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首页> 外文期刊>African Journal of Business Management >Decision support model for supplier selection in healthcare service delivery using analytical hierarchy process and artificial neural network
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Decision support model for supplier selection in healthcare service delivery using analytical hierarchy process and artificial neural network

机译：基于层次分析法和人工神经网络的医疗服务提供者选择决策支持模型

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The healthcare industry today has grown rapidly and emphasizing the efficiency and effectiveness within the healthcare delivery systems has become a major priority in the field. In order to increase the satisfaction and safety of patient, hospitals must improve their overall performance. We established from our review that a number of models have been developed for supplier selection using diverse methods. Most of the models were used to evaluate the performance of healthcare service sector but there is little emphasis on suppliers of health service facilities. And also to the best of our search, we could not find research works on models for evaluating and selecting suppliers in the healthcare unit of tertiary institution. Hence our focus in this study is to develop a decision support model for evaluating and selecting suppliers in the healthcare service of universities. The use of manual techniques for supplier selection in healthcare unit of universities in developing countries is quite tedious and inefficient particularly when several criteria are taken into consideration. These make decision making difficult and also cause the health centre to frequently stock out. Moreover deciding when to order and how much to order is not very easy and hence not meeting patients’ demands adequately. This study focuses on investigating and developing a decision support model for evaluating and selecting suppliers in the healthcare service of tertiary institutions using analytical hierarchy process (AHP) and artificial neural network (ANN). Our case study is the health center of Redeemers University, Nigeria. According to the Overall Priority Vector, the priority values for the respective criteria are: Quality = 0.2192, Service = 0.2160, Delivery = 0.2102, Cost = 0.1968 and Risk = 0.1860.?? Our results revealed that the quality of product supply by the supplier is the most important criterion, while the risk on the supplies is the least important. To improve on the accuracy of these results, the AHP model was supplemented by a 3-layer artificial neural network, adding a learning component to the model. The result also shows that quality is the most important criterion, but with a high index of 0.6845 as opposed to 0.2192 for the AHP alone. This shows that the hybrid model is much better than the AHP alone.
机译：当今的医疗保健行业发展迅速，强调医疗保健传递系统内的效率和有效性已成为该领域的首要任务。为了提高患者的满意度和安全性，医院必须改善其整体性能。从我们的审查中我们发现，已经开发出了多种模型，用于使用多种方法选择供应商。大多数模型用于评估卫生保健服务部门的绩效，但很少强调卫生服务设施的供应商。而且，根据我们的最佳搜索结果，我们找不到有关大专院校医疗部门评估和选择供应商的模型的研究工作。因此，我们在这项研究中的重点是开发一种决策支持模型，用于评估和选择大学医疗服务中的供应商。在发展中国家的大学的医疗保健部门中，使用手动技术选择供应商非常繁琐且效率低下，尤其是在考虑了多个标准的情况下。这些使决策变得困难，并且还导致保健中心频繁缺货。此外，决定何时订购以及订购多少并不是一件容易的事，因此不能充分满足患者的需求。这项研究的重点是研究和开发决策支持模型，用于使用层次分析法（AHP）和人工神经网络（ANN）评估和选择大专院校医疗服务的供应商。我们的案例研究是尼日利亚救世主大学的健康中心。根据总体优先级向量，相应标准的优先级值为：质量= 0.2192，服务= 0.2160，交付= 0.2102，成本= 0.1968和风险= 0.1860。我们的结果表明，供应商提供产品的质量是最重要的标准，而供应风险则是最不重要的。为了提高这些结果的准确性，AHP模型通过三层人工神经网络进行了补充，为模型增加了学习成分。结果还表明质量是最重要的标准，但是AHP的指数为0.6845，而AHP的指数为0.2192。这表明混合模型比单独的AHP更好。

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