Over the past 20 years, the term “ecosystem” has become pervasive in discussions of strategy, both scholarly and applied. Its rise has mirrored an increasing interest and concern among both researchers and managers with interdependence across organizations and activities. This article presents a structuralist approach to conceptualizing the ecosystem construct. It presents a clear definition of the ecosystem construct, a grammar for characterizing ecosystem structure, and a characterization of the distinctive aspects of ecosystem strategy. This approach offers an explicit examination of the relationship among ecosystems and a host of alternative constructs (business models, platforms, coopetition, multisided markets, networks, technology systems, supply chains, value networks) that helps characterize where the ecosystem construct adds, and does not add, insight for the strategy literature.

建设富有韧性的数字创新生态系统是抵御外部风险冲击、推动区域创新发展数字转型的必由之路。本文以28个省市的数字创新生态系统为分析对象，通过指标评价方法测度其韧性，并使用fsQCA方法研究治理利基组态对区域数字创新生态系统韧性的影响。研究识别了导致高韧性的“知识-资源”驱动和“市场驱动”两种组态，以及导致低韧性的“资源主导”和“知识主导”两种组态。研究发现有助于数字创新生态及其治理理论的发展，也对制定区域数字创新生态系统发展政策制定具有启示意义。

建设富有韧性的数字创新生态系统是抵御外部风险冲击、推动区域创新发展数字转型的必由之路。本文以28个省市的数字创新生态系统为分析对象，通过指标评价方法测度其韧性，并使用fsQCA方法研究治理利基组态对区域数字创新生态系统韧性的影响。研究识别了导致高韧性的“知识-资源”驱动和“市场驱动”两种组态，以及导致低韧性的“资源主导”和“知识主导”两种组态。研究发现有助于数字创新生态及其治理理论的发展，也对制定区域数字创新生态系统发展政策制定具有启示意义。

基于直接传导机制、间接传导机制和异质性传导机制三个维度，利用文本挖掘的方法，以中国A股制造业上市公司为样本，阐述了智能化发展是否促进企业进行颠覆性创新，探讨两者之间的内在机理，并从实证方面检验了颠覆性创新在智能化发展和企业绩效之间的中介效应。研究发现，智能化发展显著提高了企业颠覆性创新水平，是新时代企业实现颠覆性创新的主要途径；智能化发展通过加大固定资产投资和优化人力资本结构的机制间接促进企业颠覆性创新；在考虑企业异质性特征时，发现国有企业、资本技术密集型企业智能化发展对颠覆性创新的影响更明显；最后，企业智能化发展可以通过颠覆性创新提高企业的绩效，助推企业高质量发展。研究结论为推动企业智能化发展、实现颠覆性创新提供了一条可行的路径。

A new round of industrial revolution with intelligent manufacturing as the core is sweeping across the world. As the starting point and primary goal of industry 4.0, intelligent manufacturing is the main direction of "made in China 2025", and disruptive innovation is an important way for Chinese manufacturing enterprises to gain core competence under the background of intelligent manufacturing. Therefore it is very crucial to study the relationship between intelligent development and disruptive innovation from the enterprise level. In order to comprehensively explore the relationship between intelligent development and disruptive innovation, this paper analyzes the impact mechanism of intelligent development on disruptive innovation of manufacturing enterprises, which is based on three dimensions of direct transmission mechanism, indirect transmission mechanism and heterogeneous transmission mechanism, so as to provide reference for intelligent development of enterprises and make up for the shortcomings of existing research. Taking China's A-share listed manufacturing companies from 2000 to 2017 as samples, this paper uses text mining method to construct indicators that are difficult to quantify, studies whether intelligent development promotes China’s A-share manufacturing listed companies’ disruptive innovation and discusses the internal mechanism between intelligent development and disruptive innovation. At the same time, disruptive innovation is divided into disruptive business model innovation and disruptive technological innovation, the purpose is to deeply understand the internal meaning of disruptive innovation. In further analysis, the econometric model is used to empirically test the intermediary effect of disruptive business model innovation and disruptive technological innovation between intelligent development and enterprise operating performance, getting through the transformation path of "intelligent development-disruptive innovation-enterprise high-quality development", and deeply understand the transformation mode of manufacturing enterprises in line with the background of intelligent manufacturing. It is found that intelligent development significantly improves disruptive business model innovation and disruptive technological innovation of manufacturing enterprises, which is the main way for enterprises to realize disruptive innovation in the new era. Intelligent development can indirectly promote enterprise disruptive business model innovation and disruptive technological innovation, and this mechanism is realized by increasing enterprise fixed asset investment and improving the level of human capital. Manufacturing enterprises can create good development conditions for enterprise disruptive innovation by increasing investment in intelligent infrastructure and introducing high-quality talents; When considering the characteristics of enterprise heterogeneity, the samples of listed companies are divided into two groups according to the characteristics of ownership and factor intensity, it is found that the intelligent development of state-owned enterprises, capital-intensive enterprises and technology-intensive enterprises has a more significant impact on disruptive innovation, while intelligent development of non-state-owned enterprises and labor-intensive enterprises have less influence on disruptive business model innovation and disruptive technological innovation. It can be seen that state-owned enterprises, capital-intensive enterprises and technology-intensive enterprises have obvious advantages in promoting disruptive innovation in the era of intelligent manufacturing; Finally, the development of enterprise intelligence can improve enterprise performance and boost the high-quality development of enterprises through disruptive business model innovation and disruptive technological innovation. The research conclusion enriches the theoretical framework of the relationship between intelligent development and enterprise disruptive innovation, and provides a feasible path for promoting enterprise intelligent development and realizing disruptive innovation.

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.

基于2003-2015年中国省级面板数据，使用DEA-Malmquist模型测算了中国制造业全要素生产率的变动，并实证检验了智能化对于全要素生产率的影响。Malmquist测算结果表明：中国制造业全要素生产率在研究期内年均增长8.2%，且技术进步贡献了主要的全要素生产率的增长；制造业全要素生产率的增长存在明显的区域异质性，西部地区增长最快，其次是东部地区和中部地区。实证结果表明：智能化显著促进了全要素生产率的增长，且智能化是通过促进技术进步增长的方式实现对全要素生产率的促进作用，智能化对制造业技术效率没有明显的促进作用；智能化显著促进了中西部地区制造业全要素生产率的增长，且对西部地区促进作用更大，但对东部地区没有显著的促进作用。

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.

建设创新生态系统并发挥共生效应是推动地区科技创新发展的首选战略。结合2007-2015年中国30个省市相关数据，利用共生测度模型计算我国区域创新生态系统共生度，并进一步建立静态和动态面板数据模型，实证分析区域创新生态系统共生与科技创新绩效间的关系。研究结果表明：我国区域创新生态系统共生度整体呈“U”型发展特征，东部地区远高于中西部地区，地区间差异较大且下降幅度尚显微弱；短期内创新生态系统共生对科技创新的促进作用相对较弱，共生单元的作用效果并不显著，而长期内创新生态系统共生的正向驱动效应明显放大，且共生单元呈负向抑制作用；地区科技创新的累积效应明显，共生基质、共生平台和共生环境始终对科技创新具有正向驱动作用，而共生网络的正向驱动效应均不明显。

Building the innovation ecosystem and playing a symbiotic role is the preferred strategy for promoting the development of regional sci-tech innovation. Combined with relevant data from 30 provinces in China from 2007 to 2015, the symbiosis level of China's regional innovation ecosystem using the symbiotic measurement model is measured, and the relationship between regional innovation ecosystem symbiosis and sci-tech innovation is empirically analyzed by establishing the static and dynamic panel data model. The results show that: the symbiosis degree of regional innovation ecosystem is generally characterized by "U", the eastern region is much higher than the central and western regions, the regional differences are large and the decline is still weak. In the short term, innovation ecosystem symbiosis has a relatively weak role in promoting sci-tech innovation, and the effect of symbiosis unit is not significant, in the long term, the positive driving effect of innovation ecosystem symbiosis is obviously amplified, and the symbiosis unit has a negative inhibitory effect on sci-tech innovation. The accumulative effects of sci-tech innovation are obvious, the symbiosis matrix, symbiosis platform, and symbiosis environment always have positive driving effects on sci-tech innovation, and the positive driving effects of symbiosis network is not obvious.

近年来，微创新是创新研究领域的热点，如何驱动企业微创新是相关研究亟需回答的问题。整合创新生态系统3个层面六大要素，运用模糊集定性比较分析（fsQCA）方法，以18个微创新案例为样本，探讨创新生态系统驱动企业微创新的复杂因果机制。结果发现：第一，单个创新生态系统要素并不构成企业高微创新的必要条件。第二，存在3条高微创新驱动路径，即机会识别主导下的用户驱动型、机会识别主导下的环境与用户参与驱动型，以及机会识别主导下的环境、组织学习与领先用户驱动型。此外，非高微创新驱动路径仅有一条，且与高微创新驱动路径存在非对称关系。第三，机会识别能力作为核心条件出现在高微创新的3个组态及非高微创新一个组态中，说明机会识别能力对企业微创新具有重要作用。

本研究基于生态位理论构建了区域创新生态系统生态位适宜度评价指标体系和评价模型，并对中国30个省市2009-2018共十年的区域创新生态系统进行评价。研究结果表明：⑴ 中国整体的创新生态位适宜度较低，但进化空间较大，发展趋势较好；⑵ 中国的创新引领地区和创新领先地区共涵盖20%的省市，其余为创新落后地区，创新生态系统发展呈现区域不均衡；⑶ 在区域分布方面，创新生态位适宜度呈现从东部到西部递减趋势。此外，采用GM（1,1）模型预测系统对2020-2024五年的生态位适宜度进行预测，研究结果表明：⑴ 2020-2024年，中国整体的创新生态位适宜度将有所提升；⑵ 在权重方面，2020-2024年，生境生态位将继续占据区域创新生态系统最重要的位置。

本研究基于生态位理论构建了区域创新生态系统生态位适宜度评价指标体系和评价模型，并对中国30个省市2009-2018共十年的区域创新生态系统进行评价。研究结果表明：⑴ 中国整体的创新生态位适宜度较低，但进化空间较大，发展趋势较好；⑵ 中国的创新引领地区和创新领先地区共涵盖20%的省市，其余为创新落后地区，创新生态系统发展呈现区域不均衡；⑶ 在区域分布方面，创新生态位适宜度呈现从东部到西部递减趋势。此外，采用GM（1,1）模型预测系统对2020-2024五年的生态位适宜度进行预测，研究结果表明：⑴ 2020-2024年，中国整体的创新生态位适宜度将有所提升；⑵ 在权重方面，2020-2024年，生境生态位将继续占据区域创新生态系统最重要的位置。