The development of emerging industries is vital for a city’s sustainable growth and represents new momentum for urban development. Most of present researches concentrate on specific industries without addressing systematic development and targeted promotion. This study uses data mining and fuzzy-set qualitative comparative analysis (fsQCA) to examine multiple industries and identify key resources for a city’s competitive advantage. Comparing 290 cities in China, emerging industries can be divided into natural resource endowment-based industries and non-natural resource endowment-based industries. For natural resource endowment-based industries, economic capacity and natural resources play crucial roles in enabling cities to gain high industrial comparative advantages. For non-natural resource endowment-based industries, the technology innovation entity and government support capability are more valuable in forming high industrial comparative advantage. The findings aim to provide a theoretical basis for fostering emerging industries toward sustainable urban development.

As a strategic technology propelling the new wave of technological revolution and industrial transformation, artificial intelligence (AI) is fundamentally re-configuring manufacturing models and corporate architectures. Analyzing the evolutionary mechanisms of these transformations is crucial for promoting the development of industries and enterprises to a higher level. This study explores the evolution of industrial revolutions and manufacturing models from two perspectives: market demand-driven forces and intelligent manufacturing technologies. It summarizes China's decade-long innovations in manufacturing models and corporate structures, including the shift from mass production to customized manufacturing, the transition from competition and monopoly to collaborative and shared frameworks, and the evolution from production-oriented to service-oriented manufacturing. In the next decade, the focus should be on service-oriented manufacturing reforms, along with brand building, utilization of AI-powered technologies, and establishment of standards systems. These innovations in manufacturing models and corporate structures will serve as the foundation for the development of a manufacturing powerhouse.

Technology convergence is meaningful for emerging technology development and transitional industry transformation, and there are more and more researches focusing on its development pathway and effects. However, there are still few researches concerning why the technology convergence appears and changes. This research proposes to unfold its evolution mechanism from the perspective of network evolution. Besides the network structure features, this research tries to embed the nature features of nodes to analyze the mechanism based on multiple exponential random graph models, such as technology features, enterprises features, etc. It utilizes patentee cooperation network and IPC co-occurrence network to characterize the enterprise cooperation and technology convergence based on patent data, and conduct empirical study on industrial robots to test the mechanism. The results indicate that the network structure features of two networks and the nature features of nodes which contain technology features and enterprise features all have a significant impact on the mechanism of technology convergence, and the impact on converging mechanism changes over time. The findings of this research bear concrete implications for capturing technology convergence mechanism and the direction of technology development within the technical field.

Significant convergence has occurred between new-generation artificial intelligence technology and industrial robot technology. However., there are still limitations in the research to use quantitative methods to analyze the technology convergence process. This study proposes to analyze the technical knowledge contained in patent data from the perspective of knowledge flow, to describe the development trend of technology convergence by building a patent knowledge flow network and technology convergence network, to identify the technology convergence path and key convergence components, and to conduct empirical research in the field of industrial robots. The study has identified the technology convergence clusters with high technical control force and high technical value. The results can support relevant researchers to grasp technological opportunities in advance in the rapid development of industrial robots.

随着市场需求的牵引和智能制造技术的驱动,服务在制造业全生命周期中的作用越来越重要,制造业产业模式与产业形态正在发生革命性变革.基于价值链理论和"微笑曲线",从价值创造的角度阐述了产业模式的演变过程;总结提出产业模式的创新业务形式.研究表明,日益增长的美好生活需要和智能制造等新兴技术正在推动制造业从"以产品为中心"向"以客户为中心"转变,不同终端制造企业将会选择不同的业务发展途径.在分析当前所面临挑战的基础上,针对产业模式创新应用提出建议:提高对服务型制造的认识、持续支持服务型制造相关基础工作、加强服务型制造相关技术的研究与应用,努力推动制造业从产业链中低端走向中高端.

数字创新生态系统的共生演化模式对于我国打造数字经济新优势,实现经济高质量发展具有强烈的现实意义.本文融合数字经济、生态系统、共生理论和博弈论等理论,考虑创新主体的多样性特征,构建数字创新生态系统两主体和三主体的Lotka-Volterra动态演化模型,研究数字创新生态系统的共生演化模式,通过数值模拟仿真验证并分析两主体核心式数字企业种群和卫星式数字企业种群的共生模式,在此基础上引人高校科研机构种群至数字创新生态系统以破解主流两主体共生模式的局限性,仿真分析研究高校科研机构种群的入驻对数字创新生态系统三主体共生关系及演化模式的影响.研究结果表明:(1)数字创新生态系统是由核心式数字企业共生单元、卫星式数字企业共生单元和高校科研院所共生单元在一定的共生环境中,共同开展数字创新活动的生态系统;(2)数字创新生态系统两主体共生发展存在数字技术资源过度依赖和协同不够的问题,难以真正实现互惠共生模式;(3)通过高校科研机构种群向数字创新生态系统注入创新活动可持续性的动力,达成数字创新生态系统演化的最佳目标导向——三主体互惠共生模式.最后提出中国数字创新生态系统走向互惠共生演化的策略建议.

[目的 /意义]由于新兴技术本身的超前性,其刚出现的关注度往往不是很高.目前研究更多遵循技术发展路径依赖进行新兴技术的识别,会忽略一些颠覆现有技术轨道的技术研发.通过对与领域内主流技术相似度较低的离群专利进行分析,可以更有效地识别这类技术研发并预测新兴技术.[方法/过程]提出一种基于深度学习的离群专利识别与新兴技术预测方法.首先使用BERT预训练模型基于专利文本构建相似度网络,识别离群专利,然后基于DNN模型构建离群专利指标与技术影响力之间的关系,实现从海量离群专利中快速、准确地预测新兴技术.最后以数控系统领域为例,从德温特专利数据库获取近10年领域内所有专利,进行实证分析.[结果/结论]数控系统领域的实证分析结果验证了模型的有效性,同时对国家的技术发展政策制定以及相关领域企业技术布局具有重要的指导意义.

The analysis of technology convergence process for strategic emerging industries is helpful to deeply understand the generation process and development law of industrial technology, thereby helping master the development trend of the field and promoting the healthy development of the industry. To identify the trajectory and degree of technology convergence of the strategic emerging industries, this study conducts a multi-case study on four fields which present a trend of convergence and attract social attention, namely, high-end equipment manufacturing, new-generation information technology, new medicine, and new energy. This study adopts a knowledge convergence trajectory analysis method based on citation network and text information. It utilizes a graph neural network model and encodes the citation network, title, and abstract of the publications as vectors. Five knowledge convergence trajectories are identified, after analyzing the data of the selected four technical fields. The research results show that information technology and numerical control equipment, biomedicine and solar photovoltaic technology have shown a trend of deep convergence, respectively; and the convergence of the information technology and numerical control equipment is deeper. Numerical control equipment and solar photovoltaic technology, information technology and solar photovoltaic technology have shown a converging trend, respectively; however, the current degree of convergence is still insufficient, due to the late start of convergence. Numerical control equipment and biomedicine have not shown any trend of convergence.

The importance of technology convergence of multidisciplinary knowledge has increased recently, and it is a crucial way to spur emerging technologies. Therefore, to understand and identify the technology convergence, which refers to the combination of two or more technological elements for a new system with new functions, is an important issue for both the researchers and the company directors. To identify and investigate the patterns of technology convergence, this research examines the numerical control machine tool, which has typical characteristics of technology convergence in recent years. Based on the numerical control machine tool related publications published between 1997 and 2019, we perform a deep learning approach based on Graph Neural Network model using publication citation network topology and text information together, to identify the technology convergence trajectory and to examine the dynamic role of corresponding technology sub-fields in the technology convergence. The results show that there was an obvious increase for the interdisciplinary citations from information technology to NC machine tool in recent years, and the technology convergence on NC machine tool is signal processing in machining and application of intelligent algorithms in motion control and process planning. In addition, the revelation of the technology convergence early identification contributes to the formation theory of emerging technologies that are interdisciplinary, and is of great interest to researchers, policy makers, and industrialists.

根据"协同育人"人才培养的教育理念,结合邮政行业人才培养的特点,以建构主义学习理论为指导,将知识融合背景下研究协同育人的人才培养模式导入高校邮政人才培养的策略,探索多元协同育人模式,强化比较优势,开展项目共建、成果共享的人才培养机制,以改善目前高校人才培养的效果,实现邮政行业人才培养模式的创新.

The convergence of multi-disciplinary knowledge may spur emerging technologies. It is important to understand this convergence process that helps to identify these emergent technologies; however, relevant research remains sparse. Therefore, this study aims to develop a novel framework to reveal the convergence process of scientific knowledge. This novel framework integrates the machine-learning topology clustering and visualization methods, and analyzes paper citation networks. This study selects the biological–informatics domain (bioinformatics) to conduct the empirical analysis. This paper finds two major stages throughout the convergence process: the fast-changing incubation stage and the stabilized development stage. In the incubation stage, the interactions between the biology and informatics knowledge domains becomes increasingly intensive, while emergent technology is yet to form; in the stable development stage, the emergent technology starts to form as a core cluster, and based on which it grows amid stabilized knowledge interactions between the original two domains. The revelation of this convergence process contributes to the formation theory of emerging technologies that are inter-disciplinary, and is of great interest to researchers, policy makers, and industrialists.

<span id="ChDivSummary" name="ChDivSummary" class="abstract-text">文章运用了一种新的基于专利数据的技术预测方法以保证企业的技术投资能够成功。该技术预测方法主要包含四个维度,即技术生命周期、扩散速度、专利的权威性以及扩张潜力。其中,专利的权威性和扩张潜力是表征技术范畴的指标。最后,文章使用了一种数据融合算法将不同维度的数据分析结果进行结合,以完成综合评估。文章还使用实证分析的方法验证了这种预测方法的有效性和潜力。实证中,本研究利用汤森路透的全球专利库评估了快递物流领域的三项技术——运输规划技术、远程信息处理技术和无线射频识别技术。实证分析表明,现阶段在快递物流领域内运输规划技术的投资优先级要高于远程信息处理技术和无线射频识别技术。</span>

Driven by market demands and the artificial intelligent technology, mass customization is emerging. It thus becomes significant to analyze the influence of artificial intelligent technology on the development trend of the mass customization service mode and to summarize the breakthroughs of key technologies that need to be made in the future. Through case studies and expert interviews on furniture, household appliances, clothing and automobile industries, this paper analyzes the development trends of multiple key technologies such as multi-source cross-media heterogeneous database construction, a big-data-based design requirement feature mining system, a virtual experience system and virtual manufacturing, and whole-process information automatic collection, according to various market demands. Suggestions are proposed for popularizing the mass customization service mode integrated with artificial intelligent technology from aspects of top-level design, enterprise, talent and finance.

This research aims to study the technology frontier of mass-customized (MC) production service based on technology development trajectory analysis. MC production service has been put forward for about 50 years, and the development of artificial intelligence (AI) raises the intriguing possibility of using MC production mode to satisfy the more and more diverse needs of customers. In this research, the author utilizes both expert interviews and patent analysis to explore the technology development trajectory of information technology and customized production technology to realize MC production, and to identify the technology frontier. The paper purposes a method based on patent analysis integrated the expert opinions to identify the technology frontier. Based on the analysis, the technology related with customized production has been divided into five parts -production process algorithm, production scheduling technology, product storage and transportation technology, customers' demands analysis technology, and system optimization technology. Latent Dirichlet Allocation (LDA) and social network analysis based on patent data are utilized to the fusion development trajectory of information technology and the five parts of customized production technology, respectively. As the results, Derwent Innovation database is utilized to obtain the patent data and the citation network data, and the analysis indicates that AI technology provides more opportunities on the development of MC production service. The fusion of AI technology and customers' demands analysis, and the fusion of AI technology and system optimization are more likely to be achieved, while the fusion of AI technology and production scheduling technology and product storage and transportation technology are still to be developed, one of which is the core process of manufacturing -production scheduling. Finally, this research suggests to support the development of MC production service converged with AI technology, especially on the development of production scheduling technology.

Guidelines for the implementation of the China Manufacturing 2025 Regional Action Plan focus on the development of major areas and sub-areas in various provinces and cities. In order to comprehensively understand provincial and municipal action plans in China, consistency analyses for major development areas and difference analyses for major development sub-areas are fundamental. This paper proposes a method of analyzing policy documents based on Chinese word segmentation, feature extraction, and similarity calculation using text mining, which can help to analyze a large number of policy documents efficiently. The results indicate consistencies and differences in the action guidelines for various provinces and cities.

In 2015,the Chinese Academy of Engineering launched a major advisory project:Manufacturing Power Strategy Ⅱ.This project conducted a systematic and in-depth analysis of the major obstacles affecting China's position as a manufacturing power,presented relevant suggestions,and formed a research report.Based on a preliminary study of this project,this paper examines and discusses related issues involving manufacturing power indexes,China Manufacturing 2025 strategy,typical cases,and experts' opinions,by means of data mining,case studies,and expert interviews.The results indicate the main factors that obstruct the construction of China's manufacturing power,which include:the growth pattern of manufacturing in China;the unbalanced implementation of the five projects within China Manufacturing 2025 strategy;the similar focuses of different local governments on industrial development;and,finally,the risk of neglecting traditional industries.To solve these issues,these authors suggest promoting high-quality manufacturing and new technological transformation in order to accelerate the transformation of the economic growth pattern and the upgrading of traditional industries.They also suggest coordinating the implementation of the five projects with local industry policies in order to develop China's manufacturing power strategy more efficiently.

It is critical for “catching-up” countries to narrow innovation gaps with developed countries by developing emerging industries. This research introduces a data-mining based method to systematically assess the national innovation gap that is specifically for emerging industries. The method examines the five key attributes of emerging industries, including the ownership of platform technologies, globalization intention, international knowledge position, university-industry linkage, and cross-disciplinary technology development. In particular, this method combines data-mining with experts' knowledge to build patent-training examples, and then uses a support vector machine-based classifier to single out all high-quality patents for each innovation attribute. Based on the selected high-quality patents, the authors utilize a factorial design analysis to systematically evaluate the innovation gap between countries. This method can significantly reduce measurement bias of traditional single patent indicators. In addition, it also can robustly adjust measuring weights in response to the specifics of each innovation attribute, while traditional multi-attribute evaluation methods cannot. As a result, this research empirically shows that China' industrial robot sector has apparent innovation gaps compared to developed economies, specifically in university-industry linkage, cross-disciplinary competence, and globalization intention, and this calls for the attention of policy makers and industrial experts.

In recent years, China has started to change its growth strategy to a more sustainable model in response to the limits-to-growth dilemma. Specifically, the national policy advocates to promote the use of green-manufacturing technologies through demonstration projects, and to incentivize Chinese manufacturers to adopt these green-technologies that are also encouraged by local governments. These green technologies can increase the economic gains of manufacturers by reducing costs on energy consumption and shift away from selling low-margin products. However, the local authorities often encounter obstacles when implementing policies for promoting these technologies among manufacturing firms. This paper explores the factors that affect the decision-making of user firms throughout the policy implementation process. Based on the econometric analysis of the survey for China's electric motors upgrading project in Guangdong Province, this study shows that three key factors are helpful in the local government's effort to implement the national project, i.e. manufacturers' awareness, the understanding of the energy-efficiency technology, and the long-term macroeconomic benefits. In addition, encouraging the participation of financial institutions is especially useful for local governments to convince small-and-medium sized firms. These findings are beneficial for local implementation of green-manufacturing technology diffusion policies in China and have worldwide policy implication as well.

今年1月23日，北京青年报起诉新浪网侵犯著作权案在北京市海淀区人民法院开庭。新浪网未经北京青年报许可转载《我为何要公布公务员“收入真相”》等9篇文章。5月15日，海淀区人民法院作出一审判决，新浪网因侵权9名记者共计32447字和11张新闻图片被判赔偿18100元。