請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80582完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 馬鴻文(Hwong-Wen Ma) | |
| dc.contributor.author | Hio-Lam Lai | en |
| dc.contributor.author | 黎曉琳 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:09:55Z | - |
| dc.date.available | 2021-11-03 | |
| dc.date.available | 2022-11-24T03:09:55Z | - |
| dc.date.copyright | 2021-11-03 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-10-24 | |
| dc.identifier.citation | [1] Biswas, A. Roy, M. (2016). A study of consumers’ willingness to pay for green products. Journal of Advanced Management Science, 4(3), pp. 211–215. [2] Archila A. Moreno S. (2001). Neuropsyhological test performance in Auuaco Indians : an exploratory study. J Int Neuropsychol Soc, 7, pp. 510 -515. [3] Athanasiadis, I. N., A. K. Mentes, P. A. Mitkas, and Y. A. Mylopoulos (2005). A hybrid agent‐based model for estimating residential water demand Simulation, 81, pp. 175-187. [4] Ajzen, I., Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall. [5] Ajzen, I. (1985). From intentions to action: A theory of planned behavior. In J. Kuhl J. Beckman (Eds.), Action control: From cognitions to behaviors, pp. 11–39. [6] Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, pp. 179-211. [7] Anink D, Mak J Boonstra C. (1996). Handbook of sustainable building: an environmental preference method for selection of materials for use in construction refur-bishment. London: James James. [8] Amyx, D. A., DeJong, P. F., Lin, X., Chakraborty, G., Wiener, J. L. (1994). Influencers of purchase intentions for ecologically safe products: An exploratory study. InAMA winter educators’ conference proceedings, 5, pp. 341-347. [9] A.O. Abisuga O.O. Oyekanmi. (2014). Organizational factors affecting the usage of sustainable building materials in the Nigerian construction industry. J. Emerg. Trends Econ. Manag. Sci., 5 (2), pp. 113-122. [10] A. Raihanian Mashhadi S. Behdad. (2018). Environmental impact assessment of the heterogeneity in consumers’ usage behavior: An agent-based modeling approach. J Ind Ecol, 22 (4), pp. 706-719. [11] Babaei, A.A., Alavi, N., Goudarzi, G., Teymouri, P., Ahmadi, K. Rafiee, M. Household recycling knowledge, attitudes and practices towards solid waste management. Resour. Conserv. Recycl., 102, 94–100. [12] Bamberg, S., Hunecke, M. Blo¨baum, A. (2007). “Social context, personal norms the use of public transportatio n: two field studies”. Journal of Environmental Psychology, 27(3), pp. 190-203. [13] Best, H. Mayerl, J. (2013). Values, beliefs, attitudes: An empirical study on the structure of environmental concern and recycling participation. Soc. Sci. Q., 94, pp. 691–714. [14] C. Caprioli, M. Bottero E. De Angelis. (2020). Supporting policy design for the diffusion of cleaner technologies: a spatial empirical agent-based model. ISPRS Int. J. Geo-Inf., 9 (10), pp. 581-589. [15] Chaniotakis, I., and Lymperopoulos, C. (2009). Service quality effect on satisfaction and word-of-mouth in the healthcare industry. Managing Service Quality, 19(2), pp. 229-242. [16] Chen, Y., Wang, Q., Xie, J. (2011). Online social interactions: A natural experiment on word of mouth versus observational learning. Journal of Marketing Research, 48(2), pp. 238–254. [17] Chen, Y.S., Lin, C.L., Chang, C.H. (2014). The influence of greenwash on green word-of-mouth (green WOM): the mediation effects of green perceived quality and green satisfaction. Qual. Quant. 48(5), pp. 2411–2425. [18] C. Jebarajakirthy A.C. Lobo. (2014). War affected youth as consumers of microcredit: an application and extension of the theory of planned behavior J. Retail. Consum. Serv., 21(3), pp. 239-248 [19] Close A. Akhtar A.K. Sarmah. (2018). C D waste generation properties of recycled aggregate concrete: a global perspective J. Clean. Prod., 186, pp. 262-281. [20] Delaware. K. (2003). Construction demolition waste management:assessment of dem supply of recycled materials in the Western Cape. University of Cape Town. [21] Ding, Z., Wang, Y., Zou. P.X.W. (2016). An agent based environmental impact assessment of building demolition waste management: conventional versus green management J. Clean. Prod., 133, pp. 1136-1153 [22] Ding, Z., Gong, W., Li, S., Wu, Z. (2018). System Dynamics versus Agent-Based Modeling: A Review of Complexity Simulation in Construction Waste Management. Sustainability, 10, 2484. [23] D.J. Bryde L. Robinson. (2005). Client versus contractor perspectives on project success criteria International Journal of Project Management, 23 (8), pp. 622-629. [24] Fishbein, M., Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley. [25] Gifford, R. Nilsson, A. (2014). Personal and social factors that influence pro-environmental concern and behaviour: A review. Int. J. Psychol, 49, pp. 141–157. [26] Hansen, T. (2005). “Adoption of online grocery buying: a discriminant analysis”. International Journal of Retail Distribution Management, 33(2), pp. 101-121. [27] Hatfield-Dodds, S., H. Schl, D. Newth, M. Obersteiner, Y. Cai, T. Baynes, J. West, P. Havlik. (2017). Assessing global resource use greenhouse emissions to 2050, with ambitious resource efficiency climate mitigation policies. Journal of Cleaner Production, 144, pp. 403-414. [28] H. Muelder T. Filatova. (2018). One theory - many formalizations: testing different code implementations of the theory of planned behaviour in energy agent-based models J. Artif. Soc. Soc. Simul., 21, pp. 5. [29] International Resource Panel (IRP). (2019). Global Resources Outlook 2019: Natural Resources for the Future We Want. A Report of the International Resource Panel. United Nations Environment Programme. Nairobi, Kenya. [30] International Resource Panel (IRP). (2018). Resource Efficiency for Sustainable Development: Key Messages for the Group of 20. [31] I. Sartori A.G. Hestnes. (2007). Energy use in the life cycle of conventional lowenergy buildings: a review article, Energy Buildings, 39, pp. 249–257. [32] J. Waskito, I. Imronudin C. Chuzaimah. (2019).'Observing pro-environmental behavior based on consumer attitudes norms'. Diponegoro International Journal of Business, 2(2), pp. 76-85. [33] Kinzig, A. P. et al. (2013). Social norms global environmental challenges: the complex interaction of behaviors, values, policy. BioScience, 63, pp. 164–175. [34] Labelle, A. Frayret, J.-M. (2018). Agent-Based Model for End-of-Life Product Flow Analysis. Resources, 7, pp. 42-50. [35] Laroche, M., Bergeron, J. Barbaro-Forleo, G., (2001). Targeting Consumers Who Are Willing to Pay More for Environmentally Friendly Products, Journal of Consumer Marketing, 18(6), pp. 503-520. [36] J. Li, J. Zuo, H. Cai, G. Zillante. (2018). Construction waste reduction behavior of contractor employees: an extended theory of planned behavior model approach J Clean Prod, 172, pp. 1399-1408. [37] L. Linkola, C.J. Andrews T. Schuetze. (2013). An agent-based model of household water use. Water, 5(3), pp. 1082-1100. [38] Loughlin D. H. Barlaz M. A. (2006). Policies for strengthening markets for recyclables: a worldwide perspective. Environ. Sci. Technol. 36, pp. 287–326. [39] Macal. CM North. MJ. (2010). Tutorial on agent-based modelling and simulation. J Simul. 4, pp. 151–162. [40] Keller, E., Fay, B. (2012). Word-of-mouth advocacy: A new key to advertising effectiveness. Journal of Advertising Research, 52, pp. 459–464. [41] K. Maichum, S. Parichatnon, K.C. Peng. (2016). Application of the extended theory of planned behavior model to investigate purchase intention of green products among Thai consumers Sustainability, 8(10), pp. 1077-1089. [42] M. Luo, X. Song, S. Hu, et al. (2019). Towards the sustainable development of waste household appliance recovery systems in China: an Agent-based modeling approach J. Clean. Prod., 220, pp. 431-444. [43] Macovei, O. I. (2015). Determinants of Consumers’ Pro-Environmental Behavior–Toward an Integrated Model. Journal of Danubian Studies and Research, 5(2), pp. 261-275. [44] Macovei, O.-I. (2015). Applying the theory of planned behavior in predicting proenvironmental behaviour: The case of energy conservation. Int. J. Approx. Reason. 54, pp. 701–716. [45] Mercure, J.-F. et al. (2018). Environmental impact assessment for climate change policy with the simulation-based integrated assessment model E3ME-FTT-GENIE. Energy Strategy Rev. 20, pp. 195–208. [46] M. Tonglet, P.S. Phillips A.D. (2004). Read Using the theory of planned behaviour to investigate the determinants of recycling behaviour: A case study from Brixworth, UK Resources Conservation and Recycling, 41, pp. 191-214. [47] N.Z. Abidin. (2009). Sustainable construction in Malaysia developers’ awareness World Acad. Sci. Eng. Tech., 53, pp. 807-814. [48] C. Oztekin, G. Teksoz, S. Pamuk, E. Sahin, D.S. Kilic. (2017). Gender perspective on the factors predicting recycling behavior: implications from the theory of planned behavior Waste Manag., 62, pp. 290-302. [49] OECD. (2019). Skills Matter: Additional Results from the Survey of Adult Skills. [50] Ohtomo, S. Hirose, Y. (2007). The dual-process of reactive inte ntional decision-making involved in eco-friendly behavior. Journal of Environmental Psychology, 27(2), pp. 117-125. [51] López-Mosquera, N., Lera-López, F. Sánchez, M. (2015). Key factors to explain recycling, car use and environmentally responsible purchase behaviors: A comparative perspective. Resour. Conserv. Recycl., 99, pp. 29–39. [52] P. Kunzlik. (2003). The environmental performance of public procurement: issues of policy coherence N. Johnstone (Ed.) (1st ed.), Organisation for Economic Cooperation Development, Paris, pp. 157-235. [53] Railsback, S.F. Grimm, V. (2011). Agent-Based and Individual-Based Modeling: A Practical Introduction; Princeton University Press: Princeton, NJ, USA. [54] R. Jin, B. Li, T. Zhou, D. Wanatowski P. Piroozfar. (2017). An empirical study of perceptions towards construction demolition waste recycling reuse in China Resour. Conserv. Recycling, 126, pp. 86-98. [55] Rai, V. Robinson, S. A. (2015). Agent-based modeling of energy technology adoption: empirical integration of social, behavioral, economic, and environmental factors. Environ. Modell. Softw., 70, pp. 163–177. [56] Schramm ME, Trainor KJ, Shanker M, Hu MY. (2010) An agent-based diffusion model with consumer and brand agents. Decis Support Syst., 50(1), pp. 234–242. [57] Shimp, T., Kavas, A. (1984). The theory of reasoned action applied to coupon usage. Journal of Consumer Research, 11, pp. 795-809. [58] Sidique, S.F., Joshi, S.V. Lupi, F. (2010). Factors influencing the rate of recycling: An analysis of Minnesota counties. Resour. Conserv. Recycl., 54, pp. 242–249. [59] Spoerri A, Lang DJ, Binder CR Scholz RW (2009). Expert-based scenarios for strategic waste and resource management planning—C D waste recycling in the Canton of Zurich, Switzerland. Resour Conserv Recycling, 53, pp. 592–600. [60] Stern, P.C. (2000). New environmental theories: Toward a coherent theory of environmentally significant behavior. J. Soc. Issues, 56, pp. 407–424. [61] Taylor, S.a., Todd, P.A. (1995). Understanding information technology usage: A test of competing models. Information Systems Resarch, 6, pp. 144-176. [62] Thøgersen, J. (1996). Recycling and morality: A critical review of the literature. Environ. Behav. 28, pp. 536–558. [63] United Nations Environment Programme (UNEP). (2011). Decoupling Natural Resource Use Environmental Impacts from Economic Growth. A Report of the Working Group on Decoupling to the International Resource Panel. [64] United Nations Environment Programme (UNEP). (2015). Policy Coherence of the Sustainable Development Goals－A Natural Resource Perspective. [65] United Nations Environment Programme (UNEP). (2017). Towards a Zero-Emission, E_cient, Resilient Buildings Construction Sector. Global Status Report. [66] United Nations (UN). (2018). World Urbanization Prospect The 2018 Revision. [67] United Nations (UN). (2019). World Population Prospect The 2019 Revision. [68] L.O. Oyedele, S.O. Ajayi K.O. Kadiri. (2014). Use of recycled products in UK construction industry: an empirical investigation into critical impediments strategies for improvement Resour. Conserv. Recycl., 93, pp. 23-31 [69] Knoeri C, Nikolic I, Althaus H-J Binder CR. (2014). Enhancing Recycling of Construction Materials an Agent Based Model with Empirically Based Decision Parameters. Journal of Artificial Societies Social Simulation, 17(3), pp. 10-21. [70] V.W.Y. Tam C.M. Tam. (2006). A review on the viable technology for construction waste recycling Resources Conservation Recycling, 47, pp. 209-221. [71] Lee, C.Y., (2002). Extended Producer Responsibility the Market Development for Recmycled Plastics Two Norwegian cases of using recycled polypropylene in chairs. Master’s theses. Lund Universiy, Sweden. [72] Mills, T.H., E. Showalter., D. Jarman. (1999). A cost effective waste management plan. Cost Engineering, 41(3), pp. 35–43. [73] T Ramesh, R Prakash KK. Shukla. (2010). Life cycle energy analysis of buildings: an overview Energy and Buildings, 10, pp. 1592-1600. [74] Weil M, Jeske U, Schebek L. (2006). Closed-loop recycling of construction demolition waste in Germany in view of stricter environmental threshold values. Waste Manage Res 24(3), pp. 197–206. [75] Williams, K. Dair, C. (2007). What is stopping sustainable building in Engl ? Barriers experienced by stakeholders in delivering sustainable development. Sustainable Development 15, pp. 135–147. [76] W. Zhao, R.B. Leeftink V.S. Rotter. (2010). Evaluation of the economic feasibility for the recycling of construction demolition waste in China—the case of Chongqing Resour., Conserv. Recycling, 54(6), pp. 377-389. [77] X. Meng, Z. Wen Y. Qian. (2018). Multi-Agent based simulation for household solid waste recycling behavior Resour. Conserv. Recycl., 128, pp. 535-545. [78] Y. Joshi Z. Rahman. (2015). Factors affecting green purchase behaviour future research directions Int. Strateg. Manag. Rev., 3(1), pp. 128-143. [79] Young, W., Hwang, K., McDonald, S. Oates, C.J. Sustainable Consumption: Green Consumer Behaviour When Purchasing Products, Sustainable Development, 18(1), pp. 20-31. [80] Yuan, H.P. (2013). A SWOT analysis of successful construction waste management Journal of Cleaner Production, 39(1), pp. 1-8. [81] Zhang, L., Chen, L., Wu, Z., Zhang, S. Song, H. (2018). Investigating young consumers’ purchasing intention of green housing in China. Sustainability, 10, pp. 1044-1056. [82] Zhang, L., Li, D., Cao, C., Huang, S. (2018). The influence of greenwashing perception on green purchasing intentions: The mediating role of green word-of-mouth and moderating role of green concern. Journal of Cleaner Production, 187, pp. 740–750. [83] CDTFA (2021). California City County Sales Use Tax Rates. https://www.cdtfa.ca.gov/taxes-and-fees/sales-use-tax-rates.htm [84] EPA (1990). National Environmental Education Act. https://www.epa.gov/education/national-environmental-education-act [85] OECD (2018). Survey of Adult Skills (PIAAC): Full selection of indicators. https://gpseducation.oecd.org/Home# [86] RCC (2021). Sales Tax Rates by Province. https://www.retailcouncil.org/resources/quick-facts/sales-tax-rates-by-province/ [87] USGBC (2019). Top 10 Countries and Regions for LEED Green Building. https://www.usgbc.org/articles/us-green-building-council-announces-top-10-countries-and-regions-leed-green-building [88] USGBC (2019). the Top 10 States for LEED Green Building. https://www.usgbc.org/articles/usgbc-releases-top-10-states-leed-recognizing-leaders-committed-more-sustainable-and [89] 王民(2009)。《巴西國家環境教育法》解讀。環境教育，6，15-21。 [90] 內政部建築研究所補助研究報告(2008)。再生綠建材開發與推廣應用計畫。 [91] 李元展(2003)。解讀永續發展。92年度設造培力點動力營一次梯次講稿。桃園縣文化局。 [92] 李明聰、甘志展(2007)。國家公園遊客對綠建築旅館之願付價格研究－以墾丁國家公園為例。中華建築學刊，3(2)，1-14。 [93] 行政院環境保護署(2018)。107至109年資源回收再利用推動計畫。 [94] 吳鈴筑(2009)。國內外環境教育法之研究。臺灣碩博士論文知識加值系統。 [95] 巫勝吉(2012)。環境教育法推動之執行現況、成效、衍生問題及解決策略之探討。臺灣碩博士論文知識加值系統。 [96] 郭家鉷(2015)。環境教育對營造工作者環境素養及學習意願之影響。臺灣碩博士論文知識加值系統。 [97] 姚靜、孫學禮，洪明(2004)。正常成人認知功能與年齡、性別、受教育程度的關係。中國臨床心理學雜誌，12(4)，414-416。 [98] 陳禹(2001)。複雜適應系統( CAS) 理論及其應用———由來、內容與啟示。系統辯證學學報，9(4)，35-39。 [99] 唐婉庭、楊上禾(2019)。以時間序列法檢測臺灣雞蛋產地價格之影響因素。中國畜牧學會會誌，48(4)，275-288。 [100] 財團法人資源循環臺灣基金會(2018)。邁向台灣2030永續發展。 [101] 許世璋(2003)。大學環境教育課程對於環境行動與其它環境素養變項之成效分析。科學教育學刊，11(1)，97-119。 [102] 國家發展委員會(2016)。政府捐助之財團法人105年度行政監督總報告。 [103] 曾育慧、江東亮 (2017)。全球發展新紀元：從千禧年發展目標到永續發展目標。台灣公共衛生雜誌，36(1)，1-5。 [104] 黃淮文(2014)。國際鎳金屬價格之影響。華藝線上圖書館。 [105] 黃慧新(2015)。從生態效益觀點探討綠色廣告特徵與消費者特質對綠色產品購買意願。中華管理評論國際學報，18(1)。 [106] 劉繼和、趙海濤(2003)。日本環境教育法及其解讀。環境教育期刊，17-19。 [107] 全國法規資料庫。環境教育法。https://law.moj.gov.tw/LawClass/LawAll.aspx?pcode=O0120001 [108] 中國稅務總局。https://12366.chinatax.gov.cn/xiaohui/?guide=1.2 [109] 臺北市政府民政局。臺北市人口數及教育程度。https://ca.gov.taipei/News.aspx?n=8693DC9620A1AABF sms=D19E9582624D83CB [110] 政府資料公開平台。臺北市人口密度、綠標章頒發數。https://data.gov.tw/dataset/131821 [111] 營建物價資訊平台。建築材料物價查詢。https://ccd.tcri.org.tw/ [112] 內政部營建署。營造業家數、建築使用執照頒發數。https://www.cpami.gov.tw/ [113] 衛生福利部。財團法人社會福利慈善事業基金會基本資料。https://dep.mohw.gov.tw/dos/cp-2989-13996-113.html [114] 教育部統計處。臺北市各級學生人數。https://depart.moe.edu.tw/ed4500/cp.aspx?n=1B58E0B736635285 s=D04C74553DB60CAD [115] 臺北市政府教育局。各級學校教職員工及教育程度比例結構。https://statistic.tp.edu.tw/dialog/statfile9.asp [116] 臺北市政府主計處。在職人士數量及教育程度比例結構。https://dbas.gov.taipei/News_Content.aspx?n=72EB69FFAC3565DF sms=96C0B436A542605B s=0EE1734BF15D2DCD [117] 臺北市政府人事處。全國各機關、公營事業機構人數以及教育程度比例結構。https://dop.gov.taipei/News_Content.aspx?n=6260D2F329E6CAB4 sms=A6D1377856550DDE s=C13D0078B4F5E797 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80582 | - |
| dc.description.abstract | 人們需要都市建築物來滿足自身的生活需求。都市化仍然是世界未來的趨勢，在這個趨勢下人們就會興建更多建築物來迎合自身的需求，社會對天然建材的需求亦越來越多，龐大的自然資源開採會對環境造成不可逆轉的破壞。永續發展已經成為世界重要的研究領域，若可以提高營造業使用再生建材之意願，有助再生建材使用量的提升，將能夠減緩世界自然資源的壓力，同時可以促進二次物料市場的發展，提升營造廢棄物回收率，減少土地壓力。 本研究利用Agent-Based Model結合計劃行為理論，摸擬營造業使用再生建材的行為，比起以往研究模擬再生建材的使用，Agent-Based Model能夠從更細微的角度出發，本研究考慮到市民與市民之間的影響、市民對營造業的影響以及每間營造業對彼此之間的影響，這些影響造成每間營造業使用再生建材意願的變化，使研究結果將更貼切現實情況。在Agent-Based Model中加入計劃行為理論能夠更準確地預測人類的行為，包括營造業的行為，使本研究可以從經濟、社會、環境三個層面來探討影響營造業使用再生建材行為的因子。本研究將模擬分析臺北市營造業未來50年使用再生建材意願的趨勢情況，探討三個因子對營造業使用再生建材意願的影響，包括再生建材價格偏好、社會規範及營造業內部的環境意識等，也會討論對傳統建材課稅之經濟政策與環境教育政策對營造業使用再生建材意願的影響。 本研究的目的為立志找出影響營造業使用再生建材的重要因子，並在不同的經濟和環境教育政策組合中找出能夠提高營造業使用再生建材意願的最優政策組合。望這些因子和政策可以提供給臺北市決策者參考，在決策者為提高臺北市營造業使用再生建材意願進行決策時能以這些因子和政策組合作為施力點，提升決策效率。 研究結果顯示，臺北市營造業在2019年至2040年時使用再生建材意願持續增加，而2041年以後意願將維持穩定狀態，而再生建材價格偏好、營造業內部的環境意識和社會規範皆對營造業使用再生建材意願有重要影響，再生建材價格偏好與社會規範因子對提升臺北市營造業使用再生建材意願具有即時性效果，而營造業環境意識因子需要一定年時的積累才能使臺北市營造業平均使用再生建材意願獲得提升效果，在有效提升臺北市營造業使用再生建材意願之政策組合方面，加拿大魁北克省對傳統建材徵收14.975%稅率之經濟政策與日本環境教育政策為最優的調控政策組合。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:09:55Z (GMT). No. of bitstreams: 1 U0001-2410202121411200.pdf: 2455805 bytes, checksum: 707aeb4123b51bdb427fcb2cedda08a0 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | "誌謝 I 中文摘要 II Abstract IV 目錄 VI 圖目錄 IX 表目錄 XI 第一章 緒論 1 1.1 研究背景 1 1.2 研究目的 2 1.3 研究流程 3 第二章 文獻回顧 5 2.1 永續發展與永續發展目標 5 2.1.1 永續發展的進程 5 2.1.2 永續發展目標(Sustainable Development Goals, SDGs) 6 2.2 營造業與永續發展目標 8 2.2.1 營建工程對環境的衝擊 8 2.2.2 營造業連結永續發展目標 10 2.3 Agent-Based Model與計劃行為理論 11 2.3.1 Agent-Based Model 11 2.3.2 計劃行為理論 15 2.3.3 Agent-Based Model結合計劃行為理論之應用 22 2.3.4 本研究計劃行為理論與ABM結合應用說明 26 2.4 影響營造業者使用再生建築材料的因子 27 2.4.1 再生建築材料價格影響建業使用意願 28 2.4.2 環境意識影響營造業使用再生建築材料意願 28 2.4.3 社會規範影響營造業使用再生建築材料意願 29 2.4.4 市民環境意識對營造業使用再生建築材料意願的影響 29 第三章 研究方法 31 3.1 研究目的及系統範疇界定 31 3.2 Agent-Based Model設計 31 3.2.1 Agent的分類及其的互動規則 32 3.2.2 Agent的互動規則 35 3.2.3 Agent由紅色狀態轉變為綠色狀態的條件 38 3.3 營造業使用再生建材意願的計算公式 46 3.4 傳統建材與再生建材價格的迴歸推演 56 3.5 Agent-Based Model的運行 58 第四章 結果與討論 61 4.1 模型參數設定 61 4.2 模型輸出結果分析 63 4.2.1 基準政策模擬結果分析 63 4.2.2 無交互基準政策模擬結果分析 69 4.3 政策調控對營造業使用再生建材意願影響之分析比較 71 4.3.1 對建築材料課稅的經濟政策模擬結果分析及比較 71 4.3.2 實施環境教育政策的模擬結果分析及比較 74 4.3.3 政策組合調控之模擬結果分析及比較 79 4.3.4 討論 82 第五章 結論與建議 84 5.1 結論 84 5.2 建議 85 參考文獻 88 附錄一 兩種不同規格的高壓混凝土地磚價格與混凝土空心磚歷年價格 100" | |
| dc.language.iso | zh-TW | |
| dc.subject | 計劃行為理論 | zh_TW |
| dc.subject | Agent-Based Model | zh_TW |
| dc.subject | 再生建材 | zh_TW |
| dc.subject | 永續都市 | zh_TW |
| dc.subject | 環境意識 | zh_TW |
| dc.subject | environmental awareness | en |
| dc.subject | Theory of Planned-Behavior | en |
| dc.subject | Agent-based Model | en |
| dc.subject | recycled material | en |
| dc.subject | sustainable city | en |
| dc.title | 以個體為基礎模型預測臺北市營造業使用再生建材意願之研究 | zh_TW |
| dc.title | Predicting Contractors’ Intention to Use Recycled Construction Material in Taipei City with Agent-Based Model | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 闕蓓德(Hsin-Tsai Liu),陳必晟(Chih-Yang Tseng) | |
| dc.subject.keyword | Agent-Based Model,再生建材,永續都市,環境意識,計劃行為理論, | zh_TW |
| dc.subject.keyword | Agent-based Model,recycled material,sustainable city,environmental awareness,Theory of Planned-Behavior, | en |
| dc.relation.page | 103 | |
| dc.identifier.doi | 10.6342/NTU202104093 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-10-25 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 環境工程學研究所 | zh_TW |
| 顯示於系所單位： | 環境工程學研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| U0001-2410202121411200.pdf 授權僅限NTU校內IP使用（校園外請利用VPN校外連線服務） | 2.4 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。