全文获取类型
收费全文 | 16825篇 |
免费 | 4篇 |
专业分类
财政金融 | 2659篇 |
工业经济 | 763篇 |
计划管理 | 2565篇 |
经济学 | 3884篇 |
综合类 | 482篇 |
运输经济 | 2篇 |
旅游经济 | 1篇 |
贸易经济 | 4502篇 |
经济概况 | 1355篇 |
信息产业经济 | 44篇 |
邮电经济 | 572篇 |
出版年
2023年 | 1篇 |
2021年 | 3篇 |
2020年 | 1篇 |
2019年 | 3篇 |
2018年 | 2308篇 |
2017年 | 2056篇 |
2016年 | 1209篇 |
2015年 | 96篇 |
2014年 | 88篇 |
2013年 | 69篇 |
2012年 | 441篇 |
2011年 | 1946篇 |
2010年 | 1828篇 |
2009年 | 1521篇 |
2008年 | 1514篇 |
2007年 | 1869篇 |
2006年 | 68篇 |
2005年 | 386篇 |
2004年 | 465篇 |
2003年 | 551篇 |
2002年 | 251篇 |
2001年 | 61篇 |
2000年 | 49篇 |
1998年 | 17篇 |
1997年 | 1篇 |
1996年 | 14篇 |
1986年 | 13篇 |
排序方式: 共有10000条查询结果,搜索用时 15 毫秒
991.
Death, injury, conflict, and disorder caused by natural and man-made disasters have resulted in significant challenges to good governance and impeded the goal of achieving the benign development of society. This paper uses a particular method for analyzing the research situation and identifying current trends and focuses. It then proceeds to explore future research needs. The study finds that future researchers will shift their emphasis from the risks caused by natural disasters to those arising from man-made disasters; meanwhile, the study will consider the complex systems of interaction to understand causality. The objectives of management, hence, should change from investigating the impacts of risks to crisis control. Eventually, an evolutionary disaster-based social-risk framework is established, and some suggestions for future research are provided. 相似文献
992.
Didier Nibbering Richard Paap Michel van der Wel 《International Journal of Forecasting》2018,34(2):288-311
This paper studies what professional forecasters predict. We use spectral analysis and state space modeling to decompose economic time series into trend, business cycle, and irregular components. We examine which components are captured by professional forecasters by regressing their forecasts on the estimated components extracted from both the spectral analysis and the state space model. For both decomposition methods, we find that, in the short run, the Survey of Professional Forecasters can predict almost all of the variation in the time series due to the trend and the business cycle, but that the forecasts contain little or no significant information about the variation in the irregular component. 相似文献
993.
Are productivity estimates good proxies for unobserved management? And, does management affect production in a neutral and monotonic fashion as assumed by these proxies? We use Bloom and Van Reenen’s management data to show that two popular proxies, fixed effects and inefficiency scores, correlate with observed management practices. We find that the correlations are positive but weak. Also, management explains only a fraction of the proxies’ variances. The data rejects the assumptions of neutrality and monotonicity. Last, our results suggest that management has characteristics both of a technology and an input. 相似文献
994.
A problem with index number methods for computing TFP growth is that during recessions these methods show declines in TFP. This is rather implausible since it implies technological regress. We develop a new method to decompose TFP growth into technical progress and inefficiency arising from the short run fixity of capital and labour, and apply this to new data on the US corporate nonfinancial sector and the noncorporate nonfinancial sector. The analysis sheds light on sources of the productivity growth slowdowns over the period 1960–2014. 相似文献
995.
The proposed method of Stochastic Non-smooth Envelopment of Data (StoNED) for measuring efficiency has to date mainly found application in the analysis of production systems which have exactly one output. Therefore, the objective of this paper is to examine the applicability of StoNED when a ray production function models a production technology with multi-dimensional input and output. In addition to a general analysis of properties required by a ray production function for StoNED to be applicable, we conduct a Monte Carlo simulation in order to evaluate the quality of the frontier and efficiencies estimated by StoNED. The results are compared with those derived via Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). We show that StoNED provides competitive estimates in regard to other methods and especially in regard to the real functional form and efficiency. 相似文献
996.
997.
998.
999.
1000.
Fabian Pfaffenberger 《Publizistik》2018,63(1):53-72
Twitter has a high presence in our modern society, media and science. Numbers of studies with Twitter data – not only in communication research – show that tweets are a popular data source for science. This popularity can be explained by the mostly free data and its technically high availability, as well as the distinct and open communication structure. Even though much research is based on Twitter data, it is only suitable for research to a limited extent. For example, some studies have already revealed that Twitter data has a low explanatory power when predicting election outcomes. Furthermore, the rise of automated communication by bots is an urgent problem of Twitter data analysis. Although critical aspects of Twitter data have already been discussed to some extent (mostly in final remarks of studies), comprehensive evaluations of data quality are relatively rare.To contribute to a deeper understanding of problems regarding the scientific use of Twitter data leading to a more deliberate und critical handling of this data, the study examines different aspects of data quality, usability and explanatory power. Based on previous research on data quality, it takes a critical look with the following four dimensions: availability and completeness, quality (regarding authenticity, reliability and interpretability), language as well as representativeness. Based on a small case study, this paper evaluates the scientific use of Twitter data by elaborating problems in data collection, analysis and interpretation. For this illustrative purpose, the author typically gathered data via Twitter’s Streaming APIs: 73,194 tweets collected between 20–24/02/2017 (each 8pm) with the Streaming APIs (POST statuses/filter) containing the search term “#merkel”.Concerning data availability and completeness, several aspects diminish data usability. Twitter provides two types of data gateways: Streaming APIs (for real-time data) and REST APIs (for historical data). Streaming APIs only have a free available Spritzer bandwidth, that is limited to only one percent of the overall (global) tweet volume at any given time. This limit is a prevalent problem when collecting Twitter data to major events like elections and sports. The REST APIs do not usually provide data older than seven days. Furthermore, Twitter gives no information about the total or search term-related tweet volume at any time.In addition to incomplete data, several quality related aspects complicate data gathering and analysis, like the lack of user specific and verified information (age, gender, location), inconsistent hashtag usage, missing conversational context or poor data/user authenticity. Geo data on Twitter is – if available at all – rarely correct and not useful for filtering relevant tweets. Searching and filtering relevant tweets by search terms can be deceptive, because not every tweet concerning a topic contains corresponding hashtags. Furthermore, it is difficult to find a perfect search term for broader and dynamically changing topics. Besides, the missing conversational context of tweets impedes interpretation of statements (especially with regard to irony or sarcasm). In addition, the rise of social bots diminishes dataset quality enormously. In the dataset generated for this work, only three of the top 30 accounts (by tweet count) could be directly identified as genuine. One fourth of all accounts in this dataset generated about 60% of all tweets. If the high-performing accounts predominantly consist of bots, the negative impact on data quality is immense.Another problem of Twitter analysis is Internet language. While Emojis can be misinterpreted, abbreviations, neologisms, mixed languages and a lack of grammar impede text analysis. In addition to low data quality in general, the quality of tweet content and its representativeness is crucial. This work compares user statistics with research articles on SCOPUS as well as media coverage of two selected, German quality newspapers. Twitter is – compared to its user count – enormously overrepresented in media and science. Only 16% of German adults (over 18 years) are monthly active (MAUs) and merely four percent are daily active users.Considering all presented problems, Twitter can be a good data source for research, but only to a limited extent. Researchers must consider that Twitter does not guarantee complete, reliable and representative data. Ignoring those critical points can mislead data analysis. While Twitter data can be suitable for specific case studies, like the usage and spread of selected hashtags or the twitter usage of specific politicians, you cannot use it for broader, nation-based surveys like the prediction of elections or the public opinion on a specific topic. Twitter has a low representativeness and is mostly an “elite medium” with an uncertain future (concerning the stagnating number of users and financial problems). 相似文献