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Big data and smart cities: a public sector organizational learning perspective

机译：大数据与智慧城市：公共部门组织学习的视角

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Public sector organizations (city authorities) have begun to explore ways to exploit big data to provide smarter solutions for cities. The way organizations learn to use new forms of technology has been widely researched. However, many public sector organisations have found themselves in new territory in trying to deploy and integrate this new form of technology (big data) to another fast moving and relatively new concept (smart city). This paper is a cross-sectional scoping study—from two UK smart city initiatives—on the learning processes experienced by elite (top management) stakeholders in the advent and adoption of these two novel concepts. The findings are an experiential narrative account on learning to exploit big data to address issues by developing solutions through smart city initiatives. The findings revealed a set of moves in relation to the exploration and exploitation of big data through smart city initiatives: (a) knowledge finding; (b) knowledge reframing; (c) inter-organization collaborations and (d) ex-post evaluations. Even though this is a time-sensitive scoping study it gives an account on a current state-of-play on the use of big data in public sector organizations for creating smarter cities. This study has implications for practitioners in the smart city domain and contributes to academia by operationalizing and adapting Crossan et al’s (Acad Manag Rev 24(3): 522–537, 1999) 4I model on organizational learning.
机译：公共部门组织（城市当局）已开始探索利用大数据为城市提供更智能解决方案的方法。组织学习使用新技术形式的方式已得到广泛研究。但是，许多公共部门组织已发现自己在尝试将这种新形式的技术（大数据）部署和集成到另一个快速发展且相对较新的概念（智能城市）中。本文是一项横断面的范围研究（来自两个英国智慧城市计划），涉及精英（高层管理人员）利益相关者在这两个新颖概念出现和采用时所经历的学习过程。这些发现是一个关于体验性叙述的说明，说明了如何通过智慧城市计划开发解决方案来学习利用大数据来解决问题。调查结果揭示了与通过智慧城市计划探索和利用大数据有关的一系列举措：（a）知识发现； （b）知识重组； （c）组织间合作和（d）事后评估。尽管这是一项对时间敏感的范围界定研究，但它说明了公共部门组织中使用大数据创建更智能城市的当前状况。这项研究对智能城市领域的从业者具有意义，并通过实施和改编Crossan等人的研究（Acad Manag Rev 24（3）：522-537，1999）4I组织学习模型，为学术界做出了贡献。

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