Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/139143


Title: 台灣商業藝術品行業應用區塊鏈意圖之研究:個人與環境之觀點
Intention to Use Blockchain in Taiwan Artworks’ Business Sector: Personal and Environmental Perspectives
Authors: 梁碧霞
Liang, Pi-Hsia
Contributors: 洪為璽
季延平

Hung, Wei-Hsi
Chi, Yan-Ping

梁碧霞
Liang, Pi-Hsia
Keywords: 區塊鏈
感知風險
認知有用
認知易用
藝術品交易市場
行為意圖
Blockchain
Perceived Risk
Perceived Usefulness
Perceived Ease of Use
Art Market
Behavioral Intention
Date: 2022
Issue Date: 2022-03-01 16:41:25 (UTC+8)
Abstract: 全球藝術市場自2020 年受到 COVID-19 疫情影響,以實體經營爲主的藝術展演、畫廊與博物館受到重大衝擊,銷售額衰退,但線上銷售卻大幅成長,加密貨幣擴展到加密藝術領域,NFT (Non-Fungible Token)市場成為藝術金融界熱門的話題,而其背後支持的區塊鏈 (Blockchain)技術應用逐步擴大至各個產業領域。區塊鏈似乎能解決現今藝術品交易市場所遭遇到的問題,但至今未能廣泛地被藝術品交易市場參與方所接受,到底有那些因素影響了區塊鏈技術使用者之行爲意圖?此為本研究的動機。本研究將以個人與環境視角來探索影響藝術交易市場内區塊鏈使用者意圖之關鍵因素,以科技接受模型(Technology Acceptance Model,簡稱TAM)中的認知有用(Perceived Usefulness)與認知易用(Perceived Ease of Use)為核心,來探討藝術交易市場參與者使用區塊鏈的影響程度。本研究針對臺灣的藝術品商業行業參與者和潛在消費者進行問卷調查,進一步分析檢驗模型内的八項構面,涵蓋感知風險、政府支持、拍賣行倡議、信任、認知有用、認知易用、使用者態度及行為意圖,研究其相互關係,並比較和過去研究結果的不同點,以進一步完善模型架構,提升區塊鏈科技在藝術交易市場内的使用度,擴大潛在藝術品消費者的參與度。
The global artwork market has been affected by the COVID-19 pandemic ever since 2020. Art exhibitions, galleries, and museums based on physical operations have been severely impacted, and sales have declined, but contrarily, online sales have grown substantially. As cryptocurrency has expanded to the field of crypto art, the NFT (Non-Fungible Token) market has become a hot topic in the art finance industry, and the application of blockchain technology supporting it has gradually expanded to various industrial fields. Blockchain appears able to solve the problems encountered in the artwork market today, but it has not been widely accepted by participants in the artwork market. The motivation of this study is to explore what factors affect the behavioral intentions of blockchain technology users. This research will explore the key factors affecting the intention of blockchain users in the art trading market from the perspective of individuals and the environment. It further focuses on perceived usefulness and perceived ease of use in personal factors of the technology acceptance model (TAM) to explore the impact of blockchain usage by artwork market participants. This study conducts a questionnaire survey on Taiwan’s artwork business participants and potential consumers to further analyze and test the 8 aspects and 15 hypotheses of the model. It examines their interrelationships, and compares any differences with the previous research results to further improve the model structure, enhance the use of blockchain technology in the artwork trading market and expand the participation of potential art consumers.
Reference: 中文文獻
1. iThonme (2018)。區塊鏈如何打造未來經濟新藍圖。 Retrived from https://www.ithome.com.tw/article/125343 (Accessed on Oct. 14, 2021)
2. ONETOP評級(2018)。Codex Protocol:區塊鏈上的拍賣行。取自壹讀網址:: https://read01.com/aA35k6Q.html#.YWzdIhpBy70 (Accessed on 18 Oct. 2021).
3. 巴比特資訊 (2018)。優權天成創始人車克達:談談三年來的區塊鏈實踐。 取自中時新聞網網址: https://www.chainnews.com/zh-hant/articles/667887160800.htm (Accessed on Oct. 15, 2021)
4. 楊家澄 (2017)。金融科技的創新擴散:以台灣的區塊鏈技術發展為例(碩士論文)。清華大學科技管理研究所,新竹市, P1 – 55。
5. 吳孟娟 (2007)。重建、活化高雄藝術市場之策略研究(碩士論文)。成功大學藝術研究所,臺南市, P1 – 123。
6. 李雨峰 (2014)。論追續權制度在我國的構建——以《著作權法》第三次修改為中心。法律科學:西北政法學院學報, 第1期。西南政法大學民商法學院, 中國重慶市。
7. 李梓萱 (2014)。網路藝術品交易發展模式分析研究。美與時代:創意(上),清華大學美術學院視覺傳達系,新竹市。
8. 劉家蓉 & 石浩吉(2018)。區塊鏈真的能改革藝術市場嗎? 取自帝圖藝術研究中心網址: https://aerc.artemperor.tw/report/2239 (Accessed on Aug. 20, 2021)
9. 顏真真 (2019)。藝術品結合區塊鏈 不怕買到假貨。 NOWnews網址:https://kknews.cc/tech/ggbg43y.html (Accessed on Oct. 14, 2021)
10. 藝術市場通訊 (2019)。藝術市場的區塊鏈革命。取自微文庫網址: https://www.gushiciku.cn/dc_hk/201326974 (Accessed on Oct. 14, 2021)

英文文獻

1. Ajzen, I. (1989). Attitude structure and behavior. Attitude structure and function. A.R., Breckler, S.J.; Greenwald, A.G. Eds., New Jersey, USA: Lawrence Erlbaum Associates, Inc., pp. 241-274.
2. Ajzen, I; Fishbein, M. (1980). Understanding attitudes and predicting social behavior. New Jersey: Pretice-Hall.
3. Ajzen, I.; Fishbein, M.A. (1975). Bayesian analysis of attribution processes. Psychological bulletin, 82(2), pp. 261. doi:10.1037/h0076477
4. Al-Amri, R.; Maarop, N.; Jamaludin, R.; Samy, G. N.; Magalingam, P.; Hassan, N. H.; Ten, D. W. H.; Daud, S. M. (2018). Correlation analysis between factors influencing the usage intention of NFC mobile wallet payment. Journal of Fundamental and Applied Sciences, 10(2S), pp. 215–228. doi:10.4314/jfas.v10i2s.18
5. Albayati, H.; Kim, S.K.; Jeung Rho, J.J. (2020). Accepting financial transactions using blockchain technology and cryptocurrency: A customer perspective approach. Technology in Society, Volume 62(3), 101320. doi:10.1016/j.techsoc.2020.101320
6. Alexander, V.D. (2003). Sociology of the arts exploring fine and popular forms. New Jersey, USA: Wiley-Blackwell, pp. 1-388.
7. Alfadda, H.A.; Mahdi, H.S. (2021). Measuring students’ use of zoom application in language course based on the Technology Acceptance Model (TAM). J Psycholinguist Res, 50, pp. 883–900. doi:10.1007/s10936-020-09752-1
8. Alharbi, S.; Drew, S. (2014). Using the technology acceptance model in understanding academics’ behavioural intention to use learning management systems. International Journal of Advanced Computer Science and Applications, 5(1), pp. 143-155. doi:10.14569/ijacsa.2014.050120
9. Alsabawy, A.Y.; Cater-Steel, A.; Soar, J. (2016). Determinants of perceived usefulness of e-learning systems, Computers in Human Behavior, Volume 64, pp. 843-858. doi:10.1016/j.chb.2016.07.065
10. Al-Swidi, A. K.; Enazi, M. A. (2020). The trust in the intermediaries and the intention to use electronic government services: a case of a developing country Electronic Government. Electronic Government, Vol. 17, No.1, pp 27-54.
11. Arias-Oliva, M.; Borondo, J.; Matias Clavero, G. (2019). Variables influencing cryptocurrency use: A Technology Acceptance Model in Spain. Frontiers in Psychology, 10. pp. 475. doi:10.3389/fpsyg.2019.00475.
12. Art/Basel (2020). The Impact of Covid-19 on the gallery sector. Retrived from: https://d2u3kfwd92fzu7.cloudfront.net/The%20Impact%20of%20COVID-19%20Survey_Press%20Release-2.pdf (accessed on 27 Dec., 2021).
13. Artprice(2020). The Art Market in 2020. Retrived from https://imgpublic.artprice.com/pdf/zh-the-art-market-in-2020.pdf (Accessed on Oct. 13, 2021)
14. Bajari, P.; Hortaçsu A. (2004). Economic insights from internet auctions. Journal of Economic Literature, 42(2), pp. 457-486.
15. Bauer, R.A. (1960). Consumer behavior as risk taking. Robert S. Hancock., Eds.; American Marketing Association: Chicago, USA, 6(1), pp. 389-398.
16. Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), pp. 351-370.
17. Bocart, F.; Oosterlinck, K (2011). Discoveries of fakes: Their impact on the art market. Economics Letters, 113(2), pp. 124-126.
18. Chang, S.S.; Lou, S.J., Cheng; S.R.; Lin, C.L. (2015). Exploration of usage behavioral model construction for university library electronic resource. The Electronic Library, 33(2), pp. 292-307
19. Cheung, C.; Lee, M.K.O. (2020). Trust in internet shopping: A proposed model and measurement instrument (p. 406). Proceedings of the America’s Conference on Information Systems (AMCIS 2000). Long Beach, California, USA.
20. Chircu, Alina M.; Davis, Gordon B.; Kauffman, R. J. (2000). Trust, expertise, and E-Commerce intermediary adoption (p. 405). Proceedings of AMCIS 2000, Long Beach, California, USA.
21. Chong, B, Yang, Z. and Wong, C.S. (2003). Asymmetrical impact of trustworthiness attributes on trust, perceived value and purchase intention: A conceptual framework for cross-cultural study on consumer perception of online auction. Proceedings of the 5th International Conference on Electronic Commerce, ICEC 2003, Pittsburgh, Pennsylvania, USA, September 30 - October 03, 2003.
22. Chuo, Y.H.; Tsai, C.H.; Lan, Y.L.; Tsai, C.S. (2011). The effect of organizational support, self efficacy, and computer anxiety on the usage intention of e-learning system in hospital. African Journal of Business Management, vol. 5. op. 5518-5523.
23. Chuttur, M. Y. (2009). Overview of the Technology Acceptance Model: Origins, developments and future directions. Retrived from All Sprouts Content Website: https://aisel.aisnet.org/sprouts_all/290
24. Cronbach, L.J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, pp. 297–334.
25. Daley, S. (2021). 35 Blockchain applications and real-world use cases disrupting the status QUO. Retrived from Builtin BETA Website: https://builtin.com/blockchain/blockchain-applications (Accessed on 9 July 2021).
26. 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), pp. 982-1002.
27. Dekking, N. (2018). Blockchain, the holy grail? Industry Voice. Retrived from TEFAF Website: https://2018.amr.tefaf.com/voices/blockchain-technology-a-start-of-an-art-market-revolution (accessed on 23 July 2021).
28. Deloitte Insight. Deloitte's 2019 global blockchain survey. Retrived from https://www2.deloitte.com/content/dam/Deloitte/se/Documents/risk/DI_2019-global-blockchain-survey.pdf (Accessed on 12 July 2012).
29. Deloitte Insight. Deloitte's 2020 global blockchain survey. Retrived from https://www2.deloitte.com/content/dam/insights/us/articles/6608_2020-global-blockchain-survey/DI_CIR%202020%20global%20blockchain%20survey.pdf (acessed on 12 July 2021)
30. Dowling, G.R.; Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of Consumer Re-search, 20(1), pp. 119-134.
31. Fan, M.; Zhang X. (2019). Consortium blockchain based data aggregation and regulation mechanism for smart grid, IEEE Access, vol.7, pp. 35929-35940. doi:10.1109/ACCESS.2019.2905298
32. Faqih, K. M. S. (2016). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter? Journal of Retailing and Consumer Services, vol. 30, pp. 140-164.
33. Featherman, M.; Miyazaki, A.; Sprott, D. (2010). Reducing online privacy risk to facilitate e-service adoption: The influence of perceived ease of use and corporate credibility. Journal of Services Marketing, vol. 24(3). pp.219-229. doi:10.1108/08876041011040622.
34. Financial Conduct Authority. (2015) Regulatory Sandbox. Retrived from https://www.fca.org.uk/publication/research/regulatory-sandbox.pdf (Accessed on 28 Sept. 2021)
35. Fornell, C.; Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp. 39-50.
36. Gaski, J.F.; Nevin, J.R. (1985). The differential effects of exercised and unexercised power sources in a marketing channel. Journal of Marketing Research, 22, pp. 130-142.
37. Gefen, D. (1997). Building users' trust in freeware providers and the effects of this trust on users' perceptions of usefulness, ease of use and intended use of freeware. Georgia State University. Ann Arbor MI, USA. Retrived from: https://www.proquest.com/openview/d487130bdb58f2c7416869468bfc9467/1?pq-origsite=gscholar&cbl=18750&diss=y
38. Gefen, D.; Karahanna, E.; Straub, D.W. (2003). Trust and TAM in online shopping: An integrated model. MIS quarterly, 27(1): pp. 51-90. ResearchGate. doi:10.2307/3003651
39. Gerber, B.; Neeley, G.W. (2005). Perceived risk and citizen preferences for government management of routine hazards. Policy Studies Journal, 33(3), pp. 395-418
40. Geyskens, I.; Steenkamp, J.E. M.; Scheer, L. K.; Kumar, N. (1996). The effects of trust and interdependence on relationship commitment: A trans-atlantic study. International Journal of Research in Marketing, 13(4), pp. 303-317.
41. Granovetter, M. (1985). Economic action and social structure: the problem of embeddedness. Amercian Journal of Sociology Vol. 91(3), pp. 481-510. doi:10.1086/228311
42. Grazioli, S.; Jarvenpaa, S. (2000). Perils of internet fraud: An empirical investigation of deception and trust with experienced internet consumers. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on. 30. pp. 395 - 410. doi:10.1109/3468.852434.
43. Griswold, W. (2004). Cultures and societies in a changing World. 2nd ed. California USA: Sage Publications, pp. 154-196.
44. Gupta, M. (2017). Blockchain for Dummies. IBM Limited Edition, USA: John Wiley & Sons, Inc. Retrived from http://gunkelweb.com/coms465/texts/ibm_blockchain.pdf (Accessed 13 Aug 2021).
45. Gupta, S., & Kim, H. W. (2007). Developing the commitment to virtual community: the balanced effects of cognition and affect. Information Resources Management Journal, 20(1), pp. 28 – 45.
46. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., Tatham, R. L. (2006). Multivariate Data Analysis, 6th ed.; Upper Saddle River, NJ: Pearson Prentice Hall, Volume 6.
47. Hair, J.F.; Anderson, R.E.; Tatham, R.L.; Black, W.C. (1998). Multivariate Data Analysis, 5th ed.; CENGAGE: New York, Macmillan.
48. Hallema, Y.; Abbesb, I.; Hikkerovac, L.; Tagad, N. (2021). A trust model for collaborative redistribution platforms: Technological Forecasting and Social Change 170(10), 120943. doi:10.1016/j.techfore.2021.120943
49. Hansen, J. M.; Saridakis,G.; Benson, V. (2018). Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers’ use of social media for transactions, Computers in Human Behavior, Vol. 80, pp. 197-206. doi:10.1016/j.chb.2017.11.010.
50. Harrigan, M.; Feddema, K.; Wang, S.; Harrigan, P.; Diot, E. (2021). How trust leads to online purchase intention founded in perceived usefulness and peer communication. Journal of Consumer Behaviour, Vol. 20(5), pp.1297-1312. doi:10.1002/cb.1936
51. Hiscox. (2018). Hiscox online art trading report 2018. Retrived from https://arttactic.com/product/hiscox-online-art-trading-report-2018 (Accessed on July 15, 2021.)
52. Hiscox. (2019). Hiscox online art trading report 2019. ArtTactic, HISCOX. Retrived from https://www.hiscox.co.uk/sites/uk/files/documents/2019-04/hiscox-online-art-trading-report-2019.pdf (Accessed on July 14, 2021.)
53. Hiscox. (2020). Hiscox online art trading report 2020. Retrived from https://www.hiscox.co.uk/sites/uk/files/documents/2019-04/hiscox-online-art-trading-report-2020.pdf (Accessed on July 14, 2021)
54. Hong, I.B.; Cho, H. (2011). The impact of consumer trust on attitudinal loyalty and purchase intentions in B2C e-marketplaces: Intermediary trust vs. seller trust. International Journal of Information Management, 31(5), pp. 467-479.
55. Islami, M.M.; Asdar, M.; Baumassepe, A.N. (2021). Analysis of perceived usefulness and perceived ease of use to the actual system usage through attitude using online guidance application. Hasanuddin Journal of Business Strategy, Vol 3(1), pp. 52-64. doi:10.26487/hjbs.v3i1.410
56. Jacoby, J.; Kaplan, L.B. (1972). The components of perceived risk. Proceedings of the Third Annual Conference of the Association for Consumer Research, E Venkatesan eds.; Chicago, IL: Association for Consumer Research, pp. 382-393.
57. Jeong, B. K.; Yoon, T. E. (2013). An empirical investigation on consumer acceptance of mobile banking services. Business and Management Research, Sciedu Press, vol. 2(1), pages 31-40.
58. Kandaswamy, R. and Furlonger, D. (2018). Hype cycle for blockchain technologies. Retrived from Gartner Website: https://www.gartner.com/en/documents/3883991/hype-cycle-for-blockchain-technologies-2018 (Accessed on Jul 25, 2020)
59. Kang, J.W.; Namkung, Y. (2018). The information quality and source credibility matter in customers’ evaluation toward food O2O commerce. International Journal of Hospitality Management. 78. pp. 189-198. doi:10.1016/j.ijhm.2018.10.011.
60. Kaplan, K. J. (1972). On the ambivalence-indifference problem in attitude theory and measurement: A suggested modification of the semantic differential technique. Psychological bulletin, 77(5), 361. doi:10.1037/h0032590
61. Keni, K. (2020). How perceived usefulness and perceived ease-of-use affecting intent to repurchase? Jurnal Manajemen, Vol. 24(3), pp. 481-496. doi:10.24912/jm.v24i3.680
62. Keong, Y. C.; Albadry, O.; Raad, W. (2014). Behavioral intention of EFL teachers to apply e-learning. Journal of Applied Sciences, 14(20), pp. 2561-2569.doi:10.3923/jas.2014.2561.2569
63. Kim, E.-J.; Kim, J.J.; Han, S.-H. (2021). Understanding student acceptance of online learning systems in higher education: application of social psychology theories with consideration of user innovativeness. Sustainability, 13(2), 896. doi:10.3390/su13020896
64. Kim, H.-W.; Xu, Y.; Koh, J. (2004). A comparison of online trust building factors between potential customers and repeat customers. Journal of the Association for Information Systems, 5(10), pp. 392–420. doi:10.17705/1jais.00056
65. Kotler, P. (1997). Marketing management: Analysis, planning, implementation, and control. 9th ed.; Prentice Hall, Upper Saddle River.
66. Kucukusta, D.; Law, R.; Besbes, A.; Legoherel, P. (2015). Re-examining perceived usefulness and ease of use in online booking: The case of Hong Kong online users. International Journal of Contemporary Hospitality Management. 27. pp. 185-198. doi:10.1108/IJCHM-09-2013-0413.
67. Kuo, C.C.; Rogers, P.; White, R.E. (2004). Online reverse auctions: An overview. Journal of International Technology and Information Management, 13(4), pp. 5.
68. Kwon, K. J.; Mai, L. W.; Peng, N. (2020). Determinants of consumers’ intentions to share knowledge and intentions to purchase on s-commerce sites: Incorporating attitudes toward persuasion attempts into a social exchange model. Eurasian Business Review, 10(1), pp. 157–183.
69. Lee, D.; Lee, S.; Olson, D.; Chung, S. (2010). The effect of organizational support on ERP implementation. Industrial Management and Data Systems. 110. 269-283. doi:10.1108/02635571011020340.
70. Lee, Y.S. (2019). Analysis on trends of artworks blockchain platform. International Journal of Advanced Culture Technology, 7(3), pp. 149-157.
71. Leible, S.; Schlager, S.; Schubotz, M.; Gipp, B. (2019). A review on blockchain technology and blockchain projects fostering open science. Frontiers in Blockchain, Vol. 2, pp. 16. doi:10.3389/fbloc.2019.00016
72. Liang, P.-H.; Chi, Y.-P. (2021). Influence of perceived eisk of blockchain art trading on user attitude and behavioral intention. Sustainability, 13, 13470. doi:10.3390/su132313470
73. Lin, C.S.; Wu, S.; Tsai, R.J. (2005). Integrating perceived playfulness into expectation-confirmation model for web portal context. Information & Management, 42(5), pp. 683-693.
74. Liu, S.; Du, J.; Zhang, W.; Tian, X.; Kou, G. (2021). Innovation quantity or quality? The role of political connections. Emerging Markets Review, Volume 48(2), 100819. doi:10.1016/j.ememar.2021.100819.
75. Lunsford, D.A.; Burnett, M.S. (1992). Marketing product innovations to the elderly: Understanding the barriers to adoption. Journal of Consumer Marketing, 9(4), pp. 53-62.
76. Mailizar, M.; Almanthari, A.; Maulina, S. (2021). Examining teachers’ behavioral intention to use E-learning in teaching of mathematics: an extended TAM Model. Contemporary Educational Technology, 13(2), ep298. doi:10.30935/cedtech/9709
77. Malik A.N.A.; Annuar S.N.S. (2021) The effect of perceived usefulness, perceived ease of use, reward, and perceived risk toward E-Wallet usage intention. Eurasian Business and Economics Perspectives. Eurasian Studies in Business and Economics, vol 17, pp. 115-130. Springer, Cham. doi:10.1007/978-3-030-65147-3_8
78. McKnight, D.H.; Choudhury, V.; Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: A trust building model. Journal of Strategic Information Systems, 11(3-4), pp. 297-323.
79. Mearian, L. (2020). How blockchain plays into digital transformation. IDC Wwbsite: https://blogs.idc.com/2020/12/14/how-blockchain-plays-into-digital-transformation/ (accessed on 12 July 2021).
80. Meuter, M. L.; Ostrom, A. L.; Roundtree, R. I.; Bitner, M. J. (2000). Self-service technologies: Understanding customer satisfaction with technology-based service encounters. Journal of Marketing, 64(3), pp. 50-64. doi:10.1509/jmkg.64.3.50.18024
81. Milliman, R.E.; Fugate, D.L. (1998). Using trust-transference as a persuasion technique: An empirical field investigation. Journal of personal selling & sales management, 8(2), pp. 1-7.
82. Moon, J.W.; Kim, Y.G. (2001). Extending the TAM for World-Wide-Web context. Information and Management, vol. 38, pp. 217-230.
83. Mou, J.; Shin, D.; Cohen, J. (2017). Trust and risk in consumer acceptance of e-services. Electronic Commerce Research, 17(2), pp. 255-288.
84. Muftic, S.; Sanchez, I.; Beslay, L. (2016). Overview and Analysis of the Concept and Applications of Virtual Currencies. EUR 28386 EN. Luxembourg (Luxembourg): Publications Office of the European Union, JRC105207
85. Nadini, M.; Alessandretti, L.; Giacinto, F. D.; Martino, M.; Aiello, L. M.; Baronchelli, A. (2021). Mapping the NFT revolution: market trends, trade networks and visual features. Scientific Reports, 11, 20902. doi:10.1038/s41598-021-00053-8
86. Nayanajith, D. A. G. (2021). Perceived trust of E-Services, perceived usefulness and adoption of E-Banking amongst the students of university of Kelaniya: A relational study. Vidyodaya Journal of Management. Vol. 7. doi:10.31357/vjm.v7i1.4917.
87. Ngai, E.W.T.; Poon, J.K.L.; Chan, Y.H.C. (2007). Empirical examination of the adoption of WebCT using TAM. Computers & Education, Volume 48, pp.250-267. doi:10.1016/j.compedu.2004.11.007
88. Orenge, A. O.; Milani, F. P. (2018). Blockchain-based provenance solution for handcrafted jewellery. University of Tartu, Finland. Retrived from https://www.semanticscholar.org/paper/Blockchain-based-Provenance-Solution-for-Jewellery-Orenge-Milani/ff850be046c89cbdc66a2f372421a77120c7d340 (Accessed on 27 Dec. 2021)
89. Orji, I. J.; Kusi-Sarpong, S.; Huang, S. Vazquez-Brust, D. (2020). Evaluating the factors that influence blockchain adoption in the freight logistics industry. Transportation Research Part E: Logistics and Transportation Review. Volume 141, 102025.
90. Ow, T. T; Spaid, B. I; Wood, C. A; Ba, S. (2018). Trust and experience in online auctions. Journal of Organizational Computing and Electroni. vol. 28 (4), pp. 294-314.
91. Pitardi, V.; Marriott, H. R. (2021). Alexa, she's not human but… Unveiling the drivers of consumers' trust in voice-based artificial intelligence. Psychology & Marketing, Vol. 38, pp. 626-642. doi:10.1002/mar.21457.
92. Prakosa, A.; Sumantika, A. (2021). An Analysis of Online Shoppers' Acceptance and Trust toward Electronic Marketplace using TAM Model. Journal of Physics: Conference Series, Volume 1823, pp. 1-7. doi:10.1088/1742-6596/1823/1/012008
93. Qalati, S. A.; Vela, E. G.; Li, W.; Dakhan, S. A.; Thuy, T. T. H.; Merani, S. H.; Foroudi, P. (Reviewing editor). (2021). Effects of perceived service quality, website quality, and reputation on purchase intention: The mediating and moderating roles of trust and perceived risk in online shopping. Cogent Business & Management, 8(1), pp. 1-20. doi:10.1080/23311975.2020.1869363
94. Ram, S.; Sheth, J.N. (1989). Consumer resistance to innovations: The marketing problem and its solutions, Journal of Consumer Marketing, vol. 6(2), pp. 5-14.
95. Ramanathan, R.; Ramanathan, L.; Ko, L. W. L. (2014). Adoption of RFID technologies in UK logistics: Moderating roles of size, barcode experience and government support. Expert Systems with Applications, vol. 41(1), pp. 230-236, doi:10.1016/j.eswa.2013.07.024.
96. Ramli, Y.; Harwani, M.; Soelton, S.; Hariani, F.; Usman, F. (2021). The implication of trust that influences customers' intention to use mobile banking. The Journal of Asian Finance, Economics and Business, vol. 8, no. 1, pp. 353–361.
97. Ratnasingham, P. (1999). Risks in low trust among trading partner in electronic commerce. Computer and Security, vol. 18, pp.587-592.
98. Rattanaburi, K.; Vongurai, R. (2021). Factors influencing actual usage of mobile shopping applications: generation Y in Thailand. The Journal of Asian Finance, Economics and Business Vol. 8, pp. 901–13. doi:10.13106/JAFEB.2021.VOL8.NO1.901.
99. Research and Markets. (2020). Blockchain market (Global Forecast to 2025). Retrived from https://www.researchandmarkets.com/reports/5025113/blockchain-market-by-component-platform-and?w=4&utm_source=BW&utm_medium=PressRelease&utm_code=zgncsk (Accessed on 28 July 2021.)
100. Saberi, S.; Kouhizadeh, M.; Sarkis, J.; Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), pp. 2117-2135.
101. Salam, A.F.; Rao, H.R.; Pegels, C.C. (1998). An investigation of consumer-perceived risk on electronic commerce trading: The role of institutional trust and economic incentive in a social exchange framework (p.335-337), Proceedings of AMCIS, 114, Baltimore, USA. Retrived from https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1541&context=amcis1998 (Accessed on 28 July 2021.)
102. Salisbury, L. (2018). Art forgers—criminals or heroes? In the post-truth era, it's time for an unequivocal answer. Social Research: An International Quarterly, 85(4), pp. 827-836.
103. Sciarelli, M.;Prisco, A.; Muto, V. (2021). Factors affecting the adoption of blockchain technology in innovative Italian companies: an extended TAM approach. Journal of Strategy and Management. DOI:10.1108/jsma-02-2021-0054.
104. Sekaran, U.; Bougie, R. (2009). Research Methods for Business: A Skill Building Approach, 5th ed; UK.: John Wiley and Sons, Chichester.
105. Shapiro, S. P. (1987). The social control of impersonaltrust. American Journal of Social Psychology, 93(3), pp. 623–658.
106. Shin, D. (2019). Blockchain: the emerging technology of digital trust. Telematics and Informatics, 45, pp. 1-11.
107. Shin, D. (2010). The effects of trust, security and privacy in social networking: a security-based approach to understand the pattern of adoption. Interacting with Computers, 22(5), pp. 428-438.
108. Shneiderman, B. (2000). Designing trust into online experiences, Communications of the ACM , 43(12), pp. 57-59.
109. Shu, Y.; Yu, J.; Yan, W. (2019). Blockchain for security of a Cloud-based online auction system. Exploring Security in Software Architecture and Design, NZ: Auckland University of Technology, pp.189-210. doi:10.4018/978-1-5225-6313-6.ch008
110. Siegrist, M.; Zingg, A. (2014). The role of public trust during pandemics implications for crisis communication. European Psychologist, 19(1), pp. 23-32.
111. Siegrist, M.; Luchsinger, L.; Bearth, A. (2021). The impact of trust and risk perception on the acceptance of measures to reduce COVID-19 Cases. Risk Analysis, 41(5), pp. 787-800. doi:10.1111/risa.13675
112. Simon, H. A. (1957). Models of man, social and rational: Mathematical essays on rational human behavior. New York: Wiley
113. Soohoo, S. (2020). Blockchain spending quick look: U.S. buying behavior by industry, company size, and LOB versus IT — 2020 Update. Retrived from IDC Website: https://www.idc.com/getdoc.jsp?containerId=US47039120 (accessed on 15 July 2021).
114. Suh, B.; Han, I. (2002). Effect of trust on customer acceptance of Internet banking. Electronic Commerce Research and Applications. 1. pp. 247-263. doi:10.1016/S1567-4223(02)00017-0.
115. Sweeney, J.C.; Soutar, G.N.; Johnson, L.W. (1999). The role of perceived risk in the quality-value relationship: A study in a retail environment, Journal of Retailing, 75(1), pp. 77-105.
116. Swilley, E.; Goldsmith, R. (2007). The role of involvement and experience with electronic commerce in shaping attitudes and intentions toward mobile commerce. International Journal of Electronic Marketing and Retailing. Vol.1(4), pages 370-384. doi:10.1504/IJEMR.2007.014850.
117. Taat, M. S.; Francis, A. (2019). Factors influencing the students’ acceptance of E-Learning at teacher education institute: an exploratory study in Malaysia. The International Journal of Higher Education, 9, 133. doi:10.5430/ijhe.v9n1p133
118. Tang, T.-W.; Chi, W.-H. (2005). The role of trust in customer online shopping behavior: Perspective of Technology Acceptance Model. Proccedings of NAACSOS Conference 2005 Indiana, USA.
119. Tapscott, A.; Tapscott, D. (2017). How blockchain is changing finance. Retrived from Harvard Business Review Website: https://hbr.org/2017/03/how-blockchain-is-changing-finance (accessed online on 13 July 2021).
120. Tawafak, R., ALFarsi, G., Jabbar, J., Iqbal Malik, S., Mathew, R., AlSidiri, A., Shakir, M. & Romli, A. (2021). Impact of Technologies During COVID-19 Pandemic for Improving Behavior Intention to Use E-learning. Retrived from International Association of Online Engineering Website: https://www.learntechlib.org/p/218695/. (Accessed on 7 Jan. 2022).
121. Taylor J. W. (1974). The role of risk in consumer behavior: A comprehensive and operational theory of risk taking in consumer behavior. Journal of Marketing, Volume: 38, pp. 54-60. doi:10.1177/002224297403800211
122. Taylor, S.; Todd, P. A. (1995).Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, Vol. 6(2), pp. 144-176.
123. Tella, A.; Tsabedze, V.; Ngoaketsi, J.; Enakrire, R.T. (2021) Perceived usefulness, reputation, and tutors' advocate as predictors of MOOC Utilization by distance learners: implication on library services in distance learning in Eswatini. Journal of Library & Information Services in Distance Learning, 15:1, 41-67, doi:10.1080/1533290X.2020.1828218
124. The Art Market (2018). The Art Basel and UBS global art market report 2018. Art Basel Press Release. Retrived from UBS Contemporary Art Website: https://d2u3kfwd92fzu7.cloudfront.net/Art%20Basel%20and%20UBS_The%20Art%20Market_2018.pdf (accessed on Oct. 10, 2021).
125. The Art Market. (2019). The Art Basel and UBS global art market report 2019. Art Basel Press Release. Retrived from UBS Contemporary Art Website: https://d2u3kfwd92fzu7.cloudfront.net/The%20Art%20Market%202019_Press%20Release-2.pdf (Accessed on July 30, 2021.)
126. The Art Market. (2020). The Art Basel and UBS global art market report 2020. Art Basel Press Release. Retrived from UBS Contemporary Art Website: https://www.ubs.com/global/en/our-firm/art/collecting/art-market-report.html (Accessed on 30 July 2021).
127. Thong, J.Y.L.; Hong, S.J.; Tam, K.Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), pp. 799-810.
128. Tian, X.; Kou, G.; Zhang, W. (2020). Geographic distance, venture capital and technological performance: Evidence from Chinese enterprises. Technological Forecasting and Social Change. Vol. 158(5), 120155. doi:10.1016/j.techfore.2020.120155.
129. Van, H. N.; Pham, L.; Williamson, S.; Chan, C.Y.; Thang, T.D.; Nam, V. X. (2021). Explaining intention to use mobile banking: integrating perceived risk and trust into the technology acceptance model. International Journal of Applied Decision Sciences, Vol. 14, pp. 55-80.
130. Venkatesh, V.; Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: four longitudinal field studies. Management Science 46(2), pp. 186-204.
131. Venkatesh, V.; Bala, H. (2008). Technology Acceptance Model 3 and a research agenda on interventions. Decision Sciences. DECISION SCI. 39. 273-315. doi:10.1111/j.1540-5915.2008.00192.x.
132. Verhagen, T., Meents, S., & Tan, Y. (2006). Perceived risk and trust associated with purchasing at electronic marketplaces. European Journal of Information Systems, 15, 542–555.
133. Wafiyyah, R. S.; Kusumadewi, N.M.W. (2021). The effect of perceived usefulness, perceived ease of use, and trust on repurchase intention on ECommerce Shopee. International Journal of Innovative Science, Vol. 8, pp. 2348 – 7968.
134. Wan, J.; Ehrmann, T. (2017). The Art Market in 2017. Retrived from Artprice Website: https://www.artprice.com/artprice-reports/the-art-market-in-2017 (Accessed on 20 Aug. 2021).
135. Wang, S.; Archer, N. (2017). Strategic choice of electronic marketplace functionalities: a buyer-supplier relationship perspective. Journal of Computer-Mediated Communication, 10(1). doi:10.1111/j.1083-6101.2004.tb00236.x
136. Wang, Z.; L. Yang, Q.; Wang, D. L.; Xu Z.; Liu, S. (2019). Art chain: Blockchain-enabled platform for art marketplace. Proceedings of 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), Seoul, South Korea, pp. 447-454, doi:10.1109/Blockchain.2019.00068.
137. Whitaker, A. and Kraussl, R. (2018). Democratizing art markets: fractional ownership and the securitization of art. SSRN Electronic Journal. doi:10.2139/ssrn.3100389.
138. Whitaker, A. (2019). Art and blockchain: a primer, history, and taxonomy of blockchain use cases in the arts. Artivate, 8(2), pp. 21-46.
139. Wilmoth, J. (2018). Patent application eyes Bitcoin Blockchain for artwork provenance. Retrived from Yahoo! finance Website: https://finance.yahoo.com/news/patent-application-eyes-bitcoin-blockchain-184556575.html (Accessed on 15 Oct. 2021)
140. Wilson, N.; Keni, K.; Tan, P.; Henriette, P. (2021). The role of perceived usefulness and perceived ease-of-use toward satisfaction and trust which influence computer consumers' loyalty in China. Gadjah Mada International Journal of Business, Vol. 23 Issue 3, p262-294. 33p.
141. Wingreen, S.C.; Baglione, S.L. (2005). Untangling the antecedents and covariates of e-commerce trust: Institutional trust vs. knowledge-based trust. Electronic Market, 15(3), pp. 246-260.
142. Yao, W.; Ye, J.;Murimi, R.; Wang, G.(2021). A survey on consortium Blockchain consensus mechanisms. Cornell University. ArXiv. org. Retrived fromhttps://arxiv.org/pdf/2102.12058.pdf (Accessed on 7, Oct. 2021).
143. Zand, D.E. (1972). Trust and managerial problem solving. Administrative science quarterly, pp. 229-239. doi:10.2307/2393957
144. Zeren, D.; Kara, A. (2021). Effects of brand heritage on intentions to buy of airline services: the mediating roles of brand trust and brand loyalty. Sustainability, 13, 303. doi:10.3390/su13010303
145. Zhang, H. (2021). Online travel agencies in China: The impact of online reviews, trust, perceived risk, perceived ease of use, perceived usefulness and perceived enjoyment on purchase intention. Bangkok University, Thailand. Retrived from http://dspace.bu.ac.th/handle/123456789/4975 (Accessed on 11, Nov. 2021)
146. Zhang, W.; Zhang, X.; Tian, X.; Sun, F. (2021). Economic policy uncertainty nexus with corporate risk-taking: the role of state ownership and corruption expenditure. Pacific-Basin Finance Journal, Vol. 65(C). doi:0.1016/j.pacfin.2021.101496
147. Zheng, Y. (2021). Blockchain, Privacy, and Artwork Registries: Consensus between Constraints. New York University, New York City, USA. Retrived from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3857241 (Accessed on 27 Sept. 2021).
148. Zucker, L. (1986). Production of trust: institutional sources of economic structure, 1840-1920. Research in Organizational Behavior, Volume 8, pp. 53-111.
Description: 博士
國立政治大學
資訊管理學系
104356512
Source URI: http://thesis.lib.nccu.edu.tw/record/#G0104356512
Data Type: thesis
Appears in Collections:[資訊管理學系] 學位論文

Files in This Item:

File Description SizeFormat
651201.pdf3341KbAdobe PDF0View/Open


All items in 學術集成 are protected by copyright, with all rights reserved.


社群 sharing