基于价值共创和要素集聚视角，采用文本挖掘方法，以2011-2019年沪深A股上市公司中的传统制造企业为样本，验证智能化转型是否提升了传统制造企业绩效，同时探讨成本粘性在智能化转型与传统制造企业绩效之间的中介效应。研究发现，智能化转型对传统制造企业的绩效水平具有显著的正向作用，且智能化转型能够通过降低成本粘性提升传统制造企业的绩效水平。当考虑企业异质性特征时，与资本密集型企业相比，劳动密集型企业的智能化转型更易降低成本粘性、实现企业绩效提升；与非国有企业相比，国有企业进行智能化转型对降低成本粘性、提升企业绩效的影响更明显。研究结论为推动我国传统制造企业智能化转型、改善企业成本管理提供理论借鉴。

Based on the perspective of value co-creation and element aggregation, this paper selects the A-share traditional manufacturing listed enterprises from 2011 to 2019 as empirical samples to verify whether intelligent transformation improves the performance of traditional manufacturing enterprises, and also discuss the moderating effect of cost stickiness through using the text mining methods. The empirical results show that, intelligent transformation has a significant positive impact on the performance of traditional manufacturing enterprises. That is, intelligent transformation of traditional manufacturing enterprises can achieve "intelligence" to win, and intelligent transformation can improve enterprise performance by reducing cost stickiness. Also, considering the heterogeneous characteristics of enterprises, compared with non-state-owned enterprises, intelligent transformation of State Owned Enterprises（SOEs）has a more obvious impact on reducing cost stickiness and improving enterprise performance; compared with capital-intensive manufacturing enterprises, intelligent transformation of labor-intensive manufacturing enterprises is also easier to reduce cost stickiness and achieve the improvement of enterprise performance. This paper provides the useful reference for promoting intelligent transformation of traditional manufacturing enterprises and improving enterprise cost management.

工业革命4.0开启了智能化生产时代，如何持续推进智能化大发展成为经济高质量发展的重要命题。利用熵权法测算了2009-2019年我国制造业智能化指数，运用固定效应模型、门槛效应模型、系统GMM以及滞后一期工具变量法考察创新能力与劳动力成本对制造业智能化水平的影响及机制。研究结果表明，创新能力、劳动力成本对制造业智能化转型均有促进作用。创新能力与中、高技能劳动力成本的交互显著提升了制造业智能化水平，其中与高技能劳动力成本交互的正向作用具有时滞性。进一步的区域异质性检验表明，东部地区中高技能劳动力成本提高会增强创新的制造业智能化转型效应，低技能劳动力成本的增强效应不显著；中部地区低、中、高三种技能劳动力成本提高均会有上述增强效应；西部地区不同技能劳动力成本的上述增强效应均不显著；以上意味着东部地区的传导机制更多是智能技术研发，中部地区的传导机制是技术研发与技术应用兼有，西部地区的传导机制均尚未激活。

This paper uses the entropy weight method to measure the intelligence index of China’s manufacturing industry from 2009 to 2019, and uses the fixed effect model, the threshold effect model, the system GMM and instrumental variable method to examine the impact mechanism of innovation capacity and labor costs on the level of manufacturing intelligentization. The results show that innovation capacity and labor cost both promote the intelligent transformation of manufacturing industry. The interaction between innovation capacity and the cost of medium and high-skilled labor has a significant positive effect on the improvement of the level of manufacturing intelligence, and the positive effect of the interaction with the cost of high-skilled labor has a time lag. Furthermore, regional heterogeneity shows that the increase in the cost of medium and high-skilled labor in the eastern region will enhance the intelligent transformation effect of innovation in manufacturing, while the enhancement effect of the cost of low-skilled labor is not significant. the increase in labor costs of low-, medium-, and high-skilled labor in the central region will have the above-mentioned enhancement effect, and in the western region are both not significant. The transmission mechanism in the eastern region is more intelligent technology research and development, and the transmission mechanism in the central region is both technology research and development as well as technology application, while the conduction mechanisms in the western region has not yet activated.

为揭示信息化对制造企业智能化转型影响的黑箱，基于中石化智能化转型案例与文献分析，从认知逻辑与行为逻辑双视角，提出信息化战略认知与信息化建设行为分别通过知识偏好、技术创新对制造企业智能化转型产生积极影响的理论假设。结合逐步回归法与Bootstrap法综合验证了其完全中介效应的存在，并通过调节作用检验证实了技术人才丰富的制造企业其信息化建设行为对技术创新的促进作用更显著；通过稳健性检验一方面证实了结论可靠性，另一方面也表明机械设备制造企业技术创新对智能化转型的作用更显著。因此，制造企业尤其是具有高技术要求的制造企业，需重视技术人才培养，通过信息化发展促进企业形成知识偏好，加强技术创新，推进智能化转型。

为破解开放式网络环境下制造企业服务创新困境，基于社会网络理论和组织搜索理论，采用层次回归分析法实证检验网络位置对制造企业服务创新绩效的作用机制。通过对313家中国制造企业的调研数据分析发现：网络位置对制造企业服务创新绩效有显著正向影响；跨界搜索在网络位置与制造企业服务创新绩效之间起部分中介作用；吸收能力不仅在跨界搜索与制造企业服务创新绩效的关系中起调节作用，而且正向调节了跨界搜索在网络位置与制造企业服务创新绩效间的中介作用。研究结论拓展了网络位置影响效果研究，进一步澄清了网络位置对制造企业服务创新绩效影响的过程机制和边界条件，对制造企业利用跨界搜索突破资源局限，快速推进服务创新具有一定启示。

通过构建我国制造企业技术能力与发展模式之间关系的理论模型，利用面板probit计量模型分析我国智能制造试点企业，探讨了我国制造企业技术能力与智能化发展模式之间的内在联系。研究发现，我国智能制造企业大体可以分为两种发展模式：并行模式与递进模式，其中递进模式，可分为网络递进模式与智能递进模式。在并行模式与递进模式之间，企业随着其技术能力的提高，会更倾向于选择并行模式；在智能递进模式和网络递进模式之间，企业随着其技术基础能力的提高，将倾向于选择智能递进模式，随着技术创新能力的提高，将倾向于选择网络递进模式；政策和融资的支持促进了企业对模式选择的分化；模式选择在企业性质、行业特征、地域分布上显现出一定的异质性。

The networked and intelligent manufacturing industry is an important part of China's new round of scientific and technological revolution, and it is the main path for the transformation and upgrading of the manufacturing industry. In the past 20 years, China as a major manufacturing country, has significantly improved its manufacturing scale, manufacturing quality and international competitiveness, and even surpassed developed economies in some fields. At this stage, the primary goal of China's economic development strategy is still industrialization, especially industrial intelligence with intelligent manufacturing as the core. Under the new wave of technology, new technologies have had a profound and significant impact on manufacturing process technology, production methods, operation mechanisms, organizational processes, management models, and business models, which has made China's manufacturing industry change from traditional manufacturing to the process of accelerating the transformation of the modern manufacturing industry, it can no longer stick to the intelligent development paradigm of developed economies, walk out of the intelligent development path different from developed countries, gradually change from a chaser to a leader, and realize the transformation from a manufacturing power to a manufacturing power. The transformation of intelligent manufacturing seeks to lead the transformation of the global manufacturing industry. Due to the status quo of China's intelligent manufacturing technology and industrial segmentation, the development of industrial intelligence has been greatly inhibited. Manufacturing enterprises in different regions and industries have different levels of technical capabilities, and the external environment faced by enterprises is also different. intelligentization. Therefore, in order to achieve intelligent transformation and upgrading, manufacturing enterprises need to formulate an appropriate intelligent development model according to their actual technical level.By constructing a theoretical framework of the relationship between the technical capabilities and development models of intelligent manufacturing enterprises, the development model of China's intelligent manufacturing enterprises is analyzed, and on this basis, corresponding theoretical models and panel probit measurement models are constructed. of listed companies, and deeply explored the inherent relationship between the technical capabilities and development models of China's smart manufacturing enterprises. The results show that Chinese manufacturing enterprises are still in the early stage of intelligent transformation, and intelligent manufacturing enterprises can be roughly divided into three development modes: parallel mode (networked and intelligent development at the same time), network progressive mode (prioritized network development), intelligent Progressive mode (prioritizing intelligent development). The technical capability of an intelligent manufacturing enterprise has a significant impact on the choice of its development model. The study found that between the parallel mode and the progressive mode, with the improvement of their technical capabilities, enterprises will be more inclined to choose the parallel mode; it will tend to choose the intelligent progressive model, with the improvement of its technological innovation ability, and it will tend to choose the network progressive model; the support of policies and financing promotes the differentiation of enterprises' choice of models, and policy support and financing capabilities will The selection of the parallel mode has a positive regulatory effect, and the selection of the progressive mode has a negative regulatory effect. In the mode selection of network progression and intelligent progression, policy support and financing capacity will have a positive regulatory effect on network progression and a negative regulatory effect on intelligent progression. The model selection conforms to the above characteristics in terms of enterprise nature, industry characteristics, and geographical distribution, but shows a certain degree of heterogeneity. Among them, non-state-owned enterprises have a more significant impact on technological innovation capabilities, and labor-intensive enterprises are more inclined to choose network progressive mode, the eastern region is more inclined to choose the parallel mode.

在新一轮科技革命浪潮下，企业组建创新联合体成为大势所趋。合作创新网络中的多元化技术已经成为企业创新的关键外部资源，但关于创新网络技术多元化如何影响企业创新绩效的研究仍然缺乏，且现有研究往往忽略企业内外部资源的不同组合对企业创新绩效可能产生的差异性影响。文章融合社会网络理论、知识基础理论与动态能力理论，依据信息技术产业上市公司联合申请专利数据构建合作创新网络，采用面板数据随机效应负二项回归法，从个体网络视角分析创新网络技术多元化影响企业创新绩效的权变因素与内在机制，检验了一个被中介的调节效应模型。研究结果表明：创新网络技术多元化正向影响企业创新绩效；企业知识基础深度正向调节创新网络技术多元化与企业创新绩效的关系，而企业知识基础宽度的调节效应并不显著；企业知识基础深度对创新网络技术多元化与企业创新绩效关系的调节通过吸收能力的中介实现。研究结论对企业技术创新具有重要的理论及现实指导意义。

Under the new wave of the Science and Technology Revolution, the formation of innovative consortiums among firms is a general trend. Diverse technologies in cooperative innovation networks have become key external resources for firm innovation. However, empirical studies about how technological diversity of innovation network influences firm’s innovation performance are still lacking. Besides, existing studies often ignore the possible different influences from different combinations of firm’s internal and external resources on the firm’s innovation performance. Combining the theories of social network, knowledge base and dynamic capability, this article constructed cooperative innovation networks with joint patent application data of listed companies in the information technology industry, used random-effect negative binomial regression analytical method of panel data, analyzed the contingency factor and inner mechanism of how technological diversity of innovation network influences firm’s innovation performance, and finally examined a mediated moderation model. The results show that technological diversity of innovation network positively affects firm’s innovation performance; firm’s knowledge depth positively moderates the relationships between technological diversity of innovation network and firm’s innovation performance, while the moderation effect of firm’s knowledge width is not significant; the moderation effect of firm’s knowledge depth on the relationships between technological diversity of innovation network and firm’s innovation performance is mediated by absorptive capacity. The conclusions of this study are of great theoretical and practical guiding significance to firms’ technological innovation.

以2009~2016年沪深A股上市公司为样本，实证检验了我国上市公司创新活动（研发投入和专利产出）是否存在社会网络同群效应，并考察了企业社会网络特征对同群效应强度的影响。研究发现：同群企业创新能够显著正向影响企业创新，企业创新活动存在社会网络同群效应；在排除地区行业同群效应的干扰后，企业创新活动的社会网络同群效应依旧显著存在；制度环境对企业创新活动的社会网络同群效应具有负向调节作用，在制度环境欠佳的地区，企业创新活动表现出更强烈的社会网络同群效应；企业所处的社会网络位置越核心、中心度越高、联结数量越多、网络影响力越大，研发投入和专利产出的社会网络同群差异越小，企业创新活动的同群效应越强。

Based on a sample of listed companies in China during the period 2009 to 2016, this study empirically tests whether corporate innovation activities (both R&D investment and patent output) have social network peer effect, and examines the impact of corporate social network characteristic on peer effect intensity. The results show that corporate innovation is positively affected by the peer firms’ innovation in the social network, and corporate innovation has social network peer effect. After excluding the peer effect in the same region and industry, social network peer effect of corporate innovation still exists significantly. The institutional environment has a negative moderating effect on the social network peer effect of corporate innovation. Corporate innovation activities have a stronger social network peer effect in areas with poor institutional environment. The corporate network centrality is negatively related to the peer difference of R&D investment and patent output, and positively related to the peer effect intensity of corporate innovation.