研究生: |
楊昕婷 Yang, Hsin-Ting |
---|---|
論文名稱: |
影響直播串流平台觀眾購買汽車周邊商品關鍵因素 The Key Factors Affecting Audiences' Purchasing Car Peripherals on Live Streaming Platforms |
指導教授: |
李景峰
Li, Jeen-Fong |
口試委員: |
羅乃維
Lo, Nai-Wei 楊嘉麗 Yang, Chia-Lee 李景峰 Li, Jeen-Fong |
口試日期: | 2023/07/21 |
學位類別: |
碩士 Master |
系所名稱: |
工業教育學系 Department of Industrial Education |
論文出版年: | 2023 |
畢業學年度: | 111 |
語文別: | 英文 |
論文頁數: | 139 |
中文關鍵詞: | 直播銷售 、汽車周邊商品 、文字探勘 、偏最小平方結構方程模型 、決策實驗室分析基礎之網路程序分析法 |
英文關鍵詞: | Live-stream sales, Car Peripherals, Partial Least Squares- Equation Modeling (PLS-SEM), Text Mining, The Decision-Making Trial and Evaluation Laboratory (DEMATEL) based analytic network process (DANP) |
研究方法: | 文字探勘 、 偏最小平方結構方程模型 、 決策實驗室分析基礎之網路程序分析法 |
DOI URL: | http://doi.org/10.6345/NTNU202301621 |
論文種類: | 學術論文 |
相關次數: | 點閱:229 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 |
隨著網路行銷日益普及,消費者使用串流平台,於直播中購物的金額大幅攀升。汽車周邊商品具多樣性,能夠滿足各種不同市場區隔中,車主的需求和偏好,並有效提昇汽車的功能性、外觀、安全性或便利性,於部分國家或經濟體串流平台之銷售額日增。雖然汽車周邊商品之商機龐大,且已經擴散至如中國大陸等新興市場之串流平台,但於大部份國家之市場仍然處於萌芽期,因此,行銷相關之議題非常值得關注與研究,唯目前少有學者著墨。因此本研究擬分析消費者透過直播,購買汽車周邊商品的行為模式,並探討影響消費者透過直播購買汽車周邊商品的關鍵因素。
本研究首先爬取與汽車周邊直播銷售相關網頁,並以基於隱含狄利克雷分布 (Latent Dirichlet Allocation,LDA) 之主題模型分析(Topic Modeling),探勘網頁中蘊含之主題;其次,以階層式集群分析法(Hierarchical Cluster Analysis)分群主題後,將各群主題歸入技術接受模式的構面,並以偏最小平方結構方程模型(Partial Least Squares Structural Equation Modeling,PLS-SEM)驗證各路徑顯著與否。除此之外,本研究亦同時邀集專家,以基於決策實驗室分析法(Decision Making Trial and Evaluation Laboratory,DEMATEL)之分析網路流程(DEMATEL based Analytic Network Process,DANP),推衍影響直播串流平台觀眾購買汽車周邊商品之關鍵因素,並比較社群網路探勘與專家意見法兩者結果之差異。
依據實證研究,與購買意願相關係數最高的變數為「推廣效果」,分析網路爬取資料,與專家提供之意見一致,共同認為「推廣效果」為影響消費者透過直播,購買汽車周邊商品之最關鍵要素。本研究之結果,可作為未來制定直播行銷策略之基礎,發展之方法,亦可作為訂定發展其他新興網路媒體策略之用。
As online marketing continues to gain prominence, there has been a marked escalation in the expenditure of consumers on purchases made via live streaming platforms. Automotive peripherals and accessories boast a wide variety, capable of satisfying the diverse needs and preferences of car owners across different market segments. They effectively enhance a vehicle's functionality, aesthetics, safety, and convenience. In some countries or economies, sales figures on streaming platforms for these products are growing daily. While the business opportunity for automotive peripherals and accessories is vast and has expanded to streaming platforms in emerging markets, such as Mainland China, the market in most countries remains in its infancy. Thus, marketing-related topics in this area are very much worth attention and research. However, there's been limited scholarly attention to this subject. This study aims to analyze the behavioral patterns of consumers purchasing automotive peripherals and accessories through live streaming and to delve into the key factors influencing their buying decisions on these platforms.
This study initially crawled web pages related to live streaming sales of automobile peripherals and accessories and employs Topic Modeling based on Latent Dirichlet Allocation (LDA) to mine the underlying themes from these posts. Subsequently, the Hierarchical Cluster Analysis method is used to categorize these themes under the dimensions of the Technology Acceptance Model. The significance of each pathway is then validated using the Partial Least Squares (PLS) Structural Equation Modeling (SEM), or PLS-SEM. In addition, experts are invited to apply the Decision Making Trial and Evaluation Laboratory based Analytic Network Process (DEMATEL-based ANP) to deduce the critical factors affecting the audience's purchase of car peripherals on live streaming platforms. The study further compares the results from social network mining and expert opinion.
Based on empirical research, the variable with the highest correlation to purchase intention is "promotional effectiveness." Analysis of data scraped from the internet, consistent with expert opinions, unanimously points to "promotional effectiveness" as the key determinant influencing consumers to purchase automotive-related products through live streaming. The findings of this study can serve as a foundation for formulating future live streaming marketing strategies. The methodology developed can also be applied to the strategy formulation for other emerging online media platforms.
Ackodrive. (2023, May 28). 25 Essential Car Accessories for a New Car in 2023. Retrieved from https://ackodrive.com/car-guide/car-accessories/
Alonso-González, M. J., Hoogendoorn-Lanser, S., Oort, N.V., Cats, O. (2020). Drivers and Barriers in Adopting Mobility as a Service (MaaS)–A Latent Class Cluster Analysis of Attitudes. Transportation Research, 132, 378-401.
Arghashi, V., Yuksel, C. (2021). Interactivity, Inspiration, and Perceived Usefulness! How retailers' AR-Apps Improve Consumer Engagement Through Flow. Journal of Retailing and Consumer Services, 64, 102-122.
Aruldoss, M., Lakshimi, T.M., Venkatesan, V.P. (2013). A Survey on Multi Criteria Decision Making Methods and Its Applications. American Journal of Information Systems, 1(1), 31-43.
Asshidin, N.H.N., Abidin, N., Borhan, H.B. (2016). Perceived Quality and Emotional Value that Influence Consumer’s Purchase Intention Towards American and Local Products. Procedia Economics and Finance, 36, 639-643.
Bagozzi, R.P., Yi, Y. (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16, 74–94.
Ballhaus, W., Chow, W., Rivet, E. (2022, June 6). Perspectives from the Global Entertainment & Media Outlook 2022–2026. PWC Global, Industries and sectors, Technology, Media & Telecommunications (TMT), Media, Global Entertainment & Media Outlook 2022–2026, Perspectives Report. Retrieved from https://www.pwc.com/gx/en/industries/tmt/media /outlook/outlook-perspectives.html
Basuki, R., Jiwa, Z., Siagian, H. (2022). The Effects of Perceived Ease of Use, Usefulness, Enjoyment and Intention to Use Online Platforms on Behavioral Intention in Online Movie Watching During the Pandemic Era. International Journal of Data and Network Science 6(1), 253-262.
Bhatnagar, V., Duari, S., & Gupta, S. K. (2022). Quantitative Discourse Cohesion Analysis of Scientific Scholarly Texts Using Multilayer Networks. IEEE Access, 10, 88538-88557.
Bruks, M. (1985). The Effects of Product Class Knowledge on Information Search Behavior. Journal of Consumer Research, 12(1), 1-16.
Buhamnn, K.M., Criado, J.R. (2023). Consumers' Preferences for Electric Vehicles: The Role of Status and Reputation. Transportation Research Part D: Transport and Environment, 114(0), 103530.
Chang, H. C. H., Haider, S., & Ferrara, E. (2021). Digital civic participation and misinformation during the 2020 Taiwanese presidential election. Media and Communication, 9(1), 144-157.
Charness, C., Boot, W. R. (2016). Technology, Gaming, and Social Networking. Handbook of the Psychology of Aging, 8(20), 389-407.
Chen, L.Y. (2019). The Effects of Livestream Shopping on Customer Satisfaction and Continuous Purchase Intention. International Journal Computer Science Engineering, 8(4), 1-9.
Chu, K.-M. (2018). Mediating Influences of Attitude on Internal and External Factors Influencing Consumers’ Intention to Purchase Organic Foods in China. Sustainability, 10(12), 2-15.
Cretu, A. E., Brodie, R.J. (2007). The Influence of Brand Image and Company Reputation Where Manufacturers Market to Small Firms: A Customer Value Perspective. Industrial Marketing Management, 36, 230-240.
Davis, F. D. (1989). Perceived Usefulness, Perceive Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 318-340.
Davis, F. D. (1993). User Acceptance of Information Technology: System Characteristics, User Perceptions, and Behavioral Impacts. International Journal of Man-Machine Studies, 1993, 38 (3), 475-487.
Dzuba, S., & Krylov, D. (2021). Cluster Analysis of Financial Strategies of Companies. Mathematics, 9(24), 3192-3213.
Feng, Y., Qian, W., Zhou, J. (2022). Nexus Between Consumer's Motivations and Online Purchase Intentions of Fashion Products: A Perspective of Social Media Marketing. Frontiers in Psychology, 13, 1-13.
Fu, J.-R., Lu, I.-W., Chen, J.H.-F., Farn, C.-K. (2020). Investigating Consumers' Online Social Shopping Intention: An Information Processing Perspective. International Journal of Information Management, 54, 102-120.
Garcia-Dias,R., Vieira, S., Pinaya, W.H.L., Mechelli, A. (2020). Machine Learning: Methods and Applications to Brain Disorders. Cambridge, M.S., U.S.: Academic Press
Gio. (2023, June 8). 12 must-have accessories for your car. [Web blog message] Retrieved from : https://www.gio.com.au/know-more/on-the-road/car-accessories-must-have.html
Gu, S., Slusarczyk, B., Hajizada, S., Kovalyova, I., Sakhbieva, A. (2021). Impact of the COVID-19 Pandemic on Online Consumer Purchasing Behavior. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2263-2281.
Hair, J.F., Sarstedt, M., Ringle, C.M., Mena, J.A. (2011). An Assessment of the Use of Partial Least Squares Structural Equation Modeling in Marketing Research. Journal of the Academy of Marketing Science, 40(30), 414-433.
Hareesh, K., Manjaiah, D.H. (2011). Peer-to-Peer Live Streaming and Video On Demand Design Issues and its Challenges. International Journal of Peer to Peer Networks (IJP2P), 2(4), 1-11.
Ho, C.-I., Liu, Y., Chen, M.-C. (2022). Factors Influencing Watching and Purchase Intentions on Live Streaming Platforms: From a 7Ps Marketing Mix Perspective. Information Technology and Consumer Behavior, 13(5), 239-258.
Ho, C.-T., Yang, C.-H. (2015). A Study on Behavior Intention to Use Live Streaming Video Platform Based on Tam Model. The Asian Conference on Psychology & the Behavioral Sciences, 2015(08), 263-282.
Hu, M., Chaudhry, S.S. (2021). Enhancing Consumer Engagement in E-commerce Live Streaming Via Relational Bonds. Internet Research, 30(3), 1019-1041.
Huang, C.-Y., Yang, C.-L., Hsiao, Y.-H. (2021). A Novel Framework for Mining Social Media Data Based on Text Mining, Topic Modeling, Random Forest, and DANP Methods. Mathematics, 9(17), 2041-2062.
Huang, Y., Suo, L. (2021). Factors Affecting Chinese Consumers' Impulse Buying Decision of Live Streaming E-Commerce. Asian Social Science, 17(5), 16-32.
Karim, M. R., Beyan, O., Zappa, A., Costa, I. G., Rebholz-Schuhmann, D., Cochez, M., & Decker, S. (2021). Deep Learning-Based Clustering Approaches for Bioinformatics. Briefings in bioinformatics, 22(1), 393-415.
Keskin, S. (2023, April 30 ). Limited-Time Offers: 10 Creative Ways to Drive More Online Sales. [Web blog message] Retrieved from https://www.mdpi.com/2071-1050/15/4/3571
Kudeshia, C., Kumar, A. (2017). Social eWOM: Does it Affect the Brand Attitude and Purchase Intention of Brands? Management Research Review 40(3), 310-330.
Kumar, A., Lee, H. J., Kim, Y. K. (2009). Indian Consumers' Purchase Intention Toward a United States Versus Local Brand, Journal of Business Research, 62(5), 521-527.
Laesser, C., Luo, J.-Q., Beritelli, P. (2021). The SOMOAR Operationalization: A Holistic Concept to Travel Decision Modelling. Tourism Review, 74(3), 613-631.
Liao, Y.-K., Wu, W.-Y., Le, Q.T., Phung, T.T.T. (2022). The Integration of the Technology Acceptance Model and Value-Based Adoption Model to Study the Adoption of E-Learning: The Moderating Role of e-WOM. Sustainability, 14(2), 815-831.
Lin, N.-H., Wang, W.-C., Chiu, S.-Y., Chung, Y.-C. (2007). The Effect of Product Knowledge and Brand Image on Purchase Intention Moderated by Product Category. Marketing Review, 4(4), 481-504.
Liu, C.-H., Tzeng, G.-H., Lee, M.-H. (2012). Improving Tourism Policy Implementation—The Use of Hybrid MCDM Models. Tour Management, 33, 413–426.
Mazzei, J., McMahon, C. (2023, April 30). 38 Practical Accessories to Make Owning And Driving A Car An All Around Better Experience. [Web blog message] Retrieved from https://www.buzzfeed.com/jonathanmazzei/32-car-accessories-that-are-so-practical-youll-wonder-how
McPhail, G. (2021). The Search for Deep Learning: A Curriculum Coherence Model. Journal of Curriculum Studies, 53(4), 420-434.
Min, Y.; Tan, C.-C. (2022). A Stimulus-Organism-Response (S-O-R) Framework for Live Streaming Commerce with a Socio-Technical Perspective. International Journal of Arts and Social Science, 5(4), 118-140.
Montgomery, D.C., Peck, E.A.,Vining, G.G. (2012). Introduction to Linear Regression Analysis, 4th ed. Hoboken, N.J., U.S.: John Wiley & Sons
Murillo, G. G., Novoa-Hernández, P., & Rodriguez, R. S. (2021). Technology Acceptance Model and Moodle: A systematic mapping study. Information Development, 37(4), 617-632.
Oliveira, N. R., Pisa, P. S., Lopez, M. A., Medeiros, D. S. V., & Mattos, D. M. (2021). Identifying Fake News on Social Networks Based on Natural Language Processing: Trends and Challenges. Information, 12(1), 38-70.
Oyewole, G.J., Thopil, G.A. (2023). Data Clustering: Application and Trends. Artificial Intelligence Review, 56, 6439-6475.
Qing, C., Jin, S. (2022). What Drives Consumer Purchasing Intention in Live Streaming E-Commerce? Frontiers in Psychology, 13, 726-737.
Rachmawati, E. (2018). Product Knowledge Review on the Purchase Decision. Advances in Social Science, Education and Humanities Research, 231, 338-240.
Rahardja, U. (2022). Social Media Analysis as a Marketing Strategy in Online Marketing Business. Startupreneur Business Digital (SABDA Journal), 1(2), 176-182.
Ramen, A., Tyson, G., Sastry, N. (2018). Facebook (A) Live? Are Live Social Broadcasts Really Broadcasts? Geneva, Switzerland: International World Wide Web Conferences Steering Committee.
Roy, R., Ng, S. (2012). Regulatory Focus and Preference Reversal Between Hedonic and Utilitarian Consumption. Journal of Consumer Behavior, 11(1), 81-88.
Sawmong, S. (2023). Examining the Key Factors that Drives Live Stream Shopping Behavior. Emerging Science Journal 6(6), 1394-1408.
Shiau, W.L., Lin, B.-W., Yan, C.-M. (2023, July 7). The Intellectual Core Knowledge of the Mobile Information System. Retrieved from https://aisel.aisnet.org/pacis2016/357/
Singh, S., & Kumar, K. (2021). A study of Lean Construction and Visual Management Tools through Cluster Analysis. Ain Shams Engineering Journal, 12(1), 1153-1162.
Sohn, J.-W., Kim, J.-K. (2020). Factors that Influence Purchase Intentions in social commerce. Technology in Society, 63, 365-377.
Stankevich, A. (2017). Explaining the Consumer Decision-Making Process: Critical Literature Review. Journal of International Business Research and Marketing, 2(6), 7-14.
Tao, H., Sun, X., Liu, X., Tian, J.-F., Zhang, D. (2023, March 31). The Impact of Consumer Purchase Behavior Changes on the Business Model Design of Consumer Services Companies Over the Course of COVID-19. Frontiers in Psychology, 03. Retrieved from https://www.frontiersin.org/articles
Williams, B. (2023, March 31). The Impact of Car Accessories on Your Vehicle’s Resale Value. Retrieved from https://aboutmanchester.co.uk/the-impact-of-car-accessories-on-your-vehicles-resale-value/
Wickert, C., Post, C., Doh, J. P., Prescott, J. E., & Prencipe, A. (2021). Management Research That Makes a Difference: Broadening the Meaning of Impact. Journal of Management Studies, 58(2), 297-320.
World Health Organization. (2023, May 8). Coronavirus disease (COVID-19) pandemic. Retrieved from https://www.frontiersin.org/articles
Xiang, L., Zheng, X., Lee, M.K.O., Zhao, D. (2016). Exploring Consumers’ Impulse Buying Behavior on Social Commerce Platform: The Role of Para Social Interaction. International Journal of Information Management, 36(3), 333-347.
Xu, X.-Y., Wu, J.-H., Li, Q. (2020). What Drives Consumer Shopping Behavior in Live Streaming Commerce. Journal of Electronic Commerce Research, 2020, 144-167.
Xue, J., Zhou, Z., Zhang, L., Majeed, S. (2020). Do Brand Competence and Warmth Always Influence Purchase Intention? The Moderating Role of Gender. Frontiers in Psychology, 11, 248-259.
Yim, O.; Ramdeen, K.T. (2015). Hierarchical Cluster Analysis: Comparison of Three Linkage Measures and Application to Psychological Data. The Quantitative Methods for Psychology, 11, 8–21.
Yu, W., Zhu, C., Li, Z., Hu, Z., Wang, Q., Ji, H., & Jiang, M. (2022). A Survey of Knowledge-Enhanced Text Generation. ACM Computing Surveys, 54(11), 1-38.
Zhao, H., Yao, X., Liu, Z., Yang, Q. (2021). Impact of Pricing and Product Information on Consumer Buying Behavior with Customer Satisfaction in a Mediating Role. Frontiers in Psychology, 12, 151-162.
Zhu, P., Liu, Z., Li, X., Jiang, X., Zhu, M.X. (2022). The Influences of Livestreaming on Online Purchase Intention: Examining Platform Characteristics and Consumer Psychology. Industrial Management & Data Systems, 123(3), 862-855.
Zvarikova, K., Michalikova, K. F., & Rowland, M. (2022). Retail data measurement tools, cognitive artificial intelligence algorithms, and metaverse live shopping analytics in immersive hyper-connected virtual spaces. Linguistic and Philosophical Investigations, 21, 9-24.