# Applying ANN and TM to Build a Prediction Model for the Site Selection of a Convenience Store
## 2 Literature Review
With the checklist approach, managers use several criteria that may influence store performance and/or be determined from business strategies [27]. The focus of the determination of these criteria is on potential sales at the site. Consequently, the values for all criteria are evaluated based on either a company \"rule\" (e.g., standard operating policy, previous benchmarks, ex ante decision) or subjective judgments by decision makers. Adecision might thus be made by assessing the tradeoffs among all the candidate sites or simply using judgment. The analog method [28] searches for similarities based on a variety of pre-determined properties observed in existing stores and considers the requisite criteria from all these sites. The selected site is the one matching the criteria in extant successful outlets. Although the analog approach follows a systematic guideline to select worthy sites [6], the procedure generally relies on personal experience and instinct [5]. Because there are variations in the circumstances of the sites, identifying similarities, or presumed similarities, for the various locations is infeasible. Regression models are another alternative for use in site selection. To identify statistically the factors that influence pre-determined business performance, this method provides a sound framework for site selection. However, it has several key limitations: the potential ignorance of multicollinearity among the independent variables, the requirement for sufficient data size, concerns about the validity of the distribution assumption, and an imbalance problem between different data sources, all of which can lead to analytical bias or skewness from unrevealed facts. The simulation model inputs predefined variables with parameters into a framed system--such as pedestrian behavior--to discover their relationship with store sites and transports for the purpose of finding recurring patterns of customer links to business establishments. The major drawback of simulation is the associated difficulty of framing all the variables in practical cases--in particular, the firm's customers' behaviors and environments. As discussed above, an increasing number of site studies employ multi-criteria decision-making procedures, such as AHP, ANP, and ANN. Recent research has shown that the applications of ANN techniques in the decision-making domain are promising (e.g., [6]). By overcoming the multicollinearity problem, the ANN model achieves good results in evaluating and ranking alternatives. The trainability and applicability of ANN techniques to address the problems of multi-attribute utility have also been confirmed. [PERSON] et al. [3] defined the location selection criteria of a retail store and used the AHP to establish a selection model. [PERSON] et al. [4] developed a methodology for the process of selecting a retail site location that combined geographic information systems (GIS) with the AHP. They found that the success factors for a supermarket were related to its location and competition. Some scholars have focused on ascertaining the weights of the factors influencing site selection by using the AHP [3,4] or ANP [1,2]. These two methods were mainly used to identify factors influencing site selection or determine the weights of these factors. Such methods are relatively subjective, and their reference value is limited. In the application of an ANN in site location selection, [PERSON] et al. [8] proposed a model of a four-stage geospatial site selection (GSS) theory and architecture and used ANN techniques with two metrics, a confusion matrix and receiver operational characteristics, to verify the model. The findings indicated that the ANN provides reasonable and effective results. An example is given by [PERSON] et al. [9]. They found that the location of a wastewater treatment plant required the consideration of multiple spatial data. They constructed a multi-level criteria table with reference to various spatial data and then used the AHP to weigh the criteria according to expert opinions.