| 研究生: |
郭律旻 Lu-Min Kuo |
|---|---|
| 論文名稱: |
外送平台演算法對外送員行為影響之研究 A Study on the Influence of Delivery Platform Algorithms on the Behavior of Delivery Couriers |
| 指導教授: |
陳炫碩
Shiuann-Shuoh Chen |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 企業管理學系 Department of Business Administration |
| 論文出版年: | 2023 |
| 畢業學年度: | 111 |
| 語文別: | 中文 |
| 論文頁數: | 56 |
| 中文關鍵詞: | 外送平台演算法 、工作自主性 、工作不確定性 、工作歸屬感 、外送員行為 、實證研究 |
| 外文關鍵詞: | food delivery platform algorithms, job autonomy, job uncertainty, job belongingness, delivery driver behavior, empirical research |
| 相關次數: | 點閱:15 下載:0 |
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本研究旨在探討外送平台演算法對外送員行為的影響。在新冠疫情下,線上外送平台的使用頻率大幅增加,成為人們獲取商品和服務的重要途徑。本研究動機在於瞭解在疫情期間,外送員對平台演算法的認知對其工作自主性、工作不確定性和工作歸屬感的影響,並探討這些變化對他們的類市場行為和類組織行為的影響。研究方法將採用實證研究,根據 Möhlmann 等人(2021)的研究框架,研究外送員對演算法管理的角色認知與其行為和體驗之間的關係。本研究的目的是獲得關於外送員、演算法和外送市場變化的重要洞察,並深入了解演算法管理對勞動者行為和體驗在數字化零工經濟中的影響。研究結果將有助於深入了解外送員與線上勞動平台之間的關係,並為政策制定者和平台經營者提供有價值的參考,以改善外送員的工作環境和經濟福祉。
本文的組織結構包括演算法管理的文獻回顧、基於研究框架的研究設計和方法、實證研究的分析和討論結果,以及結論部分。
This study aims to explore the impact of algorithms used in food delivery platforms on the behavior of delivery drivers. With the outbreak of the COVID-19 pandemic, the frequency
of online food delivery platforms has significantly increased, becoming an important channel for people to obtain goods and services. The motivation behind this research is to understand how delivery drivers perceive platform algorithms during the pandemic and how this
perception affects their job autonomy, job uncertainty, and job belongingness, as well as their market and organizational behavior. The research will employ empirical methods and build upon the framework proposed by Möhlmann et al. (2021) to examine the relationship between
delivery drivers' perception of algorithmic management and their behavior and experiences.
The study aims to provide valuable insights into delivery drivers, algorithms, and changes in the food delivery market, as well as a deeper understanding of the impact of
algorithmic management on worker behavior and experiences in the digital gig economy. The findings of this research will contribute to a better understanding of the relationship between delivery drivers and online labor platforms and provide valuable references for policymakers and platform operators to improve the working environment and economic well-being of delivery drivers. The structure of this paper includes a literature review on algorithmic management, research design and methodology based on the proposed framework, analysis and discussion of empirical research results, and concluding remarks.
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