以大數據分析探討政府政策之推行──以台灣流浪動物零安樂死政策為例

Using Big Data Analysis to Explore the Implementation of Government Policies - Taking Taiwan’s Stray Animal Zero Euthanasia Policy as An Example

近年來隨著資料的大量化與半結構化、非結構化等多樣化資料的增加，造成大數據（Big Data）的流行。透過大數據可以從一堆看似無用或難以分類觀察的大量資料中，取出有價值的資料，並讓其有新的用途。根據台灣將在民國106年2月執行的流浪動物零安樂死政策，未來動物收容所公告十二日後仍無人認領養的流浪動物，將不會被進行人道處理。所以，許多空間有限之收容所能否安然實行該項政策值得考量。因此，本研究運用大數據的分析，對流浪動物認領養率制定認領養風險指標。再者假設未來實施零安樂死政策成功，制定收容所所內死亡率風險指標，根據無認領養風險與無所內死亡風險之縣市制定收容可靠度指標。並對流浪犬與家庭飼養犬之比率進行分析，以調查目前我國收容所的收容狀況對未來實施零安樂死之條件差距是否需要改善。 Big Data are generated from a variety of sources having different representation forms and formats, it raises are search question as how important data relevant to a business context can be captured and analyzed more accurately to represent deep and relevant business insight. According to the zero euthanasia policy of stray animals in Taiwan in February 2017, no stray animals will be accepted for euthanasia after 12 days of announcement. Therefore, it is worth considering how many shelters with limited space can be safely enforced. In this study, the big data analysis will be used, and the risk indicators for stray animals will be defined. In the study, assuming that future zero euthanasia policies would be successful; hence, the deaths risk indicator within the shelter would be developed. According to the risk of no adoption and no risk of death within the county, the receiving reliability index is defined. Finally, the status of shelters in Taiwan is investigated to ascertain whether there is a need to improve the conditional gap in the future implementation of zero euthanasia.

Big Data are generated from a variety of sources having different representation forms and formats, it raises are search question as how important data relevant to a business context can be captured and analyzed more accurately to represent deep and relevant business insight. According to the zero euthanasia policy of stray animals in Taiwan in February 2017, no stray animals will be accepted for euthanasia after 12 days of announcement. Therefore, it is worth considering how many shelters with limited space can be safely enforced. In this study, the big data analysis will be used, and the risk indicators for stray animals will be defined. In the study, assuming that future zero euthanasia policies would be successful; hence, the deaths risk indicator within the shelter would be developed. According to the risk of no adoption and no risk of death within the county, the receiving reliability index is defined. Finally, the status of shelters in Taiwan is investigated to ascertain whether there is a need to improve the conditional gap in the future implementation of zero euthanasia.