皖江城市带城市经济联系与中心城市辐射范围分析

分析经济区内城市间经济联系不仅有利于引导城市的空间发展,而且有利于空间经济的合理组织。以皖江城市带为例,引入克鲁格曼指数、建成区面积、人口素质权重系数等指标修正了以往的引力模型,并利用城市间的日发车班次数据对修正模型进行了检验。在此基础上,利用修正模型确定了各城市的主要对外联系方向及联系强度,采用断裂点公式计算了中心城市的吸引范围。结果表明:①皖江城市带内各城市对外经济联系强度差异较大;②各城市的主要联系方向呈现中心城市指向性和地域相邻指向性特征;③合肥和芜湖为皖江城市带的两个经济中心城市,它们的对外吸引范围较为狭小。     

家庭直接能耗的碳排放影响因素研究进展

家庭能源消费对环境的影响已经成为可持续发展领域热点研究课题之一。为了更好地开展家庭直接能耗的碳排放研究,对国际上近20年的研究进行总结分析,将国际上对家庭直接能耗碳排放影响因素的研究模型归纳为自上而下模型、自下而上模型及综合模型三大类,并对各种模型进行了评价;国际上对家庭直接能耗碳排放影响因素的研究集中于家庭外部环境、家庭特征及家庭成员3个方面。分析表明:家庭直接能耗碳排放影响因素的研究模型由简单走向综合;所用数据由历史统计数据到与微观住户调研数据相结合;研究的层面由国家(地区)、城市、社区向家庭内部全面展开;分析的视角由单一的宏观分析,到宏观与微观分析相结合。在基本反映家庭直接能耗碳排放影响因素研究的最新态势的同时,提出了我国家庭直接能耗碳排放影响因素研究中值得注意的几个问题。     

1990年以来江苏省区域经济差异时空格局演化及其成因分析

以1990—2007年江苏省县域人均GDP为研究指标,运用不平衡指数和空间统计模型对江苏省区域经济发展水平进行定量研究,并结合GIS的空间分析功能,系统分析了江苏省区域经济发展时空差异及空间格局演化。结果表明:江苏省区域经济发展在空间上具有较强的自相关性,在整体格局上呈现出一定的集聚态势,空间格局更多表现为苏南部分地区的高度集聚和苏北部分地区的集聚态势,成为江苏省区域经济发展的集聚核心区和低度集聚区,而苏中地区的集聚态势显得并不强烈。同时,针对区域经济自相关性发展趋势进行解释并指出以县域经济为单元的区域经济发展空间差异将长期存在。最后,构建空间数据模型对此种格局形成的原因进行空间统计学上的探讨,指出规模企业空间分布差异及人才空间分布差异是导致县域经济发展差异的主要因素,为区域经济差异分析提供了一种交互式的、可视化的新手段,进而为政府部门制定区域经济协调发展政策提供决策依据。     

基于PSR模型的广东省城市土地集约利用空间差异分析

将＂压力—状态—响应＂框架引入到城市土地集约利用评价指标体系中,采用主成分分析方法对评价指标进行赋权,对广东省21个地级市的城市土地集约利用水平进行了评价。结果表明,广东省城市土地利用集约度差异形成的主要影响因素是地理区位条件和经济发展水平,资源赋存状况也是重要的制约条件。城市土地集约利用是一个复杂的系统工程,不仅要注重提高土地利用的产出效益,还要重视系统压力状态的调节和系统反馈能力建设。研究也表明,PSR评价指标体系及主成分分析方法能较好地适应城市土地集约利用评价的需要。     

“双核”结构区旅游发展模式研究——以潮汕地区为例

"双核"结构是区域经济发展中出现的一种空间结构形态。文章在分析潮汕地区潮州—汕头"双核"空间结构现状的基础上,提出了构建潮州—汕头"双核"结构区的旅游空间发展模式和具体旅游开发模式。认为在海西经济区旅游大发展的背景下,潮汕地区必须构建合理的发展模式,即:以汕头为区域旅游发展的主核心点,以潮州为次核心点,双核形成旅游发展核心区;以揭阳、汕尾为连接节点,以梅州为拓展节点,通过聚合—扩散效应,形成粤东旅游发展的双核联动模式;并以厦深铁路为发展轴,对接两边的珠三角旅游区和厦漳泉闽三角旅游区,尽快实现有效合作,才能避免成为旅游过境地。这一研究对于类似结构地区的旅游业发展也具有一定的借鉴作用。     

基于引力模型与0-1规划模型的省域经济区划——以江苏省为例

借助2008年统计数据,采用主成分法得到江苏各地级城市综合质量指数值;根据运输的时间成本与货币成本,计算江苏地级城市间经济距离;运用引力修正模型计算江苏地级城市间相互引力,并结合0-1规划模型划分经济区;依据经济区内县域间三次产业结构差异度与位置邻近性,划分经济亚区。研究表明：①江苏省可分为宁镇扬泰、苏锡常通、徐连宿、淮盐等4大经济区和15个经济亚区。②各城市连接的地区个数遵循Zipf定律,作为一、二级节点的南京和苏州统领全省经济空间网络,而南通、宿迁、盐城没有显著的联系对象。③江苏经济区空间分布逐渐由南北向格局转为南部呈东西向、北部呈南北向的格局。④各经济区内城市间的引力相差悬殊,南部较大,北部较小。省域尺度的经济区划,可为我国将来划分标准经济区奠定基础,也可为优化全省劳动地域分工格局提供依据。     

行政区划调整对住宅价格变化的影响效应分析——以南汇并入浦东新区为例

行政区划的调整往往是为了适应城市化和区域经济一体化的要求而进行的。除经济和生态环境因素外,住宅价格还受社会、文化和政治等因素的影响和作用,但行政因素对住宅价格变化影响的实证研究并不多见。以上海市南汇区并入浦东新区为例,运用Hedonic模型、多元线性回归分析、半弹性系数等方法,从时间和空间两个方面,定量测度行政区划调整对住宅市场价格变化的影响程度。结果表明:从时间变化上看,行政区划调整以后,浦东新区各板块的住宅均价呈现上涨趋势,住宅价格比调整之前上涨2.74个百分点,且前阶段的涨幅较之后要大;从空间变化上看,外郊环、郊环外涨幅潜力更大。总体而言,行政区划调整对区域住宅价格变化有一定的正面影响,但其影响程度有限且不及区位、交通和住宅特征等因素显著。因此,地方政府和房地产开发商应当理性对待行政区划调整策略,不能过于奢望通过短期的行政区划调整来提升房地产价值,而应当更多地关注开发区位的选址及区域交通和环境条件的改善,提升物业管理水平与服务质量,完善社区公共服务配套设施建设。     

Technology level evaluation methodology based on the technology growth curve

Technology has been the driving force of development for knowledge-based economies. As competition in technology innovation among nations becomes more intense, there is a growing need for improved judgment, evaluation and prediction of scientific technology capacity in order to enhance national competitiveness. Until now, a country's technology level has been evaluated on a relative basis by comparing it with that of the country with the world's best technology. However, this kind of static methodology makes the interpretation of results unclear and makes time series analysis difficult. One of the most important limitations of this methodology is that it cannot be used to establish a strategy to improve the technology level. This paper examines the methodological problems of technology level evaluation and develops a dynamic methodology by applying the technology growth curve model. We also analyze the real technology level by using a new model application and review the relevance of this method. Finally, we discuss how to use the results in order to create a dynamic technology strategy.     

Where have all the flowers gone? Forecasting green trends in the automobile industry with a choice-based conjoint adoption model

With rising gas prices, global warming, and green thinking, all-electric vehicles are currently considered the automobile technology of the future. However, besides their advantages electric drive trains also exhibit several disadvantages. Moreover, history shows several failed attempts to establish electric vehicles. Thus, a reliable forecasting model is needed that predicts if the current trend is sustainable. We develop and empirically test a choice-based conjoint adoption model that uses individual-level preferences as a basis for prediction. Predictions are mapped to the time of the next planned purchase in order to establish the adoption process. The model extends existing research in several ways. First, no prior information, e.g., historical market data or a functional form of the adoption process, has to be integrated. Second, the model allows dynamic modifications of product specifications or competition at different points in time. Third, a no-choice option can be integrated so that a technology switch is not forced by the model itself and switching costs can be considered. The empirical results reveal different critical factors for the adoption of all-electric vehicles, such as purchase price, range, timing of the market entry, or environmental evolution, which could lead to a solid base of consumers preferring this option.     

On the forecasting of the challenging world future scenarios

Logistic and power law methodologies for both retrospective and prospective analyses of extended time series describing evolutionary growth processes, in environments with finite resources, are confronted. While power laws may eventually apply only to the early stages of said growth process, the Allee logistic model seems applicable over the entire span of a long range process. On applying the Allee logistic model to both the world population and the world gross domestic product time series, from 1 to 2008 AD, a projection was obtained that along the next few decades the world should experience a new economic boom phase with the world GDP peaking around the year 2020 and proceeding from then on towards a saturation value of about 142 trillion international dollars, while the world population should reach 8.9 billion people by 2050. These results were then used to forecast the behavior of the supply and consumption of energy and food, two of the main commodities that drive the world system. Our findings suggest that unless the currently prevailing focus on economic growth is changed into that of sustainable prosperity, human society may run into a period of serious economical and social struggles with unpredictable political consequences.