Unobserved tourism

Having more reliable statistics is essential for policy-makers to be able to make effective decisions. Nevertheless, measuring the number of tourists in a given destination is not an easy task. After reviewing the main problems affecting official statistics on tourism, this paper proposes a general framework by formalizing a theoretical model in which tourism nights and trips in a given destination are broken down into observed and unobserved components, according to the European system of tourism statistics. The main approaches related to the measurement of unobserved tourism are discussed, and some empirical findings in Sicily (Italy) are presented in order to highlight the actual magnitude of unobserved tourism.     

A GIS-based spatial statistical approach to modeling job accessibility by transportation mode: case study of Columbus,Ohio

Improving job accessibility based on transport connectivity helps to address equity issues. Spatial autocorrelation (SA) is also a focus of interest in transportation planning, but has been neglected in analyzing job accessibility in metropolitan areas. In this study, GIS-based job accessibilities by walking, transit, and car are computed for the metropolitan area of Columbus, Ohio, and three transport-based spatial autoregressive (SAR) models are estimated to account for the SA of job accessibility among neighboring block groups, while controlling for built-environment and socioeconomic factors. SA intensities and extents are compared in order to better understand local spatial clusters of job accessibility across the region. Direct and indirect spillover effects due to an investment change in transportation facilities are estimated and provide important transportation planning information. The results also show that walking-accessed jobs are primarily related to physical settings (e.g., land uses) at the local level. Locations with a higher share of zero-vehicle housing units have better job accessibility by transit. There is a spatial mismatch between Asian population clusters and transit-accessed jobs, possibly because of the car-oriented residential clusters around Honda of America Manufacturing in suburban areas. More importantly, locations with a higher share of single-parent households are at a disadvantage in overall job accessibility. Due to its complex transportation needs, a society friendly to single parents should spatially integrate accessible jobs with other needed activities via land-use and transportation planning. Alternatively, car-ownership programs and non-spatial social supports also might be effective to help secure job opportunities and perform daily life activities.     

第二届世界聋篮锦标赛中国队与前四名队技术统计比较分析

运用文献资料法、观察法、数理统计法及对比分析等方法,对第二届世界聋人篮球锦标赛中国队与前四名队的比赛数据及现场情况进行了对比分析。结果表明:现阶段我国男、女聋篮在比赛中存在的问题相对一致,在攻防两端的表现均明显弱于世界强队;命中率低,失误率高,身体条件及个人能力不足则是导致中国队失利的主要原因。此外,针对发现的问题,并结合现阶段我国聋人篮球发展现状,提出了相应对策。     

南水北调工程统计体系的建立与运行

南水北调工程统计体系在我国南水北调工程中发挥着重要作用,本文就简要的分析了南水北调工程统计体系的建立与运行情况,供广大同行参考。     

基于GIS空间统计的县级商业布局模式及形成机理研究——以吉林省乾安县城为例

在城市化快速发展背景下,城市商业布局模式创新成为城市空间变化的主要方面之一,并且在城市空间对外扩张和各种新要素的多重影响下,出现新的发展特征,形成基于传统但又有别于以往的商业布局模式。选择小尺度空间为研究对象,以区域购物流模型和GIS热点分析工具为定量研究手段,研究县城商业布局模式。研究认为,县城商业布局存在2种基本模式:以区域购物流强度为表征的交通——职能布局模式,以及由商业网点购物流强度的G统计值得出的圈层布局模式。2种布局模式相互叠加,则圈层布局模式将产生多职能中心与交通轴向的空间变异,形成变异圈层布局模式。在这一模式中,县城的商业空间划分成5个圈层和两个职能中心,并在各个圈层中都体现出商业空间向交通轴线集聚的倾向。进一步研究发现,市场、交通区位、消费空间差异性、社会关联作用是影响小尺度区域商业空间布局的主要因素。     

我国政府统计数据质量现状分析

政府统计数据的质量与国家宏观决策和企业微观决策的质量紧密相关,不正确和不完善的数据可能会导致决策的错误和失败。所以,现代社会对数据质量的关注更多。鉴于此,从我国政府统计数据质量的新进展和存在的问题两个方面,分析评价了中国政府统计数据质量现状。     

浅谈当前企业统计工作存在的问题及对策

在市场经济的今天,企业统计工作越来越重要.可以说统计工作是企业管理中的一项基础工作.但现在我们的企业统计工作中仍然存在统计方法简单、统计手段不适应现代企业发展得要求等诸多问题,使得统计影响企业的正常发展.笔者试从建立一支业务素质高的统计队伍等方面入手,探讨如何做好现代企业的统计工作.     

城镇土地级别调整方法研究

研究目的:寻求一种新的城镇土地级别调整方法———因素类比法。研究方法:文献综述法、类比分析法、实证分析法。研究结果:对现有城镇土地级别调整方法进行了简要述评;给出了因素类比法的原理和步骤;运用样点地价与实例对该方法进行了验证。研究结论:运用因素类比法进行城镇土地级别调整具有针对性强、工作量小、技术操作简单、不需要专门的地理分析软件等优点,特别适用于调整区域不多的城镇基准地价更新。     

企业统计与现代企业管理

企业统计与现代企业管理是密不可分的。文章对企业统计如何适应现代企业管理的需求,现代企业管理如何为企业统计提供用武之地和发展平台进行了阐述。     

Automated trading systems statistical and machine learning methods and hardware implementation: a survey

Automated trading, which is also known as algorithmic trading, is a method of using a predesigned computer program to submit a large number of trading orders to an exchange. It is substantially a real-time decision-making system which is under the scope of Enterprise Information System (EIS). With the rapid development of telecommunication and computer technology, the mechanisms underlying automated trading systems have become increasingly diversified. Considerable effort has been exerted by both academia and trading firms towards mining potential factors that may generate significantly higher profits. In this paper, we review studies on trading systems built using various methods and empirically evaluate the methods by grouping them into three types: technical analyses, textual analyses and high-frequency trading. Then, we evaluate the advantages and disadvantages of each method and assess their future prospects.