Skip to main content

Aggregating Multiple Decision Makers’ Judgement

  • Conference paper
  • First Online:
Intelligent and Interactive Computing

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 67))

Abstract

Selecting the best location to establish a new business site is very important in order to achieve success. It is therefore one of the most important aspect in any business plan. Multi-criteria decision-making methods such as the Analytic Hierarchy Process (AHP) has been used to elicit information that supports the decision of business site selection. However, AHP often involves multiple decision makers, each with their own opinions and biases. Different decision makers will have different opinions and views on the importance of the criteria and sub-criteria in the AHP model. In this study, three aggregation methods that can be used to carefully aggregate the resultant judgements from the multiple decision makers to form a single group judgement are discussed. The goal of obtaining the single group judgement is to use it as input to the AHP model in order to achieve the goal of selecting the most suitable business location. The study case for this paper is that of the selection of a location for a telecommunication payment point. From this study case, a conclusion can be drawn for the best aggregation method for the selection of the best location to set up a business of the telecommunication nature.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Karande K, Lombard JR (2005) Location strategies of broad-line retailers: an empirical investigation. J Bus Res 58:687–695. https://doi.org/10.1016/j.jbusres.2003.09.008

    Article  Google Scholar 

  2. Durvasula S, Sharma S, Andrews CJ (1992) STORELOC: a retail store location model based on managerial judgments. J Retail 68:420–444

    Google Scholar 

  3. Pope JA, Lane WR, Stein J (2012) A multiple-attribute decision model for retail store location. Southern Bus Rev 37:15

    Google Scholar 

  4. Grošelj P, Zadnik Stirn L, Ayrilmis N, Kuzman MK (2015) Comparison of some aggregation techniques using group analytic hierarchy process. Expert Syst Appl 42:2198–2204. https://doi.org/10.1016/j.eswa.2014.09.060

    Article  Google Scholar 

  5. Bernasconi M, Choirat C, Seri R (2014) Empirical properties of group preference aggregation methods employed in AHP: theory and evidence. Eur J Oper Res 232:584–592. https://doi.org/10.1016/j.ejor.2013.06.014

    Article  MathSciNet  MATH  Google Scholar 

  6. Yap JYL, Ho CC, Ting C-Y (2017) Analytic Hierarchy process (AHP) for business site selection. In: Proceedings—2017 6th international conference on computer science and computational mathematics

    Google Scholar 

  7. Levy M, Weitz B (2001) Retailing management. McGrawHill 688. Retrieved from https://doi.org/10.1057/jors.1992.174

    Google Scholar 

  8. Claudio D, Chen J, Okudan GE (2008) AHP based Borda count: a hybrid multi-person decision making method for design concept selection. In: IIE annual conference. Proceedings. Institute of Industrial and Systems Engineers (IISE), p 776

    Google Scholar 

  9. Escobar MT, Moreno-Jiménez JM (2007) Aggregation of individual preference structures in AHP-group decision making. Group Decis Negot 16:287–301. https://doi.org/10.1007/s10726-006-9050-x

    Article  Google Scholar 

  10. Forman E, Peniwati K (1998) Aggregating individual judgments and priorities with the analytic hierarchy process. Eur J Oper Res 108:165–169. https://doi.org/10.1016/S0377-2217(97)00244-0

    Article  MATH  Google Scholar 

Download references

Acknowledgements

This study was supported by Telekom Malaysia.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jeremy Y. L. Yap .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yap, J.Y.L., Ho, C.C., Ting, CY. (2019). Aggregating Multiple Decision Makers’ Judgement. In: Piuri, V., Balas, V., Borah, S., Syed Ahmad, S. (eds) Intelligent and Interactive Computing. Lecture Notes in Networks and Systems, vol 67. Springer, Singapore. https://doi.org/10.1007/978-981-13-6031-2_26

Download citation

Publish with us

Policies and ethics