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Management policies and the diffusion of data warehouse: a case study using system dynamics-based decision support system

机译:管理策略和数据仓库的扩散:使用基于系统动力学的决策支持系统的案例研究

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This paper studies the impact of management policies on the diffusion of data warehouse (DW) in a large commercial bank in Thailand. A system dynamics (SD)--based decision support system (DSS) is developed and analysed for this purpose. System dynamics was used as the modelling tool because of its rigorous approach in capturing interrelationships among variables and in handling dynamic aspects of the system behaviour. A qualitative model is first formulated to understand the present state of the DW diffusion. The quantitative model is then formulated to simulate seven management policies. Findings unearth two dominant policies of ‘increase level of training' and ‘decrease training delay' that will speed up the diffusion significantly. None of the policies, however, achieve the bank's target diffusion level within a specified time period. Sensitivity analyses reveal various combinations of the dominant policies that the management can adopt. The analyses act as an eye-opener for the bank executives as they understand what can be feasibly achieved given a number of constraints. With easy interfaces and supportive tools, bank executives can use the DSS to test various scenarios, which will enhance their learning process and improve their decision making.
机译:本文研究了管理政策对泰国一家大型商业银行中数据仓库(DW)扩散的影响。为此,开发并分析了基于系统动力学(SD)的决策支持系统(DSS)。系统动力学被用作建模工具,因为它采用了严格的方法来捕获变量之间的相互关系并处理系统行为的动态方面。首先建立定性模型以了解DW扩散的当前状态。然后制定量化模型以模拟七个管理策略。调查结果揭示了“提高培训水平”和“减少培训延迟”这两个主要政策,这将显着加快传播速度。但是,没有任何政策在指定的时间内达到银行的目标扩散水平。敏感性分析揭示了管理层可以采用的主导政策的各种组合。这些分析使银行高管们大开眼界,因为他们了解在许多限制条件下可以实现的目标。借助简单的界面和支持工具,银行高管可以使用DSS来测试各种情况,这将增强他们的学习过程并改善决策。

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