請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/69639完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳郁蕙(Yu-Hui Chen) | |
| dc.contributor.author | Colby Hyde | en |
| dc.contributor.author | 周海闊 | zh_TW |
| dc.date.accessioned | 2021-06-17T03:22:01Z | - |
| dc.date.available | 2018-07-02 | |
| dc.date.copyright | 2018-07-02 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-06-21 | |
| dc.identifier.citation | Chen, Chun-chao (陳春朝). (2017). Interview (Shih-chun Hsu, 許詩淳,Trans).
Chen, Shou-ren (陳守仁)、黃建智、陳羿惠、吳龍靜. (2010). 《流動的水晶─台灣櫻花蝦》. 〈科學發展〉, 452 期. Li, Yi-jie (李懿潔). (2013).《共有資源的民主治理：以東港櫻花蝦產銷班為例》. 國立 中山大學：社會學習. 碩士論文. Wu, Jin-zhen (吳金鎮). (2009). 《東港櫻花蝦漁業共同管理制度之研究》.國立臺灣海洋大學：環境生物與漁業科學學習. 博士學位論文. Ambrus, A., & Greiner, B. (2012). Imperfect public monitoring with costly punishment: an experimental study. The American Economic Review, 102(7), 3317-3332. doi: 10.1257/aer.102.7.3317 Anderies, J. M., Janssen, M. A., Bousquet, F., Cardenas, J., Castillo, D., Lopez, M., & Tobias, R. (2011). The challenge of understanding decisions in experimental studies of common pool resource governance. Ecological Economics, 70(9), 1571- 1579. doi: 10.1016/j.ecolecon.2011.01.011 Andreoni, J. (1988). Why free ride? Strategies and learning in public goods experiments. Journal of Public Economics, 37(1), 291-304. doi: 10.1016/0047-2727(88)90043-6 Apesteguia, J., & Maier-Rigaud, F. P. (2006). The role of rivalry: public goods versus common-pool resources. The Journal of Conflict Resolution, 50(5), 646-663. doi: 10.1177/0022002706290433 Bailey, M., Sumaila U.R. (2008). Destructive fishing in Raja Ampat, Indonesia: An applied principal-agent analysis. Pages 143-169 in Bailey, M., Pitcher, T.J. (Eds), Ecological and Economic Analyses of Marine Ecosystems in the Bird’s Head Seascape, Papua, Indonesia: II. Fisheries Centre Research Reports, 16(1). Bailey, M., Sumaila, U. R., & Lindroos, M. (2010). Application of game theory to fisheries over three decades. Fisheries Research, 102(1), 1-8. doi:10.1016/j.fishres.2009.11.003 Basurto, X., Blanco, E., Nenadovic, M., & Vollan, B. (2016). Integrating simultaneous prosocial and antisocial behavior into theories of collective action. Science Advances, 2(3), 1-10. doi: 10.1126/sciadv.1501220 doi: 10.6342/NTU201800921 Cason, T. N., & Gangadharan, L. (2016). Swords without covenants do not lead to selfgovernance. Journal of Theoretical Politics, 28(1), 44-73. doi:10.1177/0951629814539199 Cason, T. N., & Gangadharan, L. (2014). Promoting cooperation in nonlinear social dilemmas through peer punishment. Experimental Economics, 18(1). doi: 10.1007/s10683-014-9393-0 de Souza EN, Boerder K, Matwin S, & Worm B. (2016). Improving fishing pattern detection from satellite AIS using data mining and machine learning. PLoS ONE, 11(7): e0158248. doi: 10.1371/journal.pone.0158248 Dunbar, R. (1992). Neocortex size as a constraint on group size in primates. Journal of Human Evolution, 22(6), 469-493. doi: 10.1016/0047-2484(92)90081-J du Toit, J., & van Vuuren, J. H. (2014). Semi-automated maritime vessel activity detection using hidden Markov models. Proceedings of the 2014 ORSSA Annual Conference, 71-78. Fehr, E., & Gachter, S. (2000). Cooperation and punishment in public goods experiments. The American Economic Review, 90(4), 980-994. doi: 10.1257/aer.90.4.980. Fischbacher, U. (2007). Z-Tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10(2), 171-178. Fischer, S., Grechenig, K., & Meier, N. (2013). Cooperation under punishment: imperfect information destroys it and centralizing punishment does not help. Max Planck Institute for Research on Collective Goods. University of Bonn. 1-26. doi: 10.2139/ssrn.2243478 Grechenig, K., Nicklisch, A., & Thoni, C. (2010). Punishment despite reasonable doubt— a public goods experiment with sanctions under uncertainty. Journal of Empirical Legal Studies, 7(4), 847-867. doi: 10.1111/j.1740-1461.2010.01197.x Hardin, G. (1968). The tragedy of the commons. Science, 162(3859), 1243-1248. doi: 10.1126/science.162.3859.1243 Herrmann, B., Thoni, C., & Gachter, S. (2008). Antisocial punishment across societies. Science, 319(5868), 2-7. doi: 10.1126/science.1153808 Joo R, Bertrand S, Tam J, & Fablet R. (2013). Hidden Markov models: the best models for forager movements? PLoS ONE, 8(8): e71246. doi:10.1371/journal.pone.0071246 doi: 10.6342/NTU201800921 Kimbrough, E. O., & Vostroknutov, A. (2015). The social and ecological determinants of common pool resource sustainability. Journal of Environmental Economics and Management, 72(1), 38-53. doi: 10.1016/j.jeem.2015.04.004 Kopelman, S., Weber, J., & Messick, D. (2002). Factors influencing cooperation in commons dilemmas: a review of experimental psychological research. In The Drama of the Commons (pp. 171-178). Ostrom, E., Dietz, T., Dolsak, N., Stern, P. C., Stonich, S., & Weber, E. U. (Eds.). (2002). Washington, D.C.: National Academy Press. doi: 10.17226/10287 Levy, D. M., Padgitt, K., Peart, S. J., Houser, D., & Xiao, E. (2010). Leadership, cheap talk and really cheap talk. Journal of Economic Behavior & Organization, 77(1), 40-52. doi: 10.1016/j.jebo.2010.02.018 Lindroos, M., Kaitala, V., & Kronbak, L. G. (2007) Coalition games in fisheries economics, in Advances in Fisheries Economics: Festschrift in Honour of Professor Gordon R. Munro (eds T. Bjørndal, D. V. Gordon, R. Arnason & U. R. Sumaila), Blackwell Publishing Ltd, Oxford, UK. doi: 10.1002/9780470751589.ch11 Markussen, T., & Putterman, L. (2017). Governing collective action in the face of observational error. Working Paper, Brown University. 1-64. doi: 10.2139/ssrn.3019405 McCauley, D. J., Woods, P., Sullivan, B., Bergman, B., Jablonicky, C., Roan, A., & Hirshfield, M. (2016). Ending hide and seek at sea: new technologies could revolutionize ocean observation. Science, 351(6278), 1148-1150. doi: 10.1126/science.aad5686 Munro, G. R. (2009). Game theory and the development of resource management policy: the case of international fisheries. In Game Theory, Natural Resources, and the Environment, (pp. 7-27). Dinar, A., Albiac, J., & Sánchez-Soriano, J. (Eds.). (2009). Game Theory and Policy Making in Natural Resources and the Environment. London: Routledge. Nash, J. (1953). Two-person cooperative game. Econometrica, 21(1), 128-140. doi: 10.2307/1906951 Natale F, Gibin M, Alessandrini A, Vespe M, & Paulrud A. (2015). Mapping fishing effort through AIS data. PLoS ONE, 10(6): e0130746. doi: 10.1371/journal.pone.0130746 Nicholson, W., & Snyder, C. (2012). Game Theory. In Microeconomic Theory: Basic Principles and Extensions (11th ed., pp. 251-302). Mason, OH: South-Western: CENGAGE Learning. doi: 10.6342/NTU201800921 84 Nicklisch, A., Grechenig, K., & Thoeni, C. (2016). Information-sensitive leviathans, CeDEx Discussion Paper Series, No. 2016-12. doi: 10.1016/j.jpubeco.2016.09.008 Nosenzo, D., Quercia, S., & Sefton, M. (2013). Cooperation in small groups: the effect of group size. Experimental Economics, 18(1), 4-14. doi: 10.1007/s10683-013-9382-8 Ostrom, E. (2010). Beyond markets and states: polycentric governance of complex economic systems. American Economic Review, 100(3), 641-672. doi: 10.1257/aer.100.3.641 Ostrom, E., Walker, J., & Gardner, R. (1992). Covenants with and without a sword: selfgovernance is possible. The American Political Science Review, 86(2), 404-417. doi: 10.2307/1964229 Ostrom, Elinor. (1990). Governing the Commons: The Evolution of Institutions for Collective Action. Cambridge, UK: Cambridge University Press. doi: 10.1017/CBO9781316423936 Peel, D., & Good, N. M. (2011). A hidden Markov model approach for determining vessel activity from vessel monitoring system data. Canadian Journal of Fisheries and Aquatic Science, 1252-1264. doi: 10.1139/f2011-055 R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.Rproject. org/. Shreedhar, G., Tavoni, A., & Marchiori, C. (2016). Monitoring networks in a common pool resource dilemma: experimental evidence on extraction, punishment and beliefs (Doctoral dissertation, LSE, London). Townsend, R. E. (2010). Transactions costs as an obstacle to fisheries self-governance in New Zealand. The Australian Journal of Agricultural and Resource Economics, 54(1), 301-320. doi: 10.1111/j.1467-8489.2010.00494.x University of Zurich. Z-Tree 3.5: Tutorial and Reference Manual. Wallace, F., Williams, K., Towler, R., & McGauley, K. (2015). Innovative camera applications for electronic monitoring. In Fisheries Bycatch: Global Issues and Creative Solutions. Alaska Sea Grant, University of Alaska Fairbanks. doi: 10.4027/fbgics.2015.06 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/69639 | - |
| dc.description.abstract | 受台灣東港櫻花蝦共同管理組織成功案例之啟發，本研究利用一具有懲罰不合作者機制的共有資源賽局實驗，分析參與者在資訊不完整情形下之合作行為，主要變數為漁業資源監控的潛在錯誤。參與者共分為四組，賽局進行方式採志願投資機制 (voluntary contribution mechanism, VCM)，參與者可自由分配初始資金至私人投資或是共同經營投資，同組參與者可看到其他組員於共同經營部分的投資量，並可將初始資金用於懲罰不合作者。為凸顯監控錯誤之可能性，遊戲過程中顯示同組組員於共同經營部分的投資量存在誤差，誤差共有三種版本，分別服從標準差0、0.5、1 的常態分配。
實驗結果顯示參與者互相懲罰的頻率及額度隨監控誤差增加而提升，但懲罰效果卻下降。在標準差為 0.5 的版本下參與者懲罰的頻率及額度顯著較高，同時也因投入在共同經營部分額度小，反而有高單位報酬。懲罰系統在實驗中扮演重要角色但可能不適合應用於本研究的志願投資機制。 | zh_TW |
| dc.description.abstract | An experimental, common-pool resource game with a decentralized sanctioning mechanism was tested to analyze the effects of imperfect information on co-management
cooperation. A co-management organization of Sakura Shrimp fishermen in Donggang, Taiwan, served as inspiration for this experiment. Potential errors in fisheries monitoring technologies were the key experimental variable. The game followed the design of a voluntary contribution mechanism (VCM) with a private market and a common-pool resource market dependent on the collective contributions of all players in groups of four. Players observed the contributions of others within their group and were given the opportunity to punish non-cooperators. Subjects participated in one of three versions of the game, each varying the accuracy of the contribution signal displayed. Errors in the signal were normally distributed from the actual contribution value with standard deviations of 0, 0.5, and 1. Player punishments increased in both frequency and severity with increases in signal noise. However, the effect of punishment also decreased with increasing noise. Players in the treatment with standard deviation equal to 0.5 significantly punished more often and more severely. And yet also contributed significantly less to the common-pool resource and thus experienced consistently higher yields and efficiency. Anti-social punishment played a major role in all treatments and may not be appropriate for a voluntary contribution mechanism of this design. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T03:22:01Z (GMT). No. of bitstreams: 1 ntu-107-R05627040-1.pdf: 6969820 bytes, checksum: 452537580f82b99779f63c9e3e04e461 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | List of Tables……………………………………………………………………… v
List of Figures…………………………………………………………………… vi Acronyms…………………………………………………………………………. vii Chapter 1 Introduction…………………………………………………………… 1 1.1 Motivation…………………………………………………………… 1 1.2 Purpose……………………………………………………………… 3 1.3 Structure of Thesis…………………………………………………… 4 Chapter 2 Background…………………………………………………………… 5 2.1 Common-pool Resources and Co-Management……………………… 5 2.2 History of the Sakura Shrimp Industry in Donggang, Taiwan………. 10 2.3 Donggang’s Successful Co-Management…………………………… 20 Chapter 3 Literature Review……………………………………………………… 22 Chapter 4 Methodology…………………………………………………………… 28 4.1 Game Theory………………………………………………………… 28 4.2 Experimental Economics……………………………………………… 31 4.3 Game Design………………………………………………………… 32 4.4 Estimation Models and Methods……………………………………… 41 Chapter 5 Empirical Estimation and Results……………………………………… 47 5.1 Hypothesis…………………………………………………………… 47 5.2 Game Outcome……………………………………………………… 51 5.3 Non-Parametric Empirical Results…………………………………… 54 5.4 Linear Regression Empirical Results………………………………… 57 Chapter 6 Discussion……………………………………………………………… 66 6.1 Discussion of Major Results…………………………………………… 66 6.2 Application to Donggang……………………………………………… 70 6.3 Possible Errors………………………………………………………… 73 6.4 Further Research……………………………………………………… 74 Chapter 7 Conclusion……………………………………………………………… 78 References………………………………………………………………………… 81 Appendix………………………………………………………………………… 85 A.1 Game Introduction—English / Chinese……………………………… 85 A.2 Game Instructions—English / Chinese……………………………… 89 A.3 Z-Tree Code Example………………………………………………. 93 | |
| dc.language.iso | en | |
| dc.title | 賽局理論於東港櫻花蝦漁業資源共管之應用 | zh_TW |
| dc.title | Game Theory in Reel Life: Resource Co-Management in the Donggang Sakura Shrimp Fishery | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 胡明哲(Ming-Che Hu),詹滿色(Man-Ser Jan) | |
| dc.subject.keyword | 共有資源,賽局理論,共同管理,不確定性,志願投資機制,Z-Tree,電子監控, | zh_TW |
| dc.subject.keyword | common-pool resource,game theory,co-management,uncertainty,volunteer contribution mechanism,Z-Tree,electronic monitoring, | en |
| dc.relation.page | 93 | |
| dc.identifier.doi | 10.6342/NTU201800921 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-06-21 | |
| dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
| dc.contributor.author-dept | 農業經濟學研究所 | zh_TW |
| 顯示於系所單位： | 農業經濟學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-107-1.pdf 目前未授權公開取用 | 6.81 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。