| 研究生: |
陳薏祺 Chen, I-Chi |
|---|---|
| 論文名稱: |
以價值接受模型探討外送平台快消品購買意願之影響因素 Exploring the Factors Influencing Purchase Intention of FMCG via Food Delivery Platforms: A VAM-Based Approach |
| 指導教授: |
葉時碩
Yeh, Shih-Shuo 林佑鴻 Lin, You-Hung |
| 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: | 2025 |
| 畢業學年度: | 113 |
| 語文別: | 中文 |
| 論文頁數: | 96 |
| 中文關鍵詞: | 外送服務 、快速消費品 、價值接受模型 、購買衝動感 、消費者行為 |
| 外文關鍵詞: | Food Delivery Services, Fast-Moving Consumer Goods, Value-based Adoption Model, Urge to Buy Impulsively, Consumer Behavior |
| 相關次數: | 點閱:14 下載:0 |
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在數位科技成熟、疫情影響及生活型態轉變等因素推動下,外送服務迅速滲透市場,使用範圍亦由即時餐飲拓展至生鮮雜貨等快消品類。餐點與快消品在時效性、價格敏感度與品牌忠誠度等產品特性上存在差異,影響消費者的消費動機與決策歷程,然而過去研究多聚焦於餐飲外送,較少探討快消品使用情境。對此,本研究回顧探討外送服務與快消品相關文獻,首先將外送平台界定為消費者能夠透過行動應用程式進行操作的第三方外送平台,並以日常用品作為快消品代表類別進行後續探討。接著以價值接受模型(Value-based Adoption Model, VAM)為理論基礎,考量快消品特性進一步發展研究變數,期望藉由跳脫以往研究框架補充研究缺口,並從決策觀點更為精準地捕捉消費者選擇過程中的利弊權衡與行為機制,以提供企業策略規劃、通路佈局與行銷資源配置等方面之參考依據。
本研究採用網路問卷方式針對居住於台灣及離島地區的外送平台用戶收集數據,共回收397份有效問卷,而後以結構方程模型(Structural Equation Modeling, SEM)進行統計分析。研究結果顯示,消費者對透過外送平台購買快消品的感知價值是影響其行為意願的重要因素,而感知利益中的便利性、平台品質與享樂性,以及感知犧牲中的感知費用則透過感知價值對行為意願產生間接影響;此外,享樂性與社會形象皆正向影響消費者購買衝動感。本研究據此提出理論與實務意涵。
With the advancement of digital technology, the impact of the COVID-19 pandemic, and changes in lifestyle, food delivery services have rapidly penetrated the market, extending their offerings from restaurant-prepared meals to groceries and other fast-moving consumer goods (FMCGs). Notably, meals and FMCGs differ significantly in product characteristics such as time sensitivity, price sensitivity, and brand loyalty, which in turn shape consumer motivations and decision-making processes. However, prior research has predominantly focused on meal delivery, with limited exploration of FMCG-related usage contexts. This study reviews relevant literature on food delivery services and FMCGs to define the scope of research and to develop the research framework. To elaborate, food delivery platforms are specified as third-party services that consumers can access and operate via mobile applications, and household goods is selected as a representative category of FMCGs for subsequent analysis. In addition, adopting the Value-based Adoption Model (VAM) as the theoretical foundation, the study incorporates the specific attributes of FMCGs to refine and expand the research variables. By shifting from conventional frameworks, the study aims to bridge existing gaps in the literature. In the meantime, better capture the trade-offs and behavioral mechanisms involved in consumer decision-making, thereby offering practical insights for enterprises developing market strategies. Data were collected through an online questionnaire targeting users of food delivery platforms residing in Taiwan and its outlying islands, yielding 397 valid responses. Statistical analysis was then conducted using Structural Equation Modeling (SEM). The results indicate that perceived value plays a critical role in influencing consumers' intention to purchase FMCGs via food delivery platforms. Convenience, platform quality, enjoyment, and perceived fee have indirect effects on behavioral intention, mediated by perceived value. Furthermore, both enjoyment and social image positively influence consumers’ urge to buy impulsively. Based on these findings, theoretical and practical implications are discussed.
中文文獻
Calling訂房達人(2024年11月21日)。【外送優惠總整理-2024年11月】三大外送平台Uber Eats、foodpanda、Foodomo首購優惠碼/最新優惠/平台比較。https://www.callingtaiwan.com.tw/外送優惠總整理-foodpanda-ubereats/
The News Lens關鍵評論(2023)。2023台灣網路使用報告:95%民眾透過手機上網,八大重點洞察一次看。https://www.thenewslens.com/article/182274
于慧君(2010)。快速消費商品之零售通路演變與影響之先期研究。行銷與流通管理研究報告。
未來流通研究所(2020)。【產業地圖圖解】一張圖看懂2020台灣「餐飲外送平台」產業版圖。https://www.mirai.com.tw/2020-taiwan-food-delivery-industry-competition-map/
未來流通研究所(2022)。【產業地圖圖解】台灣實體零售「快商務」產業地圖。https://www.mirai.com.tw/taiwan-physical-retailing-quick-commerce-analysis/
未來流通研究所(2023)。【商業數據圖解】2022台灣主要零售業別商品結構基因圖譜。https://www.mirai.com.tw/analysis-of-the-2022-retail-industry-commodity-structure-in-taiwan/
林建煌(2019)。消費者行為(六版)。華泰文化事業有限公司。
柯瓊鳳(2017)。「宅經濟」vs.「群經濟」。科技大觀園。https://scitechvista.nat.gov.tw/Article/c000003/detail?ID=c824c491-6b40-4819-b76e-6f0f9d33ec5a
食力(2022)。外送時代來臨!平台使用率近8成 哪四大族群最愛叫外送?外送雙雄誰更受青睞?。https://www.foodnext.net/news/industry/paper/5111695219
張卿卿(2016)。以網路購物為例探討媒介作為娛樂的功能。中華傳播學刊,(9),3-43。
產業情報研究所(2024)。【外送大調查】外送市場邁向M型化 71%網友使用、訂閱成長5% 兩大龍頭差距擴大16% 市場經營策略出現定位區隔。https://mic.iii.org.tw/news.aspx?id=663&List=12
產業情報研究所(2025)。【外送大調查】兩大外送平台常用差距首度少於一成 四成用戶兩者皆用 外送訂閱會員達四成 18-25歲新訂閱戶漲幅最大。https://mic.iii.org.tw/news.aspx?id=706
陳鋆坪(2016)。快速消費品商業模式之探討以食品產業為例。國立臺北科技大學經營管理系碩士論文。
凱度消費者指數(2022)。凱度2022最新民生零售通路排行 電商來勢洶洶消費觸及成長50%。https://www.kantarworldpanel.com/tw/News/2022-H1-retailer-crp-ranking
楊子江(2024)。以財稅資料分析外送服務平臺於餐飲業之影響。財稅研究,53(4),74-108。
蔡翼擎、謝涵聿、呂蕙竹、陳貞錡、施嘉慧、歐德威(2020)。探討台灣餐飲外送平台如何建構競爭優勢之關鍵決策因子。管理資訊計算,9(1), 109-122。
英文文獻
Ahmad, S. A., Mehmood, W., Ahmed, S. A., Mustafa, M., Khan, M. F. T., & Yasmeen, M. (2015). Impact of Sales Promotion on consumer buying behavior in Pakistan. International Interdisciplinary Journal of Scholarly Research, 1(3), 13-22.
Akram, U., Junaid, M., Zafar, A. U., Li, Z., & Fan, M. (2021). Online purchase intention in Chinese social commerce platforms: Being emotional or rational?. Journal of Retailing and Consumer Services, 63, 102669.
Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. International Journal of Information Management, 50, 28-44.
Al-Debei, M. M., Akroush, M. N., & Ashouri, M. I. (2015). Consumer attitudes towards online shopping: The effects of trust, perceived benefits, and perceived web quality. Internet Research, 25(5), 707-733.
Allah Pitchay, A., Ganesan, Y., Zulkifli, N. S., & Khaliq, A. (2022). Determinants of customers' intention to use online food delivery application through smartphone in Malaysia. British Food Journal, 124(3), 732-753.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
Armstrong, G., Kotler, P., & Opresnik, M. O. (2017). Marketing: An Introduction (13th ed.). Pearson Education Limited.
Badgaiyan, A. J., & Verma, A. (2015). Does urge to buy impulsively differ from impulsive buying behaviour? Assessing the impact of situational factors. Journal of Retailing and Consumer Services, 22, 145-157.
Bao, Z., & Zhu, Y. (2022). Why customers have the intention to reuse food delivery apps: evidence from China. British Food Journal, 124(1), 179-196.
Beatty, S. E., & Ferrell, M. E. (1998). Impulse buying: Modeling its precursors. Journal of retailing, 74(2), 169-191.
Beauchamp, M. B., & Ponder, N. (2010). Perceptions of retail convenience for in-store and online shoppers. The Marketing Management Journal, 20(1), 49-65.
Chen, H. S., Liang, C. H., Liao, S. Y., & Kuo, H. Y. (2020). Consumer attitudes and purchase intentions toward food delivery platform services. Sustainability, 12(23), 10177.
Chen, M., Hu, M., & Wang, J. (2022). Food delivery service and restaurant: Friend or foe?. Management Science, 68(9), 6539-6551.
Chen, Z., & Dubinsky, A. J. (2003). A conceptual model of perceived customer value in e‐commerce: A preliminary investigation. Psychology & marketing, 20(4), 323-347.
Chiu, C. M., Wang, E. T., Fang, Y. H., & Huang, H. Y. (2014). Understanding customers' repeat purchase intentions in B2C e‐commerce: the roles of utilitarian value, hedonic value and perceived risk. Information systems journal, 24(1), 85-114.
Chowdhury, R. (2023). Impact of perceived convenience, service quality and security on consumers’ behavioural intention towards online food delivery services: the role of attitude as mediator. SN Business & Economics, 3(1), 29.
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences: Lawrence Erlbaum Associates.
Colby, C., & Bell, K. (2016). The on-demand economy is growing, and not just for the young and wealthy. Harvard Business Review.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
Dawson, S., & Kim, M. (2009). External and internal trigger cues of impulse buying online. Direct Marketing: An International Journal, 3(1), 20-34.
Dazmin, D., & Ho, M. Y. (2019). The relationship between consumers’ price-saving orientation and time-saving orientation towards food delivery intermediaries (FDI) services: an exploratory study. Gsj, 7(2).
DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information systems research, 3(1), 60-95.
Duarte, P., e Silva, S. C., & Ferreira, M. B. (2018). How convenient is it? Delivering online shopping convenience to enhance customer satisfaction and encourage e-WOM. Journal of Retailing and Consumer Services, 44, 161-169.
Eastin, M. S. (2002). Diffusion of e-commerce: an analysis of the adoption of four e-commerce activities. Telematics and informatics, 19(3), 251-267.
Familmaleki, M., Aghighi, A., & Hamidi, K. (2015). Analyzing the influence of sales promotion on customer purchasing behavior. International Journal of Economics & management sciences, 4(4), 1-6.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Gupta, S., & Kim, H. W. (2010). Value‐driven Internet shopping: The mental accounting theory perspective. Psychology & Marketing, 27(1), 13-35.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24.
Hansen, T., Jensen, J. M., & Solgaard, H. S. (2004). Predicting online grocery buying intention: a comparison of the theory of reasoned action and the theory of planned behavior. International Journal of Information Management, 24(6), 539-550.
Hawkes, C. (2009). Sales promotions and food consumption. Nutrition reviews, 67(6), 333-342.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43, 115-135.
Hsu, C. L., & Lin, J. C. C. (2015). What drives purchase intention for paid mobile apps?–An expectation confirmation model with perceived value. Electronic commerce research and applications, 14(1), 46-57.
Hu, B., Liu, Y. L., & Yan, W. (2023). Should I scan my face? The influence of perceived value and trust on Chinese users’ intention to use facial recognition payment. Telematics and Informatics, 78, 101951.
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
Jeong, M., Oh, H., & Gregoire, M. (2003). Conceptualizing web site quality and its consequences in the lodging industry. International Journal of Hospitality Management, 22(2), 161-175.
Jiang, L. A., Yang, Z., & Jun, M. (2013). Measuring consumer perceptions of online shopping convenience. Journal of Service management, 24(2), 191-214.
Kapoor, A. P., & Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps. Journal of retailing and consumer services, 43, 342-351.
Kenton, W. (2024). Fast-Moving Consumer Goods (FMCG) Industry: Definition, Types, and Profitability. Investopedia. https://www.investopedia.com/terms/f/fastmoving-consumer-goods-fmcg.asp
Kim, B., Choi, M., & Han, I. (2009). User behaviors toward mobile data services: The role of perceived fee and prior experience. Expert Systems with Applications, 36(4), 8528-8536.
Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision support systems, 44(2), 544-564.
Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile internet: an empirical investigation. Decision support systems, 43(1), 111-126.
Kim, H. W., Xu, Y., & Gupta, S. (2012). Which is more important in Internet shopping, perceived price or trust?. Electronic commerce research and applications, 11(3), 241-252.
Kumar, S., & Shah, A. (2021). Revisiting food delivery apps during COVID-19 pandemic? Investigating the role of emotions. Journal of Retailing and Consumer Services, 62, 102595.
Lee, C. H., Chen, C. W. D., Huang, S. F., Chang, Y. T., & Demirci, S. (2021). Exploring consumers’ impulse buying behavior on online apparel websites: An empirical investigation on consumer perceptions. International Journal of Electronic Commerce Studies, 12(1), 119-142.
Li, C., Mirosa, M., & Bremer, P. (2020). Review of online food delivery platforms and their impacts on sustainability. Sustainability, 12(14), 5528.
Lin, P. M., Au, W. C. W., & Baum, T. (2024). Service quality of online food delivery mobile application: an examination of the spillover effects of mobile app satisfaction. International journal of contemporary hospitality management, 36(3), 906-926.
McDougall, G. H., & Levesque, T. (2000). Customer satisfaction with services: putting perceived value into the equation. Journal of services marketing, 14(5), 392-410.
Mehrolia, S., Alagarsamy, S., & Solaikutty, V. M. (2021). Customers response to online food delivery services during COVID‐19 outbreak using binary logistic regression. International journal of consumer studies, 45(3), 396-408.
Melati, I., Purwanto, B. M., Caturyani, Y., Olivia Irliane, P., & Widyaningsih, Y. A. (2024). The mediation effect of the urge to buy impulsively on grocery online impulse buying decisions. Cogent Business & Management, 11(1), 2316941.
Mohammadi, H. (2015). Social and individual antecedents of m-learning adoption in Iran. Computers in Human Behavior, 49, 191-207.
Muruganantham, G., & Bhakat, R. S. (2013). A review of impulse buying behavior. International journal of marketing studies, 5(3), 149.
Nunnally, J. C. (1978). Psychometric Theory: 2d Ed. McGraw-Hill.
O’brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & quantity, 41, 673-690.
Parboteeah, D. V., Valacich, J. S., & Wells, J. D. (2009). The influence of website characteristics on a consumer's urge to buy impulsively. Information systems research, 20(1), 60-78.
Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International journal of electronic commerce, 7(3), 101-134.
Pillai, S. G., Kim, W. G., Haldorai, K., & Kim, H. S. (2022). Online food delivery services and consumers' purchase intention: Integration of theory of planned behavior, theory of perceived risk, and the elaboration likelihood model. International journal of hospitality management, 105, 103275.
Schrepp, M. (2020). On the Usage of Cronbach's Alpha to Measure Reliability of UX Scales. Journal of Usability Studies, 15(4).
Seghezzi, A., & Mangiaracina, R. (2021). On-demand food delivery: investigating the economic performances. International journal of retail & distribution management, 49(4), 531-549.
Seiders, K., Berry, L. L., & Gresham, L. G. (2000). Attention, retailers! How convenient is your convenience strategy?. MIT Sloan Management Review, 41(3), 79.
Shankar, A., Jebarajakirthy, C., Nayal, P., Maseeh, H. I., Kumar, A., & Sivapalan, A. (2022). Online food delivery: A systematic synthesis of literature and a framework development. International Journal of Hospitality Management, 104, 103240.
Sheth, J. N., Newman, B. I., & Gross, B. L. (1991). Why we buy what we buy: A theory of consumption values. Journal of business research, 22(2), 159-170.
Shukla, P. (2010). Effects of perceived sacrifice, quality, value, and satisfaction on behavioral intentions in the service environment. Services Marketing Quarterly, 31(4), 466-484.
Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of retailing, 77(2), 203-220.
Tandon, A., Kaur, P., Bhatt, Y., Mäntymäki, M., & Dhir, A. (2021). Why do people purchase from food delivery apps? A consumer value perspective. Journal of Retailing and Consumer Services, 63, 102667.
Taylor, T. A. (2018). On-demand service platforms. Manufacturing & Service Operations Management, 20(4), 704-720.
Troise, C., O'Driscoll, A., Tani, M., & Prisco, A. (2021). Online food delivery services and behavioural intention–a test of an integrated TAM and TPB framework. British food journal, 123(2), 664-683.
Venkatesh, V., Brown, S. A., Maruping, L. M., & Bala, H. (2008). Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS quarterly, 483-502.
Verma, A., Chakraborty, D., & Verma, M. (2023). Barriers of food delivery applications: A perspective from innovation resistance theory using mixed method. Journal of Retailing and Consumer Services, 73, 103369.
Wang, E. S. T., & Chou, N. P. Y. (2016). Examining social influence factors affecting consumer continuous usage intention for mobile social networking applications. International Journal of Mobile Communications, 14(1), 43-55.
Wang, H. Y., & Wang, S. H. (2010). Predicting mobile hotel reservation adoption: Insight from a perceived value standpoint. International Journal of Hospitality Management, 29(4), 598-608.
Wang, J., Shen, X., Huang, X., & Liu, Y. (2021). Influencing factors of the continuous usage intention of consumers of online food delivery platform based on an information system success model. Frontiers in psychology, 12, 716796.
Wang, Y., Wang, H., & Xu, H. (2021). Understanding the experience and meaning of app-based food delivery from a mobility perspective. International Journal of Hospitality Management, 99, 103070.
Wen, H., Pookulangara, S., & Josiam, B. M. (2022). A comprehensive examination of consumers' intentions to use food delivery apps. British Food Journal, 124(5), 1737-1754.
Yen, Y. S. (2023). Channel integration affects usage intention in food delivery platform services: the mediating effect of perceived value. Asia Pacific Journal of Marketing and Logistics, 35(1), 54-73.
Yeo, V. C. S., Goh, S. K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services. Journal of Retailing and Consumer services, 35, 150-162.
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.
Zhao, Y., & Bacao, F. (2020). What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period?. International journal of hospitality management, 91, 102683.
Zheng, X., Men, J., Yang, F., & Gong, X. (2019). Understanding impulse buying in mobile commerce: An investigation into hedonic and utilitarian browsing. International journal of information management, 48, 151-160.