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    題名: 發展適用於產險業產值之灰預測模式
    其他題名: Grey Prediction Models For Property-Liability Insurance Company In Taiwan
    作者: 楊川明
    Yang, Chuan-Ming
    貢獻者: 管理科學研究所
    林水順
    Shui-Shun Lin
    關鍵詞: 產險業;產值;灰預測
    Property insurance industry;Output value;Grey Prediction
    日期: 2004
    上傳時間: 2015-07-02 15:08:40 (UTC+8)
    摘要:   預測是政府運作與企業經營的主要工作之一,透過精確的預測能使得政府的各項功能獲得良好的控制與妥善的規劃;而就企業而言則便於日後之行銷策略、人力配置與財務管理等企業功能之開展。   一個產業產值的多少反應了該產業的景氣好壞,而各項產業產值的總合即代表了國家整體的經濟狀況。就產險業而言,因為其有保障個人財產安全與降低企業營運風險之作用,故其產值的多少對國家社會的發展而言扮演了相當重要的角色,所以做好對產險業產值之預測工作便愈顯其迫切性。   本研究根據灰色理論之方法,利用相關部門之原始數據來建構適合本產業產值之GM(1,N)模型並分析相關之影響因素。其結果顯示以GM(1,1)模型來預測其準確度達96.45%,而以GM(1,N)模型中之GM(1,4)模型來預測可達98.846%之準確度,表示該產業非常適合以此理論來預測,並可獲得精確之預測成果,故本結論應可提供政府及企業做為產值預測之參考依據。
      Forecast is one of the major tasks to both government and business operation. Accurate forecast allows government to have fine control and planning over the functions; to businesses, accurate forecast is beneficial to future marketing strategies, human resource allocation, and financial management.   The output value of one industry reflects the economic status of theindustry. The sum of all output values indicates the economic situation of thecountry on a whole. To the property insurance industry, given its purpose ofindividual asset protection and business risk management, its output value iscrucial to the development of the country. Therefore, accurate forecast on theoutput value of property insurance industry is crucial.   This study, based on Gray Theory, uses the original data of related department to construct GM(1,N) model applicable to the output value andanalyzes related factors. The result shows that the use of GM(1,1) in forecasthas accuracy as high as 96.45%. GM(1,4) model in GM(1,N) used on forecasthas accuracy as high as 98.846%. The result indicates that the industry issuitable for forecast based on Gray Theory for accurate results. Therefore, thestudy results are provided as reference on output value to government and businesses.
    顯示於類別:[企業管理學系(管理科學碩/博士班,非營利事業管理碩士班)] 博碩士論文-管理科學碩博士班

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