簡易檢索 / 詳目顯示

研究生: 郭庭伃
Ting-Yu Kuo
論文名稱: 消費者觀點的零售議題 – 新零售中的價值驅動因素
Retail Issues in the Perspectives of Consumer – Value Drivers in New Retail
指導教授: 何秀青
Mei HC Ho
口試委員: 劉顯仲
John S. Liu
王孔政
Kung-Jeng Wang
學位類別: 碩士
Master
系所名稱: 管理學院 - 科技管理研究所
Graduate Institute of Technology Management
論文出版年: 2023
畢業學年度: 111
語文別: 中文
論文頁數: 82
中文關鍵詞: 新零售消費價值價值驅動因素TF-IDF共現詞分析線性迴歸分析
外文關鍵詞: new retail, value drivers, linear regression analysis, tf-idf, co-occurrence, word analysis
相關次數: 點閱:395下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 新零售時代,智能裝置、互聯網技術為消費者帶來多樣的體驗,全通路零售被認為 是將無數接觸點和通路完全融合,實現最佳的品牌客戶體驗。科技的注入持續創新產業 商業模式,然而快速的變動也讓零售營運的價值鏈發生轉變,包括:品牌、生產、物流、 客服服務。當企業積極投入資源期望提升服務的價值的同時,在多樣的服務模式中,究 竟何種形式能夠有效的將服務的價值傳達給消費者?又企業可以如何切合消費者需求, 設計、管理、整合跨通路的功能,引起本研究的關注。若能夠以消費者的視角,探究消 費者觀點下的主題發展,及影響消費者消費價值的要素,將能夠協助企業在有限的資源 下,制定適切的營運策略。
    為了從消費者的視角探索消費價值,本研究自美國前 16 大社群論壇 Reddit 蒐集自 2020 年至 2022 年間 5568 篇社群上與科技技術、零售購物、體驗相關的貼文及評論,以 文字探勘為基礎,分析社群論壇中的關於消費者討論的零售議題,藉以了解消費者是以 何種觀點關注這些零售議題?更進一步以迴歸分析,觀察消費者在文章中對於價值的展 現,以量化模型分析在零售環境中,存在哪些因素影響消費價值的的展現?
    本研究透過共現網絡分析發現論壇中與零售相關的 4 個主要發展議題:科技技術 整合、後勤服務與混合零售、消費者動機與感知、科技產品特性,並從網絡的結構特徵, 探究主題發展樣態。在量化迴歸分析中,自科技、企業、消費者三構面皆發現影響消費 者價值展現的因素, 其中包含平台購物、線上品牌、消費者行為面向(消費者情境因素、 動機、收入)。這些因素在零售環境中,扮演重要角色,能夠有效傳達並驅動消費者消費 價值。同時亦發現在通路互動與整合及虛擬科技干擾變數涉入程度的高低差異下,影響 消費價值的因素也隨情境的不同而產生差異。高涉入程度的貼文重視技術的功能性,而 低涉入程度貼文則更關注於消費者自身條件。企業透過科技技術升級體驗時,亦仍須以 消費者自身動機為出發點,強化價值傳遞,採用雙軌並行的方式,喚起消費者對消費價 值的認同。


    In the new retail era, smart devices and the internet bring consumers a variety of experiences. The infusion of technology continues to build innovative business model in retail industry, but the rapid changes also influence the value chains of retail operations, including branding, production, logistics, and customer service. Companies invest resources actively for enhancing the value of services, however, there still leaves lots of room to explore how certain designs, in terms of new technology, business operation can effectively deliver values to consumers? And how personal factors is important in value perception?
    In order to explore the perceived value from consumer’s view, we collected posts and comments related to retail in the community from the top 16 forums in the United States in Reddit. Covering the time from 2020 to 2022, we totally have 5,568 records. By applying text mining, we analyze the main themes existing in online forums. Furthermore, we use regression analysis for observing the critical factors on consumers' value feedback.
    This study has some findings after text analysis and empirical tests. First, we identify four major retail themes in the forum: Technology Integration, Logistics and Hybrid Retailing, Consumer Motivation and Perception, and Technological Product Characteristics. Secondly, the regression analysis model shows that consumer value expression is influenced by the technological factor (platform design), business (online branding) and consumer personal factors (consumer contextual factors, motivation, and income). We also found out that the factors influencing consumer value vary in different post context, e.g., the level of involvement of channel interaction and integration and virtual technology interference. High-involvement posts focus on the functionality of the technology, while low-involvement posts focus more on the consumer's own conditions. We suggest the companies should formulate appropriate promotion plans according to different product attributes for rational and emotional consumers to evoke consumers' recognition of consumer value.

    目錄 摘要 …………………………………………………………………………..I Abstract ........................................................................ II 目錄 ............................................................................... III 圖目錄 .............................................................................V 表目錄 .............................................................................VI 1 壹、緒論........................................................................1 1.1 研究背景 ……………………………………………………………………………..1 1 .2研究問題 ................................................................................. 3 2 貳、文獻回顧...................................................................4 2.1零售的演變進程 ........................................................................ 4 2.2新零售趨勢 ............................................................................... 7 2.2.1科技注入新元素 ...................................................................... 7 2.2.2價值鏈轉變 — 企業營運挑戰.....................................................8 2.2.3驅動消費者的感知價值 ........................................................... 11 2.3文字探勘應用 ............................................................................ 14 3 參、研究方法.....................................................................16 3.1資料搜集與前置處理 ....................................................................17 3.2資料前處理 ……………………………………………………………………………..19 3.3Term Frequency - Inverse Document Frequency (TF-IDF) .........20 3.3.1計算關鍵字重要性分數矩陣 .......................................................20 3.3.2關鍵字挑選 .............................................................................. 22 3.4因素分析 …………………………………………………………………………………24 3.5迴歸分析 …………………………………………………………………………………26 3.6 K-means 集群演算法(K-meansClustering)..................................28 3.7共現詞分析(Co-occurrence Analysis) ........................................ 29 4 肆、研究結果......................................................................31 4.1探索性因素分析 ............................................................................31 4.1.1KMO 與Bartlett 球型檢定............................................................31 4.1.2變數操作說明與意涵 ..................................................................34 4.2探討零售議題網絡的發展特性 ......................................................38 4.2.1科技技術整合 ............................................................................40 4.2.2後勤服務與混合零售 ..................................................................43 4.2.3消費者動機與感知 .....................................................................45 4.2.4科技產品特性 ............................................................................47 4.2.5議題統整 ....................................................................................50 4.3消費價值的影響因素 ..................................................................... 53 4.3.1模型結果 .....................................................................................54 4.3.2內容分析與應用 ..........................................................................55 4.4通路互動整合對於消費價值因素的干擾 ......................................... 60 4.4.1模型結果 .....................................................................................60 4.4.2內容分析與應用 ...........................................................................62 4.5虛擬科技對於消費價值的干擾 ........................................................65 4.5.1模型結果 .....................................................................................65 4.5.2內容分析與應用 ........................................................................... 66 4.6小結: .............................................................................................. 71 伍、結論................................................................................72 5.1社群論壇之零售議題發展樣態 ......................................................... 72 5.2零售環境中影響消費價值的因素 ..................................................... 73 5.3研究限制與未來建議 .......................................................................76 6 附錄....................................................................................80

    吳清麟;王玉珍;李宜玫. (2019). 青少年優勢力量表之發展研究. 教育心理學報, 50(3). 林頌堅. (2010). 以詞語共現網絡分析探勘資訊傳播學領域的研究主題與關係. 圖書資訊
    學研究, 4(2), 123-148.
    許淑珮. (2018). 正在起飛的無人經濟革命. 工業技術與資訊月刊.
    awoo. (2022). https://awoo.ai/zh-hant/blog/omo-amazon/
    Azure. (2022). 文字分析.
    Beck, N., & Rygl, D. (2015). Categorization of multiple channel retailing in Multi-, Cross-, and
    Omni-Channel Retailing for retailers and retailing. Journal of Retailing and Consumer
    Services, 27, 170-178.
    Cao, L. (2014). Business model transformation in moving to a cross-channel retail strategy: A
    case study. International Journal of Electronic Commerce, 18(4), 69-96.
    Carlson, J., O’Cass, A., & Ahrholdt, D. (2015). Assessing customers’ perceived value of the
    online channel of multichannel retailers: A two country examination. Journal of
    Retailing and Consumer Services, 27, 90-102. Fortune. (2021). Fortune 500
    . https://fortune.com/fortune500/
    Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social networks,
    1(3), 215-239.
    Gawer, A., & Cusumano, M. A. (2014). Industry platforms and ecosystem innovation. Journal
    of product innovation management, 31(3), 417-433.
    Gupta, V., & Lehal, G. S. (2009). A survey of text mining techniques and applications. Journal
    of emerging technologies in web intelligence, 1(1), 60-76.
    Hair, J. F. (2009). Multivariate data analysis.
    Hartnett, M. (1998). Shopper needs must be priority. Discount Store News, 37(9), 21-22. Huré, E., Picot-Coupey, K., & Ackermann, C.-L. (2017). Understanding omni-channel shopping
    value: A mixed-method study. Journal of Retailing and Consumer Services, 39, 314-
    330.
    IBM. (2020). 打造智慧供應鏈,應對瞬息萬變的世界. 商業值研究院.
    Kaiser, M. (1974). Kaiser-Meyer-Olkin measure for identity correlation matrix. Journal of the
    Royal Statistical Society, 52(1), 296-298.
    Kim, S., Lim, H.-W., & Chung, S.-Y. (2022). How South Korean Internet users experienced the
    impacts of the COVID-19 pandemic: discourse on Instagram. Humanities and Social
    Sciences Communications, 9(1), 75. https://doi.org/10.1057/s41599-022-01087-7 Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the
    customer journey. Journal of Marketing, 80(6), 69-96.
    Lin, H.-H. (2012). The effect of multi-channel service quality on mobile customer loyalty in an
    online-and-mobile retail context. The Service Industries Journal, 32(11), 1865-1882. 78
    Mathwick, C., Malhotra, N., & Rigdon, E. (2001). Experiential value: conceptualization, measurement and application in the catalog and Internet shopping environment☆. Journal of Retailing, 77(1), 39-56.
    MoreThanDigital. (2020). 多渠道與全渠道. https://morethandigital.info/zh- hans/duoqudaoquanqudaohuogexinghua-nashishenme/
    Neslin, S. A., Grewal, D., Leghorn, R., Shankar, V., Teerling, M. L., Thomas, J. S., & Verhoef, P. C. (2006). Challenges and opportunities in multichannel customer management. Journal of Service Research, 9(2), 95-112.
    Pine, B. J., Pine, J., & Gilmore, J. H. (1999). The experience economy: work is theatre & every business a stage. Harvard Business Press.
    Piotrowicz, W., & Cuthbertson, R. (2014). Introduction to the Special Issue Information Technology in Retail: Toward Omnichannel Retailing. International Journal of Electronic Commerce, 18(4), 5-16. https://doi.org/10.2753/jec1086-4415180400
    Porter, M. E. (2001). The value chain and competitive advantage. Understanding business processes, 2, 50-66.
    Puccinelli, N. M., Goodstein, R. C., Grewal, D., Price, R., Raghubir, P., & Stewart, D. (2009). Customer experience management in retailing: understanding the buying process. Journal of Retailing, 85(1), 15-30.
    Rigby, D. (2011). The future of shopping. Harvard business review, 89(12), 65-76. Schechter, L. (1984). A normative conception of value. Progressive Grocer, executive report,
    2, 12-14.
    Statista. (2022). Retail e-commerce sales worldwide from 2014 to 2025.
    Suh, A., & Prophet, J. (2018). The state of immersive technology research: A literature
    analysis. Computers in Human Behavior, 86, 77-90.
    Teso, E., Olmedilla, M., Martínez-Torres, M., & Toral, S. (2018). Application of text mining
    techniques to the analysis of discourse in eWOM communications from a gender
    perspective. Technological Forecasting and Social Change, 129, 131-142.
    TIBC. (2016). 文字分析是什麼?
    .
    Tolman, E. C. (1938). The determiners of behavior at a choice point. Psychological Review,
    45(1), 1.
    van Esch, P., Arli, D., Gheshlaghi, M. H., Andonopoulos, V., von der Heidt, T., & Northey, G.
    (2019). Anthropomorphism and augmented reality in the retail environment. Journal
    of Retailing and Consumer Services, 49, 35-42.
    Vantrappen, H. (1992). Creating customer value by streamlining business processes. Long
    Range Planning, 25(1), 53-62.
    Verhoef, P. C., Kannan, P. K., & Inman, J. J. (2015). From multi-channel retailing to omni- channel retailing: introduction to the special issue on multi-channel retailing. Journal of Retailing, 91(2), 174-181.
    Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Waytz, A., Heafner, J., & Epley, N. (2014). The mind in the machine: Anthropomorphism
    increases trust in an autonomous vehicle. Journal of Experimental Social Psychology,
    52, 113-117.
    Wollenburg, J., Hübner, A., Kuhn, H., & Trautrims, A. (2018). From bricks-and-mortar to
    bricks-and-clicks: Logistics networks in omni-channel grocery retailing. International
    Journal of Physical Distribution & Logistics Management.
    Wu, W. (2021). 一站式、個人化、結合 AI,未來電商必備的精準行銷平台 Bluecore 獲破
    億注資晉升獨角獸!. Meet 創業小聚.
    Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end
    model and synthesis of evidence. Journal of Marketing, 52(3), 2-22.

    無法下載圖示 全文公開日期 2025/01/17 (校內網路)
    全文公開日期 2025/01/17 (校外網路)
    全文公開日期 2025/01/17 (國家圖書館:臺灣博碩士論文系統)
    QR CODE