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.
- Decision support
- Site selection
- Data analytics
- Decision analysis
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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
Durvasula S, Sharma S, Andrews CJ (1992) STORELOC: a retail store location model based on managerial judgments. J Retail 68:420–444
Pope JA, Lane WR, Stein J (2012) A multiple-attribute decision model for retail store location. Southern Bus Rev 37:15
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
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
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
Levy M, Weitz B (2001) Retailing management. McGrawHill 688. Retrieved from https://doi.org/10.1057/jors.1992.174
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
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
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
This study was supported by Telekom Malaysia.
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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
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