Skip to main content

Advertisement

Springer Nature Link
Log in

The QoS-based MCDM system for SaaS ERP applications with Social Network

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Cloud computing delivers almost all of its services including software, user’s data, system resources, processes and their computation over the Internet. Cloud computing consists of three main classes; Software as a Service, Infrastructure as a Service and Platform as a Service. Using Software as a Service (SaaS), users are able to rent application software and databases which they then install onto their computer in the traditional way. In the Enterprise Resource Planning (ERP) system, the system service environment changed so as to allow the application of the SaaS in the cloud computing environment. This change was implemented in order to provide the ERP system service to users in a cheaper, more convenient and efficient form through the Internet as opposed to having to set up their own computer. Recently many SaaS ERP packages are available on the Internet. For this reason, it is very difficult for users to find the SaaS ERP package that would best suit their requirements. The QoS (Quality of Service) model can provide a solution to this problem. However, according to recent research, not only quality attributes’ identification for SaaS ERP, but also a process for finding and recommending software in the cloud computing environment, has proved to be lacking. In this paper, we propose a QoS model for SaaS ERP. The proposed QoS model consists of 6 criteria; Functionality, Reliability, Usability, Efficiency, Maintainability and Business. Using this QoS model, we propose a Multi Criteria Decision Making (MCDM) system that finds the best fit for the SaaS ERP in the cloud computing environment and makes recommendations to users in priority order. In order to organize the quality clusters, we organized an expert group and got their opinion to organize the quality clusters using Social Network Group. Social Networks can be used efficiently to get opinion by various types of expert groups. In order to establish the priority, we used pairwise comparisons to calculate the priority weights of each quality attribute while accounting for their interrelation. Finally, using the quality network model and priority weights, this study evaluated three types of SaaS ERPs. Our results show how to find the most suitable SaaS ERPs according to their correlation with the criteria and to recommend a SaaS ERP package which best suits users’ needs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. Aramand M (2008) Software products and services are high tech? New product development strategy for software products and services. Technovation 28:154–160

    Article  Google Scholar 

  2. Baek S-J, Park S-M, Yang S-H, Song E-H, Jeong Y-S (2010) Efficient server virtualization using grid service infrastructure. J Inf Process Syst 6(4). doi:10.3745/JIPS.2010.6.4.553

  3. Benlian A, Hess T (2011) Opportunities and risks of software-as-a-service: findings from a survey of IT executives. Decis Support Syst 52:232–246

    Article  Google Scholar 

  4. Bhattacharya A, Wu W, Yang Z (2012) Quality of experience evaluation of voice communication: an affect-based approach. Hum-Centric Comput Inf Sci 2(7). doi:10.1186/2192-1962-2-7

  5. Botta-Genoulaz V, Millet P-A (2005) A classification for better use of ERP systems. Comput Ind 56:573–587

    Article  Google Scholar 

  6. Bozoki S, Fulop J, Ronyai L (2010) On optimal completion of incomplete pairwise comparison matrices. Math Comput Model 52:318–333

    Article  MathSciNet  MATH  Google Scholar 

  7. Buter B, Dijkshoorn N, Modolo D, Nguyen Q, van Noort S, van de Poel B, Salah AA, Salah AAA (2011) Explorative visualization and analysis of a Social Network for arts: the case of deviant ART. J Converg 2(1):87–94

    Google Scholar 

  8. Chadwick DW, Fatema K (2012) A privacy preserving authorisation system for the cloud. J Comput Syst Sci. doi:10.1016/j.jcss.2011.12.019

    Google Scholar 

  9. Challa JS, Paul A, Dada Y, Nerella V, Srivastava PR, Singh AP (2011) Integrated software quality evaluation: a fuzzy multi-criteria approach. J Inf Process Syst 7(3):473–518

    Google Scholar 

  10. Cuéllar MP, Delgado M, Pegalajar MC (2011) Improving learning management through semantic web and social networks in e-learning environments. Expert Syst Appl 38:4181–4189

    Article  Google Scholar 

  11. DeLone WH, McLean ER (2003) The DeLone and McLean model of information systems success: a ten-year update. J Manag Inf Syst 19(4):9–30

    Google Scholar 

  12. Deng Y, Chan FTS, Wu Y, Wang D (2011) A new linguistic MCDM method based on multiple-criterion data fusion. Expert Syst Appl 38:6985–6993

    Article  Google Scholar 

  13. Fan M, Kumar S, Whinston AB (2009) Short-term and long-term competition between providers of shrink-wrap software and software as a service. Eur J Oper Res 196:661–671

    Article  MathSciNet  MATH  Google Scholar 

  14. Garg SK, Versteeg S, Buyya R (2012) A framework for ranking of cloud computing services. Future Gener Comput Syst. doi:10.1016/j.future.2012.06.006

    Google Scholar 

  15. James A, Dimitrijev S (2012) Ranked selection of nearest discriminating features. Hum-Centric Comput Inf Sci 2(12). doi:10.1186/2192-1962-2-12

  16. Jeong HY, Kim YH (2012) A system software quality model using DeLone & McLean model and ISO/IEC 9126. Int J Digit Content Technol Appl 6(5):181–188

    Article  MathSciNet  Google Scholar 

  17. Jeong D, Shin H, Baik D-K, Jeong Y-S (2009) An efficient web ontology storage considering hierarchical knowledge for Jena-based applications. J Inf Process Syst 5(1):11–18

    Google Scholar 

  18. Jin H, Xiang G, Zou D, Wu S, Zhao F, Li M, Zheng W (2011) A VMM-based intrusion prevention system in cloud computing environment. J Supercomput. doi:10.1007/s11227-011-0608-2

    Google Scholar 

  19. Jun L, Jun W (2011) Cloud computing based solution to decision making. Proc Eng 15:1822–1826

    Article  Google Scholar 

  20. Katsaros G, Kousiouris G, Gogouvitis SV, Kyriazis D, Menychtas A, Varvarigou T (2011) A self-adaptive hierarchical monitoring mechanism for clouds. J Syst Softw. doi:10.1016/j.jss.2011.11.1043

    Google Scholar 

  21. Kim H-N, El Saddik A, Jung J-G (2012) Leveraging personal photos to inferring friendships in social network services. Expert Syst Appl 39:6955–6966

    Article  Google Scholar 

  22. Kima W, Lee JH, Hong C, Han C, Lee H, Jang B (2012) An innovative method for data and software integration in SaaS. Comput Math Appl. doi:10.1016/j.camwa.2012.03.069

    Google Scholar 

  23. Klyuev V, Yokoyama A (2010) Web query expansion: a strategy utilising Japanese WordNet. J Converg 1(1)

  24. Kumar V, Maheshwari B, Kumar U (2003) An investigation of critical management issues in ERP implementation: empirical evidence from Canadian organizations. Technovation 23:793–807

    Article  Google Scholar 

  25. Limayem F, Yannou B (2007) Selective assessment of judgmental inconsistencies in pairwise comparisons for group decision rating. Comput Oper Res 34:1824–1841

    Article  MATH  Google Scholar 

  26. Liu D, Stewart TJ (2004) Integrated object-oriented framework for MCDM and DSS modeling. Decis Support Syst 38:421–434

    Article  Google Scholar 

  27. Luo H, Shyu M-L (2011) Quality of service provision in mobile multimedia—a survey. Hum-Centric Comput Inf Sci 1(6):1–15

    Google Scholar 

  28. Malhotra R, Temponi C (2010) Critical decisions for ERP integration: small business issues. Int J Inf Manag 30:28–37

    Article  Google Scholar 

  29. Manufacturing SaaS ERP system for cloud computing (2012) http://www.plex.com/

  30. Michael A (2010) Elliott, selecting numerical scales for pairwise comparisons. Reliab Eng Syst Saf 95:750–763

    Article  Google Scholar 

  31. Oommen BJ, Yazidi A, Granmo O-C (2012) An adaptive approach to learning the preferences of users in a Social Network using weak estimators. J Inf Process Syst 8(2):191–212

    Google Scholar 

  32. Pan R, Xu G, Fu B, Dolog P, Wang Z, Leginus M (2012) Improving recommendations by the clustering of tag neighbours. J Converg 3(1):13–20

    Google Scholar 

  33. Pan R, Xu G, Fu B, Dolog P, Wang Z, Leginus M (2012) Improving recommendations by the clustering of tag neighbours. J Converg 3(1):13–20

    Google Scholar 

  34. Qin XS, Huang GH, Chakma A, Nie XH, Lin QG (2008) A MCDM-based expert system for climate-change impact assessment and adaptation planning? A case study for the Georgia Basin, Canada. Expert Syst Appl 34:2164–2179

    Article  Google Scholar 

  35. Rouse M (2012) Definition of SaaS ERP (software-as-a-service ERP hosting). http://searchmanufacturingerp.techtarget.com/definition/SaaS-ERP

  36. Saaty TL (2006) Fundamentals of decision making and priority theory with the analytic hierarchy process. RWS, Pittsburgh

    Google Scholar 

  37. Salmeron JL, Lopez C (2010) A multicriteria approach for risks assessment in ERP maintenance. J Syst Softw 83:1941–1953

    Google Scholar 

  38. Siraj S, Mikhailov L, Keane JA (2012) Enumerating all spanning trees for pairwise comparisons. Comput Oper Res 39:191–199

    Article  MathSciNet  MATH  Google Scholar 

  39. Sultan NA (2010) Reaching for the cloud: how SMEs can manage. Int J Inf Manag. doi:10.1016/j.ijinfomgt.2010.08.001

    Google Scholar 

  40. Sung K, Kong H-K, Kim T (2011) Convergence indicator: the case of cloud computing. J Supercomput. doi:10.1007/s11227-011-0706-1

    Google Scholar 

  41. Verville J, Halingten A (2003) A six-stage model of the buying process for ERP software. Ind Mark Manage 32:585–594

    Article  Google Scholar 

  42. Wei G, Vasilakos AV, Zheng Y, Xiong N (2010) A game-theoretic method of fair resource allocation for cloud computing services. J Supercomput 54:252–269. doi:10.1007/s11227-009-0318-1

    Article  Google Scholar 

  43. Wu Z, Liu X, Ni Z, Yuan D, Yang Y (2011) A market-oriented hierarchical scheduling strategy in cloud workflow systems. J Supercomput. doi:10.1007/s11227-011-0578-4

    Google Scholar 

  44. Xie S, Sun Z (2011) Improve navigation software quality by using prediction model of coding stage defect density. J Converg Inf Technol 6(4):64–69

    Article  Google Scholar 

  45. Xu X (2012) From cloud computing to cloud manufacturing. Robot Comput-Integr Manuf 28:75–86

    Article  Google Scholar 

  46. Yu H (2012) An approach to evaluating the software quality based on intelligent computation with intuitionistic fuzzy information. Int J Adv Comput Technol 4(4):276–282

    Article  Google Scholar 

  47. Zhang Z, Lee MKO, Huang P, Zhang L, Huang X (2005) A framework of ERP systems implementation success in China: an empirical study. Int J Prod Econ 98:56–80

    Article  Google Scholar 

  48. Zhao L, Ren Y, Li M, Sakurai K (2012) Flexible service selection with user-specific QoS support in service-oriented architecture. J Netw Comput Appl 35:962–973

    Article  Google Scholar 

  49. Zimbres RA (2009) Dynamics of quality perception in a Social Network: a cellular automaton based model in aesthetics services. Electron Notes Theor Comput Sci 252:157–180

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

This work was supported by NIA, KOREA under the KOREN program (1295100001-120010100).

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea

    James (Jong Huk) Park

  2. Humanitas College, Kyung Hee University, 1 Hoegi-dong, Dongdaemun-gu, Seoul, 130-701, Republic of Korea

    Hwa-Young Jeong

Authors
  1. James (Jong Huk) Park
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Hwa-Young Jeong
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Hwa-Young Jeong.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Park, J.(.H., Jeong, HY. The QoS-based MCDM system for SaaS ERP applications with Social Network. J Supercomput 66, 614–632 (2013). https://doi.org/10.1007/s11227-012-0832-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-012-0832-4

Keywords