国际食物消费可持续性研究进展

[目的]通过国际食物消费可持续性研究领域动态分析,为食物和可持续发展领域研究方向与趋势提供知识基础与借鉴。[方法]文章基于文献计量研究方法,通过趋势分析、合作网络、共被引和关键词共现等分析,对1986—2019年国际食物消费可持续性相关研究进行了总结。[结果]（1）近30多年来食物消费可持续性研究不断发展,尤其是近10年来,呈现快速发展趋势;研究主要集中在环境、食物、营养、农业和生态领域。（2）食物消费可持续性研究最多产的作者和机构位于美国和欧洲国家,中国是亚洲的一个重要节点,但研究总体仍有待进一步加强;联合国粮农组织（Food and Agriculture Organization of the United Nations,FAO）为食物消费领域与其他众多领域的研究构建了重要的桥梁;发表在Science和Nature期刊的相关研究成果是食物消费可持续性研究领域的重要基础。（3）食物消费可持续性研究的主题主要包括食物与农业系统可持续性、食物安全与营养健康质量和食物消费资源环境效应及可持续性评估三个方面。[结论]发展中国家和欠发达地区食物消费可持续性研究有待加强,同时食物消费可持续性...     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

Variable long-term trends in mineral prices: The ongoing tug-of-war between exploration,depletion, and technological change

This paper explores the use of low-frequency band-pass filters for describing long-run trends in real mineral commodity prices. This approach has the advantage of allowing long-run trend rates to evolve gradually over time, rather than assuming that they are constant (perhaps with occasional structural breaks) over time. This is a flexible way of capturing the ongoing ‘tug of war’ between exploration, depletion, and technological change.Over 100 mineral and commodities, stretching back to the late 19th or early 20th century, are considered. The variety of LR trends is astonishing, but very few increase monotonically, contrary to the prediction of the basic Hotelling model. Some decline monotonically (as predicted by Prebisch and Singer); some have the U-shaped pattern predicted by Pindyck (1978), Heal (1981) and Slade (1982). Others have changed direction up to three times in the period since 1900. The tug of war continues with exhaustion nowhere in sight.     

What are the top five journals in economics? A new meta-ranking

We construct a meta-ranking of 277 economics journals based on 22 different rankings. The ranking incorporates bibliometric indicators from four different databases (Web of Science, Scopus, Google Scholar, and RePEc). We account for the different scaling of the bibliometric indicators by standardizing each ranking score. We run a principal component analysis to assign weights to each ranking. In our meta-ranking, the top five journals are given by: Quarterly Journal of Economics, Journal of Financial Economics, Journal of Economic Literature (JEL), Journal of Finance, and Econometrica. Additionally, leaving out the JEL as a survey journal and the finance journals in our top 10 list we confirm the perceived top five journals in the economics profession.     

Updates management in mobile applications: iTunes versus Google Play

This paper focuses on a specific strategy that developers of mobile applications may use to stimulate demand: The release of updates. We develop a theoretical analysis that shows that developers have incentives to release updates when experiencing a drop in performance. The predictions of the model are then tested using an unbalanced panel of top 1,000 apps in iTunes and Google Play for five European countries. We estimate that while in iTunes the release of an update stimulates a 26% increase in download growth, in Google Play updates play a less significant role. This difference is partly due to systematic differences in apps and in developers operating in the two stores (“selection effect”), and partly to a lack of quality control on apps and updates in Google Play (“quality check effect”). These findings highlight the crucial importance of an appropriate management of updates as well as the relevance of institutional characteristics of the app stores.     

Big Data: An Institutional Perspective on Opportunities and Challenges

The data revolution is already reshaping how knowledge is produced, business conducted, humanitarian assistance handled, public officials elected, and governance enacted. Economists rely on data to describe, interpret, and forecast economic activity. Despite the rich tradition of using large datasets, institutional economics have shied away from big data. This article describes, reviews, and reflects on big data, with a particular focus on economic development. It illustrates the vast opportunities and challenges for big data as an important tool for the benefit of the public. It suggests that big data and data analytics, if used properly, can provide real-time actionable information that can be used to identify problems and needs, offer services, and provide feedback on the effectiveness of policy action.     

Examining the prospects for Gigabit Broadband: Lessons learned from Google Fiber

This study examines possible lessons learned from the deployment of residential Gigabit networks based upon the novel approach taken by the Google Fiber project started in 2010. Even though Google Fiber paused any project expansion in 2016, calling into question the viability of their business model, the approach taken by Google Fiber elicits further research interest given four major innovations that this analysis identifies in its fiber-to-the-home business model. Based on a “top-down” financial model to estimate the costs of fiber deployment, this analysis shows that these four innovations pursued by Google Fiber, and now adopted on a widespread basis by other broadband providers, lower the costs of building residential Gigabit networks, and therefore can improve the prospects for new entry of service providers of residential broadband services. With technology advances pointing to further cost reductions in the cost of Gigabit networks, this analysis elevates the need for more detailed study of ongoing changes in the cost structure of local access networks to better anticipate future prospects for broadband competition.     

Predictive power of web search behavior in five ASEAN stock markets

This paper investigates the predictive ability of web search behavior in connection with stock market returns and trading volume in five emerging economies in the ASEAN region using econometric and signal-processing techniques. More specifically, we use Vector Error Correction Model in conjunction with Wavelet analysis and find consistently low predictive ability of search activity in Google. In fact, investors in nearly all five markets appear to be interested in searching terms related to the market after high returns or high trading activities occur. In other words, high returns or high activities precede search interest. Our findings are at odds with the general results reported in earlier studies conducted in developed countries. Additionally, our analysis in the time-frequency domain detects a two-week lead-lag phenomenon in the association between search behavior and market returns for all markets but the Philippines.     

餐旅职教实训模式嬗变趋向

教学实训模式在餐旅教学理论与实践的中介上具有十分明显的优越性 ,随着中国经济发展与社会进步 ,餐旅实训模式发生嬗变 ,嬗变趋向大致可归结为集约联合、产学结合、市场中介和深入创新几种类型 ,并呈现出未来校内全景式实训氛围创建和社会化程度适度提升的双轨平行发展的大趋势。