Does data matter? Statewide longitudinal data systems and student performance in the U.S.

Although many industries have benefited from advances in data-driven technology, education is making small steps in capitalizing on the huge potential of data systems. Since 2005, the U.S. Federal Government has been making large grants to help states build statewide longitudinal data systems (SLDS) with the goal of improving programme and teacher evaluation and engage in data-driven decision-making. We analyse whether the introduction of SLDSs improved student performance, measured using test scores for math and reading tests for 4th and 8th graders, as well as high school graduation rates. We find no effects of SLDSs on student performance up to 10 years from implementation. However, we find suggestive evidence that these systems may have long-run effects, emphasizing the long-run nature of educational data collection and policy analysis.     

POI数据辅助下的泸州市城市地块用地类型现状快速判断与验证

［目的］土地利用规划和城市规划的用地地块，在实际使用过程中，都会不同程度与规划用途产生差异，如何把握规划的实施程度是土地管理中的一个重要问题。［方法］在大数据时代的背景下，通过对网络大数据可以真实地反映城市地块的真实使用状况。研究采用OSM（Open Street Map），对研究区进行城市地块的划分，形成街区尺度的城市地块。采用POI（Point of Interest）数据，建立了POI分类与城市用地分类的映射关系，计算了不同类型的POI数据的频数密度和类型比例，形成基于POI的城市地块用地类型识别方法，对研究区的城市地块进行土地利用现状识别。识别结果与第二次土地调查分类结果进行对比，验证方法的可行性。［结果］从泸州市的实证结果看，基于POI数据的城市地块识别结果与基于地籍数据的城市地块识别结果存在很大的差别。地籍数据主要是表针城市地块中不同实体的土地利用状况，两种数据采集的标准和表达的意义都不同，因此造成结果存在较大的差异性。［结论］研究认为，POI点有准确的空间位置信息和丰富的属性信息，主要是表征城市地块中不同实体的真实使用状况，可以较准确地判定快速发展的城市进程中的城市用地类型，能较为真实反映城市地块的现实使用状况，但也要注意POI数据在实际应用中存在的缺陷和不足。     

综合性国家科学中心建设公共政策绩效实证分析——以安徽合肥为例

基于科技政策评价指标体系构建和熵权法分析方法，以2013年以来安徽合肥创建和实施推进综合性国家科学中心的政策绩效为研究对象，实证测算2013—2017年科技政策的评价绩效得分。从创新载体建设、人才计划、科技项目、财税金融、科技成果产出、技术转移与产业化等方面对政策实施效果及其薄弱环节进行分析，并就综合性国家科学中心建设的科技政策的优化与完善提出政策建议。     

Tracing VARDI coefficients: a proposal

ABSTRACT

We propose a new approach for tracing the so-called ‘value-added-(re)distribution-important coefficients’ (in short the VARDI coefficients) in a world input–output model. From the perspective of a selected group of economies, VARDI coefficients may be defined as those elements in world input–output matrix in the case of which a small change in their levels leads to the maximization of a share of this group of economies in value added in global value chains. Due to the rapid development of the World Input Output Database, this approach may be easily applied in empirical research to different groups of countries and sectors in world IO models. In an illustrative empirical case study, we use the new approach in order to answer a question regarding what the main directions of the future macroeconomic policy of the U.S. could be in order to ensure the maximization of the country’s share in global value added.     

Network analysis of the Caucasus’ image

Destination image is influenced by many factors, including destination promotion materials, the mass media as a general familiarity agent, the perceivers’ own characteristics and even researchers’ methodological choices. To isolate and minimize the impact of research on destination image, different qualitative and quantitative designs and analysis techniques have been utilized. However, no previous study utilized the network analysis technique, which may be useful to reveal a picture of destination image with the interconnections and hidden dynamisms of dimensions as well as its correlates. The present study applies this technique on qualitative data from an online sample of Americans on their perceptions of a relatively remote and unfamiliar destination, the Caucasus region, in order to hone in on the dramatic impact of mass media on destination image. Results revealed networks of meanings with residue of mass media messages about Boston bombing, with some differences among different genders and education levels.     

Reviewing the DATAS of aviation research data: Diversity,availability, tractability,applicability, and sources

The field of aviation research is entering the era of big data. While data-driven advancements in aviation have clearly brought about applicable models and results with immediate implications, we argue that the influx of aviation data should be better characterized and documented to enable more efficient and standardized usage. To this end, we examine 200 well-cited research articles from sub-disciplines ranging from revenue management to air traffic control published on or after 2010 in order to analyze the diversity, availability, tractability, applicability, and sources (DATAS) of data utilized in aviation research. We find high levels of data diversity within aviation research, with 16 data categories ranging from air traffic flow management-type data to data from distributed sensors in line with the Internet-of-Things (IoT) paradigm. We identified a dominance of proprietary, non-public data in aviation research, with 68% of the 200 research articles utilizing solely proprietary data in deriving their results, and a further 8% utilizing a mixture of proprietary and publicly available data. The pervasiveness of proprietary data has implications on reproducibility and extending research results. We also highlight the increasing tractability of the data by surveying the computational power required to process the data sets, and present vignettes of applications and results that stem from these data-driven studies. Finally, we propose several recommendations regarding standardizing data source nomenclature as well as increasing the availability of and usage of publicly available data.     

Status of brands in children’s consumption: What letters to Santa posted on La Poste website tell us

The purpose of the research is to identify different consumption styles based on a large collection of letters to Santa written by some children and/or their families and submitted to the French Post website (La Poste). One of our main interests focuses on the presence and weight of brands and licenses in children’s wish lists. We have had access to all the anonymous posts sent to Santa Claus through La Poste’s website during the 2013 and 2014 Christmas holidays. We analyzed the nature of the wish lists as shown in the 43,000‐post database using several textual data analysis techniques. Extensive heterogeneity was found among children’s and families’ postures regarding that specific ritual. The different types of emails reflect the meaning families associate with Christmas time but also their different consumption styles or attitudes toward consumption: reasoned, educational, hedonistic, or materialistic, for example. When focusing on brands and licenses, we can also observe significant differences in the way families and children include them in their consumption decisions. Brands could have a very different weight in Christmas wish lists and their natures reflect different value transmission modes. The French market for Christmas children brands is rather stable and focuses on a few top leading global brands such as Playmobil, Barbie, or Lego. At least one of the ten leading brands is mentioned in half of evaluated Christmas wish lists. The analysis confirms that brands are very clearly gendered and associated with the children’s ages. Peak time for brand desire is alleged to be reached between the age of 7 and 9. To our knowledge, our research is the first to analyze a large sample of spontaneous data to capture children’s consumption styles and attitudes toward brands. Because of our classification, a first typology of parental consumption styles has also been identified.     

探究大数据时代高校智慧校园服务平台建设

在智慧校园中,各种计算机网络、云计算以及移动互联网等技术大大方便了校内师生的日常生活与学习工作。各类大数据共享和交换平台、统一身份认证管理等功能为学校管理提供助力。对于高校来说,需要认真思考大数据时代下高校智慧校园服务平台建设,对此论文展开了深入研究。     

What determines the efficiency of Australian mining companies?

We examine the firm‐specific determinants of technical efficiency in Australian mining companies using data envelopment analysis (DEA). To do so, we employ panel data sourced from individual mining companies listed on the Australian Securities Exchange (ASX) over the period 2010–2014. To ensure valid statistical inference in the presence of serial correlation between DEA efficiency scores, we apply Simar and Wilson's two‐stage bootstrap method. We find that ownership concentration, firm size, firm age, product portfolio, product diversification and growth status significantly contribute to efficiency gains. However, other firm‐specific factors, such as capacity utilisation, financial risk and overseas operations appear to have limited impact on the technical efficiency of mining firms.