서브메뉴
검색
Essays on the Digital Transformation of Retail Grocery Industry- [electronic resource]
![Essays on the Digital Transformation of Retail Grocery Industry - [electronic resource]](/Users/Baul/Images/book.png)
Essays on the Digital Transformation of Retail Grocery Industry- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214101235
- ISBN
- 9798379908959
- DDC
- 343.072
- 저자명
- Yang, Zhou.
- 서명/저자
- Essays on the Digital Transformation of Retail Grocery Industry - [electronic resource]
- 발행사항
- [S.l.]: : University of Washington., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(133 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-01, Section: A.
- 주기사항
- Advisor: Takahashi, Yuya.
- 학위논문주기
- Thesis (Ph.D.)--University of Washington, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약This dissertation looks at the profound impact of digital transformation in the grocery retail industry. It specifically focuses on the competitive repercussions of Amazon's foray into the grocery market, the effects of its Fulfillment Centers (FCs) on local labor markets, and the integration of image and text information from digital sellers into demand estimation. Spanning three interconnected chapters, the research presents a comprehensive examination of the ongoing shifts revolutionizing the retail landscape. Chapter 1 probes the entry of Amazon Fresh and its ensuing effects on local grocery stores. An intricate analysis of quarterly grocery scanner data, combined with Amazon Fresh's entry information, reveals intriguing dynamics of retail competition. Interestingly, Amazon Fresh's debut prompts a significant negative volume response and a slight positive price response from incumbent grocery stores, specifically within the juice products category. The competition extends beyond mere volume and price adjustments, revealing that incumbent stores expand their product assortments and enhance service quality to differentiate from digital retailers. This nuanced understanding of the competitive entry effect sheds light on the strategic responses of traditional brick-and-mortar stores to digital competition in a rapidly evolving marketplace.Chapter 2 broadens the scope to the county level, examining the impacts of Amazon FCs on local labor markets. Employing robust econometric methods, this chapter unveils that while FCs stimulate higher wages, they also seemingly contribute to a reduction in the overall retail workforce. Additionally, the analysis notes a decrease in juice sales volume and inconsistent price changes across the county. These findings hint at a complex interplay between labor market changes, retail market adjustments, and the ongoing digital transformation.Chapter 3 offers a comprehensive exploration of the integration of deep learning-derived features into traditional demand estimation methodologies. A comparison of econometric models with machine learning models using juice product data illuminates the efficacy of different techniques in capturing diverse product characteristics. The study further explores advanced methods like double machine learning and convolutional neural networks to address challenges inherent in high-dimensional and sparse data. Notably, we successfully incorporate deep learning into traditional demand estimation, demonstrating a substantial improvement in model performance, particularly in neural networks. This work not only enhances the representation of product features but also bolsters the models' capacity to accurately capture underlying demand dynamics.
- 기타저자
- University of Washington Economics
- 기본자료저록
- Dissertations Abstracts International. 85-01A.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008240612s2023 us |||||||||||||||c||eng d■001000016933344
■00520240214101235
■006m o d
■007cr#unu||||||||
■020 ▼a9798379908959
■035 ▼a(MiAaPQ)AAI30527898
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a343.072
■1001 ▼aYang, Zhou.
■24510▼aEssays on the Digital Transformation of Retail Grocery Industry▼h[electronic resource]
■260 ▼a[S.l.]:▼bUniversity of Washington. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(133 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-01, Section: A.
■500 ▼aAdvisor: Takahashi, Yuya.
■5021 ▼aThesis (Ph.D.)--University of Washington, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aThis dissertation looks at the profound impact of digital transformation in the grocery retail industry. It specifically focuses on the competitive repercussions of Amazon's foray into the grocery market, the effects of its Fulfillment Centers (FCs) on local labor markets, and the integration of image and text information from digital sellers into demand estimation. Spanning three interconnected chapters, the research presents a comprehensive examination of the ongoing shifts revolutionizing the retail landscape. Chapter 1 probes the entry of Amazon Fresh and its ensuing effects on local grocery stores. An intricate analysis of quarterly grocery scanner data, combined with Amazon Fresh's entry information, reveals intriguing dynamics of retail competition. Interestingly, Amazon Fresh's debut prompts a significant negative volume response and a slight positive price response from incumbent grocery stores, specifically within the juice products category. The competition extends beyond mere volume and price adjustments, revealing that incumbent stores expand their product assortments and enhance service quality to differentiate from digital retailers. This nuanced understanding of the competitive entry effect sheds light on the strategic responses of traditional brick-and-mortar stores to digital competition in a rapidly evolving marketplace.Chapter 2 broadens the scope to the county level, examining the impacts of Amazon FCs on local labor markets. Employing robust econometric methods, this chapter unveils that while FCs stimulate higher wages, they also seemingly contribute to a reduction in the overall retail workforce. Additionally, the analysis notes a decrease in juice sales volume and inconsistent price changes across the county. These findings hint at a complex interplay between labor market changes, retail market adjustments, and the ongoing digital transformation.Chapter 3 offers a comprehensive exploration of the integration of deep learning-derived features into traditional demand estimation methodologies. A comparison of econometric models with machine learning models using juice product data illuminates the efficacy of different techniques in capturing diverse product characteristics. The study further explores advanced methods like double machine learning and convolutional neural networks to address challenges inherent in high-dimensional and sparse data. Notably, we successfully incorporate deep learning into traditional demand estimation, demonstrating a substantial improvement in model performance, particularly in neural networks. This work not only enhances the representation of product features but also bolsters the models' capacity to accurately capture underlying demand dynamics.
■590 ▼aSchool code: 0250.
■653 ▼aCompetitive effect
■653 ▼aDemand estimation
■653 ▼aDigital grocery retail
■653 ▼aDigital transformation
■653 ▼aFulfillment Centers
■690 ▼a0501
■690 ▼a0338
■690 ▼a0505
■71020▼aUniversity of Washington▼bEconomics.
■7730 ▼tDissertations Abstracts International▼g85-01A.
■773 ▼tDissertation Abstract International
■790 ▼a0250
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16933344▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
