博碩士論文 108481011 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:40 、訪客IP:18.116.40.188
姓名 莊雅惠(Sophia Chuang)  查詢紙本館藏   畢業系所 企業管理學系
論文名稱 實踐淨零願景之減碳策略整合分析
(Comprehensive Analysis of Mitigation Actions for Pledging Net Zero)
相關論文
★ 台灣與大陸在ERP專案管理、專案成員向心力與離心力的不同之處★ ERP專案成員離心力與向心力對代理問題之影響
★ 事業策略、人力資源管理與組織績效之實證研究★ 商用飛機維修成本控制之研究-以某國籍航空公司為例
★ ERP系統更換關鍵成功因素研究-以Oracle系統導入為例★ 中小企業自行開發ERP 系統關鍵成功因素研究- 以高科技產業為例
★ 文化創意產業產品策略選擇之影響因素-以國片為例★ 專案管理風險對ERP專案成功之影響
★ 品質機能展開與多準則決策於設備開發應用★ ERP導入品質因素對IFRS轉換專案之影響
★ ERP投資金額對服務品質及導入後IT治理目標之分析★ ERP 導入問題對專案的影響
★ IFRS轉換對員工退休金計畫影響★ IFRS轉換對企業績效評估的影響
★ IFRS轉換問題對IFRS效益的影響★ ERP環境下企業集團自行編製合併報表能力對XBRL資訊透明度之研究
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 ( 永不開放)
摘要(中) 邇來各國政府競相依淨零承諾與減碳目標推動政策,我國亦提出“臺灣2050淨零排放路徑及策略”,雖有明確目標,惟根據本研究結果,現行政策恐無法悉所達成。衡諸國際作法與因應淨零碳排情勢,如何藉由減緩策略立基的解決面向、策略行動,以及其與達成目標的差距規劃,乃既有文獻及研究相對忽視之部分。本研究所建構A-S-A-P model ,始由單變量時間序列(ARIMA model),運用次級資料為基礎預測溫室氣體排放量,模擬未來之情境分析(Scenario analysis),再設算與國家自定預期貢獻之差距,提出每5年為一期亟須採取行動之碳排量(Action plan),最後提出管理面之政策意涵(Policy implication) 。本研究結果與目前政策相較下,確實發現不一致之處;爰此,謹研提建議供各界作為未來決策參據:(1) 針對整體受訪者與各專家群體評選之策略優先性,經分析結果互有不同,惟就淨零碳排係屬重要性議題上,咸有其共識存在。(2) 在達成目標前提下,無論現況、既定政策、考量自然風險值及延遲效應等情境,運用科技創新、行為改變、碳定價及自然為本解方,皆極為重要。(3) 我國實有必要加速期程,並師法國際制定更具影響力的政策和因應措施,冀期實踐淨零碳排之願景。
摘要(英) The urgency to respond to net zero commitments requires a more precise application of management tools to strategic priorities. The need for the government to promote relevant policies in full compliance with net zero commitments and carbon mitigation initiatives heightens the pressure for pledging net zero. This study contributes to the comprehensive analysis of proposed implementation solutions and mitigation actions related to net zero initiatives. The A-S-A-P model in this study, which applies the ARIMA approach to facilitate the prediction of greenhouse gas emissions, scenario analysis in modeling simulation, action mitigation schemes to close the gap between ambition target and projected mitigation timelines, and policy implications to prioritize emission mitigation pathways, is developed. The results of this study indicates that the A-S-A-P model offers an out-of-the-box solution to assist policymakers and related stakeholders. This finding prompted the following analyses: (1) Diverse analytical results from the overall stakeholder group are different, but the results showed consensus on the imperativeness of the net zero pledge and emissions mitigation target; (2) All the simulated conditions, including “business as usual scenario,” “stated policy scenario,” “natural hazard scenario” and “postponement scenario” cannot meet the assumptions of Taiwan’s nationally determined contributions. Considering the objectives of the “Priority for Greenhouse Gas Emission Mitigation Pathway,” technology-based solutions, behavioral changes, carbon pricing, and nature-based solutions are suggested; and (3) An accelerated timetable for more effective policies and responses aligned with global trends is required.
關鍵字(中) ★ 淨零碳排
★ 層級分析法
★ 模糊隸屬函數
★ 時間序列
★ 情境分析
★ A-S-A-P 模型
關鍵字(英) ★ Analytic Hierarchy Process
★ Fuzzy Set Theory
★ Net Zero Emissions Pathway
★ The A-S-A-P model
★ ARIMA
★ Scenario Analysis
論文目次 Table of Content
摘要 i
Abstract ii
誌謝 iii
Table of Content iv
List of Figures vi
List of Tables vii
List of Abbreviations viii
Chapter I Introduction 1
1-1 Research Motivation 1
1-2 Research Background 4
1-2-1 What Net Zero Means 4
1-2-2 Situating net zero target 4
1-3 Research purpose and procedure 6
Chapter II Literature Review 7
2-1 Overview of Announced Pledge and Policies of Key Countries 7
2-2 Identification of Alternative 13
2-2-1 Review and Analysis Alternatives for Mitigation Pathways 13
2-2-2 Conduct Pre-research and Testing 15
2-3 Description of Alternative Solutions 17
2-3-1 Carbon pricing 17
2-3-2 Technology-based solution 19
2-3-3 Nature-based solution 21
2-3-4 Behavioral change 23
Chapter III Proposed Methodology 29
3-1 Priority of GHG Emissions Mitigation Pathway 31
3-1-1 Problem identification and analytic hierarchy establishment 31
3-1-2 Creating comparison matrices and checking for consistency 33
3-1-3 Aggregation of group decisions 35
3-1-4 Solving the defuzzification 35
3-1-5 Connecting hierarchical series 35
3-2 Sample structure 36
3-3 Weighted results 38
Chapter IV The A-S-A-P Model 44
4-1 ARIMA Model 45
4-2 Scenario analysis 50
4-3 Action Plan 52
4-3-1 Setting Target 52
4-3-2 Closing Gap between TNDCs and action plan 52
4-3-3 Action Emission Patterns 54
4-4 Policy Implication 58
Chapter V Conclusion 62
5-1 Conclusion 62
5-2 Research Limitation and Future Research 63
References 64
APPENDIX 72 
List of Figures
Figure 1. Annual CO2 emissions 1990-2021 in Taiwan. 3
Figure 2. Flowchart of Proposed model 30
Figure 3. Hierarchy Frame of Priority for GHG Emission Mitigation Pathway 32
Figure 4. Radar chart for implementation solution analysis 39
Figure 5. Radar chart on the weight of mitigation action level 41
Figure 6. Procedures and steps of the A-H-A-P model 45
Figure 7. Gap emission in simulation scenarios every five years 54
Figure 8. Line Graph of Mitigation Action by Global Weight 55
Figure 9. Allocation Weight of Action Emission Scheme based on Entropy Method 56


List of Tables
Table 1. Overview of Announced Pledge and Polices of Key Countries 9
Table 2. Descriptions and Examples of Solution/ Action for GHG Emission Mitigation 26
Table 3. Linguistic variables for pairwise comparison of each criterion 34
Table 4. Representation of each stakeholder group’s expert profile 37
Table 5. Overall results on Implementation Solutions and Mitigation Actions 38
Table 6. Weighted results of implementation solution by stakeholder group 39
Table 7. Results of mitigation action level by stakeholder group 40
Table 8. ARIMA- GHG emissions Results 48
Table 9. Simulation scenario and parameter used 51
Table 10. Plan for Action Emission in Simulation Scenario to Fulfilled Gap Emission 57
Table 11. Summary of CCPI Indicators of Weighting, Rating and Rank 59

參考文獻 1. National Development Council, Taiwan’s Pathway to Net-Zero Emissions in 2050, 2022,. https://www.ndc.gov.tw/en/Content_List.aspx?n=B154724D802DC488. Accessed on 5 February, 2022
2. Hale, T., et al., Assessing the rapidly-emerging landscape of net zero targets. Climate Policy, 2022. 22(1): p. 18-29.
3. Lau, H.C. and S.C. Tsai, A Decarbonization Roadmap for Taiwan and Its Energy Policy Implications. Sustainability, 2022. 14(14): p. 8425.
4. IEA, Global Energy Review: CO2 Emissions in 2021-Global Emissions Rebound Sharply to Highest Ever Level. 2022, International Energy Agency Paris, France.
5. Jeudy-Hugo, S., L.L. Re, and C. Falduto, Understanding countries’ net-zero emissions targets. 2021.
6. Bureau of Energy. Taiwan. In: 2020 annual report of Bureau of energy, Taiwan. Ministry of Economic Affairs, Executive Yuan; 2022
7. National Development Council, Phased Goals and Actions Toward Net-Zero Transition, 2022. https://www.ndc.gov.tw/en/Content_List.aspx?n=2D918002A913582A. Accessed on 5 February, 2022
8. IPCC, Global warming of 1.5°C. An IPCC Special Report on the impacts of globalwarming of 1.5°C above pre-industrial levels and related global greenhouse gas emissionpathways, in the context of strengthening the global response to the threat of climatechange,sustainable development, and efforts to eradicate poverty, Intergovernmental Panel onClimate Change, Geneva,. 2018.
9. Cheng, F., Taiwan Addresses Climate Change: Policy Learning, Formulation and Implementation. East Asian Policy, 2022. 14(02): p. 38-55.
10. Environmental Protection Administration. Taiwan. Greenhouse gas reduction and management act. Taipei, Taiwan: Environmental Protection Administration, ExecutiveYuan; 2021
11. Grantham Research Institute on Climate Change and the Environment andVivid Economics(2020)Carbon pricing options for Taiwan. London: Grantham Research Institute on Climate Change and the Environment, London School of Economics and Political Science, and Vivid Economics
12. Dos Santos, P.H., et al., The analytic hierarchy process supporting decision making for sustainable development: An overview of applications. Journal of cleaner production, 2019. 212: p. 119-138.
13. Sindhwani, R., et al., Modeling the critical success factors of implementing net zero emission (NZE) and promoting resilience and social value creation. Technological Forecasting and Social Change, 2022. 181: p. 121759.
14. Burck, J.et.al., Climate Change Performance Index 2023. November 14th, 2022, Germanwatch.
15. Calabrese, A., et al., Integrating sustainability into strategic decision-making: A fuzzy AHP method for the selection of relevant sustainability issues. Technological Forecasting and Social Change, 2019. 139: p. 155-168.
16. Mohammed, H.J., I.A.M. Al-Jubori, and M.M. Kasim. Evaluating project management criteria using fuzzy analytic hierarchy Process. in AIP Conference Proceedings. 2019. AIP Publishing LLC.
17. Liu, Y., C.M. Eckert, and C. Earl, A review of fuzzy AHP methods for decision-making with subjective judgements. Expert Systems with Applications, 2020. 161: p. 113738.
18. Ly, P.T.M., et al., Fuzzy AHP analysis of Internet of Things (IoT) in enterprises. Technological Forecasting and Social Change, 2018. 136: p. 1-13.
19. Saaty, T.L., What is the analytic hierarchy process?, in Mathematical models for decision support. 1988, Springer. p. 109-121.
20. Vaidya, O.S. and S. Kumar, Analytic hierarchy process: An overview of applications. European Journal of operational research, 2006. 169(1): p. 1-29.
21. Vargas, L.G., An overview of the analytic hierarchy process and its applications. European journal of operational research, 1990. 48(1): p. 2-8.
22. Büyüközkan, G., C.A. Havle, and O. Feyzioğlu, An integrated SWOT based fuzzy AHP and fuzzy MARCOS methodology for digital transformation strategy analysis in airline industry. Journal of Air Transport Management, 2021. 97: p. 102142.
23. Asadabadi, M.R., E. Chang, and M. Saberi, Are MCDM methods useful? A critical review of analytic hierarchy process (AHP) and analytic network process (ANP). Cogent Engineering, 2019. 6(1): p. 1623153.
24. Ahmed, F. and K. Kilic, Fuzzy Analytic Hierarchy Process: A performance analysis of various algorithms. Fuzzy Sets and Systems, 2019. 362: p. 110-128.
25. Chan, H.K., X. Sun, and S.-H. Chung, When should fuzzy analytic hierarchy process be used instead of analytic hierarchy process? Decision Support Systems, 2019. 125: p. 113114.
26. Scrieciu, S.Ş. and Z. Chalabi, Climate policy planning and development impact assessment. Mitigation and Adaptation Strategies for Global Change, 2014. 19: p. 255-260.
27. Solangi, Y.A., et al., Analyzing renewable energy sources of a developing country for sustainable development: an integrated fuzzy based-decision methodology. Processes, 2020. 8(7): p. 825.
28. Shen, Y.-C., C.J. Chou, and G.T. Lin, The portfolio of renewable energy sources for achieving the three E policy goals. Energy, 2011. 36(5): p. 2589-2598.
29. Eskander, S.M. and S. Fankhauser, Reduction in greenhouse gas emissions from national climate legislation. Nature Climate Change, 2020. 10(8): p. 750-756.
30. Konidari, P. and D. Mavrakis, A multi-criteria evaluation method for climate change mitigation policy instruments. Energy Policy, 2007. 35(12): p. 6235-6257.
31. Press, N.A. and E.N.A.o. Sciences, Negative emissions technologies and reliable sequestration: a research agenda. 2019: National Academies Press.
32. Gland., U.N.E.P.a.I.U.f.C.o.N.N.-b.s.f.c.c.m.N.a.
33. Hasan, M., R. Chapman, and D. Frame, Acceptability of transport emissions reduction policies: A multi-criteria analysis. Renewable and Sustainable Energy Reviews, 2020. 133: p. 110298.
34. Hasan, M., R. Chapman, and D. Frame, Understanding Road Transport Emissions Reduction Policies Using Multi-criteria Analysis, in Handbook of Climate Change Mitigation and Adaptation. 2022, Springer. p. 3203-3223.
35. Doczy, R. and Y. AbdelRazig, Green buildings case study analysis using AHP and MAUT in sustainability and costs. Journal of Architectural Engineering, 2017. 23(3): p. 05017002.
36. Ohene, E., A.P. Chan, and A. Darko, Prioritizing barriers and developing mitigation strategies toward net-zero carbon building sector. Building and Environment, 2022: p. 109437.
37. Boyce, J.K., Carbon pricing: effectiveness and equity. Ecological Economics, 2018. 150: p. 52-61.
38. Green, J.F., Does carbon pricing reduce emissions? A review of ex-post analyses. Environmental Research Letters, 2021. 16(4): p. 043004.
39. Klenert, D., et al., Making carbon pricing work for citizens. Nature Climate Change, 2018. 8(8): p. 669-677.
40. Organisation for Economic Co-operation and Development. (2018). Effective carbon rates 2018: Pricing carbon emissions through taxes and emissions trading. OECD Publishing.
41. World Bank. 2022. State and Trends of Carbon Pricing 2022. State and Trends of Carbon Pricing;. © Washington, DC: World Bank. http://localhost:4000//entities/publication/a1abead2-de91-5992-bb7a-73d8aaaf767f License: CC BY 3.0 IGO.”42. Cheng, Y., et al., Carbon tax and energy innovation at crossroads of carbon neutrality: Designing a sustainable decarbonization policy. Journal of Environmental Management, 2021. 294: p. 112957.
43. Hu, H., W. Dong, and Q. Zhou, A comparative study on the environmental and economic effects of a resource tax and carbon tax in China: Analysis based on the computable general equilibrium model. Energy Policy, 2021. 156: p. 112460.
44. Tsai, W.-H., S.-Y. Lai, and C.-L. Hsieh, Exploring the impact of different carbon emission cost models on corporate profitability. Annals of Operations Research, 2022: p. 1-34.
45. Hsiao, C.-M., Economic Growth, CO2 Emissions Quota and Optimal Allocation under Uncertainty. Sustainability, 2022. 14(14): p. 8706.
46. Lin, B.Q. and C.C. Huang, Analysis of emission reduction effects of carbon trading: Market mechanism or government intervention? Sustainable Production and Consumption, 2022. 33: p. 28-37.
47. Vats, G. and R. Mathur, A net-zero emissions energy system in India by 2050: An exploration. Journal of Cleaner Production, 2022. 352: p. 131417.
48. Pye, S., et al., Modelling net-zero emissions energy systems requires a change in approach. Climate Policy, 2021. 21(2): p. 222-231.
49. García-Freites, S., C. Gough, and M. Röder, The greenhouse gas removal potential of bioenergy with carbon capture and storage (BECCS) to support the UK′s net-zero emission target. Biomass and Bioenergy, 2021. 151: p. 106164.
50. Sezgin, B., et al., Hydrogen energy systems for underwater applications. International Journal of Hydrogen Energy, 2022. 47(45): p. 19780-19796.
51. IEA (2022), Renewables 2022, IEA, Paris https://www.iea.org/reports/renewables-2022, License: CC BY 4.0
52. Blanco, H., et al., A taxonomy of models for investigating hydrogen energy systems. Renewable and Sustainable Energy Reviews, 2022. 167: p. 112698.
53. Magzymov, D., B. Dindoruk, and R.T. Johns. Carbon Capture, Utilization, and Storage in the Context of Petroleum Industry: A State-of-the-Art Review. in 2022 SPE Improved Oil Recovery Conference, IOR 2022. 2022. Society of Petroleum Engineers (SPE).
54. Hong, W.Y., A techno-economic review on carbon capture, utilisation and storage systems for achieving a net-zero CO2 emissions future. Carbon Capture Science & Technology, 2022: p. 100044.
55. Morkner, P., et al., Distilling data to drive carbon storage insights. Computers & Geosciences, 2022. 158: p. 104945.
56. English, J.M. and K.L. English, An Overview of Carbon Capture and Storage and its Potential Role in the Energy Transition. First Break, 2022. 40(4): p. 35-40.
57. Viti, M., et al., Knowledge gaps and future research needs for assessing the non-market benefits of Nature-Based Solutions and Nature-Based Solution-like strategies. Science of the Total Environment, 2022: p. 156636.
58. Tyllianakis, E., J. Martin-Ortega, and S.A. Banwart, An approach to assess the world’s potential for disaster risk reduction through nature-based solutions. Environmental Science & Policy, 2022. 136: p. 599-608.
59. Wijsman, K. and M. Berbés-Blázquez, What do we mean by justice in sustainability pathways? Commitments, dilemmas, and translations from theory to practice in nature-based solutions. Environmental Science & Policy, 2022. 136: p. 377-386.
60. Yu, M., K. Wang, and H. Vredenburg, Insights into low-carbon hydrogen production methods: Green, blue and aqua hydrogen. International Journal of Hydrogen Energy, 2021. 46(41): p. 21261-21273.
61. Liang, B., et al., Planted forest is catching up with natural forest in China in terms of carbon density and carbon storage. Fundamental Research, 2022.
62. Valatin, G., Forest Green Infrastructure and the Carbon Storage and Substitution Benefits of Harvested Wood Products, in Green Infrastructure and Climate Change Adaptation. 2022, Springer, Singapore. p. 443-456.
63. Fleischman, F., et al., How politics shapes the outcomes of forest carbon finance. Current Opinion in Environmental Sustainability, 2021. 51: p. 7-14.
64. Raihan, A., et al., Nexus between carbon emissions, economic growth, renewable energy use, urbanization, industrialization, technological innovation, and forest area towards achieving environmental sustainability in Bangladesh. Energy and Climate Change, 2022. 3: p. 100080.
65. Amundson, R. and L. Biardeau, Soil carbon sequestration is an elusive climate mitigation tool. Proceedings of the National Academy of Sciences, 2018. 115(46): p. 11652-11656.
66. Lu, X., et al., Nitrogen deposition accelerates soil carbon sequestration in tropical forests. Proceedings of the National Academy of Sciences, 2021. 118(16): p. e2020790118.
67. Hübner, R., et al., Soil carbon sequestration by agroforestry systems in China: A meta-analysis. Agriculture, Ecosystems & Environment, 2021. 315: p. 107437.
68. Rodrigues, L., et al., Achievable agricultural soil carbon sequestration across Europe from country‐specific estimates. Global Change Biology, 2021. 27(24): p. 6363-6380.
69. Schlesinger, W.H. and R. Amundson, Managing for soil carbon sequestration: Let’s get realistic. Global Change Biology, 2019. 25(2): p. 386-389.
70. Marteau, T.M., N. Chater, and E.E. Garnett, Changing behaviour for net zero 2050. BMJ (Clinical research ed.), 2021. 375: p. n2293.
71. Carmichael, R., Behaviour change, public engagement and net zero, a report for the committee on climate change. 2019.
72. Haggi, H., et al., Optimal H2 Production and Consumption for Improved Utility Operations: Path to Net-Zero Emission Energy Production. 2022.
73. Azevedo, I., et al., Net-zero emissions energy systems: what we know and do not know. Energy and Climate Change, 2021. 2: p. 100049.
74. TANHIDY, J., Y. NDAPAMURI, and R.J. GUILD, The Church′s Ethical Responsibilities towards Net-Zero Carbon Emissions Objectives. GNOSI: An Interdisciplinary Journal of Human Theory and Praxis, 2022. 5(2): p. 123-135.
75. Logan, K.G., Transportation in a Net Zero World: Transitioning Towards Low Carbon Public Transport. 2022: Springer Nature.
76. Benton, T.G., et al., A ‘net zero’equivalent target is needed to transform food systems. Nature Food, 2021. 2(12): p. 905-906.
77. Setiawan, I.C. and M. Setiyo, Renewable and Sustainable Green Diesel (D100) for Achieving Net Zero Emission in Indonesia Transportation Sector. Automotive Experiences, 2022. 5(1): p. 1-2.
78. Costa, C., et al., Roadmap for achieving net-zero emissions in global food systems by 2050. Scientific Reports, 2022. 12(1): p. 1-11.
79. Nunes, A., L. Woodley, and P. Rossetti, Re-thinking procurement incentives for electric vehicles to achieve net-zero emissions. Nature Sustainability, 2022: p. 1-6.
80. Mengis, N., et al., Net‐Zero CO2 Germany—A Retrospect From the Year 2050. Earth′s Future, 2022. 10(2): p. e2021EF002324.
81. Cohen, M.A. and M.P. Vandenbergh, The potential role of carbon labeling in a green economy. Energy Economics, 2012. 34: p. S53-S63.
82. Shewmake, S., et al., Predicting consumer demand responses to carbon labels. Ecological Economics, 2015. 119: p. 168-180.
83. Carmichael, R. and T. Wainwright. Psychology and the road to Net Zero. in Clinical Psychology Forum. 2020.
84. Wang, J. and R. Duan, A Comparative Study of Carbon labeling Policy and Application. CCBC 2022, 2022: p. 16.
85. Nelson, S. and J.M. Allwood, Technology or behaviour? Balanced disruption in the race to net zero emissions. Energy Research & Social Science, 2021. 78: p. 102124.
86. Endo, N., et al., Thermal management and power saving operations for improved energy efficiency within a renewable hydrogen energy system utilizing metal hydride hydrogen storage. International Journal of Hydrogen Energy, 2021. 46(1): p. 262-271.
87. Gabrielli, P., M. Gazzani, and M. Mazzotti, The role of carbon capture and utilization, carbon capture and storage, and biomass to enable a net-zero-CO2 emissions chemical industry. Industrial & Engineering Chemistry Research, 2020. 59(15): p. 7033-7045.
88. Saaty, T.L., The analytic hierarchy process McGraw-Hill. New York, 1980. 324.
89. Buckley, J.J., Fuzzy hierarchical analysis. Fuzzy sets and systems, 1985. 17(3): p. 233-247.
90. Jaskowski, P., S. Biruk, and R. Bucon, Assessing contractor selection criteria weights with fuzzy AHP method application in group decision environment. Automation in construction, 2010. 19(2): p. 120-126.
91. Meixner, O. Fuzzy AHP group decision analysis and its application for the evaluation of energy sources. in Proceedings of the 10th International Symposium on the Analytic Hierarchy/Network Process, Pittsburgh, PA, USA. 2009.
92. Ayhan, M.B., A fuzzy AHP approach for supplier selection problem: A case study in a Gear motor company. arXiv preprint arXiv:1311.2886, 2013.
93. Zahedi, F., The analytic hierarchy process—a survey of the method and its applications. interfaces, 1986. 16(4): p. 96-108.
94. Saaty, T.L., Modeling unstructured decision problems—the theory of analytical hierarchies. Mathematics and computers in simulation, 1978. 20(3): p. 147-158.
95. Saaty, T.L., How to make a decision: the analytic hierarchy process. European journal of operational research, 1990. 48(1): p. 9-26.
96. Csutora, R. and J.J. Buckley, Fuzzy hierarchical analysis: the Lambda-Max method. Fuzzy sets and Systems, 2001. 120(2): p. 181-195.
97. Kannan, D., et al., Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain. Journal of Cleaner production, 2013. 47: p. 355-367.
98. Buysse, K. and A. Verbeke, Proactive environmental strategies: A stakeholder management perspective. Strategic management journal, 2003. 24(5): p. 453-470.
99. Glicken, J., Getting stakeholder participation ‘right’: a discussion of participatory processes and possible pitfalls. Environmental Science & Policy, 2000. 3(6): p. 305-310.
100. Reed, M.S., Stakeholder participation for environmental management: a literature review. Biological conservation, 2008. 141(10): p. 2417-2431.
101. Manoliadis, O., I. Tsolas, and A. Nakou, Sustainable construction and drivers of change in Greece: a Delphi study. Construction Management and Economics, 2006. 24(2): p. 113-120.
102. IEA, Transport Improving the Sustainability of Passenger and Freight Transport. (2021). https://www.iea.org/topics/transport. Accessed 23 December, 2022
103. Nyoni, T. and W.G. Bonga, Prediction of co2 emissions in india using arima models. DRJ-Journal of Economics & Finance, 2019. 4(2): p. 01-10.
104. Rahman, A. and M.M. Hasan, Modeling and forecasting of carbon dioxide emissions in Bangladesh using Autoregressive Integrated Moving Average (ARIMA) models. Open Journal of Statistics, 2017. 7(4): p. 560-566.
105. Kamoljitprapa, P. and S. Sookkhee. Forecasting models for carbon dioxide emissions in major economic sectors of Thailand. in Journal of Physics: Conference Series. 2022. IOP Publishing.
106. Sharma, S., A.K. Saxena, and M. Bansal. Forecasting of GHG (greenhouse gas) Emission using (ARIMA) Data Driven Intelligent Time Series Predicting Approach. in 2022 7th International Conference on Communication and Electronics Systems (ICCES). 2022. IEEE.
107. Kour, M., Modelling and forecasting of carbon-dioxide emissions in South Africa by using ARIMA model. International Journal of Environmental Science and Technology, 2022: p. 1-8.
108. Prananda, J., R. Hantoro, and G. Nugroho, The prediction of carbon dioxide emission using ARIMA for support green energy development in Surabaya Municipality. KnE Energy, 2015: p. 106-110.
109. Lotfalipour, M.R., M.A. Falahi, and M. Bastam, Prediction of CO2 emissions in Iran using grey and ARIMA models. International Journal of Energy Economics and Policy, 2013. 3(3): p. 229-237.
110. Guarnaccia, C., et al. ARIMA models application to air pollution data in Monterrey, Mexico. in AIP Conference Proceedings. 2018. AIP Publishing LLC.
111. 2022 National Inventory Report_abstract, R.O.C.T. Environmental Protection Administration, Editor. 2022.
112. Ward, P.J., et al., Natural hazard risk assessments at the global scale. Natural Hazards and Earth System Sciences, 2020. 20(4): p. 1069-1096.
113. Samset, B.H., J.S. Fuglestvedt, and M.T. Lund, Delayed emergence of a global temperature response after emission mitigation. Nature Communications, 2020. 11(1): p. 3261.
114. Harker, P.T., Incomplete pairwise comparisons in the analytic hierarchy process. Mathematical modelling, 1987. 9(11): p. 837-848.
115. International Energy Agency. (2021). Global Hydrogen Review 2021. OECD Publishing.

指導教授 蔡文賢(Wen-Hsien Tsai) 審核日期 2023-3-14
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明