computing research. Commun Assoc Inf Syst 31(2):35–60
Acknowledgments
The authors thank 1000minds decision-making software (the software that supports PAPRIKA method) for providing us a free license and open access for the duration of the research, and Paul Hansen for his suggestions to our thinking in this area.
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Appendex 1: Ranking of Alternatives
Appendex 1: Ranking of Alternatives
Alternative | Security concerns | Cost savings | Relative advantage | Uncertainty | Privacy risk due to geo-restirction | Compatibility | Complexity | Rank | Mid-rank | Total score (%) | Solution Cost: 3 = Expensive 2 = High 1 = Reasonable 0 = Not sure | Benefits: 3 = High 2 = Average 1 = Low 0 = No benefit | Service trust: 3 = High 2 = Average 1 = Low 0 = Not sure | Quality of Service: 3 = Very High 2-High 1 = Average 0 = Not sure |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
A. Model ranking | ||||||||||||||
Public IaaS- system | Low | High | Moderate | High | Medium | Good | Low | 1st= | 2.5 | 79.6 | 1 | 1 | 1 | 1 |
Public IaaS-storage | Low | High | Moderate | High | Medium | Good | Low | 1st= | 2.5 | 79.6 | 1 | 1 | 1 | 1 |
Public PaaS | Low | High | Moderate | High | Medium | Good | Low | 1st= | 2.5 | 79.6 | 1 | 1 | 1 | 1 |
Public SaaS | Low | High | Moderate | High | Medium | Good | Low | 1st= | 2.5 | 79.6 | 1 | 1 | 1 | 1 |
Hybrid IaaS | Medium | Medium | Low | Moderate | Medium | Good | Medium | 5th= | 6 | 65.9 | 2 | 2 | 2 | 2 |
Hybrid PaaS | Medium | Medium | Low | Moderate | Medium | Good | Medium | 5th= | 6 | 65.9 | 2 | 2 | 2 | 2 |
Hybrid SaaS | Medium | Medium | Low | Moderate | Medium | Good | Medium | 5th= | 6 | 65.9 | 2 | 2 | 2 | 2 |
Private IaaS | High | Very high | Strong | Low | High | Strong | High | 8th= | 9 | 55.7 | 3 | 3 | 3 | 3 |
Private PaaS | High | Very high | Strong | Low | High | Strong | High | 8th= | 9 | 55.7 | 3 | 3 | 3 | 3 |
Private SaaS | High | Very high | Strong | Low | High | Strong | High | 8th= | 9 | 55.7 | 3 | 3 | 3 | 3 |
Status quo (not to adopt)- legacy IT | High | Low | Weak | High | High | Weak | High | 11th | 11 | 0 | 0 | 0 | 0 | 0 |
B Simulation case 1 rank | ||||||||||||||
Alternative | ||||||||||||||
Private IaaS | High | Very high | Strong | Low | High | Strong | High | 1st= | 2 | 85.5 | 3 | 3 | 3 | 3 |
Private PaaS | High | Very high | Strong | Low | High | Strong | High | 1st= | 2 | 85.5 | 3 | 3 | 3 | 3 |
Private SaaS | High | Very high | Strong | Low | High | Strong | High | 1st= | 2 | 85.5 | 3 | 3 | 3 | 3 |
Public IaaS- system | Low | High | Moderate | High | Medium | Good | Low | 4th= | 5.5 | 57.5 | 1 | 1 | 1 | 1 |
Public IaaS-storage | Low | High | Moderate | High | Medium | Good | Low | 4th= | 5.5 | 57.5 | 1 | 1 | 1 | 1 |
Public PaaS | Low | High | Moderate | High | Medium | Good | Low | 4th= | 5.5 | 57.5 | 1 | 1 | 1 | 1 |
Public SaaS | Low | High | Moderate | High | Medium | Good | Low | 4th= | 5.5 | 57.5 | 1 | 1 | 1 | 1 |
Hybrid IaaS | Medium | Medium | Low | Moderate | Medium | Good | Medium | 8th= | 9 | 53.1 | 2 | 2 | 2 | 2 |
Hybrid PaaS | Medium | Medium | Low | Moderate | Medium | Good | Medium | 8th= | 9 | 53.1 | 2 | 2 | 2 | 2 |
Hybrid SaaS | Medium | Medium | Low | Moderate | Medium | Good | Medium | 8th= | 9 | 53.1 | 2 | 2 | 2 | 2 |
Status quo (not to adopt)- legacy IT | High | Low | Weak | High | High | Weak | High | 11th | 11 | 0 | 0 | 0 | 0 | 0 |
C Simulation case 2 rank | ||||||||||||||
Alternative | ||||||||||||||
Public IaaS- system | Low | High | Moderate | High | Medium | Good | Low | 1st= | 2.5 | 77.9 | 1 | 1 | 1 | 1 |
Public IaaS-storage | Low | High | Moderate | High | Medium | Good | Low | 1st= | 2.5 | 77.9 | 1 | 1 | 1 | 1 |
Public PaaS | Low | High | Moderate | High | Medium | Good | Low | 1st= | 2.5 | 77.9 | 1 | 1 | 1 | 1 |
Public SaaS | Low | High | Moderate | High | Medium | Good | Low | 1st= | 2.5 | 77.9 | 1 | 1 | 1 | 1 |
Private IaaS | High | Very high | Strong | Low | High | Strong | High | 5th= | 6 | 71.3 | 3 | 3 | 3 | 3 |
Private PaaS | High | Very high | Strong | Low | High | Strong | High | 5th= | 6 | 71.3 | 3 | 3 | 3 | 3 |
Private SaaS | High | Very high | Strong | Low | High | Strong | High | 5th= | 6 | 71.3 | 3 | 3 | 3 | 3 |
Hybrid IaaS | Medium | Medium | Low | Moderate | Medium | Good | Medium | 8th= | 9 | 67.2 | 2 | 2 | 2 | 2 |
Hybrid PaaS | Medium | Medium | Low | Moderate | Medium | Good | Medium | 8th= | 9 | 67.2 | 2 | 2 | 2 | 2 |
Hybrid SaaS | Medium | Medium | Low | Moderate | Medium | Good | Medium | 8th= | 9 | 67.2 | 2 | 2 | 2 | 2 |
Status quo (not to adopt)- legacy IT | High | Low | Weak | High | High | Weak | High | 11th | 11 | 0 | 0 | 0 | 0 | 0 |
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Alismaili, S., Li, M., Shen, J. (2016). Cloud Computing Adoption Decision Modelling for SMEs: From the PAPRIKA Perspective. In: Hung, J., Yen, N., Li, KC. (eds) Frontier Computing. Lecture Notes in Electrical Engineering, vol 375. Springer, Singapore. https://doi.org/10.1007/978-981-10-0539-8_59
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