科技创新是推动我国产业结构升级和生产力整体跃升的重要战略引擎，已成为抢占未来科技竞争和经济发展制高点的关键要素。以31个省份为案例，基于组态视角，运用fsQCA方法探究科技创新要素与产业升级的协同效应以及各因素间的联动关系，剖析影响各省份产业升级差异的多重并发因果关系与多元路径。研究发现：高产业升级指数的驱动路径有3条，可划分为成果转化-科技资金主导和环境规制-科技人力主导两种类型，案例多集中于东部沿海地区；非高产业升级指数的驱动路径有6条，组态多样且与高指数路径相比具有非对称性，该路径中科技创新环境与科技人力投入存在替代作用，案例分布均匀且集中于中西部省份。研究结果不仅基于组态思维丰富了科技创新与产业升级领域的学术研究，而且为各省份制定实操性强的科技创新驱动产业升级相关政策提供了有益参考。

   As a strategic engine for the upgrading of China′s industrial structure and the improvement of its overall productivity, technological innovation has become the key to controlling the strategic commanding heights for future technological and economic development. In recent years, as agreement has been reached within both the academic community and the industry on the important role of technological innovation in driving industrial upgrading, a succession of corresponding policies have been formulated by provinces to increase innovation capabilities and optimize industrial upgrading. In practice, however, opinions were quite divided on which factors should be prioritized in policy making and which approaches are more effective. Therefore, it has become an important question in this field to explore the synergy between technological innovation factors and industrial upgrading, as well as the linkage between these factors, and to analyze the varied effects of these factors and their diverse approaches to driving industrial upgrading.
    Most previous studies used traditional measurement to discuss the "net effect" of an individual factor, but fail to consider the "synergistic effect" among multiple variables. Some studies analyzed the linear relationship between technological innovation and industrial upgrading by simply measuring technological innovation by scientific and technological achievements in addition to taking into account other regulatory variables. They failed to consider the complexity of the internal structure of technological innovation and thus cannot fully explain the multiple causality and asymmetry of technological innovations driving industrial upgrading in practice. Actually, as all social phenomena are featured by complex causality, they are not the making of a single factor, but of multiple factors. Industrial upgrading is enabled by multiple factors such as HR investment, financial investment and innovation environment, etc. Different combinations of these factors may contribute to different results, and the relationship between the result and a single factor is not completely symmetrical. Thus, prior to answering the question of "how technological innovations drive industrial upgrading", an investigation should be made into the linkage between these factors from the perspective of configuration, for which Fuzzy-Set Qualitative Comparative Analysis (fsQCA) is considered to be an effective method. Hence, the fsQCA method is adopted in this article to explore the multiple concurrent causality and the diverse approaches to technological innovations driving industrial upgrading, based on which to answer the following questions: what are the driving factors and core forces for driving industrial upgrading with technological innovation? Which configuration can effectively contribute to high industrial upgrading index? What are the causes for low industrial upgrading index? How do these approaches interact with each other?
    According to existing findings, the factors of technological innovation driving industrial upgrading can be roughly summarized as innovation input, innovation output and innovation environment. Besides, taking into consideration the impact of regulations on technological innovation environment and industrial upgrading, we determine six factors as conditional variables, namely, financial and HR input, technological achievements and achievement marketization, technological innovation environment and innovation environment regulations. Then, with 31 Chinese provinces as the cases, we analyzed the multiple causality and multiple approaches of technological innovation driving industrial upgrading, in an effort to open the "black box" of the operation mechanism of technological innovations driving industrial upgrading. Finally, we summarized the successful experiences of outstanding provinces and lessons of low-achieving provinces, which can serve as to useful references for provinces to formulate policies according to their local conditions.
   We found the following results: a. the core factors of technological innovations driving industrial upgrading include financial and HR input, technological achievement marketization and environmental regulations; b. There are three effective approaches to high industrial upgrading index, which can be divided into two categories, one oriented towards technological achievement marketization & technological funding, and the other towards innovation environment regulations and HR. Among them, the first category of approaches are the most adopted, mostly by eastern coastal provinces, whose core drivers include technological achievement output, technological achievement marketization, and technological financial input. The second category of approaches are taken by only a few western provinces, where environmental regulations and technological HR input have a positive effect on industrial upgrading. Cases of low industrial upgrading index are mainly central and western provinces, who take six approaches to driving industrial upgrading with technological innovation, showing that the causes for industrial upgrading index are varied and complicated. Besides, in central and western provinces with low industrial upgrading index, the technological innovation environment and HR input have a certain substitute effect. c. Approaches leading to low industrial upgrading index is not the opposites of those leading to low industrial upgrading index, evidencing the asymmetry of the empirical results of qualitative comparative analysis. d. Different from the traditional way of analyzing individual factors, the configuration perspective can be taken to explore the different approaches formed by the combination of antecedent variables contributing to outcome variables, showing that causes of high or low indexes are featured by multiple concurrencies. 
   In this article, we applied the fsQCA method into the research of industrial upgrading driven by technological innovation, providing a holistic perspective into the causal relationship between the factors in this regard, thus broadening the horizon for research in the fields of technological innovation and industrial upgrading. In addition, we explored the synergistic effects of technological innovation factors and industrial upgrading, as well as the linkage between these factors, which is a gap in existing studies. We also analyzed the differences in the impact of these factors on industrial upgrading and their diverse approaches to driving industrial upgrading, providing useful references for provinces to formulate practical policies on technological innovation.