iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://doi.org/10.1007/s10257-016-0334-7
A new integrated methodology using modified Delphi-fuzzy AHP-PROMETHEE for Geospatial Business Intelligence selection | Information Systems and e-Business Management Skip to main content

Advertisement

Springer Nature Link
Log in

A new integrated methodology using modified Delphi-fuzzy AHP-PROMETHEE for Geospatial Business Intelligence selection

  • Original Article
  • Published:
Information Systems and e-Business Management Aims and scope Submit manuscript

Abstract

Geospatial Business Intelligence (Geospatial BI) is a system that combines multidimensional analysis and cartographic visualization. It plays an important role in decision making process for enterprises. Adopting such a comprehensive solution may result in the great investment decision for them, so great deal of attention should be given in the selection of the optimal system. As there are many impacting factors in the selection of Geospatial BI system, the same process is considered as a complex multi-criteria decision making problem. In this paper, we explore the application of an integrated methodology for the evaluation of various Geospatial BI alternatives. The proposed methodology integrates the three well-known decision-making techniques, namely Modified Delphi, fuzzy analytic hierarchical process (fuzzy-AHP), and preference ranking organization method for enrichment evaluations (PROMETHEE). In this respect, the modified Delphi is used to select the most impacting factors by a few decision-makers. The fuzzy-AHP is employed to analyze the structure of the problem and to obtain the weights of the qualitative and quantitative criteria, by incorporating the uncertainty values. Then, the PROMETHEE technique is used for optimal ranking of the alternative system choices. A step-by-step, numerical study is illustrated by using the proposed methodology on the decision making problem of a company that is faced to five Geospatial BI solutions. The results demonstrate that the proposed methodology can successfully accomplish our goal of this study.

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
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Angelaccio M, Buttarazzi B, Basili A, Liguori W (2012) Using geo-business intelligence to improve quality of life. IEEE First AESS European conference on satellite telecommunications (ESTEL). doi:10.1109/estel.2012.6400196

  • Azadeh A, Shirkouhi SN, Rezaie K (2009) A robust decision-making methodology for evaluation and selection of simulation software package. Int J Adv Manuf Technol 47(1–4):381–393

    Google Scholar 

  • Badard T, Dubé E (2009) Enabling geospatial business intelligence. The Special issue on Business Intelligence for the OSBR, p 25

  • Behzadian M, Kazemzadeh RB, Albadvi A, Aghdasi M (2010) PROMETHEE: a comprehensive literature review on methodologies and applications. Eur J Oper Res 200(1):198–215

    Article  Google Scholar 

  • Boutkhoum O, Hanine M, Agouti T, Tikniouine A (2015) An improved hybrid multi-criteria/multidimensional model for strategic industrial location selection: casablanca industrial zones as a case study. SpringerPlus. doi:10.1186/s40064-015-1404-x

    Google Scholar 

  • Bozbura F, Beskese A, Kahraman C (2007) Prioritization of human capital measurement indicators using fuzzy AHP. Expert Syst Appl 32(4):1100–1112. doi:10.1016/j.eswa.2006.02.006

    Article  Google Scholar 

  • Brans JP, Mareschal B (1994) The PROMCALC and GAIA decision support system for multicriteria decision aid. Decis Support Syst 12(4–5):297–310. doi:10.1016/0167-9236(94)90048-5

    Article  Google Scholar 

  • Brans JP, Mareschal B (2004) Promethee methods, international series in operations research and management science, multiple criteria decision analysis: state of the art surveys. Springer, Berlin

    Google Scholar 

  • Bueno S, Salmeron JL (2008) Fuzzy modeling enterprise resource planning tool selection. Comput Stand Interfaces 30(3):137–147. doi:10.1016/j.csi.2007.08.001

    Article  Google Scholar 

  • Büyüközkan G, Feyzıoglu O (2004) A fuzzy-logic-based decision-making approach for new product development. Int J Prod Econ 90(1):27–45. doi:10.1016/s0925-5273(02)00330-4

    Article  Google Scholar 

  • Büyüközkan G, Ruan D (2008) Evaluation of software development projects using a fuzzy multi-criteria decision approach. Math Comput Simul 77(5–6):464–475. doi:10.1016/j.matcom.2007.11.015

    Article  Google Scholar 

  • Büyüközkan G, Kahraman C, Ruan D (2004) A fuzzy multi-criteria decision approach for software development strategy selection. Int J Gen Syst 33(2–3):259–280. doi:10.1080/03081070310001633581

    Article  Google Scholar 

  • Chang DY (1996) Applications of the extent analysis method on fuzzy AHP. Eur J Oper Res 95(3):649–655. doi:10.1016/0377-2217(95)00300-2

    Article  Google Scholar 

  • Chang C-W, Wu C-R, Chen H-C (2008) Using expert technology to select unstable slicing machine to control wafer slicing quality via fuzzy AHP. Expert Syst Appl 34(3):2210–2220. doi:10.1016/j.eswa.2007.02.042

    Article  Google Scholar 

  • Chang CW, Wu CR, Lin HL (2009) Applying fuzzy hierarchy multiple attributes to construct an expert decision making process. Expert Syst Appl 36(4):7363–7368. doi:10.1016/j.eswa.2008.09.026

    Article  Google Scholar 

  • Cochran JK, Chen H-N (2005) Fuzzy multi-criteria selection of object-oriented simulation software for production system analysis. Comput Oper Res 32(1):153–168. doi:10.1016/s0305-0548(03)00209-0

    Article  Google Scholar 

  • Dağdeviren M (2008) Decision making in equipment selection: an integrated approach with AHP and PROMETHEE. J Intell Manuf 19(4):397–406. doi:10.1007/s10845-008-0091-7

    Article  Google Scholar 

  • Durán O (2011) Computer-aided maintenance management systems selection based on a fuzzy AHP approach. Adv Eng Softw 42(10):821–829. doi:10.1016/j.advengsoft.2011.05.023

    Article  Google Scholar 

  • Durán O, Aguilo J (2008) Computer-aided machine-tool selection based on a fuzzy-AHP approach. Expert Syst Appl 34(3):1787–1794. doi:10.1016/j.eswa.2007.01.046

    Article  Google Scholar 

  • Efe B (2016) An integrated fuzzy multi criteria group decision making approach for ERP system selection. Appl Soft Comput 38:106–117. doi:10.1016/j.asoc.2015.09.037

    Article  Google Scholar 

  • Ekmekçioglu M, Can Kutlu A, Kahraman C (2011) A fuzzy multi-criteria SWOT analysis: an application to nuclear power plant site selection. Int J Comput Intell Syst 4(4):583–595

    Article  Google Scholar 

  • Eldrandaly K, Naguib S (2013) A knowledge-based system for GIS software selection. Int Arab J Inf Technol 10(2):152–159

    Google Scholar 

  • Espinilla M, Halouani N, Chabchoub H (2014) Pure linguistic PROMETHEE I and II methods for heterogeneous MCGDM problems. Int J Comput Intell Syst 8(2):250–264

    Article  Google Scholar 

  • Franklin C, Hane P (1992) An introduction to GIS: linking maps to databases. Database 15(1992):17–22

    Google Scholar 

  • Ghazanfari M, Jafari M, Rouhani S (2011) A tool to evaluate the business intelligence of enterprise systems. Sci Iran 18(6):1579–1590. doi:10.1016/j.scient.2011.11.011

    Article  Google Scholar 

  • Gumus AT (2009) Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology. Expert Syst Appl 36(2):4067–4074. doi:10.1016/j.eswa.2008.03.013

    Article  Google Scholar 

  • Gürbüz T, Alptekin SE, Işıklar Alptekin G (2012) A hybrid MCDM methodology for ERP selection problem with interacting criteria. Decis Support Syst 54(1):206–214. doi:10.1016/j.dss.2012.05.006

    Article  Google Scholar 

  • Hanine M, Boutkhoum O, Tikniouine A, Agouti T (2016a) Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection. SpringerPlus. doi:10.1186/s40064-016-2131-7

    Google Scholar 

  • Hanine M, Boutkhoum O, Tikniouine A, Agouti T (2016b) Application of an integrated multi-criteria decision making AHP-TOPSIS methodology for ETL software selection. SpringerPlus. doi:10.1186/s40064-016-1888-z

    Google Scholar 

  • Ilangkumaran M, Kumanan S (2009) Selection of maintenance policy for textile industry using hybrid multi-criteria decision making approach. J Manuf Technol Manag 20(7):1009–1022. doi:10.1108/17410380910984258

    Article  Google Scholar 

  • Khajouei H, Kazemi M, Moosavirad SH (2016) Ranking information security controls by using fuzzy analytic hierarchy process. Inf Syst E Bus Manag. doi:10.1007/s10257-016-0306-y

    Google Scholar 

  • Kilic HS, Zaim S, Delen D (2014) Development of a hybrid methodology for ERP system selection: the case of Turkish Airlines. Decis Support Syst 66:82–92. doi:10.1016/j.dss.2014.06.011

    Article  Google Scholar 

  • Kilic HS, Zaim S, Delen D (2015) Selecting ‘the best’ ERP system for SMEs using a combination of ANP and PROMETHEE methods. Expert Syst Appl 42(5):2343–2352. doi:10.1016/j.eswa.2014.10.034

    Article  Google Scholar 

  • Kwon O, Kim KY, Lee KC (2007) MM-DSS: integrating multimedia and decision-making knowledge in decision support systems. Expert Syst Appl 32(2):441–457. doi:10.1016/j.eswa.2005.12.009

    Article  Google Scholar 

  • Kwong CK, Mu LF, Tang JF, Luo XG (2010) Optimization of software components selection for component-based software system development. Comput Ind Eng 58(4):618–624. doi:10.1016/j.cie.2010.01.003

    Article  Google Scholar 

  • Li S-T, Shue L-Y, Lee S-F (2008) Business intelligence approach to supporting strategy-making of ISP service management. Expert Syst Appl 35(3):739–754. doi:10.1016/j.eswa.2007.07.049

    Article  Google Scholar 

  • Lin H-Y, Hsu P-Y, Sheen G-J (2007) A fuzzy-based decision-making procedure for data warehouse system selection. Expert Syst Appl 32(3):939–953. doi:10.1016/j.eswa.2006.01.031

    Article  Google Scholar 

  • Macharis C, Springael J, De Brucker K, Verbeke A (2004) PROMETHEE and AHP: the design of operational synergies in multicriteria analysis. Eur J Oper Res 153(2):307–317

    Article  Google Scholar 

  • Manh Nguyen T, Min Tjoa A, Nemec J, Windisch M (2007) An approach towards an event-fed solution for slowly changing dimensions in data warehouses with a detailed case study. Data Knowl Eng 63(1):26–43

    Article  Google Scholar 

  • McHugh R, Roche S, Bédard Y (2009) Towards a SOLAP-based public participation GIS. J Environ Manag 90(6):2041–2054. doi:10.1016/j.jenvman.2008.01.020

    Article  Google Scholar 

  • Minetola P, Iuliano L, Calignano F (2015) A customer oriented methodology for reverse engineering software selection in the computer aided inspection scenario. Comput Ind 67:54–71. doi:10.1016/j.compind.2014.11.002

    Article  Google Scholar 

  • Mousavi SM, Tavakkoli-Moghaddam R, Heydar M, Ebrahimnejad S (2012) Multi-criteria decision making for plant location selection: an integrated Delphi–AHP–PROMETHEE methodology. Arab J Sci Eng 38(5):1255–1268

    Article  Google Scholar 

  • Mulebeke JAW, Zheng L (2006) Analytical network process for software selection in product development: a case study. J Eng Technol Manag 23(4):337–352. doi:10.1016/j.jengtecman.2006.08.004

    Article  Google Scholar 

  • Noori B, Hossein Salimi M (2005) A decision support system for business to business marketing. J Bus Ind Market 20(4/5):226–236. doi:10.1108/08858620510603909

    Article  Google Scholar 

  • Ozgen A, Tuzkaya G, Tuzkaya UR, Ozgen D (2011) A multi-criteria decision making approach for machine tool selection problem in a fuzzy environment. Int J Comput Intell Syst 4(4):431

    Article  Google Scholar 

  • Perçin S, Kahraman C (2010) An integrated fuzzy multi-criteria decision-making approach for six sigma project. Int J Comput Intell Syst 3(5):610–621. doi:10.1080/18756891.2010.9727727

    Article  Google Scholar 

  • Rivest S, Bédard Y, Proulx MJ, Nadeau M, Hubert F, Pastor J (2005) SOLAP technology: merging business intelligence with geospatial technology for interactive spatio-temporal exploration and analysis of data. ISPRS J Photogramm Remote Sens 60(1):17–33. doi:10.1016/j.isprsjprs.2005.10.002

    Article  Google Scholar 

  • Rouhani S, Ghazanfari M, Jafari M (2012) Evaluation model of business intelligence for enterprise systems using fuzzy TOPSIS. Expert Syst Appl 39(3):3764–3771. doi:10.1016/j.eswa.2011.09.074

    Article  Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, NewYork

    Google Scholar 

  • Shyur H-J (2006) COTS evaluation using modified TOPSIS and ANP. Appl Math Comput 177(1):251–259. doi:10.1016/j.amc.2005.11.006

    Google Scholar 

  • Sung WC (2001) Application of Delphi method, a qualitative and quantitative analysis, to the healthcare management. J Healthc Manag 2(2):11–19

    Google Scholar 

  • Tolga E, Demircan ML, Kahraman C (2005) Operating system selection using fuzzy replacement analysis and analytic hierarchy process. Int J Prod Econ 97(1):89–117. doi:10.1016/j.ijpe.2004.07.001

    Article  Google Scholar 

  • Tsai H-Y, Chang C-W, Lin H-L (2010) Fuzzy hierarchy sensitive with Delphi method to evaluate hospital organization performance. Expert Syst Appl 37(8):5533–5541. doi:10.1016/j.eswa.2010.02.099

    Article  Google Scholar 

  • Tuzkaya UR (2009) Evaluating the environmental effects of transportation modes using an integrated methodology and an application. Int J Environ Sci Technol 6(2):277–290. doi:10.1007/bf03327632

    Article  Google Scholar 

  • Wickramasuriya R, Ma J, Berryman M, Perez P (2013) Using Geospatial Business Intelligence to support regional infrastructure governance. Knowl Based Syst 53:80–89. doi:10.1016/j.knosys.2013.08.024

    Article  Google Scholar 

  • Wu W-W (2008) Choosing knowledge management strategies by using a combined ANP and DEMATEL approach. Expert Syst Appl 35(3):828–835. doi:10.1016/j.eswa.2007.07.025

    Article  Google Scholar 

  • Yazgan HR, Boran S, Goztepe K (2009) An ERP software selection process with using artificial neural network based on analytic network process approach. Expert Syst Appl 36(5):9214–9222

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353. doi:10.1016/s0019-9958(65)90241-x

    Article  Google Scholar 

  • Zahedi F (1986) the analytic hierarchy process-a survey of the method and its applications. Interfaces 16(4):96–108. doi:10.1287/inte.16.4.96

    Article  Google Scholar 

  • Zaidan AA, Zaidan BB, Al-Haiqi A, Kiah MLM, Hussain M, Abdulnabi M (2015) Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS. J Biomed Inf 53:390–404. doi:10.1016/j.jbi.2014.11.012

    Article  Google Scholar 

Download references

Acknowledgments

The authors wish to acknowledge the contributions of other members of the department of computer science of Faculty of Science Semlalia of Marrakech, Cadi Ayyad University for their helpful discussions and the availability of all resources that have helped make this work in the best conditions. They wish also to thank Mr. Redouane Boulguid for pointing out many English corrections that lead to the improvement of the paper. They would also like to thank the reviewers and Editor for their remarks and suggestions.

Author information

Authors and Affiliations

  1. Department of Computer Science, Cadi Ayyad University, Marrakesh, Morocco

    Mohamed Hanine, Omar Boutkhoum, Tarik Agouti & Abdessadek Tikniouine

Authors
  1. Mohamed Hanine
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Omar Boutkhoum
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tarik Agouti
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Abdessadek Tikniouine
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohamed Hanine.

Appendix

Appendix

See Tables 14, 15 and 16.

Table 14 Geospatial BI system selection criteria
Full size table
Table 15 Alternatives evaluation comparison matrix
Full size table
Table 16 Sensitivity analysis details
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hanine, M., Boutkhoum, O., Agouti, T. et al. A new integrated methodology using modified Delphi-fuzzy AHP-PROMETHEE for Geospatial Business Intelligence selection. Inf Syst E-Bus Manage 15, 897–925 (2017). https://doi.org/10.1007/s10257-016-0334-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10257-016-0334-7

Keywords

Search

Navigation