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Artificial Neural Network Based Decision Model for Alternative Workplaces

机译:基于人工神经网络的替代工作场所决策模型

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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.
机译:由信息和通信技术支持的替代工作场所安排(AWA),将来员工可能不会在公司场所永久分配工作场所,因此很可能会继续使用。但是,设施经理考虑到组织采用的业务原因和当前的准备情况,只能从有限的工具中选择AWA类型更合适的工具。这项研究的目的是使设施管理员了解采用AWA的决策过程,并开发决策支持模型,以允许他们选择适当的AWA类型并确定预期的满意度。使用人工神经网络(ANN)方法和基于案例的推理(CBR)技术,作者已经开发并验证了决策模型,以根据组织的目标和当前的准备水平建议最合适的AWA类型。通过评估19家大型高科技公司的64个实际采用案例,对所提出的方法进行了测试。研究结果表明,基于ANN的决策模型可以为负责制定工作场所策略以满足组织当前和未来需求的设施经理的实际价值和支持决策提供准确的预测。

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