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1 Online Open Access publishing platform for Management Research Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0 Research Article ISSN Multi-criteria Decision in the Adoption of Cloud Computing Services for SME s based on BOCR Analysis Sania Khan 1, Mohammed Shahid Ahamed Khan 2, Chitta Sai Kumar 3 Ph.D Student at Gitam School of International Business, GITAM University, Visakhapatnam Sales Account Manager - IT Infrastructure Solution and Services, Computer Support House Co. Ltd., Riyadh, Kingdom of Saudi Arabia Electrical Engineer, Humaidi Munawar Al Onaizy Est., Riyadh, Kingdom of Saudi Arabia saniakhan05@gmail.com ABSTRACT Cloud computing being recognized as a huge transformation in the IT management has raised many questions among the IT experts towards its adoption in SME s (Small and Medium Enterprises). Past researches having demonstrated the strengths, weakness, opportunities and threats (SWOT) reinforced them with the technology acceptance, however they lack in suggesting the strong adoption decisions for SME s. Minimizing the economic downturn being one of the major objectives of this service adoption, it is prudent to consider the voice of cloud consumers and experts to investigate and suggest SME s with possible multi-criteria decisions based on BOCR (Benefit, Opportunity, Cost and Risk) analysis. A structural model using Analytic Hierarchy Process (AHP) was developed by assigning the weights and prioritizing each component with respect to the BOCR criteria. The findings suggested that cloud services are still in emerging stage and SME s are interested due to the excellent benefits and opportunities provided in align with the firm s growth. Despite major data security attacks and privacy issue stories from the past, if the cloud service providers can still work on ensuring and minimize such issues, cloud services will have a promising business growth in the future. This study helps organizations to strategically focus on these criteria to reach to a higher level of competitiveness and also assists decision makers to strategically leverage their efforts by effective implementation of cloud computing. Finally, the study concludes with several interesting pointers as directions for further researchers. Keywords: Cloud Computing, Cloud Computing Adoption, BOCR Analysis, Multi-Criteria Decision Making, SMEs, Structural Hierarchy Model, Analytic Hierarchy Process, AHP. 1. Introduction The growing applicatitons, stoage devices and database are proliferating the need for infrastructure drastically, while SME s with limited resources and lack of sophisticated technical expertise are facing challenges to setup their IT infrastructure in their everyday operations. At the same time it is inappropriate to accept every new technology that are being introduced in the IT industry very oftenly. However, IT experts visualized cloud computing as a key revolution in today s scenario, due to enormous sustainable benefits and opportunities provided with respect to three dimensions namely socio- economic and environment. On the other side, enterprises need to evaluate these benefits, opportunities, cost and risk which are practical in business environment before taking any strong decisions in the adoption of cloud services. 606

2 Based on this, present paper is organized into several sections. Section 2 presents the detailed review on cloud computing literature from BOCR perspectives. Section 3 explains the methodology usage in developing a muti-criteria decision and prioritization of main and subcriteria. Section 4 discusses the findings of the study and section 5 provides limitations, implications and concludes the study, followed by few possible directions for further research and adding references at the end. 2. Review of Literature The retrospective analysis of cloud computing provides several evidences, in understanding what factors are driving business organizations towards cloud adoption. Previously, many computing technologies like virtualization, web 2.0 and grid computing are adequately enough to simplify the complex IT practices establishing a high performance and easy resolutions for many business and technical concerns (Hunter, Little and Schroeter, 2008). Infact, some authors perceive cloud computing evolved from distributed and grid computing (Che et al, 2011). Similarly virtualization fetched the business to reduce the number of servers, server maintenance and staffing costs to consolidate the data center deployment (Gillen et al., 2008). Dunn, 2010; Buyya et al., 2009; 2010b; Holliday, C., and Hurst; 2006; Khajeh-Hosseini et al., 2010a; Yeboah-Boateng, E. O., and Essandoh, K. A. 2014; Schubert Jeffery and Neidecker-Lutz 2010) and it is an inevitable technology which is highly coupled with the cloud computing concept indicated by most of the firms who look for the economic downturn by reducing costs (Ogigau-Neamtiu, 2012; Hashizume et al. 2013; Kim, 2009; Mosher, 2011; Atayero and Feyisetan, 2011; Zissis and Lekkas, 2012). Buyya et al., 2009, in his Service Level Agreement (SLA) demonstrated the opportunity to minimize 53% of IT data center expenditure by reduced powering and cooling requirements. Further, Buyya et al, 2010a, also demonstrated cloud applications and services are supportive for start-up firms to generate additional revenues. Schubert, Jeffery and Neidecker-Lutz, 2010, demonstrates several benefits of cloud adoption viz., agility and adaptability being subset of elasticity, the consumer can be benefited with dynamic integration and extraction of physical resources and can pay per user licenses. These services are reliable as they provide expected output with minimum response time, guaranteed quality of service and no data loss or disruption by the service provider. Further the infrastructure and other resources in other location under others ownership are used by consumer on rent basis for a particular time period can actually help to put down the carbon emissions from their IT operations to meet legislative compliances and moreover can get good Return on Investment (ROI) (Bisong and Rahman, 2011; Rashmi et al, 2013; Qaisar and Khawaja, 2012). Despite several benefits by cloud adoption, there are many opportunities to develop new skills, organization growth, offering new products and services, improved work environment of the firm and a chance to focus on ITC s income and expenditure (Schubert, Jeffery and Neidecker-Lutz, 2010; Khajeh-Hosseini et al. (2010a). Chang et al, 2012a; Mohlameane, M. J., and Ruxwana, N. L., 2013, demonstrates the academic institutes and SME s have achieved the cost-saving with an improvement in user satisfaction through cloud adoption. Though the SME s consider the cost incurred on ICT as a key barrier, cloud services attracts them by reducing the cost of infrastructure, operations and maintenance cost. So it is crucial that the firms must analyze the costs of initial operations, compliances, privacy and security issues, and high switching costs due to 607

3 incompatibilities or migrating to different platforms necessarily, all of these components constitutes as the determinants in the overall cost of cloud adoption. However expecting risk in cloud adoption, Khajeh-Hosseini et al, (2010a) stated there might be chances of privacy and data security issues as these services are centrally operated through standard web protocols by the service providers, while few of the past failure cases from reputed organizations like Sony corporation inputs to undertake a careful understanding on these services. As cloud computing is linked with users sensitive data stored both at clients end and at cloud servers as well, identity management and authentication are very essential in cloud and these can also be outsourced to any third party specialists (Kim and Hong, 2012; Emam, 2013; Gonzalez et al, 2012; Sharma and Mittal, 2013; Han, Susilo and Mu, 2013; Yassin, A. A. et al, 2012). However third party relationship may arise a risk despite of other security threats inherent in infrastructural and virtual machine aspects (Hashizume et al., 2013). While security failure, lack of robustness and consistent being intolerable for cloud, the benefits, flexibility and agility are explained to have trivial credibility (Monjur and Mohammad Ashraf, 2014). Verification of genuine users and protecting their credential are crucial and violation of such matters will result in security concern (Kumar, 2012). However trusting the cloud depends on several aspects viz., human factor, process and policies, automation management (Abbadi and Martin, 2011). DDoS (Distributed Denial of Service) is common and major attack for cloud computing infrastructure (Dou, Chen and Chen, 2013). Other business risks can be like vendor lock-in, licensing issues, software bugs, service unavailability, provider's business discontinuity, but frankly speaking these does not come under security issues from technical perspective (Kim, 2009). User accounting, authentication and encryption are best practices of safe computing (Lee, 2012; Ogigau-Neamtiu, 2012; Singh and Jangwal, 2012). Issa M. Khalil et al, 2014 had given detail list of nine different attacks against cloud, along with their appropriate incidents, consequences and vulnerability caused by different parameters. It is known that the relay commands through Google AppEngine attacked computer (Google, 2014) and allowed to steal sensitive information from the Raytheon cloud (Raytheon, 2014). Also cloud computing found be an ideal environment for botnet attacks (Lin, W, 2012). In June, 2009 a complete homomorphism encryption scheme introduced by IBM endorsed data to be processed without getting decrypted (IBM, 2010). Differential privacy protection technology like air vat and cloud calculation stages prevented privacy leakages without authorization (Roy, I et al, 2013). Nevertheless these attempts seem to resolute data security and privacy issues, the customer also need to cope up with the minimum supporting resources and technical knowledge to properly accept the cloud, failure of which will lead to incompetent utilization of the cloud services. IT outsourcing being an alternative to cloud migration, few firms perceive as departmental downsizing and uncertainty with new technology which can deteriorate the customer care and service quality. The firms with hitech, affordable IT infrastructure and expertise believe as increased dependence on third parties with unsatisfied work. Though market size for public and hybrid cloud reached from US $59 billion to US $149 by 2014, indicating a hike in future revenue estimation, few business critical applications and 608

4 large enterprises are reluctant to move towards cloud adoption and the market is still far behind the expected one. In this direction Gartner Inc. research, Darryl Carlton, (2013) gave indications to conduct further studies on market trends and new requirements for application modernization to support business-led value. Additionally forecast on overview and analysis of public cloud world wide, the future of IT Sales and factors driving cloud evolution will gain practical knowledge to cloud computing adoption. The below Table 1 summarizes the cloud computing literature based on BOCR criteria and provides the roadmap for the study. Benefits Work productivity Agility, adaptability, scalability Better quality service Cost effective Return investment Going Green Ease of use on Table 1: List of BOCR Criteria and Sub-criteria (Source: Literature) Opportunity Emerging new skills New product/service development Pay for use licenses Standardized process Quick resolution problem Advanced work environment of Cost High cost initial High switching cost Cost uncertainty Risk Privacy and data security Lack of supporting resources Lack of cloud computing knowledge Departmental downsizing New uncertainty technology Dependence on third party Compatibility and internet connectivity Institutional readiness Legal policy and standards Migration to different platforms As all the criteria look independent and equally important, there is no clarity on hierarchy of either of them. So a research question has raised, Which is the most important criteria that explains the cloud adoption specifically in SME s? 3. Research Methodology To address the research question AHP, proposed by Thomas Satty, 1980; found to be an appropriate technique for the managers to take suitable strategic decision about a problem with the available multi-criteria decisions in hand (Sharma et al., 2008). It involves the mathematical synthesis of numerous judgments about the decision problem and decomposes into a multilevel hierarchical structure of criteria/alternatives by performing both discrete and continuous pairwise comparison of each element so as to obtain a relative importance of the 609

5 elements at each level to generate the best decision among the available one (Saaty and Vargas, 1996). The prioritization process is accomplished by assigning a number from a comparison scale (see Table 2) developed by Saaty (1980) to represent the relative importance of the criteria. Pairwise comparison matrices of these factors provide the means for calculation of importance (Sharma et al., 2008). Table 2: Pairwise Comparison Scale (Saaty, 1980; Yuksel and Dagdeviren, 2007) Intensity of Importance Explanation 1 Two criterion contribute equally to the objective ,4,6,8 Experience and judgment slightly favor one over another Experience and judgment strongly favor one over another Criterion is strongly favored and its dominance is demonstrated in practice Importance of one over another affirmed on the highest possible order Used to represent compromise between the priorities listed above The AHP method starts first with structuring the model, comparative analysis of the criteria/alternatives and then generating the priorities. Referring to the literature, AHP has been widely used in solving many decision making problems in different fields of research studies (Kurttila et al., 2000; Kangas et al., 2001, Kajanusa et al., 2004; Arslan and Turan, 2009; Sania Khan et al, 2011; Lee and Walsh, 2011). Primarily, the AHP splits the complex decision problem into a multi-criteria decision making and forms a hierarchy of interrelated decision elements in the form of a family tree (Dagdeviren et al., 2009). Secondly, it compares the criteria or the alternatives. After the problem has been decomposed and the hierarchy is constructed, prioritization procedure starts in order to determine the relative importance of the criteria. In each level, the criteria are compared pairwise according to their levels of influence and based on the specified criteria in the higher level. A multiple pairwise comparisons are conducted based on a standardized comparison scale of nine levels (Albayrak and Erensal, 2004). In the data collection procedure, the design of questionnaires for survey research (e.g. public opinion polls) represents one of the most controversial issues among survey researchers in terms of accuracy in measuring respondents perception. In order to determine the weights, the AHP determines weights of a set of factors by comparing them pair-wise and it uses its own (1/9, 1/8..8, 9) ratio scale judgments, by believing that peoples ability to make qualitative decisions is well represented by five attributes: equal, weak, strong, very strong and absolute. The numbers 2, 4, 6 and 8 stands for intermediate values between the numbers adjacent to them. The description of the scale provided by Satty (1980, p.54) is shown in Table 2. The scale 1-9 is used accordingly, based on the intensity of importance of the element i and if the element j is important than i, a fractional form of scale 1-9 is used like 1/9, 1/7 etc. The cloud computing adoption framework consists of four main criteria and each element has a number of sub-criteria resulting in five pair-wise comparison matrices (PCMs). An AHP template in Excel with self-explanatory was developed having five empty PCMs as a questionnaire, comprising only the main criteria and sub-criteria. Saudi Arabia, SMEs 610

6 account for approximately one-fourth of the country s GDP, 63% of the employment, and 98% of all the enterprises (Zawya, 2012) and also provides more job opportunities in comparison with large enterprises. Statistical data reveals about 1:28 new jobs generation for each one million of Saudi Riyal investment in large and SMEs respectively (Sadi and Henderson, 2011). In the Saudi Arabia s Ninth Economic Plan ( ) government has given emphasis on the importance of SMEs in the development of the Kingdom s economy (Saudi Gazette, 2012). All these facts provide impetus to conduct a study on Saudi Arabia s SME s. As Riyadh considered as major industrial cities in the country constituting many SME s, the questionnaire was circulated to 120 IT experts in the field of cloud computing from different SME s in Riyadh, Kingdom of Saudi Arabia (K.S.A). Only 48 respondents returned the filled in questionnaires, in that only 42 responses found to be useful. The responses from all the respondents are aggregated using the geometric mean rule, which indicates the central tendency or typical value of a set of numbers by using the product of their values and taking n th root of the resulting product value as shown below, where R is the response of each respondent. GEOMETRIC MEAN = nth (R1, R2...Rn) Let C = {Cj j = 1, 2.. n} be the set of criteria. The result of the pairwise comparison on n criteria can be summarized in an (n x n) evaluation matrix A in which every element aij (i, j = 1, 2... n) is the quotient of weights of the criteria. This pairwise comparison can be shown by a square and reciprocal matrix, (see Eq. (1)). a11 a12 a13..a1n A = (aij) nxn = a21 a22 a23..a2n.... (1) an1 an2 an3...ann Finally, each matrix is normalized and the relative weights are found. The relative weights are given by the right eigenvector (w) corresponding to the largest eigenvalue (λmax), as: Avg. of wts. = Eigen weights= λ max.w... (2) If the pairwise comparisons are completely consistent, the matrix A has rank 1 and λmax = n. In this case, weights can be obtained by normalizing any of the rows or columns of A (Albayrak and Erensal, 2004; Wang and Yang, 2007; Boraji and Yakchali, 2011). It should be noted that the quality of the output of the AHP is related to the consistency of the pairwise comparison judgments. The consistency is defined by the relation between the entries of A: aij x ajk = aik (Dagdeviren et al., 2009). The Consistency Index (CI) can be calculated by using the following formula (Saaty, 1980), n is the number of elements/criteria or alternatives based on which Random Index is considered as in Table 3. CI = (λmax n) / (n 1)... (3) 611

7 Table 3: Random Index (Source: Saaty and Vargas, 1991) N RI Table 4: Multi-criterion Weightages and Rankings Calculated Using AHP (Source: Survey Results from AHP) Sr. AHP Rank / Criterion and Sub-Criterion No. Weights Sub-Ranks 1 BENEFITS Work Productivity Agility, adaptability, Scalability Better Service Quality Cost Effective Return on Investment Going Green Ease of Use OPPORTUNITY Emerging New Skills New Product/Service Development Pay for Use Licenses Standardized Process Quick Resolution of Problem Advanced Work Environment COST High Initial Cost High Switching Cost Cost Uncertainty RISK Privacy and Data Security Lack of Supporting resources Lack of Cloud Computing Knowledge Departmental Downsizing New Technology Uncertainty Dependence on Third Party Compatibility and Internet Connectivity Institutional Readiness Legal Policy and Standards Migration to Different Platforms Using the final consistency ratio (CR) can conclude whether the evaluations are sufficiently consistent. The CR is calculated as the ratio of the CI and the random index (RI), as indicated in Eq. (4). The number 0.1 is the accepted upper limit for CR. If the final consistency ratio 612

8 exceeds this value, the evaluation procedure has to be repeated to improve consistency (Boraji and Yakchali, 2011). CR = CI/RI. (4) After calculating these values, the average weights of each criteria are considered as AHP weights and accordingly ranks are allotted for criteria and sub-criteria as shown in Table 4. The CR value being below 10%, the figure 1, represents the hierarchical structural model of BOCR criteria and sub-criteria with rankings for cloud computing adoption in SME s. 4. Results In comparison to all the main criteria, the benefits and opportunity received first and second highest weightages respectively. This is apparently because the respondents think that in the current ICT business environment benefits are significantly important and would welcome the cloud computing adoption which can provide them with best service quality and good work productivity along with expected returns on their investments. Figure 1: Hierarchical Structural Model of BOCR Criterion and Sub-criterion with Rankings for Cloud Computing Adoption in SME s Using AHP (Source: Developed from AHP Results) 613

9 They provide an opportunity for the new firms and SME s to get quick resolution for their technical problems anywhere in the world and assists them in learning new skills at a minimum cost and would establish a standard work process to be competitive in the industry. The risk is given next highest priority with a due consideration to the privacy and data security issues thinking that the new technology may be slightly uncertain and experimental in nature during the initial stages. Though it is an added advantage for the cloud adoptors to escape from the legal policies and standards, it is again a risk for service providers. The SME s rather perceiving the departmental downsizing, third party dependence as a threat, must rise their status with alternatives to understand the cloud computing well and support with necessary resources along with service providers. The cost is given least importance among all, which indicates the overall cost would be minimum to whatever extent they utilize the services accordingly. Nevertheless, the cost uncertainty, initial cost and switching cost must be competitive than the cost incurred on traditional IT process and must be discussed clearly at the earlier stage of service adoption. 5. Limitations, Implications and Conclusion As cloud computing technology is still in emerging stage and not so practically familiar in Saudi SME s the study suffers from following limitations. As cloud computing is not implemented vigorously among most of the SME s in Saudi Arabia, the study lacks the proficient experts with good knowledg and hands of experience in this field, consequently resulted in choosing only few potential experts to get accurate responses and also to manage the time frame of the study. These findings are applicable for only SME s and may not be generalized for other larger enterprises, as they differ in their business requirements, security and privacy issues. This study attempted to estimate appropriate weightages of various criterion associated with the cloud computing adoption among Saudi SME s using a multi-criterion decision method called Analytic Hierarchy process (AHP). It has also facilitated to prioritize the criterion and enabled us to provide action oriented suggestions and practical implications to Saudi SME s. On overall basis, the benefits and opportunities were prioritized as first and second respectively followed by risk and cost criteria. Hence it is understood the firms are expecting for a good quality service and instant problem solving in their regular IT operations. Even though the risk of privacy and data security are given prominent importance they can be managed by suitable type of cloud deployment among public, private, community and hybrid cloud. The cost found to be the least significant, assuming the overall idea behind welcoming such service is for cost reduction. This study also contributes in providing some useful managerial implications to the cloud service providers and SME s in understanding the enterprises and their expectations in cloud adoption and take strategial decisions to reach higher level of competitiveness respectively. The study was able to provide only the relative importance of each BOCR criteria for SME s, so further studies can focus on, 1. Other geographic locations of the world to acquire broad opinion on cloud computing adoption and also can make an attempt to develop the best marketing strategies and alternatives to overcome the barriers in cloud adoption. 2. Identifying and examining the interrelationships among the underlying factors and service quality could be useful in deriving certain inferences to the IT industry. 614

10 3. Further, investigating the dynamic behaviour of cloud consumers may help in understanding them over the time and serve better. 4. Analysing the future market trend would provide some practical implications to IT industry. 6. References 1. Abbadi, I.M. and Martin, A., (2011), Trust in the Cloud. Information Security Technical Report, 16, pp Albayrak, E., and Erensal, Y. C., (2004), Using analytic hierarchy process (AHP) to improve human performance. An application of multiple criteria decision making problem. Journal of Intelligent Manufacturing, 15, pp Arslan, O., and Turan, O., (2009), Analytical investigation of marine casualties at the Strait of Istanbul with SWOTAHP method. Maritime Policy and Management, 36(2), pp Atayero, A.A. and Feyisetan, O., (2011), Security Issues in Cloud Computing: The Potentials of Homomorphic Encryption. Journal of Emerging Trends in Computing and Information Sciences, 2(10), pp Bisong, A. and Rahman, S.S.M., (2011), An Overview of the Security Concerns in Enterprise Cloud Computing. International Journal of Network Security and Its Applications, 3(1), pp Borajee, M. and Yakchali, S. H., (2011), Using the AHP-ELECTRE III integrated method in a competitive profile matrix. International Conference on Financial Management and Economics 2011Proceedings, pp Buyya, R., Beloglazov, A., and Abawajy, J., July, (2010b), Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges. PDPTA'10 - The International Conference on Parallel and Distributed Processing Techniques and Applications, Las Vegas, USA. 8. Buyya, R., Ranjan, R., and Calheiros, R. N., (2010a), InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services, Algorithm and Architectures for Parallel Processing. Lecture Notes in Computer Science, 6081/2010, pp Buyya, R., Yeo, C. S., Venugopal, S., Broberg, J., and Brandic, I., (2009), Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Journal of Future Generation Computer Systems, 25(6), June, pp Celik, A., Holliday, J. and Hu st, Z., (2006), Data Dissemination to a Large Mobile Network: Simulation of Broadcast Clouds. The 7th International Conference on Mobile Data Management (MDM), May, Santa Clara University, USA. 615

11 11. Chang, V., Wills, G., Walters, R., and Currie, W., (2012a), Towards a structured Cloud ROI: The University of Southampton cost-saving and user satisfaction case studies. In Sustainable ICTs and Management Systems for Green Computing. IGI Global, page Che, J. Duan, Y, Zhang, T. and Fan, J., (2011), Study on the security models and strategies of cloud computing. Procedia Engineering, 23, pp Dagdeviren, M., Yavuz, S., and Kılınc, N., (2009), Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert Systems with Applications, 36, pp Darryl Carlton, (2013), Cloud Computing 2014: ready for real business? Gartner Inc. 15. Dunn, T., (2010), Identity Management: Cloud and Virtualisation. Keynote, Munich Cloud. 16. Emam, A.H.M., (2013), Additional Authentication and Authorization using Registered -ID for Cloud Computing. International Journal of Soft Computing and Engineering, 3(2), pp Gillen, A., Grieser, T., and Perry, R., July, (2008), Business Value of Virtualization: Realizing the Benefits of Integrated Solutions. White Paper, the IDC. 18. Gonzalez, N., Miers, C., Redigolo, F., Simplicio, M., Carvalho, T., Naslund, M. and Pourzandi, M., (2012), A quantitative analysis of current security concerns and solutions for cloud computing. Journal of Cloud Computing, 1(11), pp Google Cloud Platform Used for Botnet Control, (2014), Available online: accessed during January Han, J., Susilo, W. and Mu, Y., (2013), Identity-based data storage in cloud computing. Future Generation Computer Systems, 29, pp Hashizume, K., Rosado, D.G., Fernández-Medina, E., Fernandez, E.B., (2013), An analysis of security issues for cloud computing. Journal of Internet Services and Applications, 4(5), pp Hunter, J., Little, S., and Schroeter, R., (2008), The Application of Semantic Web Technologies to Multimedia Data Fusion within e-science. Book Chapter, Chapter 8, Semantic Multimedia and Ontologies, Part 3, pp IBM Discovers Encryption Scheme That Could Improve Cloud Security, Spam Filtering, (2010), at Uncovers- Encryption-Scheme-That-Could-Improve-Cloud-Security- Spam-Filtering135413/. Map Reduce, In: Castro M, Eds Proc. of the 7th Usenix Symp. On Networked Systems Design and Implementation. San Jose: USENIX Association, pp

12 24. Issa M. Khalil, Abdallah Khreishah and Muhammad Azeem, (2014), Cloud computing security: A survey, Computers, 3, pp Kajanusa, M., Kangas, J., and Kurttila, M., (2004), The use of value focused thinking and the A WOT hybrid method in tourism management. Tourism Management 25, pp Kangas, J., Pesonen, M., Kurttila, M., and Kajanus, M., (2001), A'WOT: Integrating the AHP with SWOT Analysis. 6th ISAHP 2001 Proceedings, Berne, Switzerland, pp Khajeh-Hosseini, A., Greenwood, D., and Sommerville, I., 5-10, July,(2010a), Cloud Migration: A Case Study of Migrating an Enterprise IT System to IaaS. 3rd IEEE International conference on Cloud Computing, Miami, USA. 28. Kim, J. and Hong, S., (2012), A Consolidated Authentication Model in Cloud Computing Environments. International Journal of Multimedia and Ubiquitous Engineering, 7(3), pp Kim, W., (2009), Cloud Computing: Today and Tomorrow. Journal of Object technology, 8(1), pp Kumar, A., (2012), World of Cloud Computing and Security. International Journal of Cloud Computing and Services Science, 1(2), pp Kurttila, M., Pesonen, J., Kangas, M., and Kajanus, M., (2000), Utilizing the analytic hierarchy process (AHP) in SWOT analysis- a hybrid method and its application to a forest-certification case. Forest Policy and Economics, 1, pp Lee, K., (2012), Security Threats in Cloud Computing Environments. International Journal of Security and Its Application, 6(4), pp Lee, S., and Walsh, P., (2011), SWOT and AHP hybrid model for sport marketing outsourcing using a case of intercollegiate sport. Sport Management Review, 14, pp Lin, W., Lee, D., (2012), Traceback attacks in cloud Pebbletrace botnet. In Proceedings of the nd International Conference on Distributed Computing Systems Workshops (ICDCSW), Macau, China, pp Monjur Ahmed and Mohammad Ashraf Hossain, (2014), Cloud computing and security issues in the cloud, International Journal of Network Security and Its Applications (IJNSA), 6(1), pp Mosher, R, (2011), Cloud Computing Risks. ISSA Journal, July Issue, pp Mpho Mohlameane, J. and Nkqubela Ruxwana, L., (2013), The Potential of Cloud Computing as an Alternative Technology for SME s in South Africa. Journal of Economics, Business and Management, 1(4), pp

13 38. Ogigau-Neamtiu, F., (2012), Cloud Computing Security Issues. Journal of Defense Resource Management, 3(2), pp Qaisar, S. and Khawaja, K.F., (2012), Cloud Computing: Network/Security Threats and Countermeasures. Interdisciplinary Journal of Contemporary Research in Business, 3(9), pp Rashmi, Sahoo, G. and Mehfuz, S., (2013), Securing Software as a Service Model of Cloud Computing: Issues and Solutions. International Journal on Cloud Computing: Services and Architecture, 3(4), pp Raytheon UK Targeted in Cloud-Based Attack, (2014), Available online: accessed during January Roy, I., Ramadan H.E., Setty S.T.V., Kilzer A., Shmatikov, V., and Witchel E., (2013), Airavat: Security and privacy for [14] OASIS Key Management Interoperability Protocol (KMIP)TC, /tchome. php?wg_abbrev=kmip, accessed during January Saaty, T. L., (1980), Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World. 44. Saaty, T. L., and Vargas, L. G., (1991), Prediction, Projection and Forecasting. Kluwer Academic, Boston. 45. Saaty, T. L., and Vargas, L. G., (1996), Decision Making with the Analytic Network Process. Springer, USA. 46. Sadi, M. A. and Henderson, J. C., (2011), Franchising and small medium-sized enterprises (SMEs) in industrializing economies: A Saudi Arabian perspective. Journal of Management Development, 30(4), pp Sania Khan, Abdul Razak, H., and Krishna Kumar, V., (2011), Prioritization of Green IT Parameters for Indian IT Industry: Using Analytical Hierarchy Process. World Journal of Social Sciences, 1(4), pp Saudi Gazette, IT-powered SMEs to create jobs in KSA.Saudi Gazette. (Retrieved January 3, 2012), method= home.regcon andcontentid= , accessed during January Schubert, L., Jeffery, K., and Neidecker-Lutz, B., January, (2010), The Future for Cloud Computing: Opportunities for European Cloud Computing Beyond. Expert Group report, public version Sharma, M. J., Moon, I., and Bae, H.,(2008), Analytic hierarchy process to assess and optimize distribution network. Applied Mathematics and Computation, 202, pp

14 51. Sharma, S. And Mittal, U., (2013), Comparative Analysis of Various Authentication Techniques in Cloud Computing. International Journal of Innovative Research in Science, Engineering and Technology, 2(4), pp Singh, S. and Jangwal, T., (2012), Cost breakdown of Public Cloud Computing and Private Cloud Computing and Security Issues. International Journal of Computer Science and Information Technology, 4(2), pp Wang, J. J., and Yang, D. L., (2007), Using a hybrid multi-criteria decision aid method for information systems outsourcing. Computers and Operation Research, 34(12), pp Yassin, A.A., Jin, H., Ibrahim, A., Qiang, W. and Zou, D., (2012), Efficient Password-based Two Factors Authentication in Cloud Computing. International Journal of Security and Its Applications, 6(2), pp Yeboah-Boateng, E.O., and Essandoh, K.A., (2014), Factors Influencing Adoption of Cloud Computing by Small and Medium Enterprises in Developing Economies. International Journal of Emerging Science and Engineering, 2(4), pp Yuksel, I., and Dagdeviren, M., (2007), Using the analytic network process (ANP) in a SWOT analysis-a case study for a textile firm. Information Sciences, 177(16), pp Zawya, (2012). Saudi SMEs Opportunity. Saudi_SME_opportunity -ZAWYA /, accessed on February Zissis, D and Lekkas, D., (2012), Addressing cloud computing security issues. Future Generation Computer Systems, 28, pp