网络效应、新兴产业演化与生态位培育——来自电动汽车行业的ABM仿真研究
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摘要
有限的需求规模是制约电动汽车产业发展的关键因素,如何促进市场培育是电动汽车产业演化中亟待解决的重要问题.本文在分析汽车产业网络效应的特征及其存在性基础上,利用ABM框架构建了异质性厂商和消费者的决策模型,模拟仿真了网络效应下汽车产业演化的基本过程和市场需求的分布演化特征,进而讨论了充电基础设施建设对于电动汽车市场培育的差异化作用.结果表明:汽车产业中既存在着与用户规模有关的直接网络效应,也存在着与配套基础设施有关的间接网络效应;在汽车产业的演化过程中,传统汽车始终占据市场主导地位,电动汽车的市场份额十分有限;空间分布上,电动汽车市场需求呈现出"分散—集中"的态势;充电设施建设通过增强网络效应有效地刺激了消费者购买,其政策效果在电动汽车需求分布由分散趋于集中的阶段体现出来;与全局建设相比,局部建设依靠提高特定区域充电站的密度集中强化网络效应,从而增加了潜在消费者购买电动汽车的动力,加速了电动汽车市场需求规模的扩大.
The limited market demand is the key factor restricting the development of electric vehicle industry,and the market cultivation becomes an important and urgent problem to be solved in the evolution of electric vehicle industry. In this paper,the characteristics of network effects are firstly analyze d in the automobile industry and its existence is tested. A decision-making model including both heterogeneous manufacturers and consumers is constructed based on an agent-based framework to simulate the basic evolutionary process of auto industry under network effects and the distribution of market demand. The different effects of charging infrastructure construction for the electric vehicle market cultivation are then discussed. The results show that there exists both direct and indirect network effects separately concerning the user's size and complementary infrastructure in the auto industry. Conventional vehicles have been dominating the market during the evolution,leaving a very limited market share to EVs. Regarding the spatial distribution,the demand of electric vehicles shows a"decentralized-concentrated"trend in the simulation. The construction of charging infrastructure stimulates consumers' purchase willingness effectively by enhancing the network effects,which is demonstrated in the stage when the distribution of EV demand is turning from disperse to centralized. Compared with the overall construction,local construction can strengthen the network effects intensively by increasing the density of charging stations in specific areas to increase the willingness of potential consumers to buy electric cars,and therefore,accelerates the expansion of EVs' market demand.
The limited market demand is the key factor restricting the development of electric vehicle industry,and the market cultivation becomes an important and urgent problem to be solved in the evolution of electric vehicle industry. In this paper,the characteristics of network effects are firstly analyze d in the automobile industry and its existence is tested. A decision-making model including both heterogeneous manufacturers and consumers is constructed based on an agent-based framework to simulate the basic evolutionary process of auto industry under network effects and the distribution of market demand. The different effects of charging infrastructure construction for the electric vehicle market cultivation are then discussed. The results show that there exists both direct and indirect network effects separately concerning the user's size and complementary infrastructure in the auto industry. Conventional vehicles have been dominating the market during the evolution,leaving a very limited market share to EVs. Regarding the spatial distribution,the demand of electric vehicles shows a"decentralized-concentrated"trend in the simulation. The construction of charging infrastructure stimulates consumers' purchase willingness effectively by enhancing the network effects,which is demonstrated in the stage when the distribution of EV demand is turning from disperse to centralized. Compared with the overall construction,local construction can strengthen the network effects intensively by increasing the density of charging stations in specific areas to increase the willingness of potential consumers to buy electric cars,and therefore,accelerates the expansion of EVs' market demand.
引文
[1]林伯强,杜之利.中国城市车辆耗能与公共交通效率研究[J].经济研究,2018(6):142-156.Lin Boqiang,Du Zhili.A study of China’s urban vehicle energy consumption and public transport efficiency[J].Economics Research Journal,2018(6):142-156.(in Chinese)
[2]Vernon R.International investment and international trade in the product cycle[J].The Quarterly Journal of Economics,1966:190-207.
[3]Abernathy W J,Utterback J M.Patterns of industrial innovation[J].Technology Review,Ariel,1978,64:228-254.
[4]Gort M,Klepper S.Time paths in the diffusion of product innovation[J].The Economic Journal,1982,92(367):630-653.
[5]Klepper S,Graddy E.The evolution of new industries and the determinants of market structure[J].The RAND Journal of E-conomics,1990:27-44.
[6]Schumpeter J A.Capitalism,Socialism,and Democracy[M].Fifth edition.London:George Allen and Unwin,1976.
[7]Sabatier V,Craig-Kennard A,Mangematin V.When technological discontinuities and disruptive business models challenge dominant industry logics:Insights from the drugs industry[J].Technological Forecasting and Social Change,2012,79(5):949-962.
[8]Yildizoglu M.Competing R&D strategies in an evolutionary industry model[J].Computational Economics,2002,19(1):51-65.
[9]Grodal S,Gotsopoulos A,Suarez F F.The coevolution of technologies and categories during industry emergence[J].Academy of Management Review,2015,40(3):423-445.
[10]Blankenberg A K,Buenstorf G.Regional co-evolution of firm population,innovation and public research?Evidence from the West German laser industry[J].Research Policy,2016,45(4):857-868.
[11]Kale D,Little S.From imitation to innovation:The evolution of R&D capabilities and learning processes in the Indian pharmaceutical industry[J].Technology Analysis&Strategic Management,2007,19(5):589-609.
[12]Wahab M.Asymmetric output growth effects of government spending:Cross-sectional and panel data evidence[J].International Review of Economics and Finance,2011,20(4):574-590.
[13]Schuitema G,Anable J,Skippon S,et al.The role of instrumental,hedonic and symbolic attributes in the intention to adopt electric vehicles[J].Transportation Research Part A:Policy and Practice,2013,48:39-49.
[14]周亚虹,蒲余路,陈诗一,等.政府扶持与新型产业发展---以新能源为例[J].经济研究,2015,50(6):147-161.Zhou Yahong,Pu Yulu,Chen Shiyi,et al.Government support and development of emerging industries:A new energy industry survey[J].Economics Research Journal,2015,50(6):147-161.(in Chinese)
[15]孙晓华,王昀,刘小玲.范式转换,异质性与新兴产业演化[J].管理科学学报,2016,19(8):67-83.Sun Xiaohua,Wang Yun,Liu Xiaoling.Paradigm shift,heterogeneity and evolution of emerging industry[J].Journal of Management Sciences in China,2016,19(8):67-83.(in Chinese)
[16]Egbue O,Long S.Barriers to widespread adoption of electric vehicles:An analysis of consumer attitudes and perceptions[J].Energy Policy,2012,48:717-729.
[17]Carley S,Krause R M,Lane B W,et al.Intent to purchase a plug-in electric vehicle:A survey of early impressions in large US cites[J].Transportation Research Part D:Transport and Environment,2013,18:39-45.
[18]Krupa J S,Rizzo D M,Eppstein M J,et al.Analysis of a consumer survey on plug-in hybrid electric vehicles[J].Transportation Research Part A:Policy and Practice,2014,64:14-31.
[19]Hagman J,Ritzén S,Stier J J,et al.Total cost of ownership and its potential implications for battery electric vehicle diffusion[J].Research in Transportation Business&Management,2016,18:11-17.
[20]Moons I,De Pelsmacker P.Emotions as determinants of electric car usage intention[J].Journal of Marketing Management,2012,28(3-4):195-237.
[21]Rezvani Z,Jansson J,Bodin J.Advances in consumer electric vehicle adoption research:A review and research agenda[J].Transportation Research Part D:Transport and Environment,2015,34:122-136.
[22]Byrka K,Jedrzejewski A,Sznajd-Weron K,et al.Difficulty is critical:The importance of social factors in modeling diffusion of green products and practices[J].Renewable and Sustainable Energy Reviews,2016,62:723-735.
[23]Jansson J,Nordlund A,Westin K.Examining drivers of sustainable consumption:The influence of norms and opinion leadership on electric vehicle adoption in Sweden[J].Journal of Cleaner Production,2017,154:176-187.
[24]Axsen J,Orlebar C,Skippon S.Social influence and consumer preference formation for pro-environmental technology:The case of a UK workplace electric-vehicle study[J].Ecological Economics,2013,95:96-107.
[25]Axsen J,Kurani K S.Interpersonal influence within car buyers’social networks:Applying five perspectives to plug-in hybrid vehicle drivers[J].Environment and Planning A,2012,44(5):1047-1065.
[26]Nayum A,Kl9ckner C A,Mehmetoglu M.Comparison of socio-psychological characteristics of conventional and battery electric car buyers[J].Travel Behaviour and Society,2016,3:8-20.
[27]Gnann T,Pl9tz P.A review of combined models for market diffusion of alternative fuel vehicles and their refueling infrastructure[J].Renewable and Sustainable Energy Reviews,2015,47:783-793.
[28]Yu Z,Li S,Tong L.Market dynamics and indirect network effects in electric vehicle diffusion[J].Transportation Research Part D:Transport and Environment,2016,47:336-356.
[29]Klepper S,Simons K L.Industry shakeouts and technological change[J].International Journal of Industrial Organization,2005,23(1):23-43.
[30]盛昭瀚,高洁,杜建国.基于NW模型的新熊彼特式产业动态演化模型[J].管理科学学报,2007(1):1-8.Sheng Zhaohan,Gao Jie,Du Jianguo.Neo-schumpeterian evolutionary model of industrial dynamics based on NW model[J].Journal of Management Sciences in China,2007(1):1-8(in Chinese)
[31]向诗剑,马铁驹.ABM与GIS集成及在分析新能源汽车扩散中的应用[J].管理科学学报,2014,17(1):1-10.Xiang Shijian,Ma Tieju.Integration of ABM and GIS and its application in analysis of diffusion of alternative energy vehicles[J].Journal of Management Sciences in China,2014,17(1):1-10(in Chinese)
[32]Eppstein M J,Rizzo D M,Lee B H Y,et al.Using national survey respondents as consumers in an agent-based model of plug-in hybrid vehicle adoption[J].IEEE Access,2015,3:457-468.
[33]Zhang T,Gensler S,Garcia R.A study of the diffusion of alternative fuel vehicles:An agent-based modeling approach[J].Journal of Product Innovation Management,2011,28(2):152-168.
[34]Kangur A,Jager W,Verbrugge R,et al.An agent-based model for diffusion of electric vehicles[J].Journal of Environmental Psychology,2017,52:166-182.
[35]Karaaslan E,Noori M,Lee J Y,et al.Modeling the effect of electric vehicle adoption on pedestrian traffic safety:An agent-based approach[J].Transportation Research Part C:Emerging Technologies,2018,93:198-210.
[36]Katz M L,Shapiro C.Network externalities,competition,and compatibility[J].The American Economic Review,1985,75(3):424-440
[37]Liebowitz S J,Margolis S E.Network externality:An uncommon tragedy[J].Journal of Economic Perspectives,1994,8(2):133-150.
[38]Shankar V,Bayus B L.Network effects and competition:An empirical analysis of the home video game industry[J].Strategic Management Journal,2003,24(4):375-384.
[39]Keith D,Sterman J,Struben J.Understanding spatiotemporal patterns of hybrid-electric vehicle adoption in the United States[R].2012.
[40]李永立,陈杨,樊宁远,等.考虑个体效用因素的社会网络演化分析模型[J].管理科学学报,2018,21(3):41-53.Li Yongli,Chen Yang,Fan Ningyuan,et al.Utility-based model for interpreting evolution patterns of social networks[J].Journal of Management Sciences in China,2018,21(03):41-53(in Chinese)
[41]Malerba F,Nelson R,Orsenigo L,et al.Demand,innovation,and the dynamics of market structure:The role of experimental users and diverse preferences[J].Journal of Evolutionary Economics,2007,17(4):371-399.
(2)早期研究中,“网络外部性”和“网络效应”经常被认为是相同的.但是Liebowitz和Margolis[37]指出两个概念之间存在着一定的差别,认为当网络中的其他参与者的影响能够被内部化时,应该被称作网络效应,反之则应称为网络外部性.本文研究中认为消费者的购车决策受到的其它参与者的影响会内化为效用影响,因此后文均采用“网络效应”这一名词.
(3)汽车的性能指标很多,考虑到传统车和电动汽车之前的性能差异主要体现在续航里程上,故本文选择续航里程作为性能指标.下文所涉及到的性能均指续航里程.
(4)混合logit模型是在条件logit模型中加入只随个体而变的解释变量,因此本文只详细介绍更加复杂的混合logit模型,省略条件logit模型的介绍.
(5)限于篇幅,简略了具体计量方法及过程的详细说明,如有需要,可以向作者索取.
(6)汽车的型号多种多样,价格差别也非常明显,但对于同一档次的车型而言,电动汽车价格要高于传统汽车.
(7)Melerba[41]较早从性能和价格门槛角度探讨了试验性用户对产业演化的影响,本文据此设置了消费者对于购买车辆的性能和价格门槛.C-min Cjc/n,0
(8)Ranjc/n,0=Ranc/n+0×r/rmax Cjc/n,0-min Cc/n,Ranc/nc/n表示基础性能,jc/n,0表示初始成本对初始性能的影响.
(9)不考虑厂商生产的固定成本及其他费用支出,利润πj,t=(Pj,t-Cj,t)×Qj,t.其中Qj,t表示第t期企业j的销量.
(10)比较而言,传统汽车的生产工艺较为成熟,成本下降和性能提升空间较小,速度较慢;电动汽车的成本下降和性能提升空间均较大,且速度较快.
(11)在本文中,第十期时消费者才全部进行完购车决策,因此第十一期设置退出机制,淘汰掉前十期一直没有销量的企业.之后,当连续三期没有销量时,企业自动退出,且退出后不再进入.
(12)EXCSi+n=(1+ECSi)×CSi,EXCSi+n表示第i期消费者对下次换车时周围充电站数量的心理预期,ECSi是心理预期调整系数,ECSi+1=ECSi±ΔECS,CSi表示第i期消费者周围的充电站数量.
(13)公式(8)为条件logit模型,可以通过MLE估计得到系数估计值β.
(14)在汽车产业演化过程中,传统汽车厂商作为在位企业居于市场主导地位,电动汽车厂商作为潜在进入者,与传统汽车厂商展开竞争.为了体现传统汽车厂商的先发优势,一种方法是让其提前进入市场,另一种方法是通过参数设置上的差别予以体现.经过几十年的发展,传统汽车的性能已经较为完善,价格和用户数量趋于稳定,配套基础设施建设也相对完备,因此本文选择第二种方式,即通过性能和价格属性,以及直接与间接网络效应的设定,反映其相对于电动汽车的比较优势.
(15)电动汽车的性能和价格之所以在第10期左右显著变化,很大程度上是由于第10期没有竞争力的厂商退出市场,而这部分厂商通常在价格和性能方面都处于落后水平.
(16)与生产性补贴和消费性补贴的方式不同,充电基础设施建设的效果具有时间延续性.为了避免与前5期实施的政府补贴存在交互影响,本文选择在政府补贴停止的第6期投入充电设施建设,并且只在第6期实施一期.
(17)充电站的建设来源于两方面,一是来源于电动汽车用户数增多带来的市场自发建设,二是来自于政府部门主导的建设,前者已经在模拟过程中予以考虑.
(18)这二者都会使全局建设政策下购买电动汽车的人数增加,但前者会使第20期左右电动汽车消费者的分布更集中,后者则会使第20期左右电动汽车消费者的分布相对分散
[2]Vernon R.International investment and international trade in the product cycle[J].The Quarterly Journal of Economics,1966:190-207.
[3]Abernathy W J,Utterback J M.Patterns of industrial innovation[J].Technology Review,Ariel,1978,64:228-254.
[4]Gort M,Klepper S.Time paths in the diffusion of product innovation[J].The Economic Journal,1982,92(367):630-653.
[5]Klepper S,Graddy E.The evolution of new industries and the determinants of market structure[J].The RAND Journal of E-conomics,1990:27-44.
[6]Schumpeter J A.Capitalism,Socialism,and Democracy[M].Fifth edition.London:George Allen and Unwin,1976.
[7]Sabatier V,Craig-Kennard A,Mangematin V.When technological discontinuities and disruptive business models challenge dominant industry logics:Insights from the drugs industry[J].Technological Forecasting and Social Change,2012,79(5):949-962.
[8]Yildizoglu M.Competing R&D strategies in an evolutionary industry model[J].Computational Economics,2002,19(1):51-65.
[9]Grodal S,Gotsopoulos A,Suarez F F.The coevolution of technologies and categories during industry emergence[J].Academy of Management Review,2015,40(3):423-445.
[10]Blankenberg A K,Buenstorf G.Regional co-evolution of firm population,innovation and public research?Evidence from the West German laser industry[J].Research Policy,2016,45(4):857-868.
[11]Kale D,Little S.From imitation to innovation:The evolution of R&D capabilities and learning processes in the Indian pharmaceutical industry[J].Technology Analysis&Strategic Management,2007,19(5):589-609.
[12]Wahab M.Asymmetric output growth effects of government spending:Cross-sectional and panel data evidence[J].International Review of Economics and Finance,2011,20(4):574-590.
[13]Schuitema G,Anable J,Skippon S,et al.The role of instrumental,hedonic and symbolic attributes in the intention to adopt electric vehicles[J].Transportation Research Part A:Policy and Practice,2013,48:39-49.
[14]周亚虹,蒲余路,陈诗一,等.政府扶持与新型产业发展---以新能源为例[J].经济研究,2015,50(6):147-161.Zhou Yahong,Pu Yulu,Chen Shiyi,et al.Government support and development of emerging industries:A new energy industry survey[J].Economics Research Journal,2015,50(6):147-161.(in Chinese)
[15]孙晓华,王昀,刘小玲.范式转换,异质性与新兴产业演化[J].管理科学学报,2016,19(8):67-83.Sun Xiaohua,Wang Yun,Liu Xiaoling.Paradigm shift,heterogeneity and evolution of emerging industry[J].Journal of Management Sciences in China,2016,19(8):67-83.(in Chinese)
[16]Egbue O,Long S.Barriers to widespread adoption of electric vehicles:An analysis of consumer attitudes and perceptions[J].Energy Policy,2012,48:717-729.
[17]Carley S,Krause R M,Lane B W,et al.Intent to purchase a plug-in electric vehicle:A survey of early impressions in large US cites[J].Transportation Research Part D:Transport and Environment,2013,18:39-45.
[18]Krupa J S,Rizzo D M,Eppstein M J,et al.Analysis of a consumer survey on plug-in hybrid electric vehicles[J].Transportation Research Part A:Policy and Practice,2014,64:14-31.
[19]Hagman J,Ritzén S,Stier J J,et al.Total cost of ownership and its potential implications for battery electric vehicle diffusion[J].Research in Transportation Business&Management,2016,18:11-17.
[20]Moons I,De Pelsmacker P.Emotions as determinants of electric car usage intention[J].Journal of Marketing Management,2012,28(3-4):195-237.
[21]Rezvani Z,Jansson J,Bodin J.Advances in consumer electric vehicle adoption research:A review and research agenda[J].Transportation Research Part D:Transport and Environment,2015,34:122-136.
[22]Byrka K,Jedrzejewski A,Sznajd-Weron K,et al.Difficulty is critical:The importance of social factors in modeling diffusion of green products and practices[J].Renewable and Sustainable Energy Reviews,2016,62:723-735.
[23]Jansson J,Nordlund A,Westin K.Examining drivers of sustainable consumption:The influence of norms and opinion leadership on electric vehicle adoption in Sweden[J].Journal of Cleaner Production,2017,154:176-187.
[24]Axsen J,Orlebar C,Skippon S.Social influence and consumer preference formation for pro-environmental technology:The case of a UK workplace electric-vehicle study[J].Ecological Economics,2013,95:96-107.
[25]Axsen J,Kurani K S.Interpersonal influence within car buyers’social networks:Applying five perspectives to plug-in hybrid vehicle drivers[J].Environment and Planning A,2012,44(5):1047-1065.
[26]Nayum A,Kl9ckner C A,Mehmetoglu M.Comparison of socio-psychological characteristics of conventional and battery electric car buyers[J].Travel Behaviour and Society,2016,3:8-20.
[27]Gnann T,Pl9tz P.A review of combined models for market diffusion of alternative fuel vehicles and their refueling infrastructure[J].Renewable and Sustainable Energy Reviews,2015,47:783-793.
[28]Yu Z,Li S,Tong L.Market dynamics and indirect network effects in electric vehicle diffusion[J].Transportation Research Part D:Transport and Environment,2016,47:336-356.
[29]Klepper S,Simons K L.Industry shakeouts and technological change[J].International Journal of Industrial Organization,2005,23(1):23-43.
[30]盛昭瀚,高洁,杜建国.基于NW模型的新熊彼特式产业动态演化模型[J].管理科学学报,2007(1):1-8.Sheng Zhaohan,Gao Jie,Du Jianguo.Neo-schumpeterian evolutionary model of industrial dynamics based on NW model[J].Journal of Management Sciences in China,2007(1):1-8(in Chinese)
[31]向诗剑,马铁驹.ABM与GIS集成及在分析新能源汽车扩散中的应用[J].管理科学学报,2014,17(1):1-10.Xiang Shijian,Ma Tieju.Integration of ABM and GIS and its application in analysis of diffusion of alternative energy vehicles[J].Journal of Management Sciences in China,2014,17(1):1-10(in Chinese)
[32]Eppstein M J,Rizzo D M,Lee B H Y,et al.Using national survey respondents as consumers in an agent-based model of plug-in hybrid vehicle adoption[J].IEEE Access,2015,3:457-468.
[33]Zhang T,Gensler S,Garcia R.A study of the diffusion of alternative fuel vehicles:An agent-based modeling approach[J].Journal of Product Innovation Management,2011,28(2):152-168.
[34]Kangur A,Jager W,Verbrugge R,et al.An agent-based model for diffusion of electric vehicles[J].Journal of Environmental Psychology,2017,52:166-182.
[35]Karaaslan E,Noori M,Lee J Y,et al.Modeling the effect of electric vehicle adoption on pedestrian traffic safety:An agent-based approach[J].Transportation Research Part C:Emerging Technologies,2018,93:198-210.
[36]Katz M L,Shapiro C.Network externalities,competition,and compatibility[J].The American Economic Review,1985,75(3):424-440
[37]Liebowitz S J,Margolis S E.Network externality:An uncommon tragedy[J].Journal of Economic Perspectives,1994,8(2):133-150.
[38]Shankar V,Bayus B L.Network effects and competition:An empirical analysis of the home video game industry[J].Strategic Management Journal,2003,24(4):375-384.
[39]Keith D,Sterman J,Struben J.Understanding spatiotemporal patterns of hybrid-electric vehicle adoption in the United States[R].2012.
[40]李永立,陈杨,樊宁远,等.考虑个体效用因素的社会网络演化分析模型[J].管理科学学报,2018,21(3):41-53.Li Yongli,Chen Yang,Fan Ningyuan,et al.Utility-based model for interpreting evolution patterns of social networks[J].Journal of Management Sciences in China,2018,21(03):41-53(in Chinese)
[41]Malerba F,Nelson R,Orsenigo L,et al.Demand,innovation,and the dynamics of market structure:The role of experimental users and diverse preferences[J].Journal of Evolutionary Economics,2007,17(4):371-399.
(2)早期研究中,“网络外部性”和“网络效应”经常被认为是相同的.但是Liebowitz和Margolis[37]指出两个概念之间存在着一定的差别,认为当网络中的其他参与者的影响能够被内部化时,应该被称作网络效应,反之则应称为网络外部性.本文研究中认为消费者的购车决策受到的其它参与者的影响会内化为效用影响,因此后文均采用“网络效应”这一名词.
(3)汽车的性能指标很多,考虑到传统车和电动汽车之前的性能差异主要体现在续航里程上,故本文选择续航里程作为性能指标.下文所涉及到的性能均指续航里程.
(4)混合logit模型是在条件logit模型中加入只随个体而变的解释变量,因此本文只详细介绍更加复杂的混合logit模型,省略条件logit模型的介绍.
(5)限于篇幅,简略了具体计量方法及过程的详细说明,如有需要,可以向作者索取.
(6)汽车的型号多种多样,价格差别也非常明显,但对于同一档次的车型而言,电动汽车价格要高于传统汽车.
(7)Melerba[41]较早从性能和价格门槛角度探讨了试验性用户对产业演化的影响,本文据此设置了消费者对于购买车辆的性能和价格门槛.C-min Cjc/n,0
(8)Ranjc/n,0=Ranc/n+0×r/rmax Cjc/n,0-min Cc/n,Ranc/nc/n表示基础性能,jc/n,0表示初始成本对初始性能的影响.
(9)不考虑厂商生产的固定成本及其他费用支出,利润πj,t=(Pj,t-Cj,t)×Qj,t.其中Qj,t表示第t期企业j的销量.
(10)比较而言,传统汽车的生产工艺较为成熟,成本下降和性能提升空间较小,速度较慢;电动汽车的成本下降和性能提升空间均较大,且速度较快.
(11)在本文中,第十期时消费者才全部进行完购车决策,因此第十一期设置退出机制,淘汰掉前十期一直没有销量的企业.之后,当连续三期没有销量时,企业自动退出,且退出后不再进入.
(12)EXCSi+n=(1+ECSi)×CSi,EXCSi+n表示第i期消费者对下次换车时周围充电站数量的心理预期,ECSi是心理预期调整系数,ECSi+1=ECSi±ΔECS,CSi表示第i期消费者周围的充电站数量.
(13)公式(8)为条件logit模型,可以通过MLE估计得到系数估计值β.
(14)在汽车产业演化过程中,传统汽车厂商作为在位企业居于市场主导地位,电动汽车厂商作为潜在进入者,与传统汽车厂商展开竞争.为了体现传统汽车厂商的先发优势,一种方法是让其提前进入市场,另一种方法是通过参数设置上的差别予以体现.经过几十年的发展,传统汽车的性能已经较为完善,价格和用户数量趋于稳定,配套基础设施建设也相对完备,因此本文选择第二种方式,即通过性能和价格属性,以及直接与间接网络效应的设定,反映其相对于电动汽车的比较优势.
(15)电动汽车的性能和价格之所以在第10期左右显著变化,很大程度上是由于第10期没有竞争力的厂商退出市场,而这部分厂商通常在价格和性能方面都处于落后水平.
(16)与生产性补贴和消费性补贴的方式不同,充电基础设施建设的效果具有时间延续性.为了避免与前5期实施的政府补贴存在交互影响,本文选择在政府补贴停止的第6期投入充电设施建设,并且只在第6期实施一期.
(17)充电站的建设来源于两方面,一是来源于电动汽车用户数增多带来的市场自发建设,二是来自于政府部门主导的建设,前者已经在模拟过程中予以考虑.
(18)这二者都会使全局建设政策下购买电动汽车的人数增加,但前者会使第20期左右电动汽车消费者的分布更集中,后者则会使第20期左右电动汽车消费者的分布相对分散