網路圍棋人機對弈之觀眾行為意圖研究

A Study on the Audience's Behavior Intention of Watching Human-Machine Competition in the Game of Go on the Internet

10.6214/JSRM.202212_19(2).0003

林俊毅(Chun-Yi Lin)；林淑芬(Shu-Fen Lin)

圍棋 ； 知覺玩興 ； 科技接受模式 ； 計畫行為理論 ； GO ； Perceived Playfulness ； Theory of Planned Behavior (TPB) ； Technology Acceptance Model (TAM)

運動休閒管理學報

19卷2期（2022 / 12 / 01）

42 - 62

繁體中文

本研究整合科技接受模式與計畫行為理論作為理論基礎，並以知覺玩興為延伸變數，驗證觀棋者於網路圍棋平台上觀看人機對弈的行為意圖模式。於2019/1/12至2019/3/3採網路問卷調查獲得447份有效樣本，資料使用AMOS進行驗證性因素分析及結構方程模型以驗證研究假設，十條假設路徑中唯獨一條假設未獲得支持，其理論模式配適度良好。研究結果發現：一、知覺玩興正向影響知覺易用性、知覺有用性及行為意圖，且易用性及有用性在知覺玩興對行為態度的關係具完全中介效果。二、科技接受模式架構中，知覺易用性正向影響知覺有用性及行為態度，知覺有用性正向影響行為態度。三、計畫行為理論中，行為態度、主觀規範及知覺行為控制對行為意圖皆有正向影響。分析結果顯示知覺玩興對行為意圖的總效果最為關鍵。文末對後續研究及管理實務上做出建議。

This study integrates the technology acceptance model (TAM) and the theory of planned behavior (TPB) as the theoretical basis, and takes perceived playfulness as an extended variable to verify the behavioral intention model of watching human-machine competition on the online GO platform. This study conducts a web survey from 2019/1/12 to 2019/3/3 and collects 447 samples, and the data using AMOS for confirmatory factor analysis and structural equation modeling to verify the research hypotheses. This study used structural equation model the hypotheses, ten hypotheses path alone a hypothesis is not supported, the theoretical model with moderately fit. The results were as follows: 1. Perceived playfulness positively affected perceived ease-of-use, perceived usefulness, and behavioral intentions, the effects of attitude from perceived playfulness were fully mediated by perceived ease-of-use and usefulness.2. In TAM, perceived ease-of-use was positive and significant effect on usefulness and attitude; perceived usefulness has a positive and significant effect on attitude. 3. In TPB, attitude, subjective norms and perceived behavioral control have positive effects on behavioral intention. The results show perceived playfulness was the most important to behavioral intention. Finally, based on the results, some related suggestions were provided for future research.

1. 王月鶯、李世昌、徐茂洲、顏君彰(2014)。大學生觀賞美國職棒大聯盟的行為意圖模式。大專體育學刊，16(3)，297-310。
   連結：
2. 王凱立、蕭敬安(2021)。運動競技新模式：參與者對虛實整合運動競技模式的接受度探討。運動休閒管理學報，18(1)，99-111。
   連結：
3. 余宗龍(2014)。建構職棒球賽再次購票觀賞的行為意圖模式：以涉入程度為區隔變數。大專體育學刊，16(2)，151-166。
   連結：
4. 徐茂洲、吳兆欣、謝仁瑋(2017)。臺灣球迷線上收看中華職棒比賽行為意圖模式之研究—結合科技接受模式與計畫行為理論。運動研究，26(1)，1-20。
   連結：
5. Abdullah, F., Ward, R., & Ahmed, E. (2016). Investigating the influence of the most commonly used external variables of TAM on students’ Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of e-portfolios. Computers in Human Behavior, 63, 75-90.
   連結：
6. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
   連結：
7. Bollen, K. A., & Stine, R. A. (1992). Bootstrapping goodness-of-fit measures in structural equation models. Sociological Methods & Research, 21(2), 205-229.
   連結：
8. Cheng, E. W. (2019). Choosing between the theory of planned behavior (TPB) and the technology acceptance model (TAM). Educational Technology Research and Development, 67(1), 21-37.
   連結：
9. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3) 319-340.
   連結：
10. 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.
    連結：
11. Ha, Y., & Im, H. (2014). Determinants of mobile coupon service adoption: assessment of gender difference. International Journal of Retail & Distribution Management, 42(5), 441-459.
    連結：
12. Hsu, C. L., Chang, K. C., & Chen, M. C. (2012). The impact of website quality on customer satisfaction and purchase intention: perceived playfulness and perceived flow as mediators. Information Systems and eBusiness Management, 10(4), 549-570.
    連結：
13. Huang, L. C., & Shiau, W. L. (2015). Why do people use microblogs? An empirical study of Plurk. Information Technology & People, 28(2), 281-303.
    連結：
14. Koivisto, J., & Hamari, J. (2019). The rise of motivational information systems: A review of gamification research. International Journal of Information Management, 45, 191-210.
    連結：
15. Liao, C. H., & Tsou, C. W. (2009). User acceptance of computer-mediated communication: The SkypeOut case. Expert Systems with Applications, 36(3, Part 1), 4595-4603.
    連結：
16. Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230.
    連結：
17. Padilla-MeléNdez, A., Del Aguila-Obra, A. R., & Garrido-Moreno, A. (2013). Perceived playfulness, gender differences and technology acceptance model in a blended learning scenario. Computers & Education, 63, 306-317. https://doi.org/10.1016/j.compedu.2012.12.014
    連結：
18. Potwarka, L. R., Nunkoo, R., & McCarville, R. E. (2014). Understanding television viewership of a mega event: The case of the 2010 Winter Olympics. Journal of Hospitality Marketing & Management, 23(5), 536-563.
    連結：
19. Proyer, R. T., & Brauer, K. (2018). Exploring adult playfulness: Examining the accuracy of personality judgments at zero-acquaintance and an LIWC analysis of textual information. Journal of Research in Personality, 73, 12-20.
    連結：
20. Riskinanto, A., Kelana, B., & Hilmawan, D. R. (2017). The Moderation Effect of Age on Adopting E-Payment Technology. Procedia Computer Science, 124, 536-543.
    連結：
21. Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54-67.
    連結：
22. Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13-35.
    連結：
23. Schreiber, J. B. (2017). Update to core reporting practices in structural equation modeling. Research in Social and Administrative Pharmacy, 13(3), 634-643.
    連結：
24. Sjöblom, M., & Hamari, J. (2017). Why do people watch others play video games? An empirical study on the motivations of Twitch users. Computers in Human Behavior, 75, 985-996. https://doi.org/10.1016/j.chb.2016.10.019
    連結：
25. Song, J., Kim, J., & Cho, K. (2018). Understanding users’ continuance intentions to use smart-connected sports products. Sport Management Review, 21(5), 477-490.
    連結：
26. Starbuck, W. H., & Webster, J. (1991). When is play productive? Accounting, Management and Information Technologies, 1(1), 71-90.
    連結：
27. Taherdoost, H. (2018). A review of technology acceptance and adoption models and theories. Procedia Manufacturing, 22, 960-967.
    連結：
28. Tamilmani, K., Rana, N. P., Prakasam, N., & Dwivedi, Y. K. (2019). The battle of Brain vs. Heart: A literature review and meta-analysis of “hedonic motivation” use in UTAUT2. International Journal of Information Management, 46, 222-235.
    連結：
29. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
    連結：
30. Tinati, R., Luczak-Roesch, M., Simperl, E., & Hall, W. (2017). An investigation of player motivations in Eyewire, a gamified citizen science project. Computers in Human Behavior, 73, 527-540.
    連結：
31. Ting, H., Yacob, Y., Liew, L., & Lau, W. M. (2016). Intention to use mobile payment system: A case of developing market by ethnicity. Procedia-Social and Behavioral Sciences, 224, 368-375.
    連結：
32. Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision Sciences, 33(2), 297-316.
    連結：
33. Wang, R. T., Zhang, J. J., & Tsuji, Y. (2011). Examining fan motives and loyalty for the Chinese Professional Baseball League of Taiwan. Sport Management Review, 14(4), 347-360.
    連結：
34. Yakasai, A. B. M., & Jusoh, W. J. W. (2015). Testing the Theory of Planned Behavior in determining intention to use digital coupon among university students. Procedia Economics and Finance, 31, 186-193.
    連結：
35. 王銘琬(2017)。迎接AI新時代：用圍棋理解人工智慧。台北市：遠流。
36. 周君倚、陸洛(2014)。以科技接受模式探討數位學習系統使用態度－以成長需求為調節變項。資訊管理學報，21(1)，83-106。
37. 陳寬裕、王正華(2018)。結構方程模型：運用AMOS分析。台北市: 五南圖書。
38. Bollen, K. A. (1989). Structural equations with latent variables. New York, NY: Wiley.
39. Oh, C., Lee, T., Kim, Y., Park, S., & Suh, B. (2017). Us vs. Them: Understanding Artificial Intelligence Technophobia over the Google DeepMind Challenge Match. Paper presented at the Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems.
40. Sinthamrong, P., & Rompho, N. (2015). Factors affecting attitudes and purchase intentions toward branded content on webisodes. Journal of Management Policy and Practice, 16(4), 64-72.

1. 黃美華,黃子恩,邱紹群,林靜汶(2023)。後疫情時代雲端發票續用意願之研究。管理資訊計算，12(2)，73-87。