Internet Plus government service platform and corporate digital transformation

Internet Plus government service platform and corporate digital transformation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Internet Plus government service platform and corporate digital transformation Wanyi Chen, Dongao Ji This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6903235/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In the digital economy, corporate digital transformation (CDT) has become essential for enterprises to maintain high-quality development. This study explores the impact of the government digital governance on CDT. Accordingly, this study finds that the Internet Plus government service platform facilitates CDT through interactions between the government and enterprises vis-à-vis interactive intentions, equipment, and actions. Interactive intentions, by increasing corporate exposure and reputation and optimizing the business environment, alleviate resource constraints for CDT; interactive equipment enriches the information channels and enhances digital literacy, thereby improving CDT capabilities; and interactive actions accelerate the CDT process by optimizing the coordination of internal and external resources. This study expands the antecedents of CDT from macro governance and enriches the economic consequences of digital governance effects. It provides practical implications for the government to guide CDT through macro policies and inspires enterprises to actively use digital government platforms to accelerate CDT and achieve sustainable development. Government digital governance Corporate digital transformation Interactive intentions Interactive equipment Interactive actions Figures Figure 1 1. Introduction In recent years, digital technologies, such as cloud computing, has revolutionized traditional business models, fundamentally altering how businesses evolve and engage with stakeholders. Consequently, corporate digital transformation (CDT) has emerged as a strategic pathway for firms to harness digital technologies in crafting more advantageous business models, serving as an effective mechanism for sustainable growth (Cheng et al., 2022 ). However, the CDT process is complex and protracted, requiring substantial financial investment from enterprises (Hess et al., 2016 ), generally engendering low success rates. The existing literature predominantly investigates CDT influencing factors from a firm’s perspective (Bouncken and Barwinski, 2020 ). With government policy adjustments in the post-pandemic era, the current literature focuses on the impact of macro-level policies on CDT, including tax policies (Chen et al., 2023 ) and government subsidies (Bratta et al., 2022 ). However, less attention is paid to digital governance. Digital governance leverages information technology to optimizes social relational networks and communication models through massive data exchange (Hanisch et al., 2023 ). In recent years, digital governance platforms, exemplified by the Internet Plus government service platform, have gained widespread attention. These platforms help governments address complex administrative demands through digital technology (Janowski et al., 2018 ), aiming to foster innovation-driven development and enhance the efficiency and effectiveness of governmental services by integrating Internet technology with traditional operations. Since 2015, China has launched the Internet Plus government service platform initiative to modernize its national governance system and capabilities. Accordingly, digital governance platforms have facilitated the transformation and optimization of administrative service by enhancing government performance (Allen et al., 2020 ), standardizing government information (Lourenço, 2015 ), profoundly altering the representation and dissemination of various social administrative resources (Conradie and Choenni, 2014 ), and optimizing government administration (Cellary and Rykowski, 2018 ). However, the highly procedural characteristics of government digital governance may impair organizational adaptability (Hanisch et al., 2023 ). Current literature emphasizes the impact of digital governance on firms’ short-term operational effects (Möhlmann et al., 2021 ; Commerford, 2021) and less on long-term corporate strategic development. China has achieved significant progress in digitalization in recent years. In 2022, the scale of the Chinese digital economy accounted for 41.5% of its GDP, ranking second globally 1 . In recent years, the Internet Plus government service platform has been the focus of China’s governance transformation. Since 2015, China has identified digital governance as a national strategy and has introduced a series of supporting policies including Internet Plus 2 . The Fourteenth Five-Year Plan 3 further incorporates the construction of a digital society and government, as well as the level of social digitalization and intelligence. Digital governance addresses departmental silos and provides insights into global issues like redundant construction and inefficiency (Kuhlmann and Heuberger, 2021 ). Therefore, this study focuses on Chinese digital governance reform, discussing the Chinese digital governance model represented by the Internet Plus government service platform to provide practical guidance for improving digital governance in other developing countries. This study takes A-share listed companies on the Shanghai and Shenzhen Stock Exchanges during 2017–2022 as samples. Using the theory of interactive governance, this study finds that the Internet Plus government service platform facilitates CDT from three perspectives: interactive intentions, equipment, and actions. Specifically, interactive intentions promote CDT by increasing corporate exposure and reputation, while optimizing the business environment, thereby alleviating CDT resource constraints. Interactive equipment enhances CDT capacity by enriching information reception and improving corporate digital literacy. Interactive actions accelerate the CDT process by optimizing the coordination of enterprises’ internal and external resources. This study makes three fundamental contributions. First, it extends the governance effects of digital government platforms on corporate strategic transformation. The existing literature on the economic consequences of digital governance largely focuses on government governance outcomes and market reactions, including the quality of government services (Sieber and Johnson, 2015 ), public participation (Ojo and Mellouli, 2018 ), and market development (Janowski et al., 2018 ). The impact on enterprises mainly concerns short-term business operations, including corporate risk (Commerford et al., 2021 ) and operational efficiency (Möhlmann et al., 2021 ), with less attention to long-term corporate strategies. Second, this study extends the macro-governance factors influencing CDT. Extensive research has discussed CDT factors from firm characteristics including corporate culture (Cichosz et al., 2020 ), digital strategy (Singh et al., 2021 ), and personnel characteristics (Eller et al., 2020 ; Alnuaimi et al., 2022 ). Some studies have also focused on the impact of government policies rather than government governance methods (Chen et al., 2023 ; Bratta et al., 2022 ). Third, this study provides significant practical insights for governments and corporations. From the government's standpoint, this study presents crucial guidance for government involvement and leadership in CDT initiatives, advising governments on the active advancement of digital government platforms to sculpt policies and business environments that support CDT. This study assists firms in better utilize digital government platforms for accessing the necessary resources for CDT, thereby promoting further development. 2. Literature Review 2.1 The influencing factors of CDT The existing literature examines the factors influencing CDT from both macro-level policies and micro-level enterprise characteristics. From the macro-level policy perspective,, tailored target policies are more conducive when local economic growth target policies are misaligned with CDT (Yang et al., 2022 ). Additionally, tax cuts (Chen et al., 2023 ) and government subsidy policies (Bratta et al., 2022 ) contribute to CDT. From the enterprise characteristic perspective, the main considerations include corporate culture, strategy, and organizational personnel. Digital culture promotes the use of digital equipment, thereby improving organizational digital performance (Eller et al., 2020 ). Additionally, digital culture fosters CDT by setting realistic expectations for technology (Cichosz et al., 2020 ). The ability to perceive trends in environmental changes and the capacity to seize opportunities have also been proposed as essential cultural characteristics of CDT (Dong et al., 2016 ). From a corporate strategy perspective, digital strategy acts as a driving factor (Bouncken and Barwinski, 2020 ). Digital strategy alliances promote synergistic effects (Singh et al., 2021 ), thus influencing CDT efforts. Knowledge sharing among alliance partners facilitates CDT success (Siachou et al., 2021 ). Additionally, a firm's dynamic capability strategy can promote adaptation to CDT (Teece and Leih, 2016 ). From the corporate personnel characteristic perspective, employees with relevant skills, demonstrating professionalism and digital transformational leadership, serve as effective motivating factors regarding CDT (Eller et al., 2020 ). Organizational agility also plays a facilitative role in CDT (Alnuaimi et al., 2022 ). 2.2 The economic consequences of digital governance Digital governance methods, represented by the Internet Plus government service platform, benefit from a technological backdrop. They leverage Internet technology to transform traditional methods of data storage, retrieval, preservation and utilization within organizations (Conradie and Choenni, 2014 ). This innovative approach directly advances the transition from abstract, generalized public sector data to open, usable datasets. Given the characteristics of digital governance methods, the current literature focuses on three aspects: government performance management, market transactions, and enterprise performance. From the perspective of government performance management, digital governance has four advantages. First, the open-data characteristic of digital governance promotes data circulation, aiding governments in data acquisition, thereby facilitating the provision of richer and more accurate data to market entities for service improvement (Sieber and Johnson, 2015 ). Second, digital governance can enhance public participation in government decision-making (Ojo and Mellouli, 2018 ). Third, digital governance reduces public resource waste and maximizes public sector performance. (Allen et al., 2020 ). Fourth, as government information becomes more accessible and retrievable, digital governance can also encourage improved quality of government information disclosure through supervision (Lourenço, 2015 ). From a market transaction perspective, digital governance can also serve as a channel between multiple types of market entities to promote market transactions. Moreover, from an overall development perspective, digital governance can effectively optimize the business environment by influencing citizens' habits (Fan et al., 2022 ), and further promote sustainable market development (Janowski et al., 2018 ). First, from the perspective of corporate performance, digital governance increases information flows within enterprises, effectively mitigating agency problems (Commerford et al., 2021 ). Second, digital governance can enhance the efficiency of platform-based enterprise managers through algorithmic monitoring (Möhlmann et al., 2021 ). Finally, by disclosing information, digital governance helps enterprises attract potential customers and enhance reputation (Hanisch et al., 2023 ). In summary, contemporary research mainly addresses the impact of digital governance on governments and markets, with limited focus on its influence on long-term corporate strategies. The macro factors influencing CDT have mainly centered on policy content rather than on digital governance methods. This study focuses on the impact of digital governance on corporate digital strategies. 3. Hypothesis Development Interactive governance is defined as a complex process wherein multiple social and political actors with divergent interests mobilize, communicate, and deploy actions to formulate, promote, and achieve common goals (Torfing et al., 2012 ). It’s analytical framework comprises three elements: interactive intentions, equipment, and actions (Fan et al., 2022 ). Based on the characteristics of the Internet Plus government service platform, this study situates these dimensions, constructing a framework, as shown in Fig. 1 . [Insert Fig. 1 here] Interactive intention refers to the convergence of visions and values among multiple social and political actors to achieve common goals. Within the Internet Plus government service platform, the participation levels of government and business entities drive the CDT process. Hence, the participation levels of these two entities together constitute interactive intentions. Static participation refers to the scale of entities, including the number of government departments and enterprises, joining the platform. Dynamic participation refers to the number of information posts by both entities on a platform. Interactive equipment refers to the resources available to each entity and the systems for sharing such resources. On the Internet Plus government service platform, businesses require information for operations and transformation requirements while the government possesses abundant informational resources. The exchange and sharing of this information constitute the interactive equipment dimension.. The process of businesses handling administrative tasks on the platform typifies the interactive action dimension. In summary, interactive governance within the Internet Plus government service platform demonstrates a progressive logical relationship. Governments and enterprises first enter the platform through static and dynamic participation using the platform's information for both unilateral and bilateral communication modes, ultimately accomplishing administrative tasks. This study explores the impact mechanisms of the Internet Plus government service platform on CDT under three different interaction modes. 3.1 Interactive intention and CDT The Internet Plus government service platform primarily includes two key entities: the government and enterprises, whose participation level represents their interactive intentions. As CDT entails a comprehensive reshaping of enterprises, it demands substantial and sustained financial investment (Jia et al., 2023 ). Moreover, the lengthy CDT process and delayed results may face discrimination from financial institutions when seeking financing, further restricting CDT (Hess et al., 2016 ). Increased participation on the Internet Plus government service platform can alleviate financing constraints from the following two perspectives, offering financial support for CDT. From the enterprise perspective, increased participation on the Internet Plus government services platform leads to greater information disclosure through this official governmental channel. Releasing information on government-recognized platform can have a certifying effect (Guo et al., 2022 ), signaling to the public that the enterprise is in compliance with policy, thus enhancing the company's social reputation (Hanisch et al., 2023 ). A good reputation, as a risk filter, can prove that the enterprise can actively fulfill its commitments to stakeholders, reduce investors' anticipated costs of contractual breaches, and ease the enterprise's financing constraints (Bajo et al., 2016 ). This provides a stable funding source for CDT. From the government's perspective, local governments enhance participation on the Internet Plus government service platform under the guidance 4 , increasing the number of administrative departments joining the platform. This allows companies to handle a wider variety of governmental services quickly on the platform, improving the quality of administrative services from diverse perspectives. As government participation grows, the focus shifts from the number of governments joining the Internet Plus platform to the services quality. The Enhanced service quality will further improve the business environment by optimizing administrative conditions. The openness of a favorable business environment, by building an ecological context (Chae, 2019 ), promotes market development while attracting domestic and foreign investment, thus providing enterprises with multi-channel resource supplies, expanding financing channels for enterprises (Pan et al., 2022 ), further easing financing constraints, and promoting CDT. Therefore, this study proposes that: H1 Participation on the Internet Plus government service platform promotes CDT. 3.2 Interactive equipment and CDT Owing to the complexity and high-risk nature of CDT (Yao et al., 2023 ), enterprises increasingly need to utilize information flexibly for decision-making during the transformation (Aben et al., 2021 ). When abundant information complicates CDT, ability to interpret and analyze information is crucial for acquiring key information resources, which affects CDT (Gupta and Bose, 2022 ). The interactive equipment on the Internet Plus government service platform, providing a richer information source for the entire market environment (Sieber and Johnson, 2015 ). This gradually enhances enterprises' digital literacy in interpreting information and promotes CDT. First, abundant information stemming from communication and interaction with the government can encourage businesses to learn and recognize environmental changes, thereby enhancing the perception of environmental trends. On one hand, enhanced perception helps enterprises recognize environmental changes, make timely adjustments (Ghosh et al., 2022 ), better integrate with the external macro environment and fosters CDT-related knowledge exchanges (Bouncken and Barwinski, 2020 ), thus formulating appropriate CDT strategies (Hess et al., 2016 ). On the other hand, by analyzing the environment, perception helps enterprises identify valuable market opportunities and make adjustments (Ritter and Pedersen, 2019 ), facilitating CDT (Dong et al., 2016 ). Second, increased information exchange between governmental and market entities strengthens government-enterprise relations ,enabling enterprises to gain political capital, such as more channels to identify policy information related to transformation (Casanueva et al., 2013 ). The Internet Plus government service platform effectively delivers large amounts of government information to enterprises through digital technology. Moreover, based on the publication of policies, the platform elaborates on policy details through expert interpretation and other means, facilitating enterprises’ interpretation 5 and fostering a more accurate understanding. This enables enterprises to duly comply with relevant policies and leverage government policy support (Liao, 2021 ), thereby improving digital transformation. This study proposes thus: H2 Interactive information exchange on the Internet Plus government service platform promotes CDT. 3.3 Interactive actions and CDT The process of governments and enterprises conducting business on the Internet Plus government service platform typifies interactive action. Enterprises’ resource bases influence their competitiveness and CDT (Eller et al., 2020 ). With traditional business models disrupted, enterprises struggle to adapt to the new environment. The complexity of digital resource allocation makes it difficult to predict resource needs, limiting CDT. However, by improving resource efficiency and optimizing resource matching, they can generate internal and external resource synergy, promoting digital resource integration and accelerating CDT (Amit and Han, 2017 ). From a resource coordination perspective, the Internet Plus government service platform serves as a digital governance method and migrates offline government services online, thereby expanding the geographic and spatial scope for enterprises to exchange information (Hanisch et al., 2023 ). Online platforms save time and costs for enterprises, reducing the institutional transaction costs and enhancing the resource utilization efficiency. Additionally, as an integrated service department, the Internet Plus government service platform consolidates government procedures, reducing redundant information entries and shortening business processes (Liang et al., 2019 ). Simultaneously, through the reform 6 , the Internet Plus government service platform effectively reduces resource waste from human errors, accelerating services and creating surplus resources for CDT. Surplus resources help maintain internal resources input for CDT during difficult times and serve as a buffer against potential failure(Fredrich et al., 2019 ), thereby sustaining the transformation process. From the perspective of external resource coordination, the Internet Plus government service platform precisely identifies enterprises’ governmental needs through an Internet-based mechanism. It relays this information to relevant departments for personalized handling, achieving precise supply-demand matching. This precise supply output optimizes the supply-side of government services, enabling the fastest response to enterprises’ needs and safeguarding enterprise rights (Pan et al., 2022 ), thus allowing enterprises to access the external resources most needed. Therefore, the platform enhances enterprises' ability to anticipate resource needs, improving external coordination through accurate matching. During CDT, enterprises must acquire external resource support. However, given the rapid changes in the digital age, enterprises often struggle to identify and obtain the necessary resources, which may engender inefficient resource accumulation (Zhang et al., 2023 ). Anticipating resources can reduce delays in resource searching, guiding enterprises to acquire external governmental resources more timeously, bridging the resource gap, and promoting CDT. Therefore, this study proposes that: H3 The interaction in handling governmental affairs on the Internet Plus government service platform promotes CDT. 4. Methodology 4.1 Data and sample In 2017, China enacted the Internet Plus government services platform Technology System Construction Guide 7 , standardizing the construction of the Internet Plus government service platform. In 2016, the digital economy initiative 8 was first proposed. However, considering the time lag between policy issuance and implementation, companies began significantly promoting CDT in 2017. Meanwhile, the Chinese government introduced Guidelines on Deepening the Internet Plus Advanced Manufacturing to Develop the Industrial Internet 9 . We select A-share listed companies on the Shanghai and Shenzhen Stock Exchanges during 2017–2022 as the research sample and process the sample thus: (1) exclude special treatment companies and those in the financial sector to avoid the impact of special companies and industries; and (2) exclude samples with missing key variable data. The final sample contains 16,707 firm-year observations. The Internet Plus government service platform data are collected from Chinese prefecture-level cities. These data are manually gathered from each p city's government website work and supervision annual report. As these reports are included in the performance evaluations conducted by the General Office of the State Council of the People's Republic of China 10 , the data benefit from being timely, standardized, and authoritative. Corporate financial data are obtained from the China Stock Market and Accounting Research database. Notably, CDT data are manually collected from the annual reports of listed companies. To mitigate the impact of outliers, all continuous variables are winsorized at the 1% level. 4.2 Variable measurement 4.2.1 Interactive intentions Interactive intentions consist of two variables: government and corporate participation. Government participation uses the total number of municipal government-operated websites in the current year, while corporate participation uses the number of registered users, messages received by the government platform, and opinions. Interactive intentions ( Part ) are the sum of government and corporate participation, which are nondimensionalized within [0-100] using an equal weighting method. Finally, we take logarithms of the number plus one. 4.2.2 Interactive equipment Information exchange and sharing between government and enterprises typifies interactive equipment ( IE ). It is measured by the quantity of government interpretation materials, interpretation products, media commentary articles, message processing rate (processed messages divided by the number of received messages), and the disclosure rate of survey results (disclosed periods divided by total survey periods). These variables are nondimensionalized within [0-100] using an equal weighting method, whereafter we take the logarithm of the number plus one. 4.2.3 Interactive actions For interactive actions, we use the process of enterprises handling government affairs on government service platforms as proxy variables ( Legal ). This is measured by the total number of government affairs handled by legal entities through the platform, standardized based on two indicators: the total number of service items reserved, declared, queried, and processed online, and the total number of processed applications by legal entities. These normalized values are then nondimensionalized within [0-100] using an equal weighting method. Finally, we take logarithms of the number plus one. 4.2.4 CDT Referring to Wu et al. ( 2021 ), CDT is likely to be reflected in guiding and summary documents including annual reports. Therefore, this study measures CDT by analyzing the frequency of relevant keywords in listed companies' annual reports. ata collection begins with Python crawlers to compile the reports, followed by using Java PDFBox to create a preliminary digital transformation data pool. Classic authoritative reports are consulted to determine CDT-related keywords, excluding negation words like "not" and filtering out unrelated terms. Based on the refined keywords, the frequency of corresponding keywords in the annual reports is calculated to construct a CDT index system comprising five major categories of keywords. Following Zheng et al ( 2023 ), Table 1 provides more details, and the frequencies of the key technological directions were aggregated to construct the degree of CDT. Considering that CDT frequency may only represent future expectations and exhibit right-skewed characteristic, this study takes the logarithm of the number plus one to measure CDT ( DCG ). Table 1 Structural of CDT measurement Category Keywords Artificial intelligence technology Artificial Intelligence, Business Intelligence, Image Understanding, Investment Decision Support Systems, Intelligent Data Analysis, Intelligent Robots, Machine Learning, Deep Learning, Semantic Search, Biometric Technology, Face Recognition, Voice Recognition, Identity Verification, Autonomous Driving, Natural Language Processing. Big data technology Big Data, Data Mining, Text Mining, Data Visualization, Heterogeneous Data, Credit Reporting, Augmented Reality, Mixed Reality, Virtual Reality Cloud computing technology Cloud Computing, Stream Computing, Graph Computing, In-Memory Computing, Multiparty Secure Computing, Neuromorphic Computing, Green Computing, Cognitive Computing, Converged Architecture, Billion-level Concurrency, Exabyte-level Storage, Internet of Things, Cyber-Physical Systems Blockchain technology Blockchain, Digital Currency, Distributed Computing, Differential Privacy Technology, Smart Financial Contracts Application of digital technology Mobile Internet, Industrial Internet, Mobile Connectivity, Internet Healthcare, E-commerce, Mobile Payment, Third-party Payment, NFC Payment, Smart Energy, B2B, B2C, C2B, C2C, O2O, Internet of Vehicles, Smart Wearables, Smart Agriculture, Smart Transportation, Smart Healthcare, Smart Customer Service, Smart Home, Smart Investment Advisory, Smart Cultural Tourism, Smart Environmental Protection, Smart Grid, Smart Marketing, Digital Marketing, Unmanned Retail, Internet Finance, Digital Finance, Fintech, Financial Technology, Quantitative Finance, Open Banking. Following Wu et al., ( 2021 ) and Zheng et al ( 2023 ), this study uses the frequencies of the key technological directions to construct the degree of CDT [Insert Table 1 here] 4.3 Research design To verify H1, H2 , and H3 , we construct the following model: $$\:{DCG}_{i,t}={\alpha\:}_{0}+{\alpha\:}_{1}{X}_{i,t}+{\sum\:\alpha\:}_{2}{Controls}_{i,t}+\sum\:Year+\sum\:Lnd+\sum\:Province+{\epsilon\:}_{i,t}$$ 1 where DCG represents CDT degree and X represents various indicators related to the construction of the Internet Plus government service platform, including participation from both sides ( Part ), information exchange and sharing ( IE ), and the affairs of handling the interaction of legal entities ( Legal ). Following Chen et al. ( 2023 ), Controls represent a series of control variables including (1) firm financial characteristics: firm size ( Size ), leverage ( Lev ), profitability ( Roa ), growth rate ( Growth ), cash holding ( Cash ), whether it is in a loss state ( Loss ), proportion of intangible assets ( Intangible ), and capital intensity ( Sd ). (2) Company governance characteristics: duality ( Dual ), equity concentration ( Top10 ), and board size (Board). (3) Other enterprise characteristics: enterprise age ( Age ). We also control for industry ( Ind ), year ( Year ), and province ( Province ) fixed effects. Main variables are defined in the Appendix. 5. Empirical Results 5.1 Main analysis Table 2 presents the descriptive statistics. The mean of DCG is 1.786 and standard deviation is 1.410, suggesting significant CDT variations among enterprises. The means of Part , IE , and Legal are 2.426, 1.845, and 2.320, with standard deviations of 1.575, 0.806, and 1.600, respectively, indicating an imbalance in the development of the Internet Plus government service platform across different regions. Table 2 Descriptive Statistics This table reports the descriptive statistics of influencing factors, and control variables. All variables are defined in Appendix. VARIABLE OBS MEAN STD 5% 25% MEDIAN 75% 95% Part 16707 2.426 1.575 0.000 0.993 2.844 3.834 4.615 IE 16707 1.845 0.806 0.000 1.269 1.702 2.275 4.615 Legal 16707 2.320 1.600 0.000 0.444 2.804 3.690 4.615 DCG 16707 1.786 1.410 0.000 0.693 1.609 2.773 5.283 Size 16707 22.271 1.282 20.080 21.340 22.050 22.97 26.39 Lev 16707 0.402 0.198 0.057 0.242 0.394 0.543 0.918 Roa 16707 0.036 0.076 -0.366 0.015 0.041 0.072 0.217 Growth 16707 0.148 0.343 -0.558 -0.030 0.102 0.257 1.974 Cash 16707 0.190 0.131 0.018 0.097 0.155 0.248 0.648 Loss 16707 0.132 0.338 0.000 0.000 0.000 0.000 1.000 Intangible 16707 0.044 0.047 0.000 0.017 0.032 0.053 0.309 Dual 16707 0.347 0.476 0.000 0.000 0.000 1.000 1.000 Top10 16707 0.592 0.152 0.234 0.482 0.602 0.710 0.907 Board 16707 2.213 0.170 1.792 2.079 2.303 2.303 2.639 Age 16707 2.950 0.306 2.079 2.773 2.996 3.178 3.555 Sd 16707 0.459 0.636 0.002 0.165 0.293 0.525 29.048 [Insert Table 2 here] Table 3 presents the results of Model (1). In Column (1), the coefficient of Part is 0.026, which is significant at the 1% level, indicating that the participation of both the government and enterprises can promote CDT, supporting H1 . Regarding economic significance, for each standard deviation increase in Part , the CDT degree increases by 2.29% (= (0.026 × 1.575) / 1.786). In Column (2), the coefficient of IE is 0.051, which is significant at the 1% level, suggesting that information exchange and sharing between the government and enterprises promotes CDT, supporting H2 . Economically, each standard deviation increase in IE results in a 2.30% rise in CDT degree (= (0.051 × 0.806) / 1.786). In Column (3), the coefficient of Legal is 0.030, which is significant at the 1% level, indicating that the interaction between the government and enterprise legal entities in handling government affairs promotes CDT, supporting H3 . Regarding economic significance, for each standard deviation increase in Legal , the degree of CDT increases by 2.69% (= (0.030 × 1.600) / 1.786). Table 3 Main analysis Standard errors are clustered at firm level. Industry fixed effect, year fixed effect and province fixed effect are both controlled in all regressions. *, ** , and *** indicates statistical significance at the 10%, 5%, and 1% level, respectively. (1) (2) (3) DCG DCG DCG Part 0.026 *** (0.009) IE 0.051 *** (0.018) Legal 0.030 *** (0.008) Size 0.198 *** 0.198 *** 0.198 *** (0.016) (0.016) (0.016) Lev -0.160 -0.162 -0.161 (0.100) (0.100) (0.100) Roa -0.655 *** -0.655 *** -0.660 *** (0.227) (0.227) (0.227) Growth -0.087 *** -0.088 *** -0.088 *** (0.030) (0.030) (0.030) Cash 0.854 *** 0.855 *** 0.854 *** (0.149) (0.149) (0.149) Loss 0.060 0.060 0.059 (0.042) (0.042) (0.042) Dual 0.079 *** 0.079 *** 0.079 *** (0.030) (0.030) (0.030) Intangible 0.219 0.220 0.222 (0.350) (0.350) (0.350) Top10 -0.268 ** -0.269 ** -0.269 ** (0.106) (0.106) (0.106) Board 0.059 0.060 0.059 (0.088) (0.088) (0.088) Age -0.127 ** -0.127 ** -0.127 ** (0.055) (0.055) (0.055) Sd -0.144 *** -0.144 *** -0.144 *** (0.035) (0.035) (0.035) Constant -2.316 *** -2.348 *** -2.322 *** (0.373) (0.374) (0.374) N 16707 16707 16707 Adj.R 2 0.45 0.45 0.45 [Insert Table 3 here] 5.2. Robustness test 5.2.1 Propensity score matching To address endogeneity issues from sample selection, we employ propensity score matching (PSM). First, 1/3 is selected as the cut-off point for group samples. We assign the lower 1/3 of Part ( IE, Legal ) as the control group and the higher 1/3 of Part ( IE, Legal ) as the experimental group. Following You et al. ( 2021 ), we implement one-to-one nearest neighbor matching without replacement, with a caliper set to 0.05 times the standard error of the propensity score. The matching variables include all the control variables of Model (1). Additionally, we control for the fixed effects of year, industry, and province. Column (1)-(3) of Table 4 presents the results after using the matched samples in Model (1). Part , IE , and Legal are all significant, supporting the original hypotheses. Table 4 Robustness Test Standard errors are clustered at firm level. Industry fixed effect, year fixed effect and province fixed effect are both controlled in all regressions. *, ** , and *** indicates statistical significance at the 10%, 5%, and 1% level, respectively. (1) (2) (3) (4) Stae2 (5) Stage2 (6) Stage2 DCG DCG DCG DCG DCG DCG Part 0.048 *** 0.025 *** (0.017) (0.009) IE 0.129 * 0.050 *** (0.074) (0.018) Legal 0.045*** 0.031 *** (0.014) (0.008) Size 0.201 *** 0.207 *** 0.198*** 0.196 *** 0.195 *** 0.196 *** (0.020) (0.026) (0.020) (0.025) (0.025) (0.025) Lev -0.155 0.007 -0.241* -0.159 -0.160 -0.159 (0.132) (0.163) (0.130) (0.101) (0.101) (0.101) Roa -0.731 ** -0.218 -1.437*** -0.638 *** -0.638 *** -0.642 *** (0.357) (0.407) (0.333) (0.232) (0.232) (0.232) Growth -0.065 -0.076 -0.054 -0.089 *** -0.090 *** -0.090 *** (0.048) (0.066) (0.046) (0.031) (0.031) (0.031) Cash 0.966 *** 1.058 *** 1.079*** 0.849 *** 0.849 *** 0.849 *** (0.213) (0.272) (0.207) (0.158) (0.158) (0.158) Loss 0.123 ** 0.072 0.068 0.060 0.061 0.060 (0.062) (0.085) (0.062) (0.042) (0.042) (0.042) Dual 0.072 * 0.094 * 0.011 0.080 *** 0.080 *** 0.080 *** (0.039) (0.049) (0.040) (0.031) (0.031) (0.031) Intangible 0.524 -0.098 0.290 0.252 0.252 0.255 (0.455) (0.498) (0.479) (0.359) (0.359) (0.359) Top10 -0.262 ** -0.282 * -0.142 -0.268 ** -0.268 ** -0.268 ** (0.128) (0.165) (0.138) (0.106) (0.107) (0.106) Board 0.140 0.094 0.025 0.040 0.041 0.040 (0.113) (0.136) (0.115) (0.090) (0.090) (0.090) Age -0.158 ** -0.141 * -0.077 -0.147 ** -0.147 ** -0.147 ** (0.068) (0.083) (0.072) (0.058) (0.058) (0.058) Sd -0.168 *** -0.214 *** -0.230*** -0.143 *** -0.142 *** -0.142 *** (0.058) (0.080) (0.050) (0.036) (0.036) (0.036) Imr -0.045 -0.048 -0.046 (0.236) (0.236) (0.236) Constant -2.528 *** -2.833 *** -2.447*** -2.167 *** -2.191 *** -2.175 *** (0.470) (0.589) (0.496) (0.626) (0.627) (0.626) N 6208 3518 6204 16451 16451 16451 Adj.R2 0.45 0.44 0.45 0.45 0.45 0.45 [Insert Table 4 here] 5.2.2 Heckman two-stage analysis CDT is the process whereby companies introduce digital solutions such as the Internet of Thing . Therefore, companies that have already initiated digital transformation typically have more comprehensive digital devices than those that have not yet engaged and are more capable of accessing digital governance equipment such as the Internet Plus government service platform. Additionally, companies that have entered CDT can more directly perceive the value of information in the digital era and are thus more willing to join online platform. Based on these two points, sample selection bias may exist, so we further use the Heckman two-stage model. Following Liu et al. ( 2023 ), the model adds the Internet ( Internet ) as an exogenous variable. Internet represents the interaction between the lagged national Internet user count and the 1984 fixed-line telephone count in the company's registered city. Because the number of fixed-line telephones in each city is cross-sectional, time series variables are introduced to create panel data. The inverse Mills ratio ( Imr ) is obtained in the first stage and then used as a control variable in Model (1). Column (4)-(6) of Table 4 shows the results of the Heckman two-stage analysis. The coefficients of Part , IE , and Legal are still positively significant, indicating that the results remain valid. 6. Conclusion The Internet Plus government service platform addresses enterprises' complex administrative needs, facilitating CDT. At the interactive intention level, corporate participation enhances reputation and grants access to critical transformation resources; government participation improves the business environment and creates financing channels, promoting CDT. This study has important implications for both government and companies. First, regarding interactive intention, the government can increase participation on the Internet Plus government service platform through two initiatives. The first is through administrative orders to emphasize the participation of the government and businesses on the platform, urging local administrative departments and business to fully engage. The second initiative focuses on bridging the digital divide by expanding the government service platform comprehensively. Given the economic and technological disparities across regions, the government should increase support for administrative departments and businesses in disadvantaged areas. Second, in terms of interactive equipment, the government must optimize the information quality and communication efficiency of the Internet Plus government service platform. The government should continuously improve the timeliness, accuracy, and clarity of policies published on the platform, thereby reducing information search cost for enterprises. Meanwhile, the government should actively interpret and respond to trending policies on the platform, facilitating the public's maximum understanding of new policies. The government should also effectively monitor corporate operations through the government service platform, quickly respond to business development issues, and achieve efficient communication. Additionally, the government can collaborate with third-party Internet platforms, building multi-platform to improve communication efficiency. Finally, regarding interactive actions, the government must enhance the efficiency of administrative handling and the precision of matching needs and demands. Government departments should further expand the types of online services handled to meet enterprises’ diverse service needs during CDT. Simultaneously, integrating and optimizing service processes, along with enhancing information-sharing mechanisms, can help reduce business handling costs and waiting times. The government should deeply understand enterprise needs and improve the precision of supply-demand matching, providing enterprises with appropriate policy resources. This study has some limitations that require further research. First, owing to the integrated and novel nature of the Internet Plus government service platform, there is currently no unified measurement method. This study analyzes data from government website reports, and future research could integrate other measurement methods, including textual analysis, to enhance measurement validity. Second, while this study attempts a comprehensive quantitative analysis of government-business interaction on the platform through participation, information exchange, and administrative handling, real-world interactions are more complex. Future research could conduct heterogeneity analysis in different regions and industries to deeply analyze how the Internet Plus government service platform affects CDT in different environments. 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The State Council of the People’s Republic of China.(2017) Guidelines of The State Council on Deepening 'Internet Plus Advanced Manufacturing' to develop industrial Internet. Available at: https://www.gov.cn/zhengce/content/2017-11/27/content_5242582.htm . The State Council of the People’s Republic of China. (2018) Circular of The General Office of the State Council on doing a good job in publishing annual reports on government websites. Available at: https://www.gov.cn/zhengce/content/2018-01/22/content_5259190.htm . Additional Declarations No competing interests reported. Supplementary Files Appendix.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6903235","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":478858315,"identity":"05d6e7f3-de7f-40a4-8721-173dd417dfe1","order_by":0,"name":"Wanyi Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYFACHhiD+QAzmD5AvBa2BJK18BgQp8W8vffggx81dvIGN3I+fy5sY5Dju5HA+LkAjxaZM+eSDXuOJRtuuJG7TXpmG4Ox5I0EZukZeLRISOSYSTM2MCeYAbUw87YxJG64kcDGzINPi/wb89+MDfVALTmPPwO11BPWIsFjxszYcBikhUEaqCXBgKAWnrxkyZ5jxw33n3lmJs1zTsJw5pmHzdJ4tbCfPfjhR021vGR78uPPPGU28nzHkw9+xqcFAQQSwEYAMWMDURoYGPgPEKlwFIyCUTAKRhwAAMiDSH5avrSaAAAAAElFTkSuQmCC","orcid":"","institution":"Shanghai University","correspondingAuthor":true,"prefix":"","firstName":"Wanyi","middleName":"","lastName":"Chen","suffix":""},{"id":478858316,"identity":"1ba02642-4165-4c5c-8ff1-a6d2137bfeb0","order_by":1,"name":"Dongao Ji","email":"","orcid":"","institution":"Shanghai University","correspondingAuthor":false,"prefix":"","firstName":"Dongao","middleName":"","lastName":"Ji","suffix":""}],"badges":[],"createdAt":"2025-06-16 08:23:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6903235/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6903235/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85849656,"identity":"26e2f2f6-f508-4a90-9130-4da9d3c647d5","added_by":"auto","created_at":"2025-07-02 10:10:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47182,"visible":true,"origin":"","legend":"\u003cp\u003eInteractive governance framework of Internet Plus government service platform\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6903235/v1/dc3bf1fc8eb072d07b50fe65.jpg"},{"id":85850674,"identity":"eda14db3-191a-41dd-8371-a7f2129d3c73","added_by":"auto","created_at":"2025-07-02 10:18:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1218564,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6903235/v1/bd8f56a2-37a8-4de9-8953-fe2d0eb8f7dd.pdf"},{"id":85849655,"identity":"ef0ec7e5-23c9-45ae-84e1-bec7c6a0173a","added_by":"auto","created_at":"2025-07-02 10:10:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15631,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-6903235/v1/1a930ed9b93c05b31bba4819.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Internet Plus government service platform and corporate digital transformation","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn recent years, digital technologies, such as cloud computing, has revolutionized traditional business models, fundamentally altering how businesses evolve and engage with stakeholders. Consequently, corporate digital transformation (CDT) has emerged as a strategic pathway for firms to harness digital technologies in crafting more advantageous business models, serving as an effective mechanism for sustainable growth (Cheng et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, the CDT process is complex and protracted, requiring substantial financial investment from enterprises (Hess et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), generally engendering low success rates. The existing literature predominantly investigates CDT influencing factors from a firm\u0026rsquo;s perspective (Bouncken and Barwinski, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). With government policy adjustments in the post-pandemic era, the current literature focuses on the impact of macro-level policies on CDT, including tax policies (Chen et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and government subsidies (Bratta et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, less attention is paid to digital governance.\u003c/p\u003e \u003cp\u003eDigital governance leverages information technology to optimizes social relational networks and communication models through massive data exchange (Hanisch et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In recent years, digital governance platforms, exemplified by the Internet Plus government service platform, have gained widespread attention. These platforms help governments address complex administrative demands through digital technology (Janowski et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), aiming to foster innovation-driven development and enhance the efficiency and effectiveness of governmental services by integrating Internet technology with traditional operations. Since 2015, China has launched the Internet Plus government service platform initiative to modernize its national governance system and capabilities. Accordingly, digital governance platforms have facilitated the transformation and optimization of administrative service by enhancing government performance (Allen et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), standardizing government information (Louren\u0026ccedil;o, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), profoundly altering the representation and dissemination of various social administrative resources (Conradie and Choenni, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and optimizing government administration (Cellary and Rykowski, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, the highly procedural characteristics of government digital governance may impair organizational adaptability (Hanisch et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Current literature emphasizes the impact of digital governance on firms\u0026rsquo; short-term operational effects (M\u0026ouml;hlmann et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Commerford, 2021) and less on long-term corporate strategic development.\u003c/p\u003e \u003cp\u003eChina has achieved significant progress in digitalization in recent years. In 2022, the scale of the Chinese digital economy accounted for 41.5% of its GDP, ranking second globally\u003csup\u003e1\u003c/sup\u003e. In recent years, the Internet Plus government service platform has been the focus of China\u0026rsquo;s governance transformation. Since 2015, China has identified digital governance as a national strategy and has introduced a series of supporting policies including \u003cem\u003eInternet Plus\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e. The \u003cem\u003eFourteenth Five-Year Plan\u003c/em\u003e\u003csup\u003e3\u003c/sup\u003e further incorporates the construction of a digital society and government, as well as the level of social digitalization and intelligence. Digital governance addresses departmental silos and provides insights into global issues like redundant construction and inefficiency (Kuhlmann and Heuberger, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, this study focuses on Chinese digital governance reform, discussing the Chinese digital governance model represented by the Internet Plus government service platform to provide practical guidance for improving digital governance in other developing countries.\u003c/p\u003e \u003cp\u003eThis study takes A-share listed companies on the Shanghai and Shenzhen Stock Exchanges during 2017\u0026ndash;2022 as samples. Using the theory of interactive governance, this study finds that the Internet Plus government service platform facilitates CDT from three perspectives: interactive intentions, equipment, and actions. Specifically, interactive intentions promote CDT by increasing corporate exposure and reputation, while optimizing the business environment, thereby alleviating CDT resource constraints. Interactive equipment enhances CDT capacity by enriching information reception and improving corporate digital literacy. Interactive actions accelerate the CDT process by optimizing the coordination of enterprises\u0026rsquo; internal and external resources.\u003c/p\u003e \u003cp\u003eThis study makes three fundamental contributions. First, it extends the governance effects of digital government platforms on corporate strategic transformation. The existing literature on the economic consequences of digital governance largely focuses on government governance outcomes and market reactions, including the quality of government services (Sieber and Johnson, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), public participation (Ojo and Mellouli, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and market development (Janowski et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The impact on enterprises mainly concerns short-term business operations, including corporate risk (Commerford et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and operational efficiency (M\u0026ouml;hlmann et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), with less attention to long-term corporate strategies.\u003c/p\u003e \u003cp\u003eSecond, this study extends the macro-governance factors influencing CDT. Extensive research has discussed CDT factors from firm characteristics including corporate culture (Cichosz et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), digital strategy (Singh et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and personnel characteristics (Eller et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Alnuaimi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Some studies have also focused on the impact of government policies rather than government governance methods (Chen et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Bratta et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThird, this study provides significant practical insights for governments and corporations. From the government's standpoint, this study presents crucial guidance for government involvement and leadership in CDT initiatives, advising governments on the active advancement of digital government platforms to sculpt policies and business environments that support CDT. This study assists firms in better utilize digital government platforms for accessing the necessary resources for CDT, thereby promoting further development.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 The influencing factors of CDT\u003c/h2\u003e \u003cp\u003eThe existing literature examines the factors influencing CDT from both macro-level policies and micro-level enterprise characteristics. From the macro-level policy perspective,, tailored target policies are more conducive when local economic growth target policies are misaligned with CDT (Yang et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, tax cuts (Chen et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and government subsidy policies (Bratta et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) contribute to CDT.\u003c/p\u003e \u003cp\u003eFrom the enterprise characteristic perspective, the main considerations include corporate culture, strategy, and organizational personnel. Digital culture promotes the use of digital equipment, thereby improving organizational digital performance (Eller et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Additionally, digital culture fosters CDT by setting realistic expectations for technology (Cichosz et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The ability to perceive trends in environmental changes and the capacity to seize opportunities have also been proposed as essential cultural characteristics of CDT (Dong et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). From a corporate strategy perspective, digital strategy acts as a driving factor (Bouncken and Barwinski, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Digital strategy alliances promote synergistic effects (Singh et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), thus influencing CDT efforts. Knowledge sharing among alliance partners facilitates CDT success (Siachou et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, a firm's dynamic capability strategy can promote adaptation to CDT (Teece and Leih, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). From the corporate personnel characteristic perspective, employees with relevant skills, demonstrating professionalism and digital transformational leadership, serve as effective motivating factors regarding CDT (Eller et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Organizational agility also plays a facilitative role in CDT (Alnuaimi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 The economic consequences of digital governance\u003c/h2\u003e \u003cp\u003eDigital governance methods, represented by the Internet Plus government service platform, benefit from a technological backdrop. They leverage Internet technology to transform traditional methods of data storage, retrieval, preservation and utilization within organizations (Conradie and Choenni, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This innovative approach directly advances the transition from abstract, generalized public sector data to open, usable datasets. Given the characteristics of digital governance methods, the current literature focuses on three aspects: government performance management, market transactions, and enterprise performance.\u003c/p\u003e \u003cp\u003eFrom the perspective of government performance management, digital governance has four advantages. First, the open-data characteristic of digital governance promotes data circulation, aiding governments in data acquisition, thereby facilitating the provision of richer and more accurate data to market entities for service improvement (Sieber and Johnson, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Second, digital governance can enhance public participation in government decision-making (Ojo and Mellouli, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Third, digital governance reduces public resource waste and maximizes public sector performance. (Allen et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Fourth, as government information becomes more accessible and retrievable, digital governance can also encourage improved quality of government information disclosure through supervision (Louren\u0026ccedil;o, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom a market transaction perspective, digital governance can also serve as a channel between multiple types of market entities to promote market transactions. Moreover, from an overall development perspective, digital governance can effectively optimize the business environment by influencing citizens' habits (Fan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and further promote sustainable market development (Janowski et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFirst, from the perspective of corporate performance, digital governance increases information flows within enterprises, effectively mitigating agency problems (Commerford et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Second, digital governance can enhance the efficiency of platform-based enterprise managers through algorithmic monitoring (M\u0026ouml;hlmann et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Finally, by disclosing information, digital governance helps enterprises attract potential customers and enhance reputation (Hanisch et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn summary, contemporary research mainly addresses the impact of digital governance on governments and markets, with limited focus on its influence on long-term corporate strategies. The macro factors influencing CDT have mainly centered on policy content rather than on digital governance methods. This study focuses on the impact of digital governance on corporate digital strategies.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Hypothesis Development","content":"\u003cp\u003eInteractive governance is defined as a complex process wherein multiple social and political actors with divergent interests mobilize, communicate, and deploy actions to formulate, promote, and achieve common goals (Torfing et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). It\u0026rsquo;s analytical framework comprises three elements: interactive intentions, equipment, and actions (Fan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Based on the characteristics of the Internet Plus government service platform, this study situates these dimensions, constructing a framework, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003cp\u003eInteractive intention refers to the convergence of visions and values among multiple social and political actors to achieve common goals. Within the Internet Plus government service platform, the participation levels of government and business entities drive the CDT process. Hence, the participation levels of these two entities together constitute interactive intentions. Static participation refers to the scale of entities, including the number of government departments and enterprises, joining the platform. Dynamic participation refers to the number of information posts by both entities on a platform. Interactive equipment refers to the resources available to each entity and the systems for sharing such resources. On the Internet Plus government service platform, businesses require information for operations and transformation requirements while the government possesses abundant informational resources. The exchange and sharing of this information constitute the interactive equipment dimension.. The process of businesses handling administrative tasks on the platform typifies the interactive action dimension.\u003c/p\u003e \u003cp\u003eIn summary, interactive governance within the Internet Plus government service platform demonstrates a progressive logical relationship. Governments and enterprises first enter the platform through static and dynamic participation using the platform's information for both unilateral and bilateral communication modes, ultimately accomplishing administrative tasks. This study explores the impact mechanisms of the Internet Plus government service platform on CDT under three different interaction modes.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Interactive intention and CDT\u003c/h2\u003e \u003cp\u003eThe Internet Plus government service platform primarily includes two key entities: the government and enterprises, whose participation level represents their interactive intentions. As CDT entails a comprehensive reshaping of enterprises, it demands substantial and sustained financial investment (Jia et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, the lengthy CDT process and delayed results may face discrimination from financial institutions when seeking financing, further restricting CDT (Hess et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Increased participation on the Internet Plus government service platform can alleviate financing constraints from the following two perspectives, offering financial support for CDT.\u003c/p\u003e \u003cp\u003eFrom the enterprise perspective, increased participation on the Internet Plus government services platform leads to greater information disclosure through this official governmental channel. Releasing information on government-recognized platform can have a certifying effect (Guo et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), signaling to the public that the enterprise is in compliance with policy, thus enhancing the company's social reputation (Hanisch et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A good reputation, as a risk filter, can prove that the enterprise can actively fulfill its commitments to stakeholders, reduce investors' anticipated costs of contractual breaches, and ease the enterprise's financing constraints (Bajo et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This provides a stable funding source for CDT.\u003c/p\u003e \u003cp\u003eFrom the government's perspective, local governments enhance participation on the Internet Plus government service platform under the guidance\u003csup\u003e4\u003c/sup\u003e, increasing the number of administrative departments joining the platform. This allows companies to handle a wider variety of governmental services quickly on the platform, improving the quality of administrative services from diverse perspectives. As government participation grows, the focus shifts from the number of governments joining the Internet Plus platform to the services quality. The Enhanced service quality will further improve the business environment by optimizing administrative conditions. The openness of a favorable business environment, by building an ecological context (Chae, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), promotes market development while attracting domestic and foreign investment, thus providing enterprises with multi-channel resource supplies, expanding financing channels for enterprises (Pan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), further easing financing constraints, and promoting CDT. Therefore, this study proposes that:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eH1\u003c/strong\u003e \u003cp\u003e \u003cem\u003eParticipation on the Internet Plus government service platform promotes CDT.\u003c/em\u003e \u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Interactive equipment and CDT\u003c/h2\u003e \u003cp\u003eOwing to the complexity and high-risk nature of CDT (Yao et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), enterprises increasingly need to utilize information flexibly for decision-making during the transformation (Aben et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). When abundant information complicates CDT, ability to interpret and analyze information is crucial for acquiring key information resources, which affects CDT (Gupta and Bose, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The interactive equipment on the Internet Plus government service platform, providing a richer information source for the entire market environment (Sieber and Johnson, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This gradually enhances enterprises' digital literacy in interpreting information and promotes CDT.\u003c/p\u003e \u003cp\u003eFirst, abundant information stemming from communication and interaction with the government can encourage businesses to learn and recognize environmental changes, thereby enhancing the perception of environmental trends. On one hand, enhanced perception helps enterprises recognize environmental changes, make timely adjustments (Ghosh et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), better integrate with the external macro environment and fosters CDT-related knowledge exchanges (Bouncken and Barwinski, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), thus formulating appropriate CDT strategies (Hess et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). On the other hand, by analyzing the environment, perception helps enterprises identify valuable market opportunities and make adjustments (Ritter and Pedersen, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), facilitating CDT (Dong et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSecond, increased information exchange between governmental and market entities strengthens government-enterprise relations ,enabling enterprises to gain political capital, such as more channels to identify policy information related to transformation (Casanueva et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The Internet Plus government service platform effectively delivers large amounts of government information to enterprises through digital technology. Moreover, based on the publication of policies, the platform elaborates on policy details through expert interpretation and other means, facilitating enterprises\u0026rsquo; interpretation\u003csup\u003e5\u003c/sup\u003e and fostering a more accurate understanding. This enables enterprises to duly comply with relevant policies and leverage government policy support (Liao, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), thereby improving digital transformation. This study proposes thus:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eH2\u003c/strong\u003e \u003cp\u003e \u003cem\u003eInteractive information exchange on the Internet Plus government service platform promotes CDT.\u003c/em\u003e \u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Interactive actions and CDT\u003c/h2\u003e \u003cp\u003eThe process of governments and enterprises conducting business on the Internet Plus government service platform typifies interactive action. Enterprises\u0026rsquo; resource bases influence their competitiveness and CDT (Eller et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). With traditional business models disrupted, enterprises struggle to adapt to the new environment. The complexity of digital resource allocation makes it difficult to predict resource needs, limiting CDT. However, by improving resource efficiency and optimizing resource matching, they can generate internal and external resource synergy, promoting digital resource integration and accelerating CDT (Amit and Han, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom a resource coordination perspective, the Internet Plus government service platform serves as a digital governance method and migrates offline government services online, thereby expanding the geographic and spatial scope for enterprises to exchange information (Hanisch et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Online platforms save time and costs for enterprises, reducing the institutional transaction costs and enhancing the resource utilization efficiency. Additionally, as an integrated service department, the Internet Plus government service platform consolidates government procedures, reducing redundant information entries and shortening business processes (Liang et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Simultaneously, through the reform\u003csup\u003e6\u003c/sup\u003e, the Internet Plus government service platform effectively reduces resource waste from human errors, accelerating services and creating surplus resources for CDT. Surplus resources help maintain internal resources input for CDT during difficult times and serve as a buffer against potential failure(Fredrich et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), thereby sustaining the transformation process.\u003c/p\u003e \u003cp\u003eFrom the perspective of external resource coordination, the Internet Plus government service platform precisely identifies enterprises\u0026rsquo; governmental needs through an Internet-based mechanism. It relays this information to relevant departments for personalized handling, achieving precise supply-demand matching. This precise supply output optimizes the supply-side of government services, enabling the fastest response to enterprises\u0026rsquo; needs and safeguarding enterprise rights (Pan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), thus allowing enterprises to access the external resources most needed. Therefore, the platform enhances enterprises' ability to anticipate resource needs, improving external coordination through accurate matching. During CDT, enterprises must acquire external resource support. However, given the rapid changes in the digital age, enterprises often struggle to identify and obtain the necessary resources, which may engender inefficient resource accumulation (Zhang et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Anticipating resources can reduce delays in resource searching, guiding enterprises to acquire external governmental resources more timeously, bridging the resource gap, and promoting CDT. Therefore, this study proposes that:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eH3\u003c/strong\u003e \u003cp\u003e \u003cem\u003eThe interaction in handling governmental affairs on the Internet Plus government service platform promotes CDT.\u003c/em\u003e \u003c/p\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Methodology","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Data and sample\u003c/h2\u003e \u003cp\u003eIn 2017, China enacted \u003cem\u003ethe Internet Plus government services platform Technology System Construction Guide\u003c/em\u003e\u003csup\u003e7\u003c/sup\u003e, standardizing the construction of the Internet Plus government service platform. In 2016, the \u003cem\u003edigital economy initiative\u003c/em\u003e \u003csup\u003e8\u003c/sup\u003ewas first proposed. However, considering the time lag between policy issuance and implementation, companies began significantly promoting CDT in 2017. Meanwhile, the Chinese government introduced \u003cem\u003eGuidelines on Deepening the Internet Plus Advanced Manufacturing to Develop the Industrial Internet\u003c/em\u003e\u003csup\u003e9\u003c/sup\u003e. We select A-share listed companies on the Shanghai and Shenzhen Stock Exchanges during 2017\u0026ndash;2022 as the research sample and process the sample thus: (1) exclude special treatment companies and those in the financial sector to avoid the impact of special companies and industries; and (2) exclude samples with missing key variable data. The final sample contains 16,707 firm-year observations.\u003c/p\u003e \u003cp\u003eThe Internet Plus government service platform data are collected from Chinese prefecture-level cities. These data are manually gathered from each p city's government website work and supervision annual report. As these reports are included in the performance evaluations conducted by the General Office of the State Council of the People's Republic of China\u003csup\u003e10\u003c/sup\u003e, the data benefit from being timely, standardized, and authoritative. Corporate financial data are obtained from the China Stock Market and Accounting Research database. Notably, CDT data are manually collected from the annual reports of listed companies. To mitigate the impact of outliers, all continuous variables are winsorized at the 1% level.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Variable measurement\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e4.2.1 Interactive intentions\u003c/h2\u003e \u003cp\u003eInteractive intentions consist of two variables: government and corporate participation. Government participation uses the total number of municipal government-operated websites in the current year, while corporate participation uses the number of registered users, messages received by the government platform, and opinions. Interactive intentions (\u003cem\u003ePart\u003c/em\u003e) are the sum of government and corporate participation, which are nondimensionalized within [0-100] using an equal weighting method. Finally, we take logarithms of the number plus one.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e4.2.2 Interactive equipment\u003c/h2\u003e \u003cp\u003eInformation exchange and sharing between government and enterprises typifies interactive equipment (\u003cem\u003eIE\u003c/em\u003e). It is measured by the quantity of government interpretation materials, interpretation products, media commentary articles, message processing rate (processed messages divided by the number of received messages), and the disclosure rate of survey results (disclosed periods divided by total survey periods). These variables are nondimensionalized within [0-100] using an equal weighting method, whereafter we take the logarithm of the number plus one.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e4.2.3 Interactive actions\u003c/h2\u003e \u003cp\u003eFor interactive actions, we use the process of enterprises handling government affairs on government service platforms as proxy variables (\u003cem\u003eLegal\u003c/em\u003e). This is measured by the total number of government affairs handled by legal entities through the platform, standardized based on two indicators: the total number of service items reserved, declared, queried, and processed online, and the total number of processed applications by legal entities. These normalized values are then nondimensionalized within [0-100] using an equal weighting method. Finally, we take logarithms of the number plus one.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e4.2.4 CDT\u003c/h2\u003e \u003cp\u003eReferring to Wu et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), CDT is likely to be reflected in guiding and summary documents including annual reports. Therefore, this study measures CDT by analyzing the frequency of relevant keywords in listed companies' annual reports. ata collection begins with Python crawlers to compile the reports, followed by using Java PDFBox to create a preliminary digital transformation data pool. Classic authoritative reports are consulted to determine CDT-related keywords, excluding negation words like \"not\" and filtering out unrelated terms. Based on the refined keywords, the frequency of corresponding keywords in the annual reports is calculated to construct a CDT index system comprising five major categories of keywords. Following Zheng et al (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides more details, and the frequencies of the key technological directions were aggregated to construct the degree of CDT. Considering that CDT frequency may only represent future expectations and exhibit right-skewed characteristic, this study takes the logarithm of the number plus one to measure CDT (\u003cem\u003eDCG\u003c/em\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStructural of CDT measurement\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeywords\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArtificial intelligence technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArtificial Intelligence, Business Intelligence, Image Understanding, Investment Decision Support Systems, Intelligent Data Analysis, Intelligent Robots, Machine Learning, Deep Learning, Semantic Search, Biometric Technology, Face Recognition, Voice Recognition, Identity Verification, Autonomous Driving, Natural Language Processing.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBig data technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBig Data, Data Mining, Text Mining, Data Visualization, Heterogeneous Data, Credit Reporting, Augmented Reality, Mixed Reality, Virtual Reality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCloud computing technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCloud Computing, Stream Computing, Graph Computing, In-Memory Computing, Multiparty Secure Computing, Neuromorphic Computing, Green Computing, Cognitive Computing, Converged Architecture, Billion-level Concurrency, Exabyte-level Storage, Internet of Things, Cyber-Physical Systems\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlockchain technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlockchain, Digital Currency, Distributed Computing, Differential Privacy Technology, Smart Financial Contracts\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApplication of digital technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMobile Internet, Industrial Internet, Mobile Connectivity, Internet Healthcare, E-commerce, Mobile Payment, Third-party Payment, NFC Payment, Smart Energy, B2B, B2C, C2B, C2C, O2O, Internet of Vehicles, Smart Wearables, Smart Agriculture, Smart Transportation, Smart Healthcare, Smart Customer Service, Smart Home, Smart Investment Advisory, Smart Cultural Tourism, Smart Environmental Protection, Smart Grid, Smart Marketing, Digital Marketing, Unmanned Retail, Internet Finance, Digital Finance, Fintech, Financial Technology, Quantitative Finance, Open Banking.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eFollowing Wu et al., (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Zheng et al (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), this study uses the frequencies of the key technological directions to construct the degree of CDT\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Research design\u003c/h2\u003e \u003cp\u003eTo verify \u003cb\u003eH1, H2\u003c/b\u003e, and \u003cb\u003eH3\u003c/b\u003e, we construct the following model:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{DCG}_{i,t}={\\alpha\\:}_{0}+{\\alpha\\:}_{1}{X}_{i,t}+{\\sum\\:\\alpha\\:}_{2}{Controls}_{i,t}+\\sum\\:Year+\\sum\\:Lnd+\\sum\\:Province+{\\epsilon\\:}_{i,t}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eDCG\u003c/em\u003e represents CDT degree and \u003cem\u003eX\u003c/em\u003e represents various indicators related to the construction of the Internet Plus government service platform, including participation from both sides (\u003cem\u003ePart\u003c/em\u003e), information exchange and sharing (\u003cem\u003eIE\u003c/em\u003e), and the affairs of handling the interaction of legal entities (\u003cem\u003eLegal\u003c/em\u003e). Following Chen et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), \u003cem\u003eControls\u003c/em\u003e represent a series of control variables including (1) firm financial characteristics: firm size (\u003cem\u003eSize\u003c/em\u003e), leverage (\u003cem\u003eLev\u003c/em\u003e), profitability (\u003cem\u003eRoa\u003c/em\u003e), growth rate (\u003cem\u003eGrowth\u003c/em\u003e), cash holding (\u003cem\u003eCash\u003c/em\u003e), whether it is in a loss state (\u003cem\u003eLoss\u003c/em\u003e), proportion of intangible assets (\u003cem\u003eIntangible\u003c/em\u003e), and capital intensity (\u003cem\u003eSd\u003c/em\u003e). (2) Company governance characteristics: duality (\u003cem\u003eDual\u003c/em\u003e), equity concentration (\u003cem\u003eTop10\u003c/em\u003e), and board size (Board). (3) Other enterprise characteristics: enterprise age (\u003cem\u003eAge\u003c/em\u003e). We also control for industry (\u003cem\u003eInd\u003c/em\u003e), year (\u003cem\u003eYear\u003c/em\u003e), and province (\u003cem\u003eProvince\u003c/em\u003e) fixed effects. Main variables are defined in the Appendix.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Empirical Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Main analysis\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the descriptive statistics. The mean of \u003cem\u003eDCG\u003c/em\u003e is 1.786 and standard deviation is 1.410, suggesting significant CDT variations among enterprises. The means of \u003cem\u003ePart\u003c/em\u003e, \u003cem\u003eIE\u003c/em\u003e, and \u003cem\u003eLegal\u003c/em\u003e are 2.426, 1.845, and 2.320, with standard deviations of 1.575, 0.806, and 1.600, respectively, indicating an imbalance in the development of the Internet Plus government service platform across different regions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eDescriptive Statistics\u003c/b\u003e This table reports the descriptive statistics of influencing factors, and control variables. All variables are defined in Appendix.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVARIABLE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOBS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMEAN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSTD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMEDIAN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e75%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePart\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIE\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLegal\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDCG\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5.283\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSize\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e22.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e26.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLev\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.918\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRoa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGrowth\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.974\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCash\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLoss\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIntangible\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDual\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTop10\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBoard\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.639\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3.555\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSd\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e29.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the results of Model (1). In Column (1), the coefficient of \u003cem\u003ePart\u003c/em\u003e is 0.026, which is significant at the 1% level, indicating that the participation of both the government and enterprises can promote CDT, supporting \u003cb\u003eH1\u003c/b\u003e. Regarding economic significance, for each standard deviation increase in \u003cem\u003ePart\u003c/em\u003e, the CDT degree increases by 2.29% (= (0.026 \u0026times; 1.575) / 1.786). In Column (2), the coefficient of \u003cem\u003eIE\u003c/em\u003e is 0.051, which is significant at the 1% level, suggesting that information exchange and sharing between the government and enterprises promotes CDT, supporting \u003cb\u003eH2\u003c/b\u003e. Economically, each standard deviation increase in \u003cem\u003eIE\u003c/em\u003e results in a 2.30% rise in CDT degree (= (0.051 \u0026times; 0.806) / 1.786). In Column (3), the coefficient of \u003cem\u003eLegal\u003c/em\u003e is 0.030, which is significant at the 1% level, indicating that the interaction between the government and enterprise legal entities in handling government affairs promotes CDT, supporting \u003cb\u003eH3\u003c/b\u003e. Regarding economic significance, for each standard deviation increase in \u003cem\u003eLegal\u003c/em\u003e, the degree of CDT increases by 2.69% (= (0.030 \u0026times; 1.600) / 1.786).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eMain analysis\u003c/b\u003e Standard errors are clustered at firm level. Industry fixed effect, year fixed effect and province fixed effect are both controlled in all regressions. *, \u003cb\u003e**\u003c/b\u003e, and *** indicates statistical significance at the 10%, 5%, and 1% level, respectively.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDCG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePart\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.026\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIE\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.051\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLegal\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSize\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.198\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.198\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.198\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.016)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLev\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRoa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.655\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.655\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.660\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.227)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.227)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.227)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGrowth\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.087\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.088\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.088\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.030)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCash\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.854\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.855\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.854\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.149)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.149)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.149)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLoss\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.042)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDual\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.079\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.079\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.079\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.030)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIntangible\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.350)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTop10\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.268\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.269\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.269\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.106)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBoard\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.088)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.088)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.088)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.127\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.127\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.127\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.055)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.055)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.055)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSd\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.144\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.144\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.144\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.035)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.316\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.348\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.322\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.373)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.374)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.374)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16707\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdj.R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e5.2. Robustness test\u003c/h2\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e5.2.1 Propensity score matching\u003c/h2\u003e \u003cp\u003eTo address endogeneity issues from sample selection, we employ propensity score matching (PSM). First, 1/3 is selected as the cut-off point for group samples. We assign the lower 1/3 of \u003cem\u003ePart\u003c/em\u003e (\u003cem\u003eIE, Legal\u003c/em\u003e) as the control group and the higher 1/3 of \u003cem\u003ePart\u003c/em\u003e (\u003cem\u003eIE, Legal\u003c/em\u003e) as the experimental group. Following You et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), we implement one-to-one nearest neighbor matching without replacement, with a caliper set to 0.05 times the standard error of the propensity score. The matching variables include all the control variables of Model (1). Additionally, we control for the fixed effects of year, industry, and province. Column (1)-(3) of Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the results after using the matched samples in Model (1). \u003cem\u003ePart\u003c/em\u003e, \u003cem\u003eIE\u003c/em\u003e, and \u003cem\u003eLegal\u003c/em\u003e are all significant, supporting the original hypotheses.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eRobustness Test\u003c/b\u003e Standard errors are clustered at firm level. Industry fixed effect, year fixed effect and province fixed effect are both controlled in all regressions. *, \u003cb\u003e**\u003c/b\u003e, and *** indicates statistical significance at the 10%, 5%, and 1% level, respectively.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003cp\u003eStae2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003cp\u003eStage2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003cp\u003eStage2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDCG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePart\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.048\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIE\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.129\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.050\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.074)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLegal\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.045***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.031\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSize\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.201\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.207\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.198***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.196\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.195\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.196\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.026)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.025)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLev\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.241*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.132)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.163)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.101)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRoa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.731\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.437***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.638\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.638\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.642\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.357)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.407)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.333)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.232)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.232)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.232)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGrowth\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.089\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.090\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.090\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.048)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.066)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.046)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.031)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.031)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.031)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCash\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.966\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.058\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.079***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.849\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.849\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.849\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.213)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.272)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.207)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.158)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.158)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.158)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLoss\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.123\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.062)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.085)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.062)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.042)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDual\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.072\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.094\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.080\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.080\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.080\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.049)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.040)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.031)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.031)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.031)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIntangible\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.455)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.498)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.479)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.359)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.359)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.359)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTop10\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.262\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.282\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.268\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.268\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.268\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.165)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.138)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.107)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.106)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBoard\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.136)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.115)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.090)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.090)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.090)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.158\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.141\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.147\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.147\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.147\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.068)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.083)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.058)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSd\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.168\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.214\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.230***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.143\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.142\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.142\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.080)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.036)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eImr\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.236)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.236)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.236)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.528\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.833\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.447***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.167\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.191\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2.175\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.470)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.589)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.496)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.626)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.627)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.626)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16451\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdj.R2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e5.2.2 Heckman two-stage analysis\u003c/h2\u003e \u003cp\u003eCDT is the process whereby companies introduce digital solutions such as the \u003cem\u003eInternet of Thing\u003c/em\u003e. Therefore, companies that have already initiated digital transformation typically have more comprehensive digital devices than those that have not yet engaged and are more capable of accessing digital governance equipment such as the Internet Plus government service platform. Additionally, companies that have entered CDT can more directly perceive the value of information in the digital era and are thus more willing to join online platform. Based on these two points, sample selection bias may exist, so we further use the Heckman two-stage model. Following Liu et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), the model adds the Internet (\u003cem\u003eInternet\u003c/em\u003e) as an exogenous variable. \u003cem\u003eInternet\u003c/em\u003e represents the interaction between the lagged national Internet user count and the 1984 fixed-line telephone count in the company's registered city. Because the number of fixed-line telephones in each city is cross-sectional, time series variables are introduced to create panel data. The inverse Mills ratio (\u003cem\u003eImr\u003c/em\u003e) is obtained in the first stage and then used as a control variable in Model (1). Column (4)-(6) of Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the results of the Heckman two-stage analysis. The coefficients of \u003cem\u003ePart\u003c/em\u003e, \u003cem\u003eIE\u003c/em\u003e, and \u003cem\u003eLegal\u003c/em\u003e are still positively significant, indicating that the results remain valid.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThe Internet Plus government service platform addresses enterprises' complex administrative needs, facilitating CDT. At the interactive intention level, corporate participation enhances reputation and grants access to critical transformation resources; government participation improves the business environment and creates financing channels, promoting CDT.\u003c/p\u003e \u003cp\u003eThis study has important implications for both government and companies. First, regarding interactive intention, the government can increase participation on the Internet Plus government service platform through two initiatives. The first is through administrative orders to emphasize the participation of the government and businesses on the platform, urging local administrative departments and business to fully engage. The second initiative focuses on bridging the digital divide by expanding the government service platform comprehensively. Given the economic and technological disparities across regions, the government should increase support for administrative departments and businesses in disadvantaged areas.\u003c/p\u003e \u003cp\u003eSecond, in terms of interactive equipment, the government must optimize the information quality and communication efficiency of the Internet Plus government service platform. The government should continuously improve the timeliness, accuracy, and clarity of policies published on the platform, thereby reducing information search cost for enterprises. Meanwhile, the government should actively interpret and respond to trending policies on the platform, facilitating the public's maximum understanding of new policies. The government should also effectively monitor corporate operations through the government service platform, quickly respond to business development issues, and achieve efficient communication. Additionally, the government can collaborate with third-party Internet platforms, building multi-platform to improve communication efficiency.\u003c/p\u003e \u003cp\u003eFinally, regarding interactive actions, the government must enhance the efficiency of administrative handling and the precision of matching needs and demands. Government departments should further expand the types of online services handled to meet enterprises\u0026rsquo; diverse service needs during CDT. Simultaneously, integrating and optimizing service processes, along with enhancing information-sharing mechanisms, can help reduce business handling costs and waiting times. The government should deeply understand enterprise needs and improve the precision of supply-demand matching, providing enterprises with appropriate policy resources.\u003c/p\u003e \u003cp\u003eThis study has some limitations that require further research. First, owing to the integrated and novel nature of the Internet Plus government service platform, there is currently no unified measurement method. This study analyzes data from government website reports, and future research could integrate other measurement methods, including textual analysis, to enhance measurement validity. Second, while this study attempts a comprehensive quantitative analysis of government-business interaction on the platform through participation, information exchange, and administrative handling, real-world interactions are more complex. Future research could conduct heterogeneity analysis in different regions and industries to deeply analyze how the Internet Plus government service platform affects CDT in different environments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eFirst Author: Conceptualization, Methodology, Validation, Resources, Writing - Original Draft, Supervision, Project administration, Funding acquisition. Second Author: Software, Formal analysis, Data curation, Writing - Review \u0026amp; Ed\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe acknowledge financial support from National Natural Science Foundation of China (Project No. 72102139)\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eData available at Mendeley Data, V1, doi: 10.17632/ktcdvgh4pz.1\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAben, T.A.E., van der Valk, W., Roehrich, J.K. and Selviaridis, K. (2021) Managing information asymmetry in public\u0026ndash;private relationships undergoing a digital transformation: the role of contractual and relational governance. \u003cem\u003eInternational Journal of Operations \u0026amp; Production Management\u003c/em\u003e, 41(7), 1145\u0026ndash;1191.\u003c/li\u003e\n\u003cli\u003eAllen, B., Tamindael, L.E., Bickerton, S.H. and Cho, W. 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Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gov.cn/zhengce/content/2018-01/22/content_5259190.htm\u003c/span\u003e\u003cspan address=\"https://www.gov.cn/zhengce/content/2018-01/22/content_5259190.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Government digital governance, Corporate digital transformation, Interactive intentions, Interactive equipment, Interactive actions","lastPublishedDoi":"10.21203/rs.3.rs-6903235/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6903235/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the digital economy, corporate digital transformation (CDT) has become essential for enterprises to maintain high-quality development. This study explores the impact of the government digital governance on CDT. Accordingly, this study finds that the Internet Plus government service platform facilitates CDT through interactions between the government and enterprises vis-\u0026agrave;-vis interactive intentions, equipment, and actions. Interactive intentions, by increasing corporate exposure and reputation and optimizing the business environment, alleviate resource constraints for CDT; interactive equipment enriches the information channels and enhances digital literacy, thereby improving CDT capabilities; and interactive actions accelerate the CDT process by optimizing the coordination of internal and external resources. This study expands the antecedents of CDT from macro governance and enriches the economic consequences of digital governance effects. It provides practical implications for the government to guide CDT through macro policies and inspires enterprises to actively use digital government platforms to accelerate CDT and achieve sustainable development.\u003c/p\u003e","manuscriptTitle":"Internet Plus government service platform and corporate digital transformation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-02 10:10:01","doi":"10.21203/rs.3.rs-6903235/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6080b606-f9a6-4a51-b202-9846e5f94430","owner":[],"postedDate":"July 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-02T10:10:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-02 10:10:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6903235","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6903235","identity":"rs-6903235","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}