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應用資料採礦技術於電影市場研究 / Application of Data Mining Techniques to Film Market Research

就當前電影市場的現況來看,電影發行成本的節節升高,顧客需求的複雜多變,再加上電影消費集中化趨勢越趨明顯的事實,不論是從電影發行公司或是電影映演事業的角度來看,如何透過對於市場顧客需求、行為的解讀,清楚分隔市場,並為不同市場區隔設計不同的產品及行銷組合已經成了電影工業刻不容緩的課題。
有鑑於此,本研究透過應用資料採礦之技術,選用四個決策樹(C&RT、QUEST、CHAID、C5.0)、邏輯斯迴歸以及類神經網路等方式進行模型建置,由於決策樹CHAID對於「是否去電影院看外片或國片」及「是否去電影院看電影」兩種不同的目標變數,其不論是在整體預測正確率、準確度、反查率,皆是高於其他模型,故最後兩個目標變數皆選擇CHAID此一模型,而目標變數為「是否去電影院看電影」之CHAID模型表現也較好,故主要以其結果為主。
透過目標變數為「是否去電影院看電影」之CHAID模型,共獲得十三項影響「是否去電影院看電影」之相關變數,並根據分析結果,將電影市場顧客區分為最高貢獻顧客、一般貢獻顧客及低度貢獻顧客三類,將其歸納出並找出三種不同貢獻程度的顧客族群特性,而三種不同貢獻族群在「年齡」、「教育程度」、「娛樂文化支出」、「居住地區」、「是否上網瀏覽資訊網頁」、「是否上網蒐集資訊」、「是否會收看電視外片」、「是否看電視歐美影集」、「是否會說英文」、「是否上網線上觀賞影片」、「經濟富裕」、「即時行樂」均呈現顯著的差異,故本研究以不同貢獻程度族群特性為主,以看外片或國片之族群特性為輔,作為行銷策略建議之依據。 / Considering the current film market, the publication cost of a film is steadily increased. Meanwhile, customers have complicated requirements, and the trend of concentrated film consumption is gradually clear. For the perspective of both film companies and film broadcasting business, clear market segmentation after understanding customers’ needs and interpretation of customer behaviors to design different products and marketing combination for different markets are of great urgency for the general film industry.
In view of this, the study aims to using four Decision Trees(C&RT, QUEST, CHAID, C5.0), Logistic Regression, and Artificial Neural Network to construct the model by applying Data Mining technology. Since Decision Tree-CHAID is excellent in the forecast accuracy, precision, and recall rate as compared to other models for response variables of going to the movies and going to foreign movies or Taiwan movies, the CHAID is adopted in this research for both response variables. The CHAID is more excellent for the response variable of going to the movies than the other, so use it as the main result.
Through using Decision Tree-CHAID, this study identified thirteen factors that have greater impact on going to the movies. Based on the analysis results, this study induced the characteristics of three customer groups-the highest contribution customers, regular contribution customers and low contribution customers. Three different contribution groups shows significant differences at age, education, entertainment expenditure, living area, internet surfing, collecting information from internet, watch foreign movies, watch foreign drama, speak English, watch on-lines movies, affluent, and seize the day. This study mainly based on the characteristics of the three different groups, and group characteristic of going to foreign movies or Taiwan movies as auxiliary, to provide the marketing portfolio strategy recommendations.

Identiferoai:union.ndltd.org:CHENGCHI/G0097354016
Creators蔡依庭, Tsai, Yi-Ting
Publisher國立政治大學
Source SetsNational Chengchi University Libraries
Language中文
Detected LanguageEnglish
Typetext
RightsCopyright © nccu library on behalf of the copyright holders

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