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研究生:康成安
研究生(外文):Cheng-An Kang
論文名稱:線上機能性產品銷售的影響因子:以亞馬遜上的運動用品為例
論文名稱(外文):Factors affecting online sales of functional products: Taking sport goods on Amazon.com as an example
指導教授:孔令傑孔令傑引用關係
指導教授(外文):Ling-Chieh Kung
口試委員:陳聿宏林真如
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:企業管理碩士專班
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:英文
論文頁數:45
中文關鍵詞:電子商務機能性產品銷售量迴歸
外文關鍵詞:e-commercefunctional goodssales outcomeregression
DOI:10.6342/NTU202000347
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The ability of using data from daily operations and transactions to understanding customer behavior can provide valuable information to sellers in the e-commerce industry. To recognize which factors may have influence on the sales outcome of functional products in the e-commerce industry, in this study we conduct research based on linear regression on three sport goods. The data we use are collected from company-T, a sport good provider on Amazon.com. According to previous literature and marketing reports, we propose five hypotheses regarding factors that may have impact on the sales outcome.
Across all three products, we find two of our hypotheses are fully supported. In particular, the sales outcome is higher when more customers click on the product page, and sales quantity is lower in weekends than in weekdays. For the other three hypotheses, they are partially supported by part of the three products. First, the more reviews made by customers, the higher sales for some products but the opposite for the other. Second, the influence from the prices of similar products made by competitors are positive for some products but negative for the others. Lastly, our results suggest that the sales outcome tends to be better in weeks before holidays. Our findings may help e-commerce sellers determine their selling and marketing strategy.
Abstract i
Chapter 1 Introduction 1
1.1 Background and motivation 1
1.2 Research objectives 3
1.3 Research plan 4
Chapter 2 Literature Review 5
2.1 User-generated reviews 5
2.2 Sales promotion 7
2.3 Holiday and weekend effects 8
Chapter 3 Hypotheses and Research Method 11
3.1 Hypotheses 11
3.2 Data Source 14
3.3 Data description 15
Chapter 4 Analysis 20
4.1 Exploratory data analysis 20
4.2 Model Building 29
4.3 Model Interpretation 36
Chapter 5 Conclusions and Future Directions 42
5.1 Conclusions 42
5.2 Future directions 43
Bibliography 44
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Young, J., (2019). Global ecommerce sales to reach nearly $3.46 trillion in 2019. Digital Commerce 360. Retrieved on January 9, https://www.digitalcommerce360.com- /article/global-ecommerce-sales/
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