Artificial Neural Network Based Decision Model for Alternative Workplaces

Abstract

Alternative workplace arrangements (AWAs), enabled by information and communication technology, where employees do not have permanently assigned workspaces on company premises, are likely to continue in the future. However, facility managers have limited tools to select from among the possible choices in which the AWA type is more appropriate considering their organizations′ business reasons for adoption and the current readiness condition. The aim of this research is to provide facility managers with an understanding of the decision process for AWA adoption and to develop a decision support model to allow them to select an appropriate AWA type and determine the anticipated satisfaction level. Using the artificial neural network (ANN) method and the case-based reasoning (CBR) technique, the authors have developed and validated a decision model to suggest the most appropriate AWA type given the organization′s objectives and the current readiness levels. The proposed approach is tested by evaluating 64 real adoption cases from 19 large high-tech companies. The findings reveal that the ANN-based decision model can provide an accurate prediction of the actual values and the support decisions of the facility managers responsible for developing workplace strategies to meet the organization′s current and future needs.