经济全球化条件下我国市场结构问题的理论思考和对策建议

经济全球化对我国市场结构的影响集中体现为跨国公司的进入和WTO规则的执行对我国行业中企业之间垄断竞争关系的影响.本文就此对开放条件下我国市场结构有效竞争模式进行理论思考,重点探讨了维护国家经济安全与促进国内市场开放、反对垄断与发展规模经济、促进竞争与防止竞争过度等方面问题,并在此基础上提出优化我国市场结构的政策建议.     

供应链金融利益主体的多阶段博弈研究

现代经济中,金融在资源配置方面发挥的作用明显不足,出现严重的资源浪费和供需错配现象,加剧了中小企业面临的融资难问题.本文从供应链金融的内涵切入,建立以利益相关者为主体的融资量化模型,利用多阶段博弈理论对企业不同模式下的成本收益进行检验,结果表明:供应链金融在实现上、下游各利益相关者个体的最优化的同时,也可有效促使供应链整体的利益最大化、实现高效运作和价值增值,全面实现链上企业间的资源共享、互利共赢.     

中国经济波动的产出和通胀效应 ——基于供求冲击相关的SVAR模型分析

本文结合产出缺口-通胀形式的菲利普斯曲线（AS曲线）,构建了产出缺口和通 胀率的SVAR模型,并将识别结果同B-Q约束条件下的识别结果进行比较,以此来探究我国近 三十多年来宏观经济系统中需求冲击和供给冲击对产出和通胀动态的效应。主要得出以下结 论：第一,供求冲击之间高度相关;第二,需求冲击是我国通胀波动的决定性因素,并且存在 持久稳定的效应。第三,供给冲击是我国经济增长的绝对主导力量。第四,我国存在相对陡峭 的菲利普斯曲线（AS曲线）。第五,产出缺口与同比CPI对我国经济状况的拟合效果最好。     

“丝路经济带”九省市经济金融竞争力评价

深入剖析丝绸之路沿线国内段九省市的综合发展实力,探索不同发展战略定位下省 区市竞合协同发展路径,对全面发展丝绸之路经济带具有重要意义。本文从经济发展竞争力、 环境设施与可持续发展竞争力、科技创新与财富竞争力、金融发展竞争力、对外开放竞争力五 个维度建立指标评价体系,运用分类主成分分析法全面衡量九个省市经济金融发展的分项和综 合竞争力,将九省市分为三个发展梯度,形成资源聚集与要素流动的直观剖析。在此基础上,利 用聚类分析法得出丝绸之路经济带区域经济关联的着力点与经济发展的增长极,并最终得出处 于不同梯度省区市间开展基于优势竞争力的产业间合作的三大有效路径。     

Social capital,user motivation,and collaborative consumption of online platform services

Collaborative consumption is broadly defined as sharing, obtaining, and giving access to products and services through peer networks online. As it is expected to resolve the societal and environmental problems, quite a few studies investigated consumers’ motivations that lead to positive attitudes and intention for collaborative consumption. This paper aims to study the determinants that motivate participants to perceive a positive attitude towards collaborative consumption focusing on three salient traits of social capital (shared goal, social interaction tie, and norms of reciprocity). The study found that social capital exerts a more substantial influence on intrinsic motivation (enjoyment and sustainability) than extrinsic motivation (economic benefit). The study also found that different social capital traits display different effects on motivation. In particular, the shared goal was a key determinant of both intrinsic and extrinsic motivation. And all three motivations positively affect collaborative consumption attitudes.     

知识操纵行为意向影响因素研究

知识（尤其是隐性知识）是员工生存和发展的关键资源，知识权利的不完全性决定了知识交换中不可避免地存在欺骗、偷盗、投机等失范行为。在协同创新过程中，知识型员工既相互合作又彼此竞争。除采取知识共享和知识隐藏两种策略外，员工通常会选择折中的、柔性知识操纵策略管理个体知识。由此，界定知识操纵内涵，剖析其自利性、欺骗性、不确定性和隐蔽性4个特点。在此基础上，选择扎根理论方法，通过对68名知识型员工访谈数据进行编码，构建由本体、主体、客体、载体、动机、环境、契合7个主范畴组成的知识操纵影响因素概念模型。最后，围绕知识操纵治理，提出优化创新任务属性、发挥知识操纵对象能动作用、选择高效知识管理载体、培养员工利他特质、营造协同创新环境、提高员工契合度等启示。     

高校经济管理实验中心实验室开放项目优化研究——以嘉兴学院为例

以嘉兴学院经济管理实验中心为研究对象，利用经济管理实验中心统计数据和问卷调查数据，在分析经济管理实验中心实验室开放项目现状、项目优化的必要性和可行性的基础上，提出了实验室开放项目优化的方案及其措施：调整和优化实验室开放项目比例、丰富和优化实验室开放项目内容、合理安排和调配实验室开放时间的优化实验室条件与环境。     

Economic contribution of essential air service flights on small and remote communities

The Essential Air Service Program (EAS) has attracted considerable criticism and has been a target for either modification or complete termination almost since its inception through the Airline Deregulation Act in 1978. Although its opponents emphasize the program's inefficiency, its supporters claim that the program is crucial to accessing small and remote communities, which helps them develop economically and socially. This paper demonstrates the economic contributions of EAS flights to small and remote communities. Using a two-stage least squares estimation, the major findings indicate that a 1% increase in air passenger traffic in EAS airports with a minimum annual air passenger traffic of 1000 likely leads to a 0.12% increase in per capita income of the community served by that airport. Our results also suggest that EAS communities that are able to sustain their subsidized flights experienced higher per capita income growth in the 1999–2011 period than did ex-EAS communities that lost their flights as a result of non-eligibility.     

Searching for empirical linkages between demographic structure and economic growth

Demographic structure could affect economic growth through many channels. However, little is known about how demographic structure affects economic growth since no study has examined an extensive collection of channels through which demographic structure could affect economic growth in a single context. This paper overcomes this limitation by examining 45 potential mediating variables between demographic structure and economic growth. A causal search algorithm is used to identify channels through which demographic structure affects economic growth. Our results suggest that demographic structure affects economic growth differently between developed and developing countries. For developed countries, we find that an increase in the share of middle-aged workers has a positive effect on economic growth through institutions, investment and education channels. On the other hand, an increase in the share of the senior population has a negative effect on economic growth through institutions and investment channels. For developing countries, we find (but with weak evidence) that an increase in the share of young workers has a negative effect on economic growth through investment, financial market development and trade channels.     

The eruption of Airbnb in tourist cities: Comparing spatial patterns of hotels and peer-to-peer accommodation in Barcelona

In recent years, what has become known as collaborative consumption has undergone rapid expansion through peer-to-peer (P2P) platforms. In the field of tourism, a particularly notable example is that of Airbnb. This article analyses the spatial patterns of Airbnb in Barcelona and compares them with hotels and sightseeing spots. New sources of data, such as Airbnb listings and geolocated photographs are used. Analysis of bivariate spatial autocorrelation reveals a close spatial relationship between Airbnb and hotels, with a marked centre-periphery pattern, although Airbnb predominates around the city's main hotel axis and hotels predominate in some peripheral areas of the city. Another interesting finding is that Airbnb capitalises more on the advantages of proximity to the city's main tourist attractions than does the hotel sector. Multiple regression analysis shows that the factors explaining location are also different for hotels and Airbnb. Finally, it was possible to detect those parts of the city that have seen the greatest increase in pressure from tourism related to Airbnb's recent expansion.