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11.
Adriana Gama 《Bulletin of economic research》2019,71(3):508-516
This paper endogenizes the number of firms in an industry with positive network effects, complete incompatibility, and firms that compete in quantity. To this end, we compare two possibilities: free entry and second‐best number of firms (the one that maximizes social welfare). We show that with business‐stealing competition, free entry yields, in general, more firms than the socially optimal solution. In addition, we find that by the nature of the industry with firm‐specific networks, total production may be greater or lower under free entry than with a regulator; moreover, some industries attain their maximum social welfare with a monopoly. 相似文献
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As one type of international capital flow, FDI maintains its important role in globalization. This article attempts to investigate the evolution of the FDI flows from a network perspective. Based on the bilateral FDI flows data between countries from 2003 to 2012, we construct the global FDI flows network for each year and thus quantify network measures (such as flow volumes and connections); further by analysing the tendency and changes of these network measures during the past 10 years, we delineate the features and dynamics of the FDI flows in the global network. We have the following findings: (a) the flows network changes during and after the crisis, i.e. flow volume fallen down and recovered, and flow connection restructured with more diversity; (b) the global FDI flows network is getting more loosely connected; (c) individual countries vary in different patterns. 相似文献
14.
Resource Dependence and Network Relations: A Test of Venture Capital Investment Termination in China 下载免费PDF全文
This study examines how venture capital (VC) firms terminate investments in an emerging economy context. We contend that due to the weak institutional environment, it is appropriate to draw on insights from power and social relation perspectives for a better understanding of the phenomenon. Specifically, we argue that a termination decision hinges on not only the dependence relationship between a VC firm and its portfolio companies, but also the social relationships among VC firms. Event history analyses of approximately 12,000 VC deals made in China between 2001 and 2012 reveal that when a VC firm has a greater number of investments in an industry, it is more likely to terminate investments on a portfolio company in that industry. Moreover, such effect on termination is moderated by the focal VC's embeddedness with its syndicate partners and collaboration opportunities with other VC firms outside the immediate access of the syndicate partners. Our study sheds light on research on VC decision making in emerging markets by integrating insights from resource dependence relationships and interorganizational network characteristics. 相似文献
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ABSTRACTThis study takes a micro standpoint to quantitatively verify the extent to which local interactions affect the expansion of dynamic social networks. By reviewing and synthesizing the theoretical literature in this article, we seek to establish a pragmatic analytical framework to capture the underlying functioning of local interactions. It then aims to produce findings on seven distinct marketing campaigns in which the real-world virtual communities offer intact time-series connections. In our considered cases, the firm-to-consumer interactivity plays a pivotal role in social media marketing while the customer-driven influence advances individual information transmission. The significant positive relationships demonstrate features of interactivity within subgroups including reciprocal edges and directed 3-cliques associated with the evolution of the virtual community by electronic word-of-mouth (WOM) of both firm-to-consumer and consumer-to-consumer interactions. More importantly, the attenuation of local interactions to a large extent leads to the cut-off point of the growth of the dynamic social network. 相似文献
16.
Junliang Wang Jungang Yang Xiaoxi Wang Wenjun Zhang 《Enterprise Information Systems》2018,12(6):714-732
Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation. 相似文献
17.
The problem of employees' network centrality and supervisors' error in performance appraisal: A multilevel theory 下载免费PDF全文
Lorenzo Bizzi 《人力资源管理》2018,57(2):515-528
This article reveals an unexplored paradox for HR managers: the centrality of an employee in the social network benefits performance but hampers performance appraisal because it affects supervisors' rating errors. Central employees can be erroneously rated high on performance even when they are not high performers because supervisors tend to overappraise their performance. A distinction is made between rating precision, which depends on supervisors' uncertainty regarding employees' performance, and rating accuracy, which depends on supervisors' bias in favor of employees. Employee centrality is posited to be beneficial to precision but deleterious to accuracy because it regulates the diffusion of positive information, status, and power, all of which distort supervisors' capacity and motivation to accurately appraise performance. It is then argued that rating errors caused by network centrality affect aggregate perceptions of justice in organizations. When employees are highly connected to each other in a dense network, organizations have a strong and positive justice climate. Yet when some employees are more central than others in a centralized network, organizations have a negative and weak justice climate. The article contributes to the literature because it identifies an unexplored dark side of network centrality and offers recommendations for HR managers to cope with its deleterious consequences and for scholars to study them. 相似文献
18.
The paper presents a new methodology, based on tensor decomposition, to map dynamic trade networks and to assess its strength in forecasting economic fluctuations at different periods of time in Asia. Using the monthly merchandise import and export data across 33 Asian economies, together with the US, EU and UK, we detect the community structure of the evolving network and we identify clusters and central nodes inside each of them. Our findings show that data are well represented by two communities, in which People's Republic of China and Japan play the major role. We then analyze the synchronisation between GDP growth and trade. Furthermore we apply our model to the prediction of economic fluctuations. Our findings show that the model leads to an increase in predictive accuracy, as higher order interactions between countries are taken into account. 相似文献
19.
Fredric Bauer Teis Hansen Hans Hellsmark 《Technology Analysis & Strategic Management》2018,30(8):935-947
The bioeconomy has become a central concept in many strategies for future economic development, emphasising an increasing need for collaboration across industries and sectors for innovation. This paper unpacks aspects of collaboration in the bioeconomy by looking at the development of innovation networks for biorefinery technologies from 2004 to 2014 based on innovation project data from Swedish public funding agencies using a stochastic actor-oriented model for network analysis. The analysis shows that although the network grew significantly during the time period, indicating an increasing interest in biorefinery technology innovation, inter-sectoral collaboration is not favoured over intra-sectoral collaboration. As is known from previous work on social networks trust-building is a key driver for collaboration, as actors tend to form collaborations with previous partners or indirectly connected partners, creating clustered networks. 相似文献
20.
Ting Sun Miklos A. Vasarhelyi 《International Journal of Intelligent Systems in Accounting, Finance & Management》2018,25(4):174-189
The objective of this paper is twofold. First, it develops a prediction system to help the credit card issuer model the credit card delinquency risk. Second, it seeks to explore the potential of deep learning (also called a deep neural network), an emerging artificial intelligence technology, in the credit risk domain. With real-life credit card data linked to 711,397 credit card holders from a large bank in Brazil, this study develops a deep neural network to evaluate the risk of credit card delinquency based on the client's personal characteristics and the spending behaviours. Compared with machine-learning algorithms of logistic regression, naive Bayes, traditional artificial neural networks, and decision trees, deep neural networks have a better overall predictive performance with the highest F scores and area under the receiver operating characteristic curve. The successful application of deep learning implies that artificial intelligence has great potential to support and automate credit risk assessment for financial institutions and credit bureaus. 相似文献