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Rationalizing Business Intelligence Systems and Explicit Knowledge Objects: A Prescription Toward Improving Evidence-based Management in Government Programs.

机译:合理化商业智能系统和明确的知识对象:对改善政府计划中基于证据的管理的规定。

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摘要

Summary of contributions of this study: This study contributes new knowledge regarding the prescriptive utility of business intelligence systems and explicit knowledge objects in evidence-based management, and proposes a framework to better facilitate the management of business intelligence systems geared toward a more efficient and effective use of explicit knowledge. The focus of this study is toward optimizing the use of business intelligence systems and explicit knowledge objects (i.e., prescriptive), and not necessarily on optimal decision making (i.e., normative) or the behavior of the decision maker (i.e., descriptive).;Abstract: Many public sector programs fail to leverage their business intelligence systems and explicit knowledge objects to drive efficiency and effectiveness. Given the decline in federal budgets and the need for effective government, federal programs look to business intelligence as an evidence-based decision-making practice to lead to a more lean government, improving efficiency in cost and effectiveness in delivering results. However, cost overruns, technical obstacles, and next-generation information challenges stemming from pervasive computing can reduce any perceived value of utilizing explicit knowledge systems to support evidence in decision making. Through the evaluation of five diverse projects tasked to address the use of evidence in decision-making practices, this research shows that achieving contextualization of information requirements, stakeholder alignment, and the complexity/feasibility of information integration are key factors that should be analyzed to improve the evidence-based decision-making practice in government programs, and may be accomplished through a systematic approach, such as the rationalization of business intelligence systems. Thus, a rationalization framework is provided to facilitate the management of business intelligence systems geared toward a more efficient and effective use of explicit knowledge.
机译:本研究的贡献摘要:本研究为基于证据的管理中的商业智能系统的规范用途和显式知识对象提供了新知识,并提出了一个框架,以更好地促进商业智能系统的管理,从而朝着更加高效和有效的方向发展。使用明确的知识。这项研究的重点是优化商务智能系统和显式知识对象(即规范性)的使用,而不必优化决策(即规范性)或决策者的行为(即描述性)。摘要:许多公共部门计划未能利用其商业智能系统和明确的知识对象来提高效率和效力。鉴于联邦预算的减少以及对有效政府的需求,联邦计划将商业智能视为基于证据的决策实践,以建立更精简的政府,从而提高成本效率和成果交付效率。但是,普适计算所导致的成本超支,技术障碍和下一代信息挑战,可能会降低利用显式知识系统来支持决策依据的任何感知价值。通过评估五个负责解决决策实践中证据使用问题的项目,这项研究表明,实现信息需求的上下文化,利益相关者的一致以及信息集成的复杂性/可行性是应加以分析以改善的关键因素。政府计划中基于证据的决策实践,并且可以通过系统的方法来实现,例如商业智能系统的合理化。因此,提供了一种合理化框架来促进旨在更有效地使用显式知识的商务智能系统的管理。

著录项

  • 作者

    Sapp, Carlton Emory.;

  • 作者单位

    The George Washington University.;

  • 授予单位 The George Washington University.;
  • 学科 Engineering System Science.;Information Science.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 124 p.
  • 总页数 124
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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