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The Effect of Artificial Intelligence Technology on Carbon Emissions

Xue Fei,Liu Jiaqi,Fu Yamei

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 1-9. https://doi.org/10.6049/kjjbydc.2022030149

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To actively address the issue of climate change, China has proposed a vision of "emission peak and carbon neutrality". Achieving "emission peak and carbon neutrality" is a comprehensive and profound economic and social systemic change that requires the joint efforts of the whole society. As a strategic technology for technological revolution and industrial change, Artificial Intelligence (AI) technologies will play an important role in addressing climate change and bring significant opportunities for low-carbon development. The process of achieving the "double carbon goal" is essentially a path of transformation to technology-intensive industry. However, the relationship between AI technologies and carbon emissions has been relatively under-discussed in academia compared to the much attention at the policy level and the flourishing development at the practical level. In particular, AI technologies may exhibit a more complex dual effect on carbon emissions. In view of this, this paper answers the question of whether AI technology can enable carbon neutrality and help reduce CO2 emissions. What are the mechanisms of AI technologies affecting carbon emissions? Are there any regional differences in the effect of AI technologies on carbon emissions? The purpose of this paper is to provide empirical evidence for the carbon reduction effect of AI technologies and to provide useful policy insights for achieving the goal of "double carbon".#br#In terms of theoretical research, this paper believes that the impact of AI technologies on carbon emissions may have a dual effect.On one hand, AI can increase total carbon emissions through direct energy consumption.At the same time, AI technology on carbon emissions may have a rebound effect.In addition, AI technologies has scale effect on economic growth, which will lead to the increase of total regional carbon emissions. On the other hand, AI technology can reduce carbon emissions by assisting decision-making, reshaping production and life styles, and facilitating low-carbon technological innovation.First, it can help reduce carbon emissions by assisting decision-making.Second, it can drive changes in production and consumption patterns to reduce carbon emissions.Third, AI reduces carbon emissions by enabling low-carbon technology innovation.To sum up, the relationship between AI technologies and carbon emissions is not a simple linear relationship, but depends on the combined effect of the above dual effects.In terms of influence mechanism, the effect of AI technologies on carbon emissions is mainly reflected in energy utilization efficiency.#br#This paper analyzes the effects, mechanisms and differences of AI technology on carbon emissions by manually collating AI patent data as a measure of AI technology, using panel data from 30 provinces in China from 2006 to 2019 as a research sample. The empirical results show that the effect of AI technology on carbon emissions shows an "inverted U-shaped" relationship at the national level as a whole. It means when the level of AI technology reaches a certain threshold, its carbon emission reduction effect gradually becomes prominent, and the robustness test results also reinforce this conclusion. The results of the intermediate effect test show that the effect of AI technology on carbon emissions is mainly achieved by affecting energy use efficiency. The heterogeneity analysis shows that there is a significant regional difference in the impact of AI technology on carbon emissions, with a significant "inverted U-shaped" relationship between AI technology and carbon emissions in the eastern and western regions. In the central region, AI technology has not achieved carbon emission reduction, but had a significant contribution to carbon emissions.#br#The marginal contributions of this paper are as follows. First, from the perspective of research, this paper examines the effect of AI technology on carbon emissions in a more systematic way from the perspective of AI technology for the first time. Second, in terms of the research methodology, AI patent data are collected manually to measure the level of AI technology in each region, and a panel semi-parametric model and a nonlinear mediated effects model are used. Third, from the research findings, it is found that there is an "inverted U-shaped" relationship between AI technology and carbon emissions, and there is regional heterogeneity in the effect of AI. This provides empirical support for the development of differentiated AI carbon emission reduction strategies.#br#

Xue Fei,Liu Jiaqi,Fu Yamei. The Effect of Artificial Intelligence Technology on Carbon Emissions[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 1-9., doi: 10.6049/kjjbydc.2022030149.

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Why Pretend to Start a Business? The Formation Mechanism of Symbolic Entrepreneurship:An Exploratory Study Based on Grounded Theory

Liu Lihua,Wang Bingcheng

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 10-18. https://doi.org/10.6049/kjjbydc.2021110779

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With more people starting their own business, the phenomenon of "pretending to start a business" is also growing. This phenomenon doesn't reflect the basic characteristics of entrepreneurship such as innovation, adventure, and value creation, and wastes a lot of social and policy resources. This kind of entrepreneurship is called symbolic entrepreneurship in this study. Drawing on the research results of symbolic behavior, this study believes that symbolic entrepreneurship is a behavior choice driven by the entrepreneurial behavior′s symbolic significance which is essentially different from substantive entrepreneurship for creating value. Unfortunately, existing studies have focused on substantive entrepreneurial activities, and the relevant results can′t effectively explain the various forms of symbolic entrepreneurship in practice. There is a lack of in-depth discussion on the specific types, formation paths, and mechanisms of symbolic entrepreneurship.#br#To deeply understand the formation mechanism of symbolic entrepreneurship, this paper adopts an exploratory multiple-case study on 13 symbolic start-ups. Through the open coding of the main analysis data, 40 initial categories are summarized. Then, the initial categories are condensed into 11 main categories by axial coding. Finally, three paths of symbolic entrepreneurship are summarized according to the logical relationship of the main categories, and the formation mechanism of symbolic entrepreneurship is defined as the core category in the selective coding stage. According to the different external incentives and motives, symbolic entrepreneurship can be divided into three types: infectious entrepreneurship, strategic entrepreneurship and performance entrepreneurship.#br#Infectious entrepreneurship refers to the imitation behavior to repair the negative emotions generated by the entrepreneurial stimulation of partners. The entrepreneurial actions of partners trigger individual psychological comparison, awaken unhealthy emotions such as envy and jealousy, and cause the loss of psychological resources. To eliminate or alleviate psychological imbalance, individuals imitate partners' entrepreneurial behaviors. That is, the motivation of infectious entrepreneurship stems from the negative emotions aroused by partners' entrepreneurship, rather than the commercial value of entrepreneurial opportunities. Its entrepreneurial purpose is to show self-ability and social status through entrepreneurial behavior, adjust the relative position between itself and the comparison object, and rebuild a new psychological balance. In essence, it is a psychological resource recovery measure taken when psychological resources are lost.#br#Strategic entrepreneurship is an arbitrage behavior that uses the identity of entrepreneurs due to the information asymmetry between entrepreneurs and the government. Because of incomplete information and high supervision cost, the government cannot comprehensively, accurately and timely judge the actual process and expected effect of entrepreneurship, and usually determines the support strength based on the information provided by entrepreneurs. As a result, some individuals have the motivation to make an adverse selection by using information advantage. Driven by the arbitrage motivation, some individuals take entrepreneurship as a strategic means to obtain various policy "dividends" through the organizational form and behavior consistent with the institutional norms.#br#Performance entrepreneurship is an impression management behavior to meet social norms. In some regions or groups, the long-term commercial tradition or typical demonstration effect of entrepreneurship has promoted the formation of a cultural atmosphere highly recognized for entrepreneurship, which forms a generally recognized value orientation and social preference for entrepreneurial activities. Individuals have pressure to keep consistent with group values, traditional customs and public expectations. To obtain social recognition, individuals have the motivation to uphold their self-images and meet the expectations of the society for their role. Therefore, strategic entrepreneurship is a kind of resource conservation behavior to deal with external pressure and avoid the loss of psychological resources.#br#Based on social comparison theory information asymmetry theory, and impression management theory, this study analyzes the differences of three symbolic entrepreneurship in external incentives, entrepreneurial motivation and theoretical basis. It should be noted that the motivation formation of the three types of entrepreneurial behavior is not a single incentive, but a complex process of the joint action of multiple factors such as external environment, social network, and individual psychological characteristics. The main basis of classification is the difference between leading inducement and leading motivation.#br#This study defines the research boundary between symbolic entrepreneurship and substantive entrepreneurship from the perspective of symbolic and substantive significance of entrepreneurial behavior and analyzes the differences between them in entrepreneurial purpose, driving factors, behavioral characteristics and entrepreneurs' attitudes. In addition, it explains "pretending to start a business " from the social construction significance brought by entrepreneurial behavior. The study helps to expand the research scope of entrepreneurial typology and enrich the research on entrepreneurial motivation.#br#

Liu Lihua,Wang Bingcheng. Why Pretend to Start a Business? The Formation Mechanism of Symbolic Entrepreneurship:An Exploratory Study Based on Grounded Theory[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 10-18., doi: 10.6049/kjjbydc.2021110779.

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What Kind of Digital Innovation Ecosystem Improves Regional Innovation Performance：An Analysis Based on NCA and QCA

Lin Yan,Lu Junyao

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 19-28. https://doi.org/10.6049/kjjbydc.2021110583

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It is an important path for China to enhance its digital innovation capability and participate in international competition by strengthening the construction of digital innovation ecosystem and improving regional innovation performance. However, the current theoretical research on the digital innovation ecosystem stays in the stage of framework construction, the research results are scattered and there is little research on the relationship between the element coupling of the digital innovation ecosystem and the regional innovation performance. Therefore, this paper first defines the connotation of the digital innovation ecosystem, studies the constituent elements of the system, and analyzes the relationship between each element and innovation performance. Taking 31 provinces and cities in China as the research object, this paper uses NCA method to explore if and to what extent a single element of the system is a necessary condition to improve regional innovation performance. From the perspective of configuration, this paper uses QCA method to explore the complex impact of digital innovation ecosystem on regional innovation performance, and reveals the multiple paths and mechanisms of system element coupling to improve regional innovation performance.#br#This paper believes that the digital innovation ecosystem is a complex system of coexistence between different innovation subjects and innovation environments in a region, relying on digital technology to achieve a new combination of digital resources and non-digital resources to create new products or services, it mainly includes digital enterprises, governments, universities and scientific research institutions, etc., while the innovation environment consists of digital innovation infrastructure, digital talents and financial services. On the basis of analyzing the relationship between various elements and innovation performance, the six elements involved in the digital innovation ecosystem, namely digital enterprises, governments, universities and scientific research institutions, digital innovation infrastructure, digital talents and financial services, are regarded as the antecedent variable, regional innovation performance as the outcome variable, together with 31 provinces and cities in China as samples. Since the impact of system element input on regional innovation performance has a certain time lag effect, this paper sets the lag period to two years, selects the latest available data, that is, the antecedent variable data in 2019 and the outcome variable data in 2021, NCA necessity analysis is carried out, and fsQCA is used to conduct element configuration research.#br#The results show that digital enterprises, governments, universities and scientific research institutions, digital innovation infrastructure, digital talents and financial services are the key elements of the digital innovation ecosystem, but a single element is not a necessary condition for improving regional innovation performance. In addition, four element configurations can improve regional innovation performance, and the digital innovation ecosystems are classified into the'government guidance, intelligence gathering' type, the ‘enterprise development, environmental support' type, thr 'diversified subjects, comprehensive development' type, and 'enterprise-led, capital-driven' type. It is suggested that each region should adapt to local conditions, select a suitable digital innovation ecosystem and cultivate new drivers of regional innovation to promote the new development of digital China.#br#The research conclusions of this paper provide a more detailed explanation for exploring the relationship between digital innovation ecosystem and regional innovation performance. It enriches the research framework of digital innovation ecosystem, provides new ideas for follow-up research, and inspiration for management practice. First, local governments should give full play to their guiding role, strengthen the construction and optimization of the elements of the digital innovation ecosystem, improve the system's radiation capability, and play a positive role in regional innovation performance. Second, local governments should pay attention to the combination and matching of multiple elements of the digital innovation ecosystem, and from an overall perspective, formulate targeted policies to promote the coordinated development of elements and improve regional innovation performance. Finally, local governments should choose from four systems according to their own conditions and resource endowment:'government guidance, intelligence gathering', 'enterprise development, environmental support', 'diversified subjects, comprehensive development', and 'enterprise-led, capital-driven' system types, select a digital innovation ecosystem suitable for development, formulate relevant policies, enhance regional innovation capabilities, and accelerate the construction of an innovative country.#br#

Lin Yan,Lu Junyao. What Kind of Digital Innovation Ecosystem Improves Regional Innovation Performance：An Analysis Based on NCA and QCA[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 19-28., doi: 10.6049/kjjbydc.2021110583.

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The Measurement and Spatial Pattern of Digital Economy Development:A Case of 19 National-level Urban Agglomerations

Lian Ganghui,Xu Aiting,Wang Wenpu

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 29-39. https://doi.org/10.6049/kjjbydc.2021120649

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The Outline of the 14th Five-Year Plan (2021-2025) for National Economic and Social Development and Vision 2035 of the People's Republic of China has clearly planned and laid out 19 national-level urban agglomerations, striving to form a strategic urbanization pattern of "two horizontal and three vertical". As a dynamic core in the regional economic development pattern, urban agglomeration can optimize resource allocation, attract agglomeration, and diffuse radiation in a larger area, and it has become a strategic support for the coordinated development of regional economy in China. At the same time, the digital economy, as the most promising field in China's current economic development, continues to extend the depth and breadth of integration with various fields of economic and social development. According to the Blue Book of China's Urban Digital Economy Index (2021), the top ten cities in the digital economy index in 2021 are mainly located in the more developed Yangtze River Delta and Pearl River Delta Bay urban agglomerations. The unbalanced development of the digital economy in urban agglomerations has become an important incentive to widen the economic development gap between regions. In order to explore the determinants of accelerating the bridging of the digital economy divide in urban agglomerations, shaping China's regional economic growth poles and promoting coordinated regional development, this paper examines the digital economy development trends, regional differences and spatial patterns of urban agglomerations by measuring the digital economy development levels of 19 national urban agglomerations laid out in the 14th Five-Year Plan.#br#A series of achievements have emerged in the measurement of the digital economy scale. In terms of measurement methods, the existing research can be roughly classified into three categories: value-added method, index method and satellite account method. Comparatively speaking, since the digital economy is a kind of convergence economy, the efficiency improvement of traditional industries caused by the penetration and synergy of digital technology cannot be directly measured by the industry GDP accounting method. Simultaneously, the compilation of digital economy satellite accounts is still in the theoretical stage, with several problems in industry definition, data collection and adjustment of supply. Therefore, most studies measure the scale of the digital economy by compiling the digital economy development index. But there are still some problems. First, the types of indicators are jumbled and there is too much duplication of information among indicators. Second, most of the basic data are socio-economic data based on administrative divisions at the grassroots level, without taking into account the influence of administrative boundary changes and physical-geographical interactions. Third, the research objects are mostly limited to the entire country or a certain key region, and there is still a lack of dynamic consideration of the development of the digital economy at the urban agglomeration level and its spatial pattern. #br#Given that, the paper takes the 19 national-level urban agglomerations laid out in the "14th Five-Year Plan" as the research object, construct a digital economy development evaluation system by using fuzzy sets, and establishes a grid data set with the aid of remote sensing data and geographic information system. Moreover, projection pursuit model, Dagum Gini coefficient and decomposition method, exploratory spatial autocorrelation analysis method and modified gravity model are applied to measure the digital economy development level of national urban agglomeration from 2013 to 2019, and further explore the overall situation, regional differences and spatial pattern of digital economy development in national urban agglomeration.#br#The research shows that firstly the development trend of digital economy in 19 national-level agglomerations is in a good state, with evident evolution dominated by successive transfer and supplemented by cross-level transfer. Secondly, the synergy of digital economy development in national urban agglomerations is not strong, and the characteristics of “inter-group heterogeneity and intra-group homogeneity” are gradually emerging. Thirdly, the development of digital economy in national urban agglomerations presents a positive spatial agglomeration from weak to strong, and its development model is dominated by low-low agglomeration, followed by high-high agglomeration. As a whole, the spatial pattern of the digital economy development of national-level urban agglomerations presents the “highland interlocking region” centered on Beijing-Tianjin-Hebei-Yangtze River Delta-Pearl River Delta and two “low valley regions” in the northeast and northwest, and the spatial distribution is characterized by “sparse in the east and dense in the west”, which is divided by "Hu Line".#br#Finally, this paper puts forward policy recommendations to promote the development of digital economy in urban agglomerations and to narrow the regional differencesin development of digital economy. The first is to make overall plans and strive to create new advantages for the development of the digital economy. The second is promote the synergy of inter-cluster digital economy development through diversified interaction, co-creation and sharing. The third is to accelerate the integration of the digital economy within urban agglomerations by unblocking obstacles and breaking down barriers.#br#

Lian Ganghui,Xu Aiting,Wang Wenpu. The Measurement and Spatial Pattern of Digital Economy Development:A Case of 19 National-level Urban Agglomerations[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 29-39., doi: 10.6049/kjjbydc.2021120649.

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Has Open Innovation Driven the Green Transformation of Manufacturing Industry？A Moderated Mediation Effect Model

Xing Hui,Jia Yinjie,Chen Yuanyuan

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 40-49. https://doi.org/10.6049/kjjbydc.2022050354

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As the pillar of national economic development, manufacturing industry is the main source of energy consumption and pollutant emission. Its green transformation is related to high-quality economic development and ecological civilization construction. Green transformation of manufacturing industry means that enterprises should change the traditional extensive development mode of high pollution and high energy consumption, promote independent innovation technology research and development, etc. to achieve the purpose of alleviating the contradiction between resources and environment. #br#In the era of knowledge sharing, "open innovation" characterized by openness, cooperation and sharing have come into being. In contrast to the traditional innovation, open innovation means that the boundary between innovation subjects is permeable. Enterprises can exchange innovation ideas by integrating internal and external innovation resources, expand the market by following the internal and external commercialization paths, and then increase innovation benefits. Given the carbon peaking,carbon neutrality goals and energy transformation strategy, it is of great significance to study whether and how open innovation can drive the green transformation of manufacturing industry.Since there are relatively few studies that integrate open innovation and green transformation performance of manufacturing industry within the same research framework, and the impact and mechanism of open innovation on manufacturing industry transformation and the differences in the role of dual open innovation are not very clear,this paper provides an empirical analysis to make up for the above deficiencies.#br#Throughthe theoretical analysis, this study clarifies the relationship among open innovation, green transformation performance of manufacturing industry, technology R & D capability, energy consumption structure and market structure, and puts forward research hypotheses. In the empirical test, this study draws on the panel data of 30 provinces (excluding Tibet, Hong Kong, Macao and Taiwan) in China from 2013 to 2020, and uses a two-way fixed effect model with moderated mediators to explore the impact effect and realization path of open innovation on the green transformation performance of manufacturing industry. The results show that open innovation can significantly help the green transformation performance of manufacturing industry by reducing green unexpected output and increasing green expected output. After replacing the estimation method and processing the sample, the above results are still robust. The mechanism analysis shows that open innovation can improve the green transformation performance of manufacturing industry by enhancing technology R&D capability and optimizing energy consumption structure; market structure can adjust the mediating effect between technology R & D capability and energy consumption structure on open innovation and green transformation performance of manufacturing industry.#br#In addition, dual open innovation is an epoch-making proposition. In order to adapt to the rapidly changing international situation and meet its own development needs, the manufacturing industry needs to make strategic use of global innovation resources from a higher starting point, and conduct more in-depth exchanges and interactive cooperation with strategic partners, which puts forward requirements for exploring the role differences of dual open innovation and finding an innovation model suitable for the green transformation of China's manufacturing industry.The heterogeneity analysis finds that dual open innovation can improve the green transformation performance of manufacturing industry. Although there are obvious differences in their roles, they can complement each other from both inside and outside, and complete higher-level cooperation and exchanges with external organizations. Meanwhile the regression results show that the role of inbound open innovation is stronger than outbound open innovation, which is consistent with the mainstream research, and confirms the fact that inbound open innovation is more concerned by the academic community.#br#According to the research conclusion and the current situation of green transformation of China's manufacturing industry, this study puts forward the suggestions for China's manufacturing industry to strengthen its innovation advantages and accelerate the green transformation of manufacturing industry. For local governments, it is vital to comprehensively improve the level of open innovation in the manufacturing industry from the two aspects of inbound and outbound open innovation, and optimize the regional market structure and create green manufacturing clusters. For enterprises it is imperative to accelerate the cultivation of scientific and technological innovation ability and improve the energy consumption structure.#br#

Xing Hui,Jia Yinjie,Chen Yuanyuan. Has Open Innovation Driven the Green Transformation of Manufacturing Industry？A Moderated Mediation Effect Model[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 40-49., doi: 10.6049/kjjbydc.2022050354.

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An Explantion of Disputes in Manufacturing Servitization Research: Two Types of Basic Services and Enterprise Performance

Liu Xiaoyan

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 50-60. https://doi.org/10.6049/kjjbydc.2022050752

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Servitization is the transformation trend for global manufacturing industry, but there are disputes on servitizaiton-performance relationship and the transformation path in the existing research. These two aspects are important issues on whether and how to carry out servitization. Research disputes have brought confusion to further theoretical research and enterprise practice.#br#Through the literature review, this paper first defines manufacturing servitization as manufacturer transformation from product-centered strategy to service-centered strategy, involving the reconstruction and renewal of organizational resources, capabilities, processes, culture and so on. Then it is found that the existing servitization-performance relationship research rarely quantitatively tests the relationship between different services, and the existing servitization transformation path research mainly adopts case and qualitative research methods. Services Supporting the supplier's products (SSP) and services supporting the clients’ actions (SSC ) reflect the two stages in servitization development which are also the embodiment of enterprise business logic and organizational resources transformation. They are regarded as the research object for manufacturing enterprise services in this study. However, existing studies have drawn different views on the performance impact of the two types services, and little attention has been paid to the relationship between them. The resource-based view can help enterprises identify, acquire and use key resources, and servitization with sufficient resources to establish service businesses is more likely to succeed. From the perspective of resource-based view , this paper summarizes three types of valuable, rare, inimitable and non-substitutable (VRIN) resources contained in manufacturing servitization: the installation foundation, unique and complex offerings, and service-enhanced relationships. Three sets of research hypotheses are proposed: the relationship between SSP and SSC, the impact of SSP on enterprise performance and the impact of SSC on enterprise performance. A theoretical model on the relationship among SSP, SSC and enterprise performance is built, and the relationship among SSP and SSC and their respective performance impact will be empirically tested. #br#After enterprise survey and expert consultation in the representative universities, this study draws on the ideas in existing literature and make a formal questionnaire after pre-test. The formal questionnaire survey is conducted on the service business and performance in Chinese durable consumer goods and industrial goods manufacturing enterprises, and 241 valid questionnaires are collected. The samples are widely distributed in various regions and industries, and they can represent the overall status on China's manufacturing enterprises. The survey data are statistically analyzed by confirmatory factor analysis and structural equation model. It is found that SSP promotes SSC, and SSC has a positive impact on enterprise performance, while SSP has an indirect impact on enterprise performance by promoting SSC.#br#On the basis ofthe above research conclusions, the existing research disputes on the positive, negative and nonlinear servitization-performance relaitionship are explained from the dimension of dynamic evolution time, while existing studies have analyzed these disputes from the dimensions of industry, region and organization design spatial. This paper enriches the explanation on servitization-performance relationship from the time dimension. It also explains the research disputes on the linear, coexistence and deservitization transformation path from three VRIN resources perspective. Suggestions on China's enterprise practice and government policies are put forward as follows: (1) servitization transformation decision-making and path design in various industries and regions should be treated differently according to the servitization process; (2) governments at all levels should strengthen the statistics for service business income and servitization development process data of local manufacturing enterprises，and provide support for manufacturing enterprises to improve the digital technology level.#br#

Liu Xiaoyan. An Explantion of Disputes in Manufacturing Servitization Research: Two Types of Basic Services and Enterprise Performance[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 50-60., doi: 10.6049/kjjbydc.2022050752.

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Can Digitization Adjust the Synergy between Product Innovation and Service Transformation？An Empirical Study Based on A-share Manufacturing Listed Companies

Lou Yong,Zhao Shuo,Hao fengxia

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 61-70. https://doi.org/10.6049/kjjbydc.2021060259

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Since the outbreak of the global COVID-19 pandemic, the world economy has continued to decline. The external demand market is sluggish, the risk of trade frictions has increased, and the price of factors has risen across the board. Since the reform and opening up, China's export-oriented economic development model has relied on the comparative advantages of labor and other primary factors. In this complex environment, this model is unsustainable and thus the CPC Central Committee puts forward a new development scheme “prioritizing the domestic big cycle and mutually promoting the domestic and international double cycles".This is an important strategic measure to cope with the unprecedented economic changes in the world from the past century till now, and at home and abroad. #br#Manufacturing enterprises play an important role in the construction of a new dual-cycle development pattern, and their high-quality development is related to the overall development of the economy. Under the background of “dual cycle”, product innovation and service transformation are important aspects for the outstanding development of manufacturing companies. Many companies choose to promote both product innovation and service transformation strategies in their productive and operational practices, expecting to create the synergy between each other. However, due to the limitation of resources and capability, these promotions often lead to internal resource competition, which calls for urgent consideration from manufacturing enterprises to create the synergy of the two on enterprise performances. #br#Existing studies have explored the complex relationship between product innovation and service transformation from different perspectives, reaching a preliminary consensus that digital technology can help promote the strategic synergy between these two at a practical level, and revealing the relationship and mode of influence between each other. However most of the existing studies have explored the one-way promoting relationship between product innovation and service transformation, with few discussing the dynamic interaction between the two. At the micro level, the dynamic interaction mechanism between product innovation and service transformation is still a “black box” that requires further study. Besides many case studies are without necessary supporting theories. Finally, there is still no study on how the interactive relationship between product innovation and service transformation in the digital context is affected by the transformation of corporate digitization, which asks for further analysis. This paper argues that if the theoretical and empirical basis is developed by simply studying the one-way relationship between product innovation and service transformation while ignoring the dynamic interaction between each other and the regulation effect of digitalization, the manufacturing enterprises that adopted such basis may encounter resource conflicts in the process of pursuing rapid development, which in turn might be unfavorable to the high-quality development of manufacturing enterprises.#br#Therefore, this paper applies the knowledge-based view theory and uses the panel data of 668 listed companies in the A-share manufacturing industry in China's Shanghai and Shenzhen stock markets from 2012 to 2019 to bring product innovation and service transformation into the same framework, and empirically tests the interactive effect of the two on enterprise performance. With focus on the dynamic interaction between product innovation and service transformation in manufacturing enterprises, it constructs digital indicators by using python text mining technology, studies the regulating effect of digitalization on the interaction between them, and analyzes the mechanism of digital technology regulating the two strategies in order to provide some practical guidance for the high-quality development of manufacturing enterprises.#br#It is concluded that the interaction effect between product innovation and service transformation is related to the service level of manufacturing industry. With the improvement of service level, the interaction effect shows a U-shaped relationship with inhibition first followed by promotion; the introduction of digital technology by manufacturing enterprises will significantly promote the coordinated development of product innovation and service transformation and move the inflection point of the U-shaped curve to the left; further discussion on the heterogeneity between enterprise types shows that the interactive effects between product innovation and service transformation vary among enterprises with different ownership and scales, as well as the moderating role of digitalization.The research results are conducive to promoting the synergistic results of product innovation and service transformation of manufacturing enterprises, and have important practical significance for realizing high-quality development.#br#

Lou Yong,Zhao Shuo,Hao fengxia. Can Digitization Adjust the Synergy between Product Innovation and Service Transformation？An Empirical Study Based on A-share Manufacturing Listed Companies[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 61-70., doi: 10.6049/kjjbydc.2021060259.

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Impact of Institutions and Cooperative Environment on the Open Innovation Path of Enterprises: A Fuzzy-set Qualitative Comparative Analysis Based on 26 Chinese and American Enterprises

Ma Xiaofei,Du Zhongwen

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 71-80. https://doi.org/10.6049/kjjbydc.2022060415

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At present, due to the impact of COVID-19, enterprises are facing a more complex and changeable innovation environment, and the risk of open innovation is greatly increased. At the same time, dual-cycle development pattern also provides opportunities for enterprises to reconstruct the path of open innovation. In this context, it is critical to choose the appropriate open innovation path to adapt to the new changes in the external environment, and then improve the open innovation performance.Open innovation in the United States started earlier, but there is still a lack of comparative research on the open innovation paths of Chinese and American enterprises. Therefore, this paper makes a comparative analysis on the open innovation paths of Chinese and American enterprises, which can provide certain reference significance for Chinese enterprises. The existing open innovation research mostly focuses on the impact of internal factors of enterprises on their open innovation performance, leaving the impact of external environmental factors of enterprises and the influence of different combinations of factors untapped. In fact, the success of open innovation of enterprises is the complex result of the combined action of various factors. Therefore, from the perspective of configuration, this paper makes an in-depth study on the synergistic effects of various external environmental factors in the process of open innovation.#br#The institutional logic theory and social network theory believe that the behavior of enterprises will be affected by the complex institutional environment and cooperative network, and the key innovation resources needed by enterprises for open innovation widely exist in them. Thus, it is necessary to study what kind of institutional environment elements and cooperation environment can constitute the path of high open innovation performance of enterprises. On the basis of these two theories, this study constructs a framework for studying enterprise open innovation performance from six aspects, including government subsidies, intellectual property protection, foreign direct investment, outward foreign direct investment, cooperation depth and cooperation breadth. Meanwhile, the fuzzy set qualitative comparative analysis method(fsQCA) is used to explore the synergistic mechanism of multiple factors in the complex institutional environment. Thus, this study selects 26 typical enterprises from the Internet and manufacturing industries of China and the United States, then adopts the fuzzy set method to analyze their different paths to achieve high open innovation performance.#br#Research results show that the open innovation behavior of enterprises is the result of the joint action of multiple factors, and there is no single core condition that can directly contributes to high open innovation performance of enterprises. The core conditions for achieving high open innovation performance are intellectual property protection and cooperation breadth. For both Chinese and American enterprises, there are different conditional paths to obtain high open innovation performance. What these paths have in common are that they have multiple ways to obtain key external innovation resources and all have the core conditions for open innovation performance. On the contrary, the core conditions of those non-high open innovation performance paths are all in a state of absence, and the paths to obtain external innovation resources are also insufficient. These findings indicate that there are multiple ways for enterprises to achieve high open innovation performance. They can choose the open innovation path suitable for their own development according to the actual situation of external environment. By comparing the performance paths of high open innovation between China and the United States, it is found that Chinese enterprises mainly rely on foreign direct investment or outward foreign direct investment to acquire external innovation resources. However, in the long run, this is not conducive to the sustainability of China's open innovation, and weakens China's independent innovation ability.#br#The contributions of this paper are as follows. Firstly, from the perspective of institutional environment and cooperative environment, this paper studies the influence of the external environment of enterprises on their open innovation performance, and proposes that the synergistic effect of various external environments is more conducive to the enterprises to obtain higher open innovation performance. Secondly, this paper uses QCA fuzzy-set analysis method to reveal the relationship between the external environment factors and enterprise open innovation, and find out the core conditions and multiple paths to improve enterprise open innovation performance，which provides a variety of options for enterprises to obtain high open innovation performance.#br#

Ma Xiaofei,Du Zhongwen. Impact of Institutions and Cooperative Environment on the Open Innovation Path of Enterprises: A Fuzzy-set Qualitative Comparative Analysis Based on 26 Chinese and American Enterprises[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 71-80., doi: 10.6049/kjjbydc.2022060415.

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The Motivation Factors of the Urban Sci-tech Innovative Talents Policy Diffusion and Differences in Temporal and Spatial Dimensions

Peng Chuanyu,Liu Yue

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 81-90. https://doi.org/10.6049/kjjbydc.2021090742

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Talents play a vital role in scientific and technological innovation. The competition for technological innovation talents among cities has become increasingly fierce, and various cities have introduced policies to attract technological innovation talents. With the continuous policy implementation of scientific and technological innovation talents in various regions and departments, it also realizes the diffusion of policies.#br#As a frontier field of current international public management and public policy research, policy diffusion focuses on factors that drive cities at different levels and regions to adopt a certain policy or project one after another. Most of the existing studies have carried out policy description and characteristic analysis, text content analysis, and evaluation system construction of the science and technology innovation talent policy from a static perspective. However, few scholars have studied the science and technology innovation talent policy from the perspective of policy diffusion. It is beneficial?to study the motivation factors of the science and technology innovation talent policy diffusion and their temporal and spatial differences for it can not only expand the research perspective, contribute to the analysis of the diffusion of public policies for scientific and technological innovation talents in the Chinese scenario, but also help optimize urban science and technology talent policy.#br#This paper takes the cities at the fourth-tier and above prefecture-levelin China as the research object, and the investigation period is from 2012 to 2020. Samples from 161 cities are obtained after screening. On the basis of the Berry couple's internal decision model and regional diffusion model, this paper constructs a "demand-pull-pressure-push" model of technological innovation talent policy diffusion. Demand-pull factors originate from the internal environment of public policies and are closely related to the internal economic conditions of cities. This paper selects four variables of urban economic development level, population size, the proportion of tertiary industry and fiscal revenue to measure the impact of demand-pull factors on the diffusion of scientific and technological innovation talent policies. The pressure-push factors come from the external environment of public policies. This paper selects three variable of administrative orders, intergovernmental competition and public opinion to measure the impact of pressure-push factors on the diffusion of science and technology innovation talent policies. Finally, this paper puts forward seven research hypotheses from the two aspects of demand pull and pressure push, and uses event history analysis to verify the motivation factors of the diffusion of science and technology innovation talent policy. In addition, this paper divides the development of science and technology innovation talent policy diffusion into three stages according to the curve of the diffusion of science and technology innovation talent policies, including the steady growth period of policy diffusion, the acceleration period of policy diffusion and the deceleration period of policy diffusion, and analyzes the factors for the diffusion of science and technology innovation talent policies at each stage. At the same time, the 161 city samples are classified from the spatial dimension, and the factors affecting the diffusion of scientific and technological innovation talent policies are analyzed from the perspective of different regions in the east, middle and west. #br#It is found that the diffusion of urban science and technology innovation talent policy has a dual motivation factors. In the demand-pull factors, the level of economic development and fiscal revenue are the main factors affecting the urban science and technology innovation talent policy diffusion. In the pressure-driven factors, administrative instructions, inter-governmental competition and public opinion has a significant impact on the diffusion of urban science and technology innovation talent policies. In the period of steady growth of policy diffusion, the dual factors act together on the process of policy diffusion; while in the period of accelerated and decelerated growth of policy diffusion, the policy diffusion factors of urban science and technology innovation talents are different. In the eastern and central regions, the pressure-driven factor is dominant and in the western region, the dual factors have played a role.#br#This paper draws on the theoretical framework of policy diffusion and combines the policy practice of scientific and technological innovation talents in China to refine the motivation factor model of the diffusion of urban scientific and technological innovation talents. Different from previous studies, this paper uses discrete-time event history analysis to study the science and technology innovation talent policy from the perspective of policy diffusion, which enriches the research in the field of public policy diffusion in China and improves the dimensions and perspectives of policy diffusion research.#br#

Peng Chuanyu,Liu Yue. The Motivation Factors of the Urban Sci-tech Innovative Talents Policy Diffusion and Differences in Temporal and Spatial Dimensions[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 81-90., doi: 10.6049/kjjbydc.2021090742.

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Legal Boundaries of the Processing of Personal Data in Scientific Research from the Perspective of Comparative Law

Sun Zhenfeng

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 91-99. https://doi.org/10.6049/kjjbydc.2021050565

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In the digital age, the coexistence of the value and risk of using personal data for scientific research prevails, and the key question is not whether the data should be used for research, but how to obtain the benefits of scientific research based on the basic principles of respecting ethics and privacy. In this regard, when research may bring harm to the subject of research or other relevant persons, the law needs to intervene in a timely manner and set limits for it, and this restriction itself should also abide by the provisions of the law.
In spite of the promulgation of Personal Information Protection Law of the People's Republic of China in 2021, it does not directly stipulate the purpose of "scientific research", and the regulation of scientific research behavior in China's established legal system is in a sporadic state, far from being systematized. It does not provide clear and appropriate guidance for scientific research on the processing of personal data, whether based on the direct content of the provisions or the normative interpretation. Moreover the legal regulation of similar scientific research behaviors sometimes shows inconsistencies, and there is a lack of special data processing supervision authorities and supervision mechanisms in the legal norms.
The study has the following findings. First, the legislative model for "scientific research" in most countries is to adopt the legislative path of the Basic Law positioning and supplemented by other relevant norms of a lower rank. Second, the trend of legislation is not to impose absolute restrictions on scientific research in terms of the type and scope of individuals, but to impose restrictions on data processing behavior, thereby creating a relaxed environment for scientific research. Third, the innovation of scientific research stems from its uncertainty, the discovery of new materials or the improvement of research methods will change the specific purpose of the original research. If the purpose of its data processing behavior is strictly limited, it may inhibit the vitality of scientific research, and thus the principle of unconstrained purpose has become the mainstream model of extraterritorial legislation. Fourth, the consent of the subject or alternative measures needs to be sought for personal data with legibility, and consent is not required for personal data that is not identifiable. In general, the binding force of consent is weakening in cases where the principle of limitation of purpose is exempted from application. Fifth, the extraterritorial legal system basically recognizes the derogation of personal data rights in scientific research acts, but there are different approaches in the types and degrees of derogations of derogation rights. The current consensus is that derogations from the rights of data subjects should not only comply with the statutory preconditions, but also take corresponding protective measures. Sixth, at present, the safeguards for scientific research to process personal data include both technical and organizational measures. Specific types of measures for both types of measures are still being explored.
It is proposed that first the normative construction of China's scientific research on the handling of personal data should be provided by the Personal Information Protection Law, and the special law regulating various specific research acts needs to provide more detailed rules according to their respective circumstances. Second, in terms of the assumption of the obligations of data processors, scientific researchers can receive special preferential treatment for the processing of personal data based on the consideration of public welfare expansion. Third, consent of data subjects is a developing concept, and as scientific research clarifies the data types of individuals, the precise application of tiered consent and layered consent models will highlight the effectiveness of consent. Fourth, in scientific research, absolute de-identification cannot be blindly required for different types of research, and processed data that is extremely unlikely to be identified or not harmed in the context of the current situation are acceptable, but it is still necessary to regularly assess and monitor whether there are new risks and if the technical means already taken are necessary to update and adjust. Fifth, it is necessary to improve the technical and organizational safeguardsfor data processing in scientific research.

Sun Zhenfeng. Legal Boundaries of the Processing of Personal Data in Scientific Research from the Perspective of Comparative Law[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 91-99., doi: 10.6049/kjjbydc.2021050565.

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Risk Assessment and Early Warning System of Science and Technology Security

Cai Jinsong,Ma Qi,Tan Shuang

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 100-108. https://doi.org/10.6049/kjjbydc.2021060403

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Science and technology security is an important component of national security. However, the complex international situation, rigorous technical restrictions and the subversive development trend of contemporary science and technology have triggered a series of major issues related to science and technology security, which also have brought tough challenges to China's national security. Science and technology security is affected by many endogenous and exogenous factors, like national technology strategy, innovation capacity, technology management system, resources, talents, technical industry, and other multifaceted conditions. In the face of scientific and technological security risks, in addition to improving the ability of scientific and technological innovation, it is equally important to prevent problems before they occur. As for those risks that may endanger scientific and technological security, advance prevention and timely warning are in pressing need.#br#This study is a combination of normative and empirical analysis to explore the meaning and elements of science and technology security in China, and to clarify the framework of science and technology security assessment and early warning mechanism, which may contribute some ideas and theoretical supports for improving the monitoring and early warning system of science and technology security. From the perspective of risk assessment and security early warning, this research follows the early warning logic of “variable design-data evaluation-security early warning-plan call”, combines the analytic hierarchy process and expert grading method, and constructs the “science and technology security risk assessment framework” and the “science and technology security early warning system”. Among them, the “science and technology security risk assessment framework” is developed with normative reasoning and grounded theory method. Both first-hand and second-hand text materials are involved, including in-depth expert interviews, policy documents, literatures, newspapers and so on. By employing a three-step text analysis, an assessment framework including four kinds of key evaluation indicators (essentiality, reflexivity, autonomy, and security) is developed.#br# Theearly warning mechanism of science and technology security is based on the risk assessment framework. Before developing the mechanism, an early warning logic is clarified. Generally, in the engineering control logic of early warning, it is necessary to set and clarify the science and technology security early warning objectives and targets. And then, a series of variables and indicators related with the target should be assessed. After that, a conclusion of safety level can be calculated. To assessing the risk variables and indicators, there are some necessary tasks, including risk variables identification, weighting, ordering and some other calculation. This study provides an approach to weighting science and technology risk variables and to calculating safety levels. On the basis of the“science and technology security risk assessment framework” and the analysis of early warning logics and techniques, the mechanism of science and technology security early warning is developed. The mechanism mainly relies on the modules of emergency assessment, emergency report, decision-making management, and contingency plan, which involving multiple variables and subjects, and the four modules operate circularly in practice.#br#In summary, this study focuses on the risk assessment and early warning mechanism of science and technology security in China by developing and clarifying the assessment framework and early warning methods. In the process of constructing the science and technology security early warning mechanism, this study systematically analyzes the science and technology security early warning logic, hoping to provide new ideas for China's science and technology governance and security.#br#In future research, the identification and assessment of S&T security risks can be more widely incorporated into quantitative and textual data corresponding to different core technology fields,so as to further refine evaluation indicators and improve their usability and computability. In view of the predictability and timeliness of science and technology security monitoring and early warning, the follow-up research could aim at a science and technology security monitoring and early warning system, develop a large sample database and case base of science and technology security, combine data science research paradigm to establish a continuous intelligent prediction model of science and technology security monitoring and early warning, and improve the overall early warning research and judgment efficiency.#br#

Cai Jinsong,Ma Qi,Tan Shuang. Risk Assessment and Early Warning System of Science and Technology Security[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 100-108., doi: 10.6049/kjjbydc.2021060403.

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The Technological Innovation Capability Evaluation of Universities under the Background of Constructing World-class Universities with Chinese Characteristics

Chen Guofu,Jiang Qingquan,Tang Yanzhao

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 109-118. https://doi.org/10.6049/kjjbydc.CZ202107085

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The Chinese government is endeavoring to build a world-class university with Chinese characteristics. The study about the scientific and technological innovation capabilities of universities will help to explore the construction of world-class universities with Chinese characteristics. Universities should not only complete the fundamental task of building morality and cultivating people, but also continuously improve their scientific and technological innovation capabilities. Therefore, this paper takes scientific and technological innovation as the research perspective, and seeks for the improvement path of China's world-class university construction.
Existing research on the evaluation system of scientific and technological innovation capability in universities has paid more attention on the measurement of multi-dimensional perspectives, and the measurement indicators include scientific research achievements and management level. Moreover the evaluation system highlights the scientific research environment and national policies, and pays attention to the impact of research results on the economy and society. Existing research not only focuses on the universities themselves, but also extends to the impact on the regional economy and society. Third, the evaluation system is centered on scientific research achievements. Scientific research results are an important indicator to measure the scientific and technological innovation capability of universities, and more attention may be paid to the quality of scientific research results in the future. At present, China is undergoing great changes in the external environment, national policies and educational concepts. Therefore, it is necessary to carry out systematic research in combination with the new requirements for the development of Chinese universities in the new era. This paper attempts to explore the path to promote the construction of world-class universities with Chinese characteristics from the perspective of scientific and technological innovation capabilities. Following the resource allocation theory, this study constructs an evaluation index system for the scientific and technological innovation capability of universities from four aspects: technological innovation resource conditions, technological innovation resource input, technological innovation and innovation vitality, and technological innovation output benefits.
The main conclusions of this study are as follows. First, at present, the scientific and technological innovation capacity of universities in various regions of China present a regional, staged and differentiated development pattern. Overall, the technological innovation capabilities of universities in various regions are on the rise. Second, the output benefit of scientific and technological innovation has a greater impact on the scientific and technological innovation capacity of universities, while the impact of scientific and technological innovation vitality is small. There is a certain gap between the output benefits of scientific and technological innovation and the basic conditions of scientific and technological innovation, resource input and innovation vitality. Third, the human factor in universities has a small impact on the technological innovation capability, while the capital factor has a greater impact on the technological innovation capability.Forth, the current development of scientific and technological innovation capabilities in universities pays more attention to the transformation of economic value of scientific and technological achievements,weakening the diffusion of academic value and social benefits of research results. The government should encourage universities to improve their scientific and technological innovation capabilities, improve the intellectual property protection mechanism for scientific research achievements, and promote scientific and technological innovation activities in universities.
The following recommendations are made. First, it is necessaary to improve the basic conditions for scientific and technological innovation. The government also needs to take into account different regional policies and resource allocation, encourage independent innovation of universities, and provide policy support. Second, there is the urgent need to optimize the competition mechanism, for the construction of world-class universities requires concentrated efforts,and allows some qualified universities to use their advantageous resources and policies to carry out scientific and technological innovation and give priority to some achievements. Third, it is essential to improve the resource allocation mechanism.It is necessary to strengthen scientific and technological innovation in universities, and encourage cooperation among universities, enterprises and the government. The fourth is to make full use of the advantages of abundant scientific and technological innovation resources, active innovative ideas and strong innovative atmosphere in universities in economically developed regions, and vigorously advocate scientific and technological innovation.

Chen Guofu,Jiang Qingquan,Tang Yanzhao. The Technological Innovation Capability Evaluation of Universities under the Background of Constructing World-class Universities with Chinese Characteristics[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 109-118., doi: 10.6049/kjjbydc.CZ202107085.

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The Knowledge Field in S&T Cooperative Governance of Cross-Straits: Paradigm Design and Spatiotemporal Evolution

Li Yingbo

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 119-129. https://doi.org/10.6049/kjjbydc.2022100861

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Science and technology (S&T) cooperation is an indispensable part of the promotion of the S&T integration across the Straits and national reunification in the new era. Cross-straits cooperation in S&T has achieved remarkable progress. However, cross-straits relations are facing new challenges from the external environment. Especially in the recent interference of the United States and other international factors, the "Taiwan issue" has been increasingly internationalized. Cross-straits S&T cooperation, such as the integrated circuit industry and other key areas, faces significantly increased uncertainties and risks, and the "field" of cooperation is undergoing drastic changes.
As a theoretical perspective to understand the evolution of social structure driven by social movement, "knowledge field" is of theoretical value for deepening cross-straits S&T cooperation and governance. This paper formulates the theoretical paradigm of "knowledge field" in S&T cooperative governance of cross-straits in terms of structure, relationship and practice. The knowledge field in S&T cooperation governance of cross-straits is the S&T relations rooted in the two sides’ common S&T goals, common social structure formed by S&T exchanges towards national unification. The knowledge field has structural, relational and practical characteristics. Structuralcharacteristics reflect the diversity of types of governance actors of cross-straits, relationalcharacteristics reflect the closeness of cooperation network, and practicalcharacteristics emphasize that governance actors implement collective action and establish a common narrative in the governance scene.
The actors of cross-Straits S&T cooperation governance include the researchers, innovators and facilitators. Research institutions, universities and enterprises on both sides are the researchers and innovators. Government departments, industry associations and technological intermediaries are the facilitators. In particular, researchers and entrepreneurs on both sides are the micro-level producers of knowledge in S&T cooperation. The relevant departments promoting cross-straits S&T cooperation include central departments such as the Taiwan Affairs Office of the State Council and the Ministry of Science and Technology, state public institutions such as the National Natural Science Foundation of China and China Association for Science and Technology, as well as local governments. The extensive participation of the actors in knowledge field can help to shape the symmetrical flow of information and knowledge sharing among those actors, and mitigate the goal differences caused by the cognitive bias of the actors. The diversity of actor can also help to solve the problems of opaque decision-making and indirect democratic accountability in the governance groups.
Cross-straits S&T cooperation comes from the common belief of actors on both sides in scientific rationality, public value and national identity, reflecting the inherent initiative of scientists, researchers and academic institutions on both sides. The paper discusses the spatiotemporal evolutionary characteristics of knowledge field from four aspects: development process, spatial features, regional practice and common narrative. Furthermore, the paper analyzes the practical effects of knowledge field from three scenarios: fundamental research, patent cooperation and collective standardization of industry. However, the complexity of the knowledge field implies that challenges always exert influence. The interference factors in the knowledge field of bilateral cooperation governance mainly include the disturbance of Taiwan political factors and international factors.
The policy implications of this paper are as follows. (1) Knowledge producers should deepen their connection in S&T cooperation governance field. In the face of the ever-changing situation of cross-straits relations, technological enterprises, research institutions and universities on both sides should integrate themselves into the national strategic layout of high-level scientific and technological self-reliance and strengthen their technological adaptation and policy adaptability. (2) The departments should increase the supply of cross-straits S&T cooperation governance field system, promote their collective action, strengthen S&T, education, talent and innovation policy linkages, such as the state-led establishment of cross-straits key S&T leading talent cooperation, chip industry patent cooperation fund and industrial common standard data centers. (3) The actors of cross-straits should deepen their S&T cooperation governance scenario network. Fundamental research, patent activities and industry standard development are a long chain and interrelated scene network. However, the actors of the two sides are less involved in the frontier public technology, patent layout, intellectual property transaction, and the development of broader industrial standards. Therefore, it should be rooted in the innovation scenarios, research project processes and specific geographical spaces to promote cross-straits multi-agent S&T cooperation and governance experiments. The research helps to understand the internal principle and evolving direction of S&T cooperative governance, responding to new challenges and deepening cross-straits S&T integration.

Li Yingbo. The Knowledge Field in S&T Cooperative Governance of Cross-Straits: Paradigm Design and Spatiotemporal Evolution[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 119-129., doi: 10.6049/kjjbydc.2022100861.

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Collaborative Innovation Knowledge Sharing Based on Blockchain Technology

Fang Gang,Wang Jiahui

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 130-140. https://doi.org/10.6049/kjjbydc.2020120878

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Collaborative innovation is a comprehensive and in-depth cooperative innovation behavior and process with innovation as the goal and multi-agent, multi-element and multi-stage collaborative interaction as the center. From the perspective of knowledge innovation, collaborative innovation refers to the network organization that promotes knowledge flow and sharing through knowledge acquisition, transmission, application and feedback activities, and increases the knowledge reserve of each member, and finally forms knowledge advantages through knowledge collaborative creation. Among them, knowledge sharing is not only an important part of the above process, but also the main way to realize the diffusion of knowledge among collaborative subjects (enterprises and research institutions). However, collaborative innovation knowledge sharing needs to coordinate the knowledge elements and the environment, as well as the relationship between knowledge sharing subjects, in order to integrate the scattered and disordered knowledge in the system into a new orderly knowledge system, and realize collaborative innovation. Existing research believes that blockchain, as an open source underlying technology, can attract collaborative innovation partners with different knowledge structures and organizational cultures, but the impact of blockchain technology on knowledge sharing in collaborative innovation and the mechanism through which this impact plays a role are vogue. This paper aims to explore the knowledge sharing process of collaborative innovation under the influence of blockchain, and build a knowledge sharing network system for collaborative innovation based on blockchain to promote the application of blockchain technology in collaborative innovation system in practice.#br#The existing knowledge sharing theory of collaborative innovation believes that the nature of knowledge, the relationship between subjects, the level of conflict, and even the recognition of knowledge sharing results and the expectation of income distribution will affect the knowledge sharing process in collaborative innovation. From the perspective of the nature and characteristics of knowledge, with the advancement of collaborative innovation, tacit knowledge continues to increase, and the higher the complexity of knowledge, the worse the transferability of knowledge. Secondly, in the relationship between knowledge sharing subjects, trust plays a crucial role. Thirdly, from the perspective of inter-subject conflict, due to the differences in knowledge structure, organizational culture and innovation goals among the cooperating parties, conflicts among cooperative members are inevitable in the process of knowledge sharing, and this conflict will affect the process of knowledge sharing. Even in the case of the same goals, due to the bounded rationality of human beings and the complexity of knowledge, there will be coordination problems in knowledge sharing in collaborative innovation, and corresponding transaction costs will be generated. While blockchain technology can create a trustless distribution, and provides a solution to the problems of high maintenance cost, low transmission efficiency and low data security reliability existing in knowledge sharing between organizations.#br#Facing the problem of knowledge sharing in collaborative innovation, this paper introduces the case of collaborative innovation knowledge sharing in the Steemit blockchain network community and combines the characteristics of blockchain, uses VensimPLE software to build a system dynamics model for simulation analysis, and discusses the influence and mechanism of trustless partnership and high-heterogeneous partners in the process and results of collaborative innovation knowledge sharing. Among them, the experimental data adopts two parameter estimation methods: the first is to collect relevant data from literature search and white papers issued by authoritative organizations; the second is to collect real data information in the MSSQL database. The initial value of the total number of Steemit tokens is determined by collecting data information in the SteemDB browser. The experimental results show that trustless knowledge sharing partnership and high heterogeneity knowledge sharing partnership based on blockchain technology have a significant impact on improving the quality of knowledge sharing in collaborative innovation. To sum up, the process and performance of collaborative innovation knowledge sharing under the blockchain technology have been significantly improved. The trustless knowledge sharing partnership can ensure the authenticity of information in the process of collaborative innovation, promote mutual learning among collaborative innovation members, accelerate the transfer of tacit knowledge, and enhance the knowledge creation and knowledge sharing power of collaborative innovation members. High heterogeneity knowledge sharing partners can attract more collaborators, promote the formation of knowledge creation groups and knowledge sharing groups, and provide a wider range of knowledge sharing sources for collaborative innovation knowledge sharing, thus consolidating the foundation of knowledge creation.#br#

Fang Gang,Wang Jiahui. Collaborative Innovation Knowledge Sharing Based on Blockchain Technology[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 130-140., doi: 10.6049/kjjbydc.2020120878.

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How to Enhance Employee Creativity in the Context of Organizational Change:A Configuration Analysis Based on the Theory of Creativity Interaction

Zhu Suli,Yuan Tongjie,Long Lirong

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 141-150. https://doi.org/10.6049/kjjbydc.2021050367

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In the rapidly changing market environment, "organizational change" has become the necessity of survival and development for companies. There are two types of change in organizations：radical organizational change which is an intense adjustment and leap for organizational management; another is incremental organizational change which is a step-by-step approach to change over a longer period of time, resulting in a gradual and gentle revision and improvement of the organization. Both radical and incremental change involve changes in employees' existing working patterns and potentially cause greater demands on their creativity. How can employees' creativity be stimulated to make the change happen? What factors play more important roles in stimulating employee creativity in different types of organizational change? The answers to these questions are of great relevance to the search for ways to effectively stimulate employee creativity. However, existing research lacks an analysis of the interactive mechanism of multi-dimensional factors on employee creativity in organizational change situations, and does not distinguish different organizational change situations. There are differences in the impact of radical and incremental organizational change on the companies and the psychological perception of employees, and therefore there may be different paths for the stimulation of employee creativity between these two types of change. Woodman's interaction theory of creativity suggests that individual creativity is influenced not only by individual factors, but also by the group and organizational context.#br#According to the interaction theory of creativity, this paper explores the different configurations that stimulate high employee creativity in organizational change situations by incorporating organizational, leadership and individual multi-level factors from an integrative perspective. Specifically, it incorporates organizational change contexts, transformational leadership, Chinese family-like employee-organization relationship, and individual harmonious passion into the integrated research model. The analysis is carried out using the method of fuzzy-set qualitative comparative analysis(fsQCA) to integrate factors at the organizational, leadership and individual levels to find the configurations that stimulate high levels of employee creativity in different organizational change contexts.#br#Employees in R&D positions within companies that are experiencing or have just experienced organizational change are taken as the target sample for this study. The supervisor-employee matching questionnaires are distributed in mainland China, and supervisors evaluate the creativity of subordinate employees and employees evaluate their own perceived frequency of organizational change and magnitude of change, the transformational leadership style of their supervisors, and the family-like employee-organization relationship. In the end, 65 valid questionnaires from 12 R&D teams in 8 companies are collected. Then the fsQCA method is used to carry out configuration analysis and explore the collective effect of different influence factors on employee creativity. It is found that there are three ways can stimulate employee creativity in three kinds of organizational change situations.(1)“Passion-driven model” in the context of radical organizational change. The positive state of psychological arousal brought about by the individual's harmonious passion for work is more prominent in dissipating the high level of environmental uncertainty and psychological insecurity associated with radical change, and plays a key role in the rapid adaptation and positive response of employees to intense change. Harmonious passion is therefore also more effective in stimulating employee creativity in the context of radical organizational change. (2)“Leadership-driven model” in the context of radical organizational change. Transformational leaders are strong at presenting a clear vision of change and expressing high expectations of their subordinates' abilities to evoke their awareness for change, while strongly guiding their subordinates to respond adaptively and creatively for change. Therefore, in the process of radical organizational change, transformational leadership plays an active role in influence employee creativity. (3) “Family-like relationship driven model” in the context of incremental organizational change. Family-like employee-organization relationship is a central force in promoting employee creativity in the context of incremental change. This Chinese style of high-quality employee-organization relationship is the integrated relationship in which both employees and their organizations are oriented towards meeting each other's needs. It makes employees more receptive to less intense changes in organizational work situations and willing to actively contribute to meeting the expectations of change. The different paths identified in this paper are useful for organizational managers to select appropriate management approaches, stimulate employee creativity and promote the process of change according to different changes.#br#

Zhu Suli,Yuan Tongjie,Long Lirong. How to Enhance Employee Creativity in the Context of Organizational Change:A Configuration Analysis Based on the Theory of Creativity Interaction[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 141-150., doi: 10.6049/kjjbydc.2021050367.

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Exchange and Cooperation: A Meta-analysis of the Effect of Transactive Memory System on Team Effectiveness

Su Tao,Deng Silu,Xie Hong,Chen Xiude,Ma Wencong

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2022, 39(24): 151-160. https://doi.org/10.6049/kjjbydc.2022060572

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The transactive memory system (TMS) has been prominent and popular in the current management practice. It is beneficial for teams to release individual memory burden, improve the utilization efficiency of team members' knowledge and skills, enhance team knowledge sharing ability, and obtain team efficacy (TE). Quite a lot of scholars in various fields have paid more attention to its effectiveness. It is of both practical and theoretical significance to systematically clarify the influence mechanisms and boundary conditions of TMS.#br#Despite of the fruitful results achieved on the impact of TMS on TE, there are still four shortcomings generally. First, the conclusion of the influence mechanisms of TMS on team effectiveness has not been drawn. Second, the existing research results mainly focus on team performance, and the variables involved are too scattered. Third, there is a lack of meta-analysis to test the discriminant validity of TMS in three dimensions. Finally, its boundary conditions are still unclear. Therefore, this paper uses the meta-analysis method to clarify the issues listed above, which is helpful to bridge the differences with existing conclusions and promote the research on the effectiveness of TMS.#br#According to the social cognition theory (SCT), individual behavior acts as a moderator between him/her and the corresponding environment. While his/her behavior changes the environment, the environment also guides the individual behavior. Actually, the effect of TMS is the result of the individual social cognition continuously. Under the influence of TMS, members strengthen their own cognition and improve the self system, which make it possible for their team to efficiently achieve the goals.#br#Following the SCT, this study conducts a periodical meta-analytic examination on the effectiveness of TMS using 97 empirical studies, with 300 effect sizes and 50 903 independent samples. Schmidt and Hunter’s psychometric meta-analysis method is used to calculate the estimates reported in the above literature. This method estimates what the results would have been had if all the studies were conducted without methodological limitations or flaws. In this study, the meta-analysis operation mainly incorporates publication bias analysis, main effect analysis and moderator analysis.#br#In the first part, the study systematically evaluates transactive memory system′s effectiveness, and compares its different promotion effects on team behavior, team performance and team emotion. Periodical conclusions with less second-order sampling error are gained by main effect analysis from meta-analytic examination. TMS is found to promote TE. Specifically, its impact on team behavior comes first while it exerts the similar promoting effects on team performance and team affect.In the second part, the discriminant validity of the three-dimension structure of expertise-credibility-coordination of TMS are checked and their different effects on TE are also explored. The three-dimension structure is verified to possess enough discriminative validity. The effects of credibility and coordination dimensions on TE are similar and stronger than that of expertise dimension.In the third part, it also examines the moderating effects of 4 potential factors, including the regional culture (macro level), organization type (middle level), team size (micro level) and measurement tool (measurement level), on the relationship between team transactive memory system and TE. They are proved to play a role. It indicates that TMS exerties stronger positive effects when teams are in the Confucian culture context (compared with in the Anglo-Saxon culture context) or in high-tech enterprises (compared with low-tech enterprises),or belong to small groups (compared with in large groups).#br#This paper contributes to the existing literature in the following three aspects. First, it systematically summarizes the effects of TMS on team effectiveness, and forms an overall framework for summarizing the effects, theoretical basis, measurement methods and moderating variables on team effectiveness. Second, more reliable results show that the division of expertise-credibility-coordination dimensions has good discriminative validity. What′s more, credibility and coordination have stronger correlations with TE. Third, the moderating effects of the region culture (macro level), organization type (middle level), team size (micro level) and measurement tool (measurement level) on the team effectiveness of TMS are clarified, which make it possible to describe the internal mechanisms of TMS.#br#The practical implications are finally discussed. First, managers can stimulate TE building TMS. Second, when building TMS, it is more effective to create the team atmosphere of credibility and coordination compared with emphasizing the expertise of members. Third, for those small groups embedded in Chinese high-tech enterprises, the construction of TMS should be paid more attention for the TMS can exert more positive influence on teams.#br#

Su Tao,Deng Silu,Xie Hong,Chen Xiude,Ma Wencong. Exchange and Cooperation: A Meta-analysis of the Effect of Transactive Memory System on Team Effectiveness[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(24): 151-160., doi: 10.6049/kjjbydc.2022060572.

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25 December 2022, Volume 39 Issue 24

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25 December 2022, Volume 39 Issue 24