Governing Suburbia through regionalized land-use planning? Experiences from the Greater Frankfurt region

This paper explores the case of peripheral settlement growth in the Greater Frankfurt (Main) region within current debates on global suburbanization. Within Germany’s sophisticated spatial planning regime, Greater Frankfurt’s system of regionalized land-use planning marks an ambitious initiative to contain urban sprawl. Nonetheless, expansive peripheral settlement growth, and socio-spatial polarization remain distinct characteristics of the booming region. Analyzing state regulation vis-à-vis dynamics of capitalist urbanization and private authoritarianism, we decipher the complex governance arrangements producing this, at first sight, contradictory simultaneity. We uncover the rationales of local growth politics of autonomous municipalities and the region’s multiplied institutional fragmentation that undermine planning ambitions to contain suburban growth. We conclude by critically assessing the political economies of suburbanization in Greater Frankfurt and point to prospects for regional reform.     

金融资源配置、技术进步与经济高质量发展

随着我国发展阶段及内外部条件的变化,科技创新已成为新时代引领我国经济高质量发展的核心驱动力。本文以金融驱动技术进步的视角,构建内生增长DSGE模型,分析金融资源配置、技术进步和经济增长之间的关系。研究佐证了我国技术创新的逆周期性,并发现金融资源在企业生产性投资与创新投资之间的分配,可以通过改变生产要素投入规模和技术进步率两种途径影响经济增长,且这两种影响之间存在“跷跷板”关系,但后者更具主导性。在此基础上,诠释了金融、技术与经济的动态传导机制:经济扩张期,企业生产规模扩张,金融资源对生产性投资的支持增加,对创新的投入相对减少,技术进步率放缓;经济收缩期,企业缩减生产规模,金融资源对生产性投资的支持减少,对创新的投入相对增加,技术进步率提升。本研究的政策启示为,面对当前发展新矛盾、新挑战,应把握发展新格局、新机遇,进一步深化金融改革,优化金融资源配置机制,鼓励创新投资,充分发挥股权市场对企业研发创新的支持作用,并辅以稳健适度的宏观调控政策,为企业创新提供良性的宏观环境,激活企业创新需求,促进技术进步,推动经济高质量发展。     

Feeling hungry? let's order through mobile! examining the fast food mobile commerce in China

This study proposes a unique framework that aids to enrich online shopping experience (psychological and monetary gains) and accelerates fast food mobile commerce (m-commerce). The extended technology acceptance model (TAM) is applied while the stimulus–organism–response (S–O–R) paradigm served as the predominant framework combined with the acquisition-transaction utility theory. This study investigates the mobile website quality, website brand equity (stimulus) influence on (PEOU) and (PU) (organism) to predict Chinese consumer intention to use fast food mobile commerce (response). A total of 936 respondents were participated while data were collected using a convenience sampling technique in China. Results reveal that all dimensions of mobile WQ (i.e., service quality, system quality, and information quality) and Website BE (i.e., brand image, perceived quality, brand association, and brand loyalty) (stimulus) significantly substantially influence PEOU and PU (organism) toward the acceptance of online fast food shopping (response). Digital Coupon Proneness (an accelerator) substantially moderates the relationship between PEOU, PU, and intention to use fast food m-commerce. Based on the assumptions of acquisition-transaction utility theory, category-specific (fast food) digital coupon proneness increase m-commerce for online fast food buying– a novel contribution of the study. Furthermore, research provides unique managerial insights for the industry to utilize the maximum potential of m-commerce in the fast-food industry.     

城市创新行为改善生态效率了吗？——基于空间关联与溢出视角的考察

文章在理论层面探讨了创新对生态效率的影响机制，并基于城市空间关联与溢出视角，采用我国2007-2016年260个城市面板数据，运用空间计量模型检验了创新对生态效率的影响效应及多维度的城市异质性。进一步地，文章还通过对不同距离阈值上的创新空间溢出效应进行估计，测算了创新空间溢出的距离边界，检验了创新空间溢出驱动城市绿色发展的最佳地理距离区间，从而为增强区域创新合作以提升区域整体绿色发展水平提供了可供参考的量化依据。研究发现：总体而言，创新具有的增长效应、资源与环境效应、结构优化效应是促进城市生态效率改善的重要途径，且产出端创新对生态效率的驱动效应强于投入端创新；但创新对生态效率的影响具有显著的城市异质性，依赖于城市区位、所在城市群、环境政策、资源禀赋、创新能力和市场化水平；城市创新行为具有显著的空间溢出效应，但空间溢出随距离变化呈衰退趋势，350公里以内为创新活动的密集溢出区；生态效率也具有明显的空间溢出效应，经济越发达且联系越紧密、要素流动越自由、创新对生态效率驱动效应越强的地区，生态效率的空间溢出也越强。因此政府应完善创新激励政策、为创新外溢创造良好条件、注重引导创新的方向，并根据区域及城市发展实际，采取差异化的创新驱动绿色发展策略。     

创业企业何以提高创新绩效——基于创业学习与商业模式创新协同联动视角的QCA方法

以150个创业企业为样本，基于创业学习和商业模式创新理论，运用模糊集定性比较分析方法（fsQCA），探究经验学习、认知学习、新颖型商业模式创新和效率型商业模式创新对创新绩效的影响路径及机制。研究发现，存在新颖型商业模式创新等4条创新绩效产出关键路径；相较于效率型商业模式创新，新颖型商业模式创新在关键路径中更容易提高创新绩效；利用QCA方法证实了影响创业企业创新绩效的组态内部各要素之间的替代性。结论丰富了创新绩效产出内部机制，可为创业企业提高创新绩效提供指导和借鉴。     

基于CE模型的河南省耕地生态补偿额度研究

[目的]基于生态补偿利益主体的需求和支付意愿,充分考虑区域经济发展状态,测算具有弹性的生态补偿标准,确保生态补偿机制顺利运行。[方法]以河南省457份实地调查问卷为基础,采用选择实验法,建立由4个属性水平、7个选择集组成的生态价值属性集,测算受访对象生态补偿的支付意愿。[结果]城乡居民对于耕地资源景观与生态环境关注度最高,其次是耕地质量和耕地面积;农民和市民对于耕地生态价值属性满足的支付意愿存在显著差异性,农民支付意愿为2 060.55元/hm~2,市民支付意愿为3 396.15元/hm~2,两者相差近1 335.60元/hm~2,收入水平、环保意识是影响受访对象生态补偿支付意愿的最直接因素,但两者均认为耕地面积不变、耕地质量改善和耕地景观生态环境改善为最优选择。[结论]补偿额度应充分考虑相关利益主体的支付能力和意愿,将农民的支付意愿作为生态补偿下限,市民的支付意愿作为生态补偿上限,可建立具有一定弹性的生态补偿机制。     

Do housing prices promote total factor productivity? Evidence from spatial panel data models in explaining the mediating role of population density

The issue of what to promote in total factor productivity (TFP) in urban areas has been widely discussed in academia and housing prices and population density are confirmed to be two of the most essential driving factors. However, research into the interaction of housing prices and population density with TFP has been neglected, with no previous studies taking spatial factors into consideration, which may bias the results. From this perspective, using spatial panel data models and employing instrumental variables to solve the endogenous problem, this study examines the impact of housing prices on TFP through the mediating effect of population density for 283 Chinese cities during the period 2000–2013, and confirms that the mediating effect accounts for 18.70 % of the total effect. The results show the positive and significant association of housing prices with TFP and the inverted U-shape of population density. The underlying logic is that housing prices change population density by attracting people with high purchasing power and discouraging those unable to afford housing, whereas increased density helps to promote productivity since the settled inhabitants always have highly developed work skills and are well educated. The influencing mechanism of housing prices on TFP through population density is analyzed, namely the spillover effect. We find that the spillover effect exists in the eastern and central regions, as well as first, second, and third tier cities, while for western regions and fifth tier cities, population mobility and increased in housing prices slows their economic development. There is no evidence of any spillover effect in fourth tier cities. A discussion and suggested policy implications are also provided.     

Does the spatial representation affect criteria weights in environmental decision-making? Insights from a behavioral experiment

The need and interest to consider cognitive and motivational biases has been recognized in different disciplines (e.g. economics, decision theory, risk analysis) and has recently reached environmental decision-making. Within this domain, the intrinsic presence of a spatial dimension of both alternatives and criteria calls for the use of maps throughout the decision-making process to properly represent the spatial distribution of the features under analysis. This makes spatial Multi Criteria Decision Analysis (MCDA) a particularly interesting domain to explore new dimensions of cognitive biases. This study proposes a behavioral experiment aimed at discovering to what extent the spatial visualization (i.e. maps) of criteria versus the non-spatial one (i.e. tables) can bias the weight elicitation phase of a spatial MCDA process. The experiment simulates a very common analysis in environmental and land use planning: land suitability analysis. Our findings show that there are significant consequences on how important we perceive a certain criterion to be, depending on whether it is represented as a map or as a table among a mix of maps and tables. Indeed, the map representation of the same criterion leads to higher weights attributed to that criterion compared to the table representation. Visualizing the same information as a map or as a table, although technically equivalent, is thus not psychologically equivalent for Decision Makers. The results of this experiment are expected to have implications for spatial decision-making processes, by generating better awareness on the impacts of map-mediated land suitability analysis.     

An information-theoretic approach for forecasting interval-valued SP500 daily returns

We develop an iterative and efficient information-theoretic estimator for forecasting interval-valued data, and use our estimator to forecast the SP500 returns up to five days ahead using moving windows. Our forecasts are based on 13 years of data. We show that our estimator is superior to its competitors under all of the common criteria that are used to evaluate forecasts of interval data. Our approach differs from other methods that are used to forecast interval data in two major ways. First, rather than applying the more traditional methods that use only certain moments of the intervals in the estimation process, our estimator uses the complete sample information. Second, our method simultaneously selects the model (or models) and infers the model’s parameters. It is an iterative approach that imposes minimal structure and statistical assumptions.     

Forecasting using heterogeneous panels with cross-sectional dependence

In this paper, we focus on forecasting methods that use heterogeneous panels in the presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimating the factor structure: a residuals-based approach, and an approach that uses a panel of auxiliary variables to extract the factors. Small sample properties of the proposed methods are investigated through Monte Carlo simulations and applied to predict house price inflation in OECD countries.