| 摘要: | 近十年來，因為資通訊科技(Information Communications Technologies, ICTs)的進步(例如雲端科 技、巨量資料等），social media (例如Facebook, twitter, etc.)以及公民社會(Civil Society)的快速發展， 官僚體制(Bureaucracy)裡的政務官與公務人員(public administrator)在制定政策時，必須要有新的思 維，除了要能因應今日益變動的決策環境，善用新科技蒐集與分析資訊，以降低決策的不明確性 (uncertainty)，更重要的是，要能回應公民社會的訴求，以及人文社會(Humanity)中公共價值(public values)的實踐。
本計晝目的在了解行政體系如何體認巨量資料對於公共政策制定的影響，著重公共政策制定的 核心，研究重點在於，公務人員是否能體認新科技以及公民社會的發展，運用巨量資料方法？決策 機制與成效是否因為政府内部資料與外部民意舆情蒐集方式引進巨量資料方法而有所改變。計晝内 容包括：
1.政策制定者(policy maker)行為分析一官僚體系中的公務人員的特質與態度如何影響其採行新科 技(巨量資料)於其工作與政策制定過程；
2.決策資訊與機制分析一公務體系中，那些工作與決策適用巨量資料方法，以及那些決策平台因 素影響其使用行為？
3.決策平台绩效分析一分析決策過程中，組織機制與資料中心機制(data-centric mechanism)彼此間 動態關係，以及決策者巨量資料使用行為及其決策平台的評價。
Due to the progress of information communications technologies (e.g., cloud technology and big data analysis), social media (e.g., facebook, twitter), and civil society, the mindsets of bureaucrats and public administrators at all levels of government need to be changed to adopt new ICTs, respond to citizens’ needs, and make policies of high quality to meet the goal of public values. Big data (BD) promotes greater openness and accountability in government, strengthens democracy and drives innovation and economic opportunities for all people. The success of big data policies and projects hinges on robust assessment strategy that not only provides a valuable understanding of the impacts on stakeholders, but also provides an effective feedback mechanism for mid-course corrections. Considering the importance of internal and external big data, this research will focus on the adoption and performance assessment of big data in government in order to make a contribution to the existing literature.
There are three main foci of this research:
1.In the first year, we will further review literature regarding the international opportune movement of big data analysis. We will propose a model to assess the BD adoption behavior of public administrators.
2.In the second year, we plan to develop a BD platform and then evaluate the usage behavior of public administrators on the platform, paying particularly close attention to factors affecting their usage toward big data, such as decision routine, uncertainty, information types, , etc.
3.In the third year, we plan to develop a performance evaluation model and conduct a survey to understand their usage satisfaction and also the impacts of big data on organizational innovation. |
