本論文集分為三篇研究
第一篇為中古車市場動態模擬：代理人基建模方法之應用。
第二篇 實驗性預測市場的效率：公開資訊、信念演變和人格特質。
第三篇 研究電動車未來展望分析-以創新擴散理論為依據。

第一篇 中古車市場動態模擬：代理人基建模方法之應用，本研究以(Kim,1985) 的模型出發，建立一個動態的中古車市場模型，考慮資訊不對稱、車輛的耐用年限、折舊、消費者所得與偏好、中古車商、新車製造商的策略，將以模型驗證此趨勢及分析未來的產業發展研究中古車市場的成功條件及廠商競爭的動態。本研究顯示向消費者提供完全透明的資訊並不是車商最有利的策略，而較低的訂價或亦是在相同的情形之下提供更好的品質，則是車商可以取得競爭優勢的方向。由我們的模擬分析可知，資訊透明與價格競爭皆是中古車商致命的弱點，從本研究也可以看到原廠車商兼營中古車市場其實不一定是最佳的策略。

第二篇 實驗性預測市場的效率：公開資訊、信念演變和人格特質，本文研究市場匯集資訊的能力，使市場上產生的價格包含所有可用資訊的最佳估計。本文研究個人如何依據市場價格從其公開和私人資訊中“更新”其最初的信念。特別是本文觀察於個人在公開資訊與私人資訊之間的權重。同樣，通過擁有私人資訊的交易者數量增加，市場中的資訊對市場價格的品質具有正面影響。最後，如果在市場上“高效而有組織”的交易者的比例各不相同，交易者的人格特質會產生一些正面影響。
   
第三篇 電動車未來展望分析-以擴散理論為依據。本文從討論電動汽車的沿革再分析電動汽車未來發展，並以波特五力分析圖，說明五個影響電動車產業發展決定性的因素，還有不可忽視的就是電動汽車的儲能電池。其中最關鍵的是電池技術有待突破，目前占電動車成本三分之一以上的電池，也是讓電動車的價格無法下降的主因。電池的持續性，壽命、價格將影響電動汽車的發展，還有充電站普及化,各家廠商尚未統一。這些問題將會是決定電動車的發展速度最主要因素，亦將成為各車廠競相全力提升的目標，本研究將以Bass擴散理論及產品生命週期進行分析電動車的展望及相關進展。

Essay 1: Although used car market has grown rapidly over two decades in Taiwan, quality and price are the main criteria that consumers concerned when buying a used car. Due to lack of a used car certified standard, the reputation among car dealers varies. How to verify the quality of used cars is a crucial factor for buyers. Two decades ago, some unethical used car dealers sold vehicles with hidden issues, for instance, accidents or damage vehicles. These problems had restrained the growing of used car markets. Akerlof (1970) pointed out that the used car market will be failure due to the information asymmetry. The quality uncertainty makes consumers’ rights in the used car market cannot be reasonably protected, and often causes disputes after sales. Kim (1985) suggested that the information asymmetry in the used car market is not only limited to the used car buyers, but also many individual used car sellers. Inspired by the model of Kim (1985), this study established a dynamic model of a used car market. The model considered information asymmetry, the life of the vehicle, depreciation, consumer income, preference, the strategies of the used car dealers and new car manufacturers to identify the business model and the competition advantage of used car industry. This study 
will validate the trend with agent-based models and analyze the future of used car dynamics.

Essay 2: This paper examines the ability of markets to aggregate information so that the price generated from the market contains the best estimate of all the available information. The paper investigates how individuals “update” their initial beliefs from their public and private information in light of market prices. In particular, the paper looks at individuals' weighting of public information versus private information. Also, the volume of information in the market via an increased number of traders with private information has a positive impact on the quality of the market price. Lastly, the personality traits of the traders seem to provide some positive impact if the traders are diverse in terms of the proportion of “efficient and organized”traders in the market.

Essay 3: This article discusses the evolution of electric vehicles and analyzes the development of electric vehicles. Another key issue that cannot be ignored is the automotive energy storage battery. The durability, life, and price of batteries will affect the development of electric vehicles, as well as the popularization of charging stations. These issues will be the important factors in determining the development speed of electric vehicles, and they will also become the goal of various car manufacturers to strive for improvement. This study will analyze the prospects and related developments of electric vehicles.

目錄                                                                     I

表目錄                                                                   V

圖目錄   
                                                                VI
第一章         本論文介紹                                                1     

第二章         中古車市場動態模擬：代理人基建模方法之應用                4
  2.1          研究背景與目的                                        4
    2.1.1      研究背景                                                  4
    2.1.2      研究目的                                                  6
  2.2         文獻探討                                                   7
    2.2.1      資訊不對稱                                               8
    2.2.2      影響消費者決策之因素                                     9
      2.2.2.1  知覺風險                                                 10
      2.2.2.2  品牌形象與信任                                           10
      2.2.2.3  價格與服務                                               11
      2.2.2.4  中古車聯盟與售後服務                                    12
      2.2.2.5  所得與資訊的不對稱影響中古車市場規模                    13
  2.3         研究方法                                               13
    2.3.1      模型                                                    14
    2.3.2      代理人基中古車市場                                      16
      2.3.2.1  代理人                                                  17
      2.3.2.2  代理人限制及策略                                        18
  2.4.         實驗設計與模擬結果                                      21
    2.4.1      實驗設計                                                21
    2.4.2      模擬結果                                                24
  2.5         結論                                                    32

第三章         實驗性預測市場的效率：公開資訊、信念演變和人格特質      34
  3.1	       前言                                                    34
  3.2          預測市場之文獻綜述                                      35
  3.3          實驗設計                                                37
    3.3.1      受試者                                                  38
    3.3.2      資訊發佈設計                                            38
    3.3.3      受試者的信念                                            39
    3.3.4      交易                                                    39
    3.3.5      清算                                                    41
  3.4          實驗數據分析                                              41
    3.4.1      市場效率                                                42
    3.4.2      回歸模型                                                46
    3.4.3      人格特質的異質性                                          47
    3.4.4      假設                                                    48
  3.5          結果與討論                                                49
    3.5.1      公開資訊                                                 52
    3.5.2      交易者人數                                              53
    3.5.3      性別差異                                                53
    3.5.4      限價單比率                                              54
    3.5.5      人格特質的差異性                                        54
    3.5.6      重複交易的經驗程度                                      54
  3.6          結論                                                    55

第四章         電動車的未來展望分析：以創新擴散理論為依據               57
  4.1          介紹                                                    57
    4.1.1      研究背景與動機                                          57
  4.2          文獻探討                                                59
  4.3          模型                                                    61
    4.3.1      Bass模型簡介                                           61
    4.3.2      電動車的生命週期-新創期、成長期、成熟期、衰退期         62
      4.3.2.1  實驗室-測試者簡介                                       64
      4.3.2.2  早期成長期-早期消費者簡介                               65
      4.3.2.3  成長期-消費者簡介                                       69
      4.3.2.4  早期衰退期-晚期消費者簡介                               71
      4.3.2.5  衰退期與博物館期-落後者簡介                             74
  4.4          研究分析                                                76
    4.4.1      利用波特五力分析電動車產業的概況                        76
    4.4.2      產業興起要素 RMCE 分析                                  79
  4.5          結論                                                    81

第五章         綜合結論                                                84

參考文獻                                                               86

表目錄
表 2.1     新車與中古車領牌數                                          7
表 2.2     實驗參數設計表                                              22
表 3.1     市場效率測試                                                45
表 3.2     敘述統計表                                                  48
表 3.3     基本面偏誤的迴歸結果                                          50
表 3.4     信念偏誤的迴歸結果                                          51
表 3.5    回合固定效果(αt) 和 趨勢迴歸結果                           52
表 4.1     各種能源自用小客車新增掛牌數                                67
表 4.2     電動車的優缺點比較表                                        74

圖目錄
圖  2.1    代理人狀態轉換圖                                            16
圖  2.2    新車與中古車各期成交量                                      24
圖  2.3    新車與中古車各期銷售額                                      24
圖  2.4    消費者各期總效用                                            26
圖  2.5    中古車商各期平均營運資金餘額                                27
圖  2.6    原廠車商各期平均營運資金餘額                                28
圖  2.7    車輛各期平均年數                                            29
圖  2.8    車輛各期平均維護水準                                        30
圖  2.9    車輛各期平均交易次數                                        30
圖  2.10   消費者採用策略所占之比例                                    31                                
圖  3.1    兩種處理的定價誤差 (pc – FV)（y 軸）與每個真實值 (K)（x 軸）   43
圖  4.1    電動車不同階段的表示圖                                      63
圖  4.2    自用小客車新增掛牌數                                        67
圖  4.3    2016~2019 全球各國電動車銷售量                              72
圖  4.4    透過這個波特五力分析圖                                       77

英文文獻
Aaker, D. A. and Biel, A. L. (1995). Brand Equity and Advertising: Advertising's Role in Building Strong Brand. New Jersey Lawrence Erlbaum Associates.
Abdellaoui, M. (2000). Parameter-free elicitation of utilities and probability weighting functions. Management Science, 46, 1497-1512.
Abdellaoui, M., F. Vossmann, & M. Weber (2005). Choice-based elicitation and decomposition of decision weights for gains and losses under uncertainty. Management Science, 51, 1384-1399.
Ackert, L. F., B. K. Church, & P. Zhang (2002). Market behavior in the presence of divergent and imperfect private information: experimental evidence from Canada, China, and the United States. Journal of Economic Behavior & Organization, 47, 435-450.
Akerlof, G. (1970). The market for "lemons": Quality uncertainty and the market mechanism. The Quarterly Journal Economics, 84(3), 488-500.
Ali, M. M. (1977). Probability and utility estimates for racetrack bettors. Journal of Political Economy, 85, 803-15.
Arias, N.B., S. Hashemi, & P.B. Andersen (2019). Distribution system services provided by electric vehicles: recent status, challenges, and future prospects.IEEE Transactions on Intelligent Transportation Systems, Volume: 20, 4277 - 4296.
Ballinger, T. P., E. Hudson, L. Karkoviata, & N. T. Wilcox (2011). Saving behavior and cognitive abilities. Experimental Economics, 14, 349-374.
Bass, F. (1969). A new product growth for model consumer durables. Management Science, 15 (5), 215-227. doi:10.1287/mnsc.15.5.215.
Bauer, R. A. (1960). Consumer behavior as risk taking, in Dynamic Marketing for a Changing World, ed. Robert S. Hancock, Chicago. American Marketing Association, pp. 267-281.
Belch, G. E. & M. A. Belch (1998). Advertising and Promotion. New York: McGraw-Hill.
Berg, J. & T. Rietz (2006). The Iowa electronic markets: stylized facts and open issues. in R. W. Hahn and P. C. Tetlock (ed.), Information Markets: A New Way of Making Decisions AEI-Brookings Joint Center for Regulatory Studies, 142-169.
Berg, J. Nelson, F. & T. Rietz (2008). Prediction market accuracy in the long run. International Journal of Forecasting, 24, 285-300.
Browne, H. (1999). Fail-Safe Investing: Lifelong Financial Security in 30 Minutes. N.Y.: St. Martin's Press. 
Camerer, C. F. & T. H. Ho (1994). Nonlinear weighting of probabilities and violations of the betweenness axiom. Journal of Risk and Uncertainty, 8, 167-196.
Chamberlin, E. H. (1948). An experimental imperfect market. Journal of Political Economy, 56, 95-108.
Christiansen, J. D. (2007). Prediction markets: practical experiments in small markets and behaviours observed. The Journal of Prediction Markets, 1, 17-41.
Cheng, M. & M. Tong (2017).Development status and trend of electric vehicles in China.Chinese Journal of Electrical Engineering, Volume: 3, Issue: 2, Page(s): 1 - 13.
Covic, GA., J.T. Boys, M. Budhia, & C.Y. Huang(2010).Electric Vehicles-Personal transportation for the future.World Electric Vehicle Journal,, 4(4), 693-704
Copeland, T. E. & D. Friedman (1987). The effect of sequential information arrival on asset prices: an experimental study. Journal of Finance, 42, 763-797.
Costa, P. T. & R. R. McCrae Jr. (1985). The NEO personality inventory manual, Odessa, FL: Psychological Assessment Resources.
Cox, D. F., & Rich, S. U. (1964). Perceived risk and consumer decision-making: The case of telephone shopping. Journal of Marketing Research, 1(4), 32-39. 
Cox, B., C.L. Mutel, & C. Bauer (2018). Uncertain environmental footprint of current and future battery electric vehicles. Environ. Sci. Technol, 52, 8, 4989-4995
Croson, R. & U. Gneezy (2009). Gender differences in preferences. Journal of Economic Literature, 47, 448-474.
Cunningham, M. S. (1967). The Major Dimensions of Perceived Risk. In Risk Taking and Information Handling in Consumer Behavior. Boston, MA: Harvard Business Press. 
Deck, C., S. Lin, & D. Porter (2013). Affecting policy by manipulating prediction markets: experimental evidence. Journal of Economic Behavior & Organization, 85, 48-62.
Dowling, G. R. & R. Staelin (1994). A model of perceived risk and intended risk-handling activity. Journal of Consumer Research, 21(1), 119-134.
Dreber, A., E. von Essen, & E. Ranehill (2011). Outrunning the gender gap-boys and girls compete equally. Experimental Economics, 14, 567-582.
Dong J, C. Liu, & Z. Lin (2014). Charging infrastructure planning for promoting battery electric vehicles: An activity-based approach using multiday travel data. Transportation Research Part C: Emerging Technologies,Volume 38, 44-55
Du, J. & D. Ouyang (2017). Progress of Chinese electric vehicles industrialization in 2015: A review. Applied Energy, Volume 188, 529-546
Ehmke, M. D. T. (2006). Dissertation abstract: The influence of culture on economic behavior with applications to food and the environment. Experimental Economics, 9, 167-168.
Featherman, M. S. & P. A. Pavlou (2003). Predicting e-services adoption: a perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451-474.
Figlewski, S. (1978). Market 'efficiency' in a market with heterogeneous information. Journal of Political Economy, 86, 581-597.
Figlewski, S. (1979). Subjective information and market efficiency in a betting market. The Journal of Political Economy, 87, 75-88.
Fischbacher, U. (2007). z-Tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10, 171-178.
Forsythe, R. & R. Lundholm (1990). Information aggregation in an experimental market. Econometrica, 58, 309-347. 
Forsythe, R., F. Nelson, G. Neumann, & J. Wright (1992). Anatomy of an experimental political stock market. The American Economic Review, 82, 1142-1161.
Forsythe, R., T. Rietz, & T. Ross. (1999). Wishes, expectations and actions: a survey on price formation in election stock markets. Journal of Economic Behavior & Organization, 39, 83-110.
Gandoman, F.H., A. Ahmadi, & P. Van den Bossche (2019).Status and future perspectives of reliability assessment for electric vehicles. Reliability Engineering & System Safety,Volume 183, Pages 1-16
Gjerstad, S. (2005). Risk aversion, beliefs, and prediction market equilibrium. Unpublished Manuscript, Economic Science Laboratory, University of Arizona.
Gresik, T. A. & M. A. Satterthwaite (1989). The rate at which a simple market converges to efficiency as the number of traders increases: an asymptotic result for optimal trading mechanisms. Journal of Economic Theory, 48, 304-332.
Griffith, R. M. (1949). Odds adjustments by american horse-race bettors. The American Journal of Psychology, 62, 290-294.
Hahn, R. W. & P. C. Tetlock (2006). Information markets: a new way of making decisions, AEI-Brookings Joint Center for Regulatory Studies.
Hanson, R. D. (2006). Designing real terrorism futures. Public Choice, 128, 257-274.
Hanson, R., R. Oprea, & D. Porter (2006). Information aggregation and manipulation in an experimental market. Journal of Economic Behavior & Organization, 60, 449-459.
Haruvy, E., Y. Lahav, & C. N. Noussair (2007). Traders' expectations in asset markets: experimental evidence. American Economic Review, 97, 1901-1920.
Hayek, F. (1945). The use of knowledge in society. American Economic Review, 35, 519-530.
Hazen, T. L. (1987). Volatility and market inefficiency: a commentary on the effects of options, futures, and risk arbitrage on the stock market. Washington and Lee Law Review, 44, 789-805.
Hurley, W. & L. McDonough (1995). Note on the Hayek hypothesis and the favorite-longshot bias in parimutuel betting. American Economic Review, 85, 949-955.
Isaacs, R. (1953). Optimal horse race bets. American Mathematical Monthly, 60, 310-315.
Jing, W. Y Yan, I Kim, & M Sarvi (2016). Electric vehicles: A review of network modelling and future research needs. Advances in Mechanical engineering,Volume: 8 issue: 1
Karden, E. S Ploumen, B Fricke, & T Miller(2007).Energy storage devices for future hybrid electric vehicles.Journal of Power Sources, Volume 168, Pages 2-11
Kim, J. C. (1985). The market for "lemons" reconsidered: A model of the used car market with asymmetric information. The American Economic Review, 75(4), 836-843.
Knetsch, J. F. F. Tang, & R. Thaler (2001). The endowment effect and repeated market trials: is the Vickrey auction demand revealing? Experimental Economics, 4, 257-269.
Kotler, P. (2000). Marketing Management, 10th Ed. Englewood Cliffs, N.J.: Prentice-Hall. 
Kong, D. Q Xia, Y Xue, & X Zhao (2020).Effects of multi policies on electric vehicle diffusion under subsidy policy abolishment in China: a multi-actor perspective.Applied Energy,Volume 266, 114887
Lee, D. S. & E. Moretti (2009). Bayesian learning and the pricing of new information: evidence from prediction markets. American Economic Review, 99, 330-336.
Leibbrandt, A. (2012). Are social preferences related to market performance? Experimental Economics, 15, 589-603.
Li, Z. A Khajepour, & J Song(2019). A comprehensive review of the key technologies for pure electric vehicles. Energy, Volume 182, 824-839.
Liu, J. & C Zhong (2019). An economic evaluation of the coordination between electric vehicle storage and distributed renewable energy. Energy, Volume 186, 115821.
Loomes, G. C. Starmer, & R. Sugden (2003). Do anomalies disappear in repeated markets? Economic Journal, 113, C153-C166.
Maloney, M. T. & J. H. Mulherin (2003). The complexity of price discovery in an efficient market: the stock market reaction to the Challenger crash. Journal of Corporate Finance, 9, 453-479.
Milligan, A. (2003). Samsung points the way for Asian firms in global brand race. Media, 8-8.
Monroe, K. B. (1990). Pricing: Making Profitable Decisions 2nd Ed. New York, McGraw-Hill.
Oechssler, J. (2012). Finitely repeated games with social preferences. Experimental Economics, doi:10.1007/s10683-012-9336-6.
Oliven, K. & T. A. Rietz (2004). Suckers are born but markets are made: individual rationality, arbitrage, and market efficiency on an electronic futures market. Management Science, 50, 336-351.
Oosterbeek, H., R. Sloof, & G. Van De Kuilen (2004). Cultural differences in ultimatum game experiments: evidence from a meta-analysis. Experimental Economics, 7, 171-188.
Ottaviani, M. & P. N. Sørensen (2007). Outcome manipulation in corporate prediction markets. Journal of the European Economic Association, 5, 554-563.
Ottaviani, M. & P. N. Sørensen (2010). Noise, information, and the favorite-longshot bias in parimutuel predictions. American Economic Journal: Microeconomics, 2, 58-85.
Ouyang, D. X. Ou, Q. Zhang, & C. Dong (2020). Factors influencing purchase of electric vehicles in China.Mitigation and Adaptation Strategies for Global Change, volume 25, 413-440.
Peter, J. P. & Tarpey, L. X. (1975). Comparative analysis of three consumers decision strategies. Journal of Consumer Research, 2(1), 29-37.
Plott, C. R. & S. Sunder (1982). Efficiency of experimental security markets with insider information: an application of rational-expectations models. Journal of Political Economy, 90, 663-698.
Plott, C. R. & S. Sunder (1988). Rational expectations and the aggregation of diverse information in laboratory security markets. Econometrica, 56, 1085-1118. 
Plott, C. R., J. Wit, & W.C. Yang (2003). Parimutuel betting markets as information aggregation devices: experimental results. Economic Theory, 22, 311-351. 
Rassaei, F., W.S. Soh, & K.C. Chua (2015). Demand response for residential electric vehicles with random usage patterns in smart grids.IEEE Transactions on Sustainable Energy, Volume: 6, Issue: 4, 1367 - 1376 
Richa, K. C.W. Babbitt, G. Gaustad, & X. Wang (2014). A future perspective on lithium-ion battery waste flows from electric vehicles.Resources, Conservation and Recycling,Volume 83, 63-76
Roll, R. (1984). Orange juice and weather. American Economic Review, 74, 861-880.
Roselius, T. (1971). Consumer rankings of risk reduction methods. Journal of Marketing, 35(1), 56-61.
Rosenberg, B., K. Reid, & R. Lanstein (1985). Persuasive evidence of market inefficiency. Journal of Portfolio Management, 11, 9-16.

Salmasi, FR. (2007). Control strategies for hybrid electric vehicles: Evolution, classification, comparison, and future trends.IEEE Transactions on Vehicular Technology, Volume: 56, Issue: 5,  2393 - 2404
Shepherd, S. P Bonsall, & G Harrison(2012). Factors affecting future demand for electric vehicles: A model based study.Transport Policy,Volume 20, 62-74
Situ. L. (2009). Electric vehicle development: the past, present & future.2009 3rd International Conference on Power Electronics Systems and Applications (PESA),INSPEC Accession Number: 10860727
Smith, S., and Wheeler, J. (2002). Managing the Customer Experience: Turning Customers into Advocates. Pearson Education.
Smith, V. L. (1962). An experimental study of competitive market behavior. Journal of Political Economy, 70, 111-137.
Smith, V. L. (1982). Microeconomic systems as an experimental science. American Economic Review, 72, 923-955.
Snowberg, E., J. Wolfers, & E. Zitzewitz (2007). Partisan impacts on the economy: evidence from prediction markets and close elections. Quarterly Journal of Economics, 122, 807-829.
Spence, M. (1977). Consumer misperceptions, product failure and product liability. The Review of Economic Studies, 44(3), 561-572.
Stott, H. P. (2006). Cumulative prospect theory's functional menagerie. Journal of Risk and Uncertainty, 32, 101-130.
Taylor, J. W. (1974). The role of risk in consumer behavior. Journal of Marketing, 38(2), 54-60.
Terrell, D. & A. Farmer (1996). Optimal betting and efficiency in parimutuel betting markets with information costs. Economic Journal, 106, 846-868.
Tufano, F. (2010). Are 'true' preferences revealed in repeated markets? an experimental demonstration of context-dependent valuations. Experimental Economics, 13, 1-13.
Tversky, A. & C. Fox (1995). Weighing risk and uncertainty. Psychological Review, 102, 269-283.
Tversky, A. & D. Kahneman (1992). Advances in prospect theory: cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5, 297-323.
Veiga, H. & M. Vorsatz (2010). Information aggregation in experimental asset markets in the presence of a manipulator. Experimental Economics, 13, 379-398.
Visser, M. S. & M. R. Roelofs (2011). Heterogeneous preferences for altruism: gender and personality, social status, giving and taking. Experimental Economics, 14, 490-506.
Weitzman, M. (1965). Utility analysis and group behavior: an empirical study. Journal of Political Economy, 73, 18-26. Weinert, J. J Ogden, D Sperling, A Burke(2008).The future of electric two-wheelers and electric vehicles in China.Energy Policy,Volume 36, 2544-2555
Wiseman, F. (1971). A segmentation analysis on automobiles buyers during the new model year transition period. Journal of Marketing, 35(2): 42-49.
Wlezien, C. & R. S. Erikson (2004). The fundamentals, the polls, and the presidential vote. PS: Political Science and Politics, 37, 747-751.
Wolfers, J. & E. Zitzewitz (2004). Prediction markets. The Journal of Economic Perspectives, 18, 107-126.
Wood, C. M. & L. K. Scheer (1996). "Incorporating perceived risk into models of consumer deal assessment and purchase intent", in NA - Advances in Consumer Research Volume 23, eds. Kim P. Corfman and John G. Lynch Jr., Provo, UT: Association for Consumer Research, 399-404.
Wu, G. & R. Gonzalez (1996). Curvature of the probability weighting function. Management Science, 42, 1676-1690.
Zhang, Q. C Li, & Y Wu (2017).Analysis of research and development trend of the battery technology in electric vehicle with the perspective of patent.Energy Procedia, Volume 105, 4274-4280
Zhuge, C. B. Wei, C Dong, C Shao, & Y Shan (2019). Exploring the future electric vehicle market and its impacts with an agent-based spatial integrated framework: A case study of Beijing, China.Journal of Cleaner Production, Volume 221, 1 June 2019, Pages 710-737.

中文文獻
林茂文(2020)。全球電動車發展之挑戰與契機。 石油季刊，56卷1期，1 - 28。
周宜德、曾振南、陳中邦(2018)。台灣電動車產業政策與推廣措施之探討。石油季刊，54卷3期，23 - 36。
柴海波、鄢治國、況明偉、吳建東(2013)。電動車驅動電機發展現狀。微特電機，第4期，52 - 57。
陳映蓉、尤晴韻(2020)。歐美國家電動車發展趨勢。臺灣經濟研究月刊，43卷4期，36 - 44。
蔡佩玲 (2018)。電動車充電站關鍵成功因素之探討。國立成功大學機構典藏。
謝依芸（2021)。電動車時代：機會，挑戰與展望。土木水利，48卷4期，79 - 87。
謝騄璘 (2018)。電動車最普及國家 - 挪威電動車市場剖析。機械工業雜誌，421期，33 - 38