描述数据分析工作中的管理和利益相关者包容性:密苏里州堪萨斯城的合作方法

IF 2.4 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
Felippe Cronemberger, José Ramón Gil-García
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引用次数: 2

摘要

目的地方政府在内部运作和提供公共服务方面面临着越来越复杂的挑战。然而,关于他们如何接受数据分析实践等循证方法的研究仍然很少,这些方法可以帮助他们应对其中的一些挑战。本研究旨在通过研究密苏里州堪萨斯城(KCMO)的数据分析实践,为现有知识做出贡献。该市因通过彭博社的“什么是有效的城市”(WWC)倡议参与数据分析而变得突出,目的是提高效率并加强对当地选民的响应。设计/方法论/方法本研究对在KCMO有数据分析经验的公务员进行了半结构化访谈。分析在转录本中寻找常见和新出现的模式。建立了一个基于相关研究的概念框架,并将其用作评估案件中观察到的证据的理论基础。FindingsFindings表明,数据分析实践由组织领导层赞助,但由数据管理员培养,他们与其他利益相关者接触,并在解决重要问题时将数据资源纳入他们的分析计划。这些管理者合作培育包容性网络,利用以往经验中的知识来指导当前的分析工作。研究局限性/含义这项研究探索了一个城市的经验,因此它没有解释类似地方政府的成功和失败,这些地方政府也是彭博社WWC的一部分。此外,选定的受访者至少在一定程度上参与了数据分析,这一事实增加了他们的数据分析经验相对比其他地方政府雇员的经验更积极的可能性。实际含义结果表明,数据分析受益于领导层的支持和指导计划,如WWC,也受益于通过协作网络利用利益相关者的知识来访问数据和组织资源。数据分析赞助的活动和组织知识的相互作用可以作为评估地方政府现有数据分析能力的手段。独创性/价值这项研究表明,正在实施智能城市议程的地方政府的数据分析实践是知识驱动的,并通过利用利益相关者知识和数据资源的包容性网络逐步发展。所发现的增量表明,数据分析举措不应被视为“白板”做法,而是由数据管理员通过协作网络利用利益相关者的知识和数据资源所推动和持续的努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characterizing stewardship and stakeholder inclusion in data analytics efforts: the collaborative approach of Kansas City, Missouri
Purpose Local governments face increasingly complex challenges related to their internal operations as well as the provision of public services. However, research on how they embrace evidence-based approaches such as data analytics practices, which could help them face some of those challenges, is still scarce. This study aims to contribute to existing knowledge by examining the data analytics practices in Kansas City, Missouri (KCMO), a city that has become prominent for engaging in data analytics use through the Bloomberg’s What Works Cities (WWC) initiative with the purpose of improving efficiency and enhancing response to local constituents. Design/methodology/approach This research conducted semistructured interviews with public servants who had data analytics experience at KCMO. Analysis looked for common and emerging patterns across transcripts. A conceptual framework based on related studies is built and used as the theoretical basis to assess the evidence observed in the case. Findings Findings suggest that data analytics practices are sponsored by organizational leadership, but fostered by data stewards who engage other stakeholders and incorporate data resources in their analytical initiatives as they tackle important questions. Those stewards collaborate to nurture inclusive networks that leverage knowledge from previous experiences to orient current analytical endeavors. Research limitations/implications This study explores the experience of a single city, so it does not account for successes and failures of similar local governments that were also part of Bloomberg's WWC. Furthermore, the fact that selected interviewees were involved in data analytics at least to some extent increases the likelihood that their experience with data analytics is relatively more positive than the experience of other local government employees. Practical implications Results suggest that data analytics benefits from leadership support and steering initiatives such as WWC, but also from leveraging stakeholder knowledge through collaborative networks to have access to data and organizational resources. The interplay of data analytics sponsored activities and organizational knowledge could be used as means of assessing local governments’ existing data analytics capability. Originality/value This study suggests that data analytics practices in local governments that are implementing a smart city agenda are knowledge-driven and developed incrementally through inclusive networks that leverage stakeholder knowledge and data resources. The incrementality identified suggests that data analytics initiatives should not be considered a “blank slate” practice, but an endeavor driven and sustained by data stewards who leverage stakeholder knowledge and data resources through collaborative networks.
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来源期刊
Transforming Government- People Process and Policy
Transforming Government- People Process and Policy INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
6.70
自引率
11.50%
发文量
44
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