臺灣博碩士論文加值系統

隨著生活水準的提高，購物享樂成為新興休閒活動。而電子商務的快速發展使得消費者常常會在網路上購買商品，所以購物中心必須提供獨特的購物價值，例如，提高實體購物經驗的樂趣或增加新的設施與服務來吸引顧客上門消費。分析過去有關購物經驗滿意度的文獻，大多數是使用統計的方法來做分析且屬於預測分析，並無法真正地瞭解消費者的購物體驗滿意度。因此，本計畫回顧過去有關提升消費者購物經驗滿意度的文章，彙整出購物中心關鍵評估屬性如舒適性、娛樂性、多樣性、購物中心特質、便利性、空間設計等六個準則(構面)及消費者行為模式(如:購買頻率、消費支出金額等)，並據此設計問卷，調查消費者對購物中心的評價與心中價值感受。研究方法採用決策樹分析消費者對於購物中心偏好因素的優先順序，再結合資料探勘探討顧客再回購頻率。

Taiwan as living standards improve, shopping pleasure become a new leisure activities. In addition, The rapid development of e-commerce consumers often buy goods on the Internet, shopping mall must provide a unique shopping value, for example, adding new facilities to attract customers and improve the shopping experience fun. Past shopping experience satisfaction (SES) articles, mostly to do analysis using statistical methods, but most of them belong to predictive analysis. These studies cannot really understand shopper satisfaction with the shopping experience. Therefore, this plan through review past literature about how to maximize SES level of problem and finishing out mall key assessment properties as comfortable, entertaining, diversity, mall traits, convenience, and space design, six criteria and the buyer who behavior mode (e.g. purchased frequency, and consumption spending amount) design a suitable questionnaire to know the mall’s position in the mind of consumers. Then, data mining technique to analyzing repurchase intention with decision tree(DS) analysis are used to solve this problem. The contribution of this plan is that DS models are used to find the factor of repurchase intention in shopping satisfaction. Finally, the results obtained by the actual data provide shopping center as business references.

指導教授推薦書
口試委員會審定書
致謝 iii
中文摘要 iv
英文摘要 v
目錄 vi
圖目錄 ix
表目錄 x
第一章 緒論 - 1 -
1.1 研究背景與動機 - 1 -
1.2 研究目的 - 2 -
1.3 研究流程 - 3 -
1.4 研究貢獻 - 4 -
第二章 文獻探討 - 6 -
2.1購物經驗滿意度 - 6 -
2.2決策樹 - 7 -
2.2.1決策樹理論概述 - 8 -
2.2.2決策樹生長 - 9 -
2.2.3決策樹修剪 - 10 -
2.3資料探勘 - 12 -
2.3.1資料探勘定義 - 12 -
2.4本章小結 - 13 -
第三章 研究方法 - 15 -
3.1問卷設計 - 15 -
3.2 研究對象 - 17 -
3.3資料分析工具 - 17 -
3.4決策樹 - 17 -
第四章 研究結果 - 21 -
4.1資料前處理 - 21 -
4.2問卷受測者資料描述 - 21 -
4.3問卷信度分析 - 25 -
4.4決策樹分析結果 - 26 -
第五章 管理意涵與建議 - 32 -
5.1 管理意涵 - 32 -
5.1.1 構面決策樹對於顧客光顧頻率之關聯 - 33 -
5.1.2 題項決策樹對於顧客光顧頻率的影響 - 33 -
5.2 管理建議 - 34 -
5.2.1 構面決策樹對於顧客光顧頻率之建議 - 34 -
5.2.2 題項決策樹對於顧客光顧頻率之建議 - 35 -
參考文獻 - 37 -
附錄 購物中心滿意度問卷 - 40 -


圖目錄
圖 1-1.研究流程圖 - 4 -
圖 2-1.決策樹示意圖 - 8 -
圖 4-1.構面決策樹 - 29 -
圖 4-2.題項決策樹 - 30 -

表目錄
表 2-1.構面與文獻之關係 - 14 -
表 3-1.問卷構面與題項 - 15 -
表 3-2.決策樹演算法之比較 - 18 -
表 4-1.受測者基本資料 - 22 -
表 4-2.六大構面與27題項敘述性統計 - 22 -
表 4-3.問卷題項平日與假日t檢定結果 - 23 -
表 4-4.問卷構面信度分析 - 26 -
表 4-5.決策樹正確分類率 - 26 -

李永翔，2012。運用資料探勘技術分析熱帶海水表面溫度，國立台灣海洋大學海洋環境資訊學系博士論文。
張淑珍，2005。利用一次性SQL 改良決策樹建立信用卡審核之信用評等，私立東吳大學資訊科學系碩士論文。
溫昆庭，2014。購物中心經營之策略行銷分析以台中X購物中心為例，國立政治大學未出版碩士論文。
蔡佳玲、洪新原、袁繼銓，2011。以決策樹模型探討未開立慢性病連續處方之影響因子，資訊管理學報，第18卷，第4期，139-164。
江羿臻、林正昌，2014。應用決策樹探討中學生學習成就的相關因素，教育心理學報，第45卷，第32期，303-327
零售業大趨勢，2014。世界經理文摘，339,18。
Berry, M. J., & Linoff, G., 1997. Data Mining Techniques: For Marketing Sales, and
Customer Support. New York: John Wiley and Sons Inc.
Björn F., Boris H.T., Takao E., Shane J. S., 2014. Affect versus cognition in the chain from perceived quality to customer loyalty: The roles of product beliefs and experience, Journal of Retailing, 90 (4), pp. 567–586.
Cardozo R. N., 1965. An experimental study of customer effort, expectation, and satisfaction. Journal of Marketing Research, 2, pp. 244–249.
Chezy O. and Itamar S., 2007.The Effect of Stating Expectations on Customer Satisfaction and Shopping Experience, Journal of Marketing Research, 164 (44 ), pp. 164–174.
Chiang W. Y., 2012. To establish online shoppers' markets and rules for dynamic CRM systems: An empirical case study in Taiwan. Internet Research, 22(5), pp. 613-625.
Chidanand A. and Sholom W., 1997.Data mining with decision trees and decision rules, Future Generation Computer Systems, 13, pp. 197-210.
Colak, I., Sagiroglu, S., & Yesilbudak, M., 2012. Data mining and wind power
prediction: A literature review. Renewable Energy, 46(0), pp. 241-247.
Davidow M., 2003.Have You Heard the Word? The Effect of Word of Mouth on Perceived Justice, Satisfaction and Repurchase Intentions Following Complaint Handling. Journal of Consumer Satisfaction, 16(1), pp. 67-80.
Dick, A., & Basu, K., 1994. Customer loyalty: toward an integrated conceptual framework. Journal of the Academy of Marketing Science, 22(2), pp. 99-113.
Dodds, W., & Monroe, K., 1985. The effect of brand and price information on
subjective product evaluations. Advances in Consumer Research, 12(1), pp. 85-90.
Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P., 1996. From Data Mining to Knowledge Discovery in Databases. AI Magazine, 17(3), pp. 37-54.
Grupe, F. H., & Mehdi Owrang, M., 1995. DATA BASE MINING Discovering New Knowledge and Competitive Advantage. Information Systems Management, 12(4), pp. 26-31.
Hedhli K. E., Chebat J. C., Sirgy M. J., 2013. Shopping well-being at the mall: Construct, antecedents, and consequences. Journal of Business Research, 66, pp. 856–863.
Jones, T., & Sasser, W., 1995. Why satisfied customers defect. Harvard Business Review, 73(6), pp. 88.
McCluskey, W., & Anand, S., 1999. The application of intelligent hybrid techniques for the mass appraisal of residential properties. Journal of Property Investment and Finance, 17(3), pp. 218-238.
Michon R. Chebat J. C., Turley L. W., 2005. Mall atmospherics: the interaction effects of the mall environment on shopping behavior. Journal of Business Research, 58, pp. 576–583.
Mohammed I. E., 2007. Shopping malls attractiveness: a segmentation approach. International Journal of Retail & Distribution Management, 35(11), pp. 936–950.
Olmeda, I., & Sheldon, P. J., 2001. Data Mining Techniques and Applications for
Tourism Internet Marketing. Journal of Travel & Tourism Marketing, 11(3), pp. 1-20.
Quinlan, J. R., 1993. C4.5: programs for machine learning, Morgan :Kaufmann Publishers Inc.
Samuel S. K., Dallen J.T., Jinsoo H., 2011. Understanding Japanese tourists’ shopping preferences using the Decision Tree Analysis method. Tourism Managent, 32, pp. 544-554.
Shim S., Eastlick, M. A., 1998. The hierarchical influence of personal values on mall Shopping Attitute and Behavior. Journal of Retailing, 74(1), pp. 139–160.
Stank, T., T. J. , G., S. K., V., & K., S., 2003. Logistics Service Performance:
Estimating its Influence on Market Share. Journal of Business Logistics, 24(1), pp. 27-55.
Stoel L., Wickliffe V., Lee K. H., 2004. Attribute beliefs and spending as antecedents to shopping value. Journal of Business Research, 57, pp. 1067-1073.
Sun P., Cárdenas D.A., Harrill R., 2016. Chinese Customers’ Evaluation of Travel Website Quality: A Decision-Tree Analysis. Journal of Hospitality Marketing and Management, 25(4), pp. 476-497
Thaler, R., 1985. Mental accounting and consumer choice. Marketing Science, 4(3),
pp. 199-214.
Wakefield K. L., Baker J., 1998. Excitement at the mall: determinants and effects on shopping response. Journal of Retailing, 74(4), pp. 515–539.
Wong, A., & A., S., 2003. Service Quality and Customer Loyalty Perspectives on Two Levels of Retail Relationships. Journal of Services Marketing, 17(5), pp. 495-513.
Zeithaml, V., 1988. Consumer perceptions of price, quality, and value: a means-end
model and synthesis of evidence. The Journal of marketing, 52(3), pp. 2-22.