我国不断涌现的创新成果引发了国内外对“中国式创新”的广泛关注。为明晰“中国式创新”的内涵和特质，通过系统梳理其他典型国家的创新模式与情境差异，以及中国企业的阶段性创新实践后发现，“中国式创新”体现为中国企业在动态情境下产生的一系列创新模式的进阶与组合，而引致“中国式创新”的本质因素则是中国的独特情境；此外，对中国情境的深入挖掘和理论化是“中国式创新”未来研究的出路所在。

The emergence of many remarkable innovations in China attracted wide attention to “Chinese-style innovation” both at home and abroad. To clarify the connotation and characteristics of “Chinese-style innovation”, this study compared the innovation patterns, context and innovative practices of Chinese enterprises in other typical countries, and it was found that “Chinese-style innovation” represents a series of innovative patterns’ combination generated by Chinese enterprises in a dynamic environment. Furthermore, the essential factor that leads to “Chinese-style innovation” was China’s unique context. So the suggestion is that deeply exploring and theorization on Chinese context is the way to furthering the relevant research.

基于2002-2017年中国与78个国家（地区）制造业贸易的面板数据，从“量”和“质”层面实证考察进口竞争对中国制造业高质量发展的影响，并引入创新作为中介变量，解构进口竞争对中国制造业高质量发展的传导路径。研究发现：进口竞争总体上抑制了中国制造业高质量发展，创新在二者的关系中发挥相应的中介作用；发达经济体的进口竞争促进了中国制造业高质量发展，但创新在“量”和“质”层面均不存在中介效应；发展中经济体的进口竞争对中国制造业高质量发展有负向影响，创新在“量”的层面表现为部分中介，在“质”的层面表现为完全中介；转型经济体的进口竞争同样对中国制造业高质量发展有负向影响，创新在“量”和“质”层面均发挥部分中介效应。

从研究方法和分析技术两个层面分析已有QCA研究中存在的问题，并提供解决思路。在研究方法层面，从理论目标、研究问题和实现途径3个方面阐明了QCA方法与定量研究方法的差异化定位；在分析技术层面，详细阐述了QCA方法应用全过程（3个阶段）的操作性策略。最后，指出QCA方法在组织与管理研究中进一步优化应用的未来方向，即提高透明性、纳入时序性和尝试混合方法。

This paper attempts to provide solutions to existing problems in Qualitative comparative analysis (QCA) research from two aspects of the research approach and analysis technique. At the level of research approach, the differences between the QCA method and quantitative research method are expounded from three aspects: theoretical objectives, research questions, and realization approaches. At the level of analysis technique, the operational strategy of the whole application process (three stages) of the QCA method is expounded in detail. Finally, three directions of further optimizing the application of the QCA methods in management and organization research are proposed, which are improving transparency, adding temporality, and trying mixed methods.

在数字经济蓬勃发展的同时，中国劳动收入份额出现止降转升的新变化。本文基于沪深A股上市公司微观数据，考察了数字化对劳动收入份额的影响及其作用机制。研究发现：劳动收入份额随数字化程度的提升而呈向下的“倒U型”关系；机制检验表明，数字化程度对技能结构的“倒U型”影响是数字化影响劳动收入份额的重要路径；进一步研究发现，现阶段上市公司数字化程度处于“倒U型”曲线的左侧，在未来一段时间内数字化程度提升仍将有助于改善劳资分配关系；不同要素密集度、所有制的上市公司数字化程度对劳动收入份额的“倒U型”影响具有显著差异。为持续提升劳动收入份额，政府应继续加速推进与数字化相关的基础设施建设，加大对企业数字化转型的扶持力度；企业应定期组织职工参与数字化培训，推动劳动者技能结构升级。

In recent years, with the rapid development of new technologies such as big data, artificial intelligence and cloud computing, the digital economy has deeply integrated with the real economy. The digital economy has become a new wave, a new driving force and a new engine leading economic development. With the vigorous development of digital economy, China’s income distribution pattern has also seen new changes. In recent years, the labor income share has shown a new trend of turning from declining to rising, and the labor-capital distribution relationship has improved. Therefore, this paper puts forward two important questions: Is there a significant relationship between the new change in China’s labor income share in recent years and the improvement of the degree of digitalization? What channels does digitalization promote the increase of labor income share?This paper uses the micro level data of A-share listed companies in Shanghai and Shenzhen in China, adopts the method of combining text analysis and manual judgment, and constructs indicators to measure the degree of enterprise digitalization from the two dimensions of digital intangible assets and digital keywords. The research finds that the labor income share presents an “inverted U-shaped” downward relationship with the increase of digitization degree. The mechanism test shows that the “inverted U-shaped” effect of digitalization on skill structure is an important path for digitalization to affect labor income share. Further research shows that the digitalization degree of listed companies at the present stage is on the left side of the “inverted U-shaped” curve, and the improvement of digitalization degree will still help to improve labor distribution relations in the future. The “inverted U-shaped” effect of different factor intensities and ownership of listed companies on labor income share is significant. The innovation of this paper mainly includes the following two aspects: First, this paper finds that booming digitalization is promoting the increase of labor income share, which provides important evidence to explain the new change of the increase of labor income share in recent years. Moreover, it is expected that in the future period of time, the improvement of digitalization degree will continue to drive the rise of labor income share. Second, from the perspective of skill structure, this paper discusses the important mechanism of the influence of digitalization on the “inverted U-shaped” labor income share. Accelerating the upgrading of labor skill structure will help to continuously increase the labor income share, and provide feasible solutions for the continuous improvement of labor distribution relations. This paper recommends that the government should continue to accelerate the construction of digital-related infrastructure and increase the support for enterprises’ digital transformation. Enterprises should regularly organize employees to participate in digital training and promote the upgrading of workers’ skill structure.

The various methodological techniques that fall under the umbrella description of qualitative comparative analysis (QCA) are increasingly popular for modeling causal complexity and necessary or sufficient conditions in medium-N settings. Because QCA methods are not designed as statistical techniques, however, there is no way to assess the probability that the patterns they uncover are the result of chance. Moreover, the implications of the multiple hypothesis tests inherent in these techniques for the false positive rate of the results are not widely understood. This article fills both gaps by tailoring a simple permutation test to the needs of QCA users and adjusting the Type I error rate of the test to take into account the multiple hypothesis tests inherent in QCA. An empirical application–a reexamination of a study of protest-movement success in the Arab Spring–highlights the need for such a test by showing that even very strong QCA results may plausibly be the result of chance.