区域知识产权保护发展的空间格局及结构体系研究

以我国各省知识产权保护制度为研究对象，创新性地将探索性空间数据分析方法与社会网络分析方法相结合，基于地理邻近视角，验证了区域知识产权保护的空间相关性、空间集聚特征和空间溢出效应。同时，突破地理近邻效应的局限，解析区域知识产权保护的空间关联特征。结果表明：我国各省知识产权保护具有全局自相关性，相似地区间存在空间集聚效应，不同发展程度地区的空间关联性质不同；网络化后的区域知识产权保护各节点间联系紧密、网络结构稳定，并且可以确定核心行动者和边缘行动者角色；长三角、珠三角、环渤海等较发达地区与其它地区之间存在较多溢出关系。     

The role of network embeddedness across multiple social networks: Evidence from mobile social network games

This article examines peer influences from network relationships within a social network game (i.e., embeddedness) and across such games (i.e., multiplexity). Drawing on social influence theory, we develop a bivariate Poisson model of users’ repeated visits and latent attrition that accommodates peer interaction after controlling for homophily. We estimate the model using data from two social network games with considerable overlap among network members. We find that friends who are only multiplex across games exert greater peer influence on users’ game visits than members who are embedded within a single game. We also determined that ignoring network multiplexity across games may lead firms to mistarget users due to biased peer influences of embedded friends. This result provides an unresearched explanation—strength of peer influence—for the mixed findings in previous literature on network embeddedness. We utilized our results to conduct several scenario analyses to demonstrate how firms can effectively manage users’ engagement and target users in multiple social network games.     

科技服务业产出测算：指标确立、数据收集与未来预测

科技服务业产出测算是对科技服务业产出数据的统计与分析，加强科技服务业产出数据的规范统计和应用分析可为我国政府调整产业政策提供重要数据支撑。以科技服务业产出测算为研究对象，结合学者观点、国家标准及各级政府相关产业政策，提出将分支产业作为初始指标的横向统计思路，构建科技服务业产出测算指标体系。在数据收集方面，强调要做好“收”与“填”两个基本工作；在指标确立和数据收集基础上，进一步提出未来预测的两种方法，以此作为科技服务业产出数据预测的初步探索；提出应从统一数据统计标准、完善数据调查与公开制度、加强数据资源开发3个方面建立健全我国科技服务业产出数据测量与管理体制机制。     

How artificial intelligence will affect the future of retailing

Artificial intelligence (AI) will substantially impact retailing. Building on past research and from interviews with senior managers, we examine how senior retailing managers should think about adopting AI, involving factors such as the extent to which an AI application is customer-facing, the amount of value creation, whether the AI application is online, and extent of ethics concerns. In addition, we highlight that the near-term impact of AI on retailing may not be as pronounced as the popular press might suggest, and also that AI is likely to be more effective if it focuses on augmenting (rather than replacing) managers’ judgments. Finally, while press coverage typically involves customer-facing AI applications, we highlight that a lot of value can be obtained by adopting non-customer-facing applications. Overall, we remain very optimistic as regards the impact of AI on retailing. Finally, we lay out a research agenda and also outline implications for practice.     

Network structure,portfolio diversification and systemic risk

We investigate the effect of portfolio diversification on banking systemic risk, where the network effect is incorporated. We analyze three kinds of interbank networks, namely, random networks, small-world networks and scale-free networks. We show that the effect of portfolio diversification on banking systemic risk depends on interbank network structures and shock types. First, systemic risk increases first and then reduces with the increase of the level of portfolio diversification in the case of the individual shock. Second, in the case of the systemic shock, systemic risk reduces with the increases of the level of portfolio diversification. Third, banking systems with scale-free network structures are the most stable, and those with small-world network structures are the most vulnerable.     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

高校跨学科创新团队知识互动程度评价研究

知识互动程度评价对改善高校跨学科创新团队知识互动具有重要意义。在界定高校跨学科创新团队知识互动及知识互动程度内涵的基础上，创新性地从知识互动深度、互动广度、互动时间3个维度建立知识互动程度评价指标体系。进一步地，采用三角模糊权重、熵权和模糊积分相结合的方法，构建知识互动程度评价模型。最后，选取一所高校跨学科创新团队进行实例分析，验证评价模型的可操作性，可为高校跨学科创新团队知识互动程度评价提供一个新视角。     

知识型员工双重社会网络对企业创新绩效作用机制研究

基于企业基础资源观和组织学习理论，从知识型员工个人和组织社会网络两个方面构建知识型员工双重社会网络影响企业创新绩效的理论模型，分析知识共享、组织学习及资源整合在员工双重社会网络对企业创新绩效影响机制中的作用。结果表明：知识型员工双重社会网络对科技型企业创新绩效的作用路径有3条，资源获取与整合、知识共享与学习及员工动态创新能力分别在其中发挥中介作用；在不同类型组织文化环境中，知识型员工双重社会网络对企业创新绩效的作用特征、作用重点以及作用机制存在显著差异，内部整合维度主要通过知识共享和组织学习影响企业创新绩效，外部适应维度主要通过隐性知识传播和资源整合影响企业创新绩效。     

数学素质教育的发现法

素质教育倡导数学教学应重视学生的主观能动性，力求使学生亲身经历数学问题的发现过程，体验研究成果的喜悦。文章就发现法教学从理论到实践阐述了这种教学方式的五种途径。     

美国深空网的同波束干涉测量技术

讨论了美国NASA深空网(DSN)对深空飞船所采用的同波束干涉(SBI)技术概念和测量原理，并介绍了这一技术的应用和发展情况。