Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/146567
|
| Title: | 吸納多棲客戶到動態金融科技生態圈之策略: 以支付系統之個案研究為例
Strategies to Attract Multi-Homing Customers into Dynamic Fintech Ecosystems- A Case Study of Multiple Digital Payments |
| Authors: | 邱淑鈴
Chiu, Lynn S.L. |
| Contributors: | 尚孝純
Shang, Shari S. C.
邱淑鈴
Chiu, Lynn S.L. |
| Keywords: | 數位支付
多棲支付用戶
金融科技生態系統
共同演進生態系統
共同學習生態系統
跨業務策略
使用者數位行為意圖
競合合作
個人化參與
忠誠獎勵
Digital Payments
Multihoming Customers
Fintech Ecosystems
Co-evolving ecosystems
Co-learning ecosystems
Cross Business Strategy
User digital behavior intentions
Coopetition
Personalization Engagement
Loyalty Rewards |
| Date: | 2023 |
| Issue Date: | 2023-08-02 14:03:40 (UTC+8) |
| Abstract: | 在數位支付市場中，有些消費者僅使用單一支付錢包，而其他許多消費者則使用多個支付服務進行交易。關於新支付系統的興起，本研究探討多棲支付客戶的行為決定因素。本研究旨在了解數位支付服務供應商如何透過跨業務策略動態擴展商業接觸點，豐富數位生態系統，並避免顧客使用多個支付服務的陷阱。
透過綜合消費者行為相關文獻，我們構建了一個二維研究框架，其中一個決定因素是使用者由線下行為轉向線上意圖，另一個決定因素是數位支付接觸點由便利性到跨業務平台。為了廣泛探討這一問題，我們選取來自英國、美國、新加坡、日本、韓國、香港和台灣等的14個數位支付系統作為研究案例。透過支付使用者數位行為和支付場景接觸點的相互作用，我們將研究案例分為四類：(1) 零售商類型：數位支付服務供應商起源於零售商，其在商店內購物支付具有高度的便利性，並提供客戶面對面的數位支付指導。支付服務供應商透過獎勵顧客忠誠度來擴展持續回購意願。(2) 社交媒體類型：數位支付使用者通常是數位原生代，他們在社交媒體或網絡上進行購物和支付。支付服務供應商可能沒有實體或線上店鋪，但具有整合金流的許可，並利用虛擬金融科技生態系統的網絡效應增進電子支付頻次。(3) 傳統銀行力圖透過與提供銀行即服務(BaaS)技術解決方案的金融科技公司合作，以重新配置銀行商品價值鏈，並實現內嵌金融服務，與擁有廣大客群的商務平台合作，並維持其業務增長。(4) 虛擬銀行專注於早期接觸，捕捉下一代的流行趨勢和盈利能力。這類支付服務向兒童提供財務管理方面的素養，並在父母支持和監督下不斷努力成為他們成年後的財務合作伙伴。
本研究針對不同類型的支付服務供應商如何透過日常接觸吸引多棲支付客戶，並在其金融科技生態系統中持續使用其支付服務，分析支付服務供應商數位創新商業模式、企業間合作與競爭等面向。研究結果揭示了策略制定的軌跡和生態系統交織的方法。零售商類型的支付服務供應商透過多角化業務擴展，提供點數回饋顧客、以擴展持續回購忠誠度；社交媒體類型的支付服務供應商匯聚媒體數位服務內容暨網絡效應，並提供新興小額資金轉帳的數位服務；傳統銀行通過實現銀行即服務（BaaS）重新配置銀行價值鏈；虛擬銀行培養兒童的財務素養，並在其一生中持續提供延伸的金融服務。
在數位支付競爭中，客戶的多棲支付行為是不可避免的。支付服務供應商可能在短期成功後、隨即因競爭者的策略操作，而再次遭遇另一波的多棲支付威脅。因此，支付服務供應商需要探索動態跨業務合作策略，不斷與同在動態金融科技生態系統的利益相關者共同演進，並讓用電子支付使用客戶擁有更廣泛、無縫的購物體驗和忠誠度且持續的使用。
In digital payment markets, some consumers use only one payment wallet while many others engage in multi-homing with a variety of payment services. Regarding the diffusion of new payment systems, we examined the determinants of the adoption of multi-homing behavior. This study aims to understand how digital payment providers dynamically expand business touchpoints with cross-business strategies to enrich the digital ecosystem and avoid the trap of multi-homing in customers.
By synthesizing consumer behavior-related literature, we constructed a two-dimensional research framework with one determinant of user digital behavior from offline to online intentions and the other determinant of digital payment touchpoints from convenient accessibility to cross-business platforms. To explore this on a broader scale, we selected 14 digital payment systems from the UK, the US, Singapore, Japan, Korea, Hong Kong, and Taiwan. With the interplays of user digital behaviors and payment touchpoints, we categorized the study cases into four types. (1) Retailer type: users who originated from retailers with high access to in-store shopping with face-to-face guidance for payment adoption. Payment Providers offer rewards for customer loyalty and expand user wallet share to bundle recurring businesses. (2) Social Media type: users are usually digital natives with high access to social media or the Internet who shop and pay digitally. Providers might not own physical or online shops but have licenses to aggregate money flows through revamping the network effects of virtual fintech ecosystems. (3) Traditional banks strive to work with fintech companies providing Banking-as-a-Service (BaaS) technology solutions to reconfigure the banking value chain and enable embedded financial services to sustain their business growth. (4) Virtual Banks focus on early-life engagement to capture the next generation from popularity to profitability. This type of payment provides children with literacy in financial management with parental support and monitoring, and they continuously strive to be their financial partners as the children transition into adulthood.
The research analyzed business growth models and inter-firm collaborations and coopetition in terms of how the different types of payment providers attract multi-homing customers through daily-life engagement and sustain them in their fintech ecosystems. The research results revealed the trajectory of strategy formulation and the approach of interweaving ecosystems. The retailer type of payment providers diversified the business to expand user wallet share and bundle recurring businesses; the social medial type of payment providers aggregated media contents and revamped network effects for the new money flows; traditional banks enabled BaaS to reconfigure the banking value chain; virtual banks nurtured the financial literacy of children and vertically engaged with extended financial service throughout life.
Customers’ multi-homing behavior is not avoidable in digital payment competition. Payment providers may encounter multiple waves of multi-homing threats after a short period of success. A dynamic cross-business collaboration strategy should be explored to continuously co-evolve the stakeholders of dynamic fintech ecosystems and allow users to have broader and more seamless shopping experiences and continual usage. |
| Reference: | 1. Abhishek & Hemchand, S., 2016. Adoption of sensor based communication for mobile marketing in India. Journal of Indian Business Research. 8(1), 65-76.
2. Accenture, 2018. Open Platform Banking: A New Era.
3. Andrews, D., Criscuolo, C., & Gal, P.N., 2016. The best versus the rest: the global productivity slowdown, divergence across firms and the role of public policy. OECD Productivity Working Papers. https://doi.org/10.1787/24139424
4. Babrovich, N., 2016. What JPMorgan Chase can teach you about mobile wallets. https://www.scnsoft.com/blog/what-jpmorgan-chase-can-teach-you-about-mobile-wallets
5. Bagla, R.K., & Sancheti, V., 2018. Gaps in customer satisfaction with digital wallets: challenge for sustainability. Journal of Management Development. Volume 37, Issue 6.
6. Bellet, et al., 2017. Treatment efficacy, adherence, and quality of life among women younger than 35 years in the international breast cancer study group TEXT and SOFT, Journal of clinical Oncology. 35(27), pp. 3113-3122.
7. Berelson, B., 1952. Content analysis in communication research. APA PsycNet.
8. Berman, S. J., 2012. Digital transformation: opportunities to create new business models. Strategy & Leadership. Vol. 40, Issue 2.
9. Best 36+ Unicorn Fintech Companies In 2022 (Updated), STARTUPS TIPS. https://startupstips.com/unicorn-fintech-companies/
10. Bonel, E. & Rocco, E., 2007. Coopeting to survive; surviving coopetition. International Studies of Management & Organization. Volume 37, Issue 2, pp. 70-96.
11. Chiang, K.P. & Dholakia, R.R., 2003. Factors driving consumer intention to shop online: an empirical investigation. Journal of Consumer psychology. Volume 13, Issues 1-2, pp. 177-183.
12. De Keyser, A., Verleye, K., & Lemon, K.N., 2020. Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use and social influence. Journal of Service Research. Volume 23, Issue 4.
13. Del Giudice, M., Khan, Z., De Silva, M., Scuotto, V., Caputo,vF., & Carayannis, F. 2017. The microlevel actions undertaken by owner-managers in improving the sustainability practices of cultural and creative small and medium enterprises: A United Kingdom–Italy comparison. Journal of Organizational Behavior. Volume 38, Issue 9, pp. 1396-1414.
14. DK Yoo, D.K., Roh, J.J., Cho, S., Yang, M.M., 2022. Coopetition in a platform ecosystem: from the complementors` perspective. Electronic Commerce Research.
15. Eisenhardt, K. M., & Graebner, M. E., 2007. Theory building from cases: Opportunities and challenges. Academy of Management Journal, 50(1), pp. 25-32.
16. Eisenhardt, K.M. & Graebner, M.E., 2007. Theory building from cases: Opportunities and challenges. Academy of management journal.
17. Eisenhardt, K.M., 1989. Building theories from case study research. Academy of management review. Vol. 14, No. 4.
18. Eisenhardt, K.M., 1989.Building theories from case study research. Academy of management review. 14(4), pp. 532-550.
19. Fintech Nexus News, 2022. GoHenry: making every kid smart with money, May. 5, 2022
20. Følstad, A., Kvale, K., 2018. Customer journeys: a systematic literature review. Journal of Service Theory and Practice. Volume 28, Issue 2.
21. Furinto, A., Pawitra, T., & Balqiah, T.E., 2009. Designing competitive loyalty programs: How types of program affect customer equity. Journal of Targeting, Measurement and Analysis for Marketing. Vol. 17, pp. 307-319.
22. Gambetti, R.C., 2010. Ambient communication: How to engage consumers in urban touch-points. California Management Review. Vol.52, No.3.
23. Gehani, R. R., 2013. Innovative Strategic Leader Transforming From a Low-Cost Strategy to Product Differentiation Strategy. Journal of Technology Management & Innovation, vol.8, Issue No. 2.
24. Global Digital Payment Market to Generate Revenue of $228.37 Billion by 2028 | Favorable Reward Program and Growing Mobile Payments are Spurring Market Growth. SkyQuest Technology Consulting Pvt. Ltd. November 29, 2022. https://finance.yahoo.com/news/global-digital-payment-market-generate-140300084.html
25. Global Payments, 2022. How Millennials and Gen Z are shaping the future of payments, issued on January 31, 2022.
26. Gnyawali, D.R. & Park, B., 2009. Co‐opetition and technological innovation in small and medium‐sized enterprises: A multilevel conceptual model. Journal of small business management. Volume 47, 2009 - Issue 3, pp. 308-330.
27. Homburg, C., Vollmayr, J., & Hahn, A., 2014. Firm value creation through major channel expansions: Evidence from an event study in the United States, Germany, and China. Journal of Marketing. Vol. 78, Issue 3.
https://rossrepublic.com/embedded-finance-introduction/
https://www.globalpayments.com/en-gb/insights/2022/01/31/millennials-and-gen-z-shaping-the-future-of-payments
https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/ecosystem-2-point-0-climbing-to-the-next-level
https://www.ofcom.org.uk/__data/assets/pdf_file/0024/234609/childrens-media-use-and-attitudes-report-2022.pdf
https://www.sciencedirect.com/science/article/pii/S102931322200077X
28. Hwang, K. & Zhang, Q., 2018. Influence of parasocial relationship between digital celebrities and their followers on followers` purchase and electronic word-of-mouth intentions, and persuasion knowledge. Computers in Human Behavior. Volume 87, pp. 155-173.
29. Katawetawaraks, C. & Wang, C., 2011. Online shopper behavior: Influences of online shopping decision. Asian Journal of Business Research. Vol.1 No. 2
30. Kireru, J.N., Ombui, K., and Omwenga, J., 2016. Influence of product differentiation strategy in achieving competitive advantage in commercial banks: A case of Equity Bank Limited. Journal of Business & Law Research. 4(2):40-52.
31. Kirk, C.P., Chiagouris, L., Lala, V., & Thomas, J.D.E., 2015. How do digital natives and digital immigrants respond differently to interactivity online?: A Model for Predicting Consumer Attitudes and Intentions to Use Digital Information Products. Journal of Advertising Research, Vol. 62, Issue 4.
32. Klee, Adrian, Embedded Finance: Banking, Payments, Lending- All you need to know
33. Krippendorff, K., 1980. Validity in content analysis. Computerstrategien für die Kommunikationsanalyse.
34. Lal, R. & Sarvary, M., 1999. When and how is the Internet likely to decrease price competition? Marketing Science. Volume 18, Issue 4.
35. Langley, P. & Leyshon, A., 2021. The platform political economy of FinTech: Reintermediation, consolidation and capitalization. New Political Economy. Volume 26, Issue 3. pp. 376-388.
36. Lemon,K.N. & Verhoef, P.C., 2016. Understanding customer experience throughout the customer journey. Journal of Marketing. Vol.80, Issue 6.
37. Li, Z., Zhao, H., Liu, Q., Huang, Z., Mei, T., & Chen, E., 2018. Learning from History and Present: Next-item Recommendation via Discriminatively Exploiting User Behaviors. KDD `18: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. pp. 1734.
38. Litvin, S.W., Goldsmith, R.E., & Pan, B., 2018. A retrospective view of electronic word-of-mouth in hospitality and tourism management. International Journal of Contemporary Hospitality Management. Volume 30, Issue 1.
39. McKinsey Digital, 2020. Ecosystem 2.0: Climbing to the next level. McKinsey & Company, September 11, 2020.
40. Morrison, J. 2022. What Is a Fragmented Industry? Smartcapitalmind.com https://www.smartcapitalmind.com/what-is-a-fragmented-industry.htm
41. Ofcom, 2022. Children and parents: media use and attitudes report 2022.
42. Porter, M.E. (1997), "COMPETITIVE STRATEGY", Measuring Business Excellence, Vol. 1 No. 2, pp. 12-17. https://doi.org/10.1108/eb025476
43. PR Dickson, P.R. & Ginter, J.L., 1987. Market segmentation, product differentiation, and marketing strategy. Journal of marketing.
44. Rawson, A., Duncan, E., Jones, C., 2013 The truth about customer experience. Harvard business review. Pp. 91-98.
45. Ritala, P. & Hurmelinna-Laukkanen, P., 2009. What`s in it for me? Creating and appropriating value in innovation-related coopetition. Technovation. Volume 29, Issue 12, pp. 819-828.
46. Ritala, P., Sainio, L.M., 2014. Coopetition for radical innovation: technology, market and business-model perspectives. Technology Analysis & Strategic Management. Volume 26, Issue 2.
47. Russ, C., 2007. Online Crowds-Extraordinary mass behavior on the Internet. Proceedings of i-Media. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1620803
48. Santoro, G., Gabteni, H., & Pellicelli, A.C., 2018. The role of big data in shaping ambidextrous business process management: Case studies from the service industry. Business Process Management Journal. Vol. 24, Issue 5
49. Sarkar, R. & Das, S., 2017. Online shopping vs offline shopping: A comparative study. International Journal of Scientific Research in Science and Technology. Volume 3, Issue 1.
50. Schierz, P.G., Schilke, O., Wirtz, B.W., 2010. Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications. Vol 9, Issue 3, pp. 209-216.
51. Selander, L., Henfridsson, O., & Svahn, F., 2010. Transforming ecosystem relationships in digital innovation. ICIS 2010 PROCEEDINGS. 138.
52. Shang, S. & Chiu, L., 2023. A RACE pathway for inventing and sustaining mobile payment innovation - A case study of a leading Bank in Taiwan. Asia Pacific Management Review.
53. Shang, S.C. & Chiu, S.L., 2022. Leveraging smart technology for user experience personalization–A comparative case study of innovative payment systems. Pacific Asia Journal of the Association for Information Systems. Volume 14, Issue 1.
54. Shang, S.C. & Chiu, S.L., 2023. A RACE pathway for inventing and sustaining mobile payment innovation- A case study of a leading Bank in Taiwan. Asia Pacific Management Review.
55. Sharma, S.K., Sharma, H., & Dwivedi, Y.K., 2019. A hybrid SEM-neural network model for predicting determinants of mobile payment services. Information Systems Management. Volume 36, Issue 3.
56. Shi, Y., Prentice, C., & He, W., 2014. Linking service quality, customer satisfaction and loyalty in casinos, does membership matter? International Journal of Hospitality Management. Volume 40, pp. 81-91.
57. Shin, D.H.,2009. Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior. Volume 25, Issue 6, pp. 1343-1354.
58. Smith, W.R., 1956. Product differentiation and market segmentation as alternative marketing strategies. Journal of marketing. Volume 21, Issue 1.
59. Swani, K., Milne, G.R., Brown, B.P., & Assaf, A.G., 2017. What messages to post? Evaluating the popularity of social media communications in business versus consumer markets. Industrial Marketing Management. Volume 62, pp. 77-87.
60. Taiminen, H.M. & Karjaluoto, H., 2015. The usage of digital marketing channels in SMEs. Journal of Small Business and Enterprise Development. Vol. 22 No. 4, pp. 633-651.
61. Teng, S. & Khong, K.W., 2021. Examining actual consumer usage of E-wallet: A case study of big data analytics. Computers in Human Behavior. Volume 121, pp. 106778.
62. Thakur, R. & Srivastava, M., 2014. Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Research. Volume 24, Issue 3.
63. The Money Advice Service and IFF Research, 2018. Financial education in secondary schools in England.
64. The Money Advice Service, 2013. New study confirms adult money habits are set by the age of seven years old.
65. Thomas, A., 2017. Multivariate hybrid pathways for creating exceptional customer experiences. Business Process Management Journal. Volume 23, Issue 4.
66. Tueanrat, Y., Papagiannidis, S., & Alamanos, E., 2021. Going on a journey: A review of the customer journey literature. Journal of Business Research. Volume 125, pp. 336-353.
67. Van Bruggen, G.H., Antia, K.D., Jap, S.D., Reinartz, W.J., & Pallas, F., 2010. Managing marketing channel multiplicity. Journal of Service Research. Vol. 13, Issue 3.
68. Verhoef, P.C. & Bijmolt, THA., 2019. Marketing perspectives on digital business models: A framework and overview of the special issue. International Journal of Research in Marketing. Volume 36, Issue 3, pp. 341-349.
69. 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. Volume 91, Issue 2, pp. 174-181.
70. Verhoef, P.C., Kooge, E., & Walk, N., 2016. Creating value with big data analytics: Making smarter marketing decisions. Taylor & Francis Group.
71. Verhoef, P.C., Neslin, S.A., & Vroomen, B., 2007. Multichannel customer management: Understanding the research-shopper phenomenon. International journal of research. Volume 24, Issue 2, pp.129-148.
72. Verhoef, R.E.J., Alsem, S.C., & Verhulp, E.E., & De Castro, B.O., 2019. Hostile intent attribution and aggressive behavior in children revisited: A meta‐analysis. Child Development. Vol. 90, Issue 5 pp. e525-e547.
73. Vermeeren, APOS., Roto, V., & Väänänen, K., 2016. Design-inclusive UX research: design as a part of doing user experience research. Behaviour & Information Technology. Volume 35, Issue 1. pp. 21-37.
74. Vida, I., Koklič, M.K., Kukar‐Kinney, M., & Penz, E., 2012. Predicting consumer digital piracy behavior: The role of rationalization and perceived consequences. Journal of Research in Interactive Marketing. Volume 6 Issue 4.
75. Vives, X. 2019. Digital disruption in banking. Annual Review of Financial Economics. Volume 11, pp. 243-272.
76. Weber, R.P., 1990. Basic content analysis. books.google.com
77. Weill, P., & Woerner, S.L., 2013. Optimizing your digital business model. “TOP 10 LESSONS ON STRATEGY”. MIT Sloan Management Review. Magazine Spring, Research Feature, pp.28.
78. Weinberg, B.D., Parise, S., & Guinan, P.J., 2007. Multichannel marketing: Mindset and program development. Business Horizons. Vol. 50, Issue 5, pp. 385-394.
79. white paper, Morgan Stanley Research, New York, January 6, 2013.
80. Wlömert, N., & Papies, D., 2016. On-demand streaming services and music industry revenues—Insights from Spotify`s market entry. International Journal of Research in Marketing. Volume 33, Issue 2, pp. 314-327.
81. Yin, R. K., 1994. Discovering the future of the case study: Method in evaluation research. Evaluation Practice, 15(3), pp. 283-290.
82. Yin, R.K., 1994. Discovering the future of the case study. Method in evaluation research. Evaluation practice.
83. Yoo, H.J & Kwak, B.E., & Kim, D.H., 2021. Competition of the roles of π-conjugated domain between emission center and quenching origin in the photoluminescence of carbon dots depending on the interparticle separation. Carbon, Volume 183, pp. 560-570.
84. Zhang, P., Zhang,X., Brown,J., Vistisen,D., & Sicree, R., 2010. Global healthcare expenditure on diabetes for 2010 and 2030. Diabetes Research and Clinical Practice. Vol. 87, Issue 3, pp. 293-301.
85. Zhong, S., Monakhov, M., Mok, H.P., Tong, T., Lai, P.S., Chew,S.H., & Ebstein, R.P., 2012. U-shaped relation between plasma oxytocin levels and behavior in the trust game. PLoS ONE 7(12): e51095. |
| Description: | 博士
國立政治大學
資訊管理學系
109356505 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0109356505 |
| Data Type: | thesis |
| Appears in Collections: | [資訊管理學系] 學位論文
|
Files in This Item:
| File |
Description |
Size | Format | |
|---|
| 650501.pdf | | 3739Kb | Adobe PDF2 | 121 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
