The role of public space in constructing experience capital: A longitudinal analysis in the hotel context

Public space plays a primary role in shaping customers' hospitality experiences. Yet how public space conditions customers' experiential outcomes in accumulating capital for hospitality organizations remains underexplored. Inspired by the theory of psychological ownership, this research presents an in-depth analysis of the impacts of customers' public space experiences on their experiential outcomes using a longitudinal hotel industry dataset merging information from customer surveys, property performance, and surrounding accessibility insights. Findings revealed the positive effects of customers’ public space experiences on their overall service experiences, the perceived value of the experience, revisit intentions, and recommendation intentions. Moreover, hotel class, other customers, and surrounding accessibility were empirically verified as moderators conditioning the positive impact of public space. These findings offer valuable implications for theory and practice that are worthy of further exploration.     

空间目标的联合矩阵束极点估计

极点作为谐振区雷达目标的最主要电磁特性，具有很大的空间目标识别前景。但是在使用频域观测数据提取目标极点时，存在虚假极点和估计精度问题。针对上述问题，首先通过加窗和截断改进了后时响应信号的获取流程，抑制了虚假极点影响；然后采用最小描述长度法（MDL）估计极点个数，避免了定阶错误引起的虚假极点；最后采用联合矩阵束法估计极点，有效减少了单角度数据估计极点时存在的遗漏极点和虚假极点问题。FEKO软件验证表明，所提算法具有更高的精度和抗噪能力。     

Factor state–space models for high-dimensional realized covariance matrices of asset returns

We propose a dynamic factor state–space model for high-dimensional covariance matrices of asset returns. It makes use of observed risk factors and assumes that the latent integrated joint covariance matrix of the assets and the factors is observed through their realized covariance matrix with a Wishart measurement density. For the latent integrated covariance matrix of the assets we impose a strict factor structure allowing for dynamic variation in the covariance matrices of the factors and the residual components as well as in the factor loadings. This factor structure translates into a factorization of the Wishart measurement density which facilitates statistical inference based on simple Bayesian MCMC procedures making the approach scalable w.r.t. the number of assets. An empirical application to realized covariance matrices for 60 NYSE traded stocks using the Fama–French factors and sector-specific factors represented by Exchange Traded Funds (ETFs) shows that the model performs very well in- and out of sample.     

Bayesian selection of technology assumptions for the transformation from supply-use to input–output tables

ABSTRACT

In the construction of input–output models from supply-use tables, technology assumptions disambiguate how an industry uses inputs in the production recipe of multiple outputs. This paper uses Bayes' theorem to select technology assumptions, taking into account empirical observations. The paper presents a formulation to explore hybrids between product and industry technology assumptions in product-by-product tables. We then present Markov chain Monte-Carlo techniques to implement the Bayesian method for selecting technology assumptions. We apply the method in a case study using Eurostat supply-use tables of 2004 and 2005, exhibiting a volume of secondary products of less than 13%, and 59 products and industries per country. The results show that the choice of technology is not important, given that there is no strong evidence in favour of any of them.     

基于底线预警的国土空间生态修复规划实施监督体系研究

国土空间生态修复是推进生态文明建设的重大举措，构建基于底线预警的国土空间生态修复规划实施监督体系是完善国土空间规划“一张图”信息系统的重要组成部分和政策支撑。通过对生态修复规划实施监督体系建设的研究，把握底线控制与监测预警机制，对接国土空间生态修复业务管理各项需求，搭建“五梯度四体系”的生态修复规划动态监测实施监督信息系统，构建以“七个一”为主要内容的生态修复规划底线预警监测评估机制，并与各层级国土空间规划“一张图”实施监督信息系统进行衔接，实现对生态修复规划实施的动态监测和预警。     

从土地资源优势区配置到主体功能区管理：一个国土空间治理的逻辑框架

研究目的:以土地资源配置方式遵从优势区开发原则到服从主体功能区分工协作规则演进规律,解释现行中国治理模式下国土空间管理逻辑。研究方法:文献分析法和理论分析法。研究结果:传统优势区开发理念为早期区域发展带来了集聚与规模经济效益,但其内部仍存在生产、生活、生态空间结构失衡等问题,降低了土地资源空间配置效率。主体功能区战略是传统优势区土地资源空间配置理念转型,是中国特定时期具有国家特色的经济发展模式,关键在于明确地方土地资源空间配置核心定位,应以法律规范"央地"土地关系、差别化实施政策制度安排、引导公众参与规划决策、创新生态(经济)补偿机制。研究结论:不同分区土地资源空间配置关系协调是世界性问题,转型时期中国国土空间优化和规制治理重点在于厘清中央与地方事权关系,精准落地县域主体功能区建设,健全主体功能配套政策体系。     

价值共创行为分析框架构建 ——基于赋能理论视角

通过文献调查并结合案例的描述性分析,提出数字技术时代价值网络中不同行为主体之间的赋能内涵、关键维度以及基于赋能跨层次效应的价值共创行为分析框架。将"赋能氛围""主体赋能"分别作为价值网络中赋能的宏观维度和微观维度进行概念化。界定了两个维度的关键组成要素,分别包括信息共享、开放性结构、协同规则以及主体关系、资源整合和影响。构建了赋能的跨层次效应模型,分析了赋能的宏观-微观跨层次效应及其对价值网络生态和主体价值创造的影响。     

基于遥测信号的测距技术及其发展趋势

基于遥测信号的测距技术可以有效解决深空测距下行链路同时传输遥测、测距信号时出现的遥测数据传输速率受限、频谱带宽增加等问题，应用前景广阔。介绍了基于遥测信号的测距技术发展历程，重点总结了其中的关键技术，包括上行测距码的选择、遥测帧的设计和传输、PN码相位估计算法，最后探讨了其发展趋势。基于遥测信号的测距技术适应未来深空测距的发展需求，是深空测距的重要发展方向之一。     

山西省乡村休闲旅游地空间分布特征及影响因素研究

［目的］通过对山西省乡村休闲旅游地的空间分布特征及影响因素进行研究，旨在为山西省的乡村旅游发展提供合理的参考建议。［方法］选取山西省213处国家级和省级乡村旅游示范点为研究对象，运用最临近点指数对其空间分布类型进行判别，并运用地理集中指数和地理联系率对其分布均衡程度和地理联系程度进行考量，通过核密度图进一步分析其空间分布指向，在此基础上对影响因素进行分析。［结果］山西省乡村休闲旅游地空间分布呈集聚分布的特点，且与经济规模和人口密度在空间上的均衡、配合程度较高。［结论］（1）山西省乡村休闲旅游地包括以太原和晋中为主的中部密集区和以临汾、运城、晋城为主的南部密集区，且都以各地级市为中心向周边扩展，大多数示范点分布于城郊地区； （2）经济发展、人口密度、资源禀赋、区位因素和社会因素是影响山西省乡村休闲旅游地分布的主要因素，其中农业科技类、农事体验类和特色村镇类多分布于经济和人口密度较高的地区。     

Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization*

Improving fuel economy and lowering emissions are key societal goals. Standard driving cycles, pre-designed by the US Environmental Protection Agency (EPA), have long been used to estimate vehicle fuel economy in laboratory-controlled conditions. They have also been used to test and tune different energy management strategies for hybrid electric vehicles (HEVs). This paper aims to estimate fuel consumption for a conventional vehicle and a HEV using personalized driving cycles extracted from real-world data to study the effects of different driving styles and vehicle types on fuel consumption when compared to the estimates based on standard driving cycles. To do this, we extracted driving cycles for conventional vehicles and HEVs from a large-scale U.S. survey that contains real-world GPS-based driving records. Next, the driving cycles were assigned to one of three categories: volatile, normal, or calm. Then, the driving cycles were used along with a driver-vehicle simulation that captures driver decisions (vehicle speed during a trip), powertrain, and vehicle dynamics to estimate fuel consumption for conventional vehicles and HEVs with power-split powertrain. To further optimize fuel consumption for HEVs, the Equivalent Consumption Minimization Strategy (ECMS) is applied. The results show that depending on the driving style and the driving scenario, conventional vehicle fuel consumption can vary widely compared with standard EPA driving cycles. Specifically, conventional vehicle fuel consumption was 13% lower in calm urban driving, but almost 34% higher for volatile highway driving compared with standard EPA driving cycles. Interestingly, when a driving cycle is predicted based on the application of case-based reasoning and used to tune the power distribution in a hybrid electric vehicle, its fuel consumption can be reduced by up to 12% in urban driving. Implications and limitations of the findings are discussed.