Technological Innovation Capability Research Articles

Research on the Influencing Factors of the Value of Listed Companies under the New Economic Environment

This paper explores the influencing factors of the value of listed companies in the new economic environment, aiming to deepen the understanding of the formation mechanism of the value of listed companies in the ever-changing economic environment. Firstly, the article analyzes the characteristics of listed companies under the new economic environment and the impact of the new economy on enterprises, including technological innovation, changes in market competition patterns, and so on. Secondly, the paper elaborates on the theoretical framework of the value of listed companies, including the concept of value, influencing factors, and evaluation methods. Finally, the article delves into the influencing factors of the value of listed companies in the new economic environment, including technological factors, innovation capability, industrial environment, and corporate governance. Through the analysis of these factors, this paper provides important theoretical references and practical guidance for understanding and evaluating the value of listed companies in the new economic era.

How Does the Digital Transformation Affect the Carbon Emissions of Manufacturing Enterprises in China? The Perspective of Green Technology Innovation

With the continuous intensification of competition among major countries and the resurgence of anti-globalization trends, countries around the world have strengthened their strategic deployment for digital transformation in the manufacturing industry. Digital development enables enterprises to transform and upgrade, and the digital transformation and green transformation of enterprises have a historic intersection. This study uses the panel data of 1900 A-share listed companies to explain the theoretical mechanism of digital transformation to promote carbon emission reduction from the perspective of green technology progress. In addition, the threshold model is used to analyze the nonlinear relationship. The results show that the digital transformation has significantly reduced the carbon emission level of Chinese manufacturing enterprises, and the conclusion is still true after the instrumental variable estimation and robustness test. Heterogeneity analysis found that the carbon emission reduction in state-owned enterprises is more obvious. Green technology innovation capability shows the technology dividend effect, which is an important way for digital transformation to promote carbon emission reduction. This study expands the research on the sustainable development of China’s manufacturing industry and provides guidance for policy makers and business decision makers.

Configurational pathways to innovation capability enhancement in high-tech enterprises: a perspective from technological innovation network

PurposeHigh-tech enterprises, as the national innovation powerhouses, have garnered considerable interest, particularly regarding their technological innovation capabilities. Nevertheless, prevalent research tends to spotlight the impact of individual factors on innovative behavior, with only a fraction adopting a comprehensive viewpoint, scrutinizing the causal amalgamations of precursor conditions influencing the overall innovation proficiency of high-tech enterprises.Design/methodology/approachThis paper employs a hybrid approach integrating necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) to examine the combinatorial effects of antecedent factors on high-tech enterprises' innovation output. Our analysis draws upon data from 46 listed Chinese high-tech enterprises. To promote technological innovation within high-tech enterprises, we introduce a novel perspective that emphasizes technological innovation networks, grounded in a network agents-structure-environment framework. These antecedents are government subsidy, tax benefits, customer concentration, purchase concentration rate, market-oriented index and innovation environment.FindingsThe findings delineate four configurational pathways leading to high innovative output and three pathways resulting in low production.Originality/valueThis study thereby enriches the body of knowledge around technological innovation and provides actionable policy recommendations.

Financial technology as a heterogeneous driver of carbon emission reduction in China: Evidence from a novel sparse quantile regression

China is facing tremendous pressure to reduce carbon emissions. This paper investigates the impact of financial technology (fintech) on carbon emissions reduction across Chinese provincial regions using annual data from 2011 to 2021. To comprehensively reflect the development level of fintech, we utilize web crawler technology and word frequency analysis to create new variables for measuring the technology level and innovation capability, with fintech-related keywords sourced from the Baidu index. Subsequently, we construct a fintech index for each province in China. Given the heterogeneous relationship between fintech and carbon emissions reduction, we employ an innovative sparse support vector quantile regression to explore the impact of fintech on carbon emissions reduction at different quantile levels. This method employs an Lp-norm regularization term to identify the key variables influencing carbon emission reduction. The empirical results indicate that fintech significantly reduces carbon emissions in all Chinese provincial regions. Furthermore, the positive effects of fintech on carbon emissions reduction are much stronger in high-carbon provinces than in low-carbon provinces. Consequently, it is imperative for policy-makers and practitioners to focus on increasing investment in digital infrastructure and enhancing digital services, particularly in Shanxi, Hebei, Henan, Shaanxi, Ningxia, and Xinjiang provinces. The mechanism analysis reveals that fintech contributes to carbon emission reduction by promoting industrial structure upgrading in more economically developed provinces, while its mediating role is absent in less developed provinces.

Natural resource and energy efficiency in BRICS countries: Can green innovation capabilities really change the game?

The inefficient exploitation of resources, overdependence on fossil fuels for energy production, and inappropriate waste management strategies have resulted in mounting environmental challenges that seriously threaten humanity and the planet.The United Nations urges businesses to transition from fossil fuels to sustainable practices, fostering cooperation between natural resources, the economy, and ecology to achieve SDGs. This shift is critical for emerging economies, which may experience rapid growth while heavily relying on fossil fuels. This study uses the nonparametric data envelopment analysis and directional distance function (DEA-DFF) model to examine how organizational green and technological innovation capabilities impact natural resource and renewable energy efficiency in BRICS countries from 2011 to 2021. The results indicated that green and technological innovation significantly improve resource and energy efficiency in BRICS economies, supporting the theoretical arguments given in the dynamic capabilities theory (DCT), business technology adoption model (BTAM), and natural resource-based view (NRBV). It all proposes theoretical and practical implications for similar developing nations. Overall, the results of the study are robust to different econometric models and data processing techniques.

欧盟科学数据发展政策与规划

The continual advancement of global scientific and technological innovation capabilities has spurred a rapid growth of scientific data. As a global benchmark for scientific data management and sharing, the European Union (EU) constantly place a high priority on the management and development of scientific data, and has formed a comprehensive array of policies and plans to advance scientific data development. Through network investigation and literature analysis, this paper focuses on consolidating and summarizing the EUs scientific data support and regulatory bodies, management policies, development plans, and evaluates the effectiveness and challenges in data application practices. Moreover, it also outlines the issues confronting the development of scientific data in China and puts forward insightful recommendations. The analysis shows that the EU’s efforts to promote open science and open scientific data, the scientific data development policy system and sustainable development program are crucial to the open sharing, effective scientific management, maximizing benefits and sustainable development of scientific data in the EU, making the EU stand at the forefront of open scientific data and open science in the world. Furthermore, the ongoing integration of science data centers into the science and innovation infrastructure system of the EU. These practices of the EU can serve as valuable references for China in the development of scientific data, the construction of scientific data centers, the formulation of scientific data policies and development plans, and the play of scientific benefits.

Could Environmental Regulations Reduce Energy Consumption: Evidence From China’s Implementation of an Environmental Pollution Tax

This article investigates the impact of environmental regulations on energy consumption. As the main way for the government to protect the environment, the implementation of environmental pollution tax has played an important role in China’s energy consumption. This article uses data from the implementation of environmental pollution tax in Chinese cities to match with urban energy consumption data, and uses the difference-in-difference method (DID) to estimate the impact of environmental regulations on energy consumption. We find that the implementation of environmental pollution tax has reduced energy consumption, but this effect is mainly effective in the central and western regions and two-controlled areas. Further analysis shows that the reduction of energy consumption by environmental pollution tax is mainly attributed to improving technological innovation capabilities, optimizing industrial structure, and increasing tax collection intensity. The results in this study provide evidence for achieving an environmentally friendly society and sustainable development.

Regression Analysis of the Relationship Between ESG Performance and Firms’ Technological Innovation Capability

This article critically examines Charles Bonnet’s seminal contributions to experimental science, particularly through his influential work, ‘Research on the Use of Leaves.’ The primary objective is to delineate the functions and forms of natural experimentation as they were understood and practiced in the mid-18th century. During this period, scientists esteemed experimentation as the zenith of scientific proof, acutely cognizant of its multifaceted functional and typological aspects. Their methodology was characterized by a detailed narration of research methodologies, fostering a ‘rhetoric of transparency’ in scientific discourse. Nevertheless, the advent of new norms in scientific discourse during the 19th century, coupled with a paradigmatic philosophical shift in the 20th century, resulted in the marginalization of empirical practices of the Enlightenment era. Contemporary historians are now endeavoring to reconcile significant terminological discrepancies and to recontextualize the divergent methodologies among natural historians of that epoch. This involves a critical distinction between exploratory and demonstrative (or discriminant) forms of experimentation. Bonnet’s systematic preference for discriminant experimentation serves as a quintessential example of the logical approach in natural history. However, this perspective does not wholly represent the 18th-century ‘art of observation,’ which embraced a plethora of methodologies including taxonomy, anatomical dissection, chemical analysis, and physical measurements.

Fostering sustainability performance in the Malaysian manufacturing companies: the role of green technology innovation and innovation capabilities

PurposeThe purpose of this study is to examine the influence of green technology innovation on sustainability performance with the moderating effect of innovation capabilities in the Malaysian manufacturing listed companies.Design/methodology/approachThis was a quantitative study and carried out by applying a research survey. The questionnaire was used to collect the data from 204 Malaysian manufacturing companies of the “consumer products and services” sector listed at Bursa Malaysia, incorporating a five-point Likert scale. All the hypothesized relationships were tested by using the partial least square structural equation modeling (PLS-SEM).FindingsThe empirical results showed that the comprehensive adoption of green technology innovation significantly promotes sustainability performance including economic, environmental and social performance. In addition, innovation capabilities significantly and positively moderate the relationship between green technology innovation and sustainability performance.Research limitations/implicationsThe scope of this study is specifically confined to the Malaysian manufacturing listed companies, operating within the consumer products and services sector listed at Bursa Malaysia. Consequently, the findings of this study may not be generalized to manufacturing companies of the different geographical contexts.Practical implicationsThe findings of this study may help the top management and policymakers of the Malaysian manufacturing listed companies to scrutinize green technology innovation and innovation capabilities to achieve higher sustainability performance.Originality/valueThis study magnifies and provides new insights into the extant literature by developing a comprehensive research model that concurrently tests the direct and moderation effects between green technology innovation, innovation capabilities and sustainability performance. Additionally, this is the first study to examine the influence of green technology innovation on sustainability performance with the moderating effect of innovation capabilities in the Malaysian manufacturing listed companies. This distinct approach significantly bolsters the originality of this study.

Enterprise technological innovation capability evaluation using a spherical fuzzy number based CSM-EDAS model

With the rapid development of science and technology, the flow of information has become more convenient, and society has entered the era of knowledge economy. In this era, technological innovation capability is becoming increasingly important and has become an important weapon for enterprises to survive in fierce competition, especially for technology-based small and medium-sized enterprises. Nowadays, technology-based small and medium-sized enterprises have developed many technological innovation achievements through continuous technological innovation, and have created a large number of high-tech products and services. Technological innovation has been proven to effectively improve the core competitiveness and economic benefits of technology-based small and medium-sized enterprises. Therefore, evaluating the technological innovation capabilities of technology-based small and medium-sized enterprises has both theoretical and practical significance. The enterprise technological innovation capability evaluation from a low carbon perspective could be deemed as the multiple attribute group decision making (MAGDM) problem. Recently, the evaluation based on distance from average solution (EDAS) technique and cosine similarity measure (CSM) technique has been employed to manage MAGDM issues. The spherical fuzzy sets (SFSs) are used as an efficient tool for portraying uncertain information during the enterprise technological innovation capability evaluation from a low carbon perspective. In this paper, the spherical fuzzy number EDAS based on the CSM (SFN-CSM-EDAS) technique is cultivated to manage the MAGDM under SFSs. Finally, a numerical study for enterprise technological innovation capability evaluation from a low carbon perspective is supplied to validate the proposed technique. The main contributions of this paper are outlined: (1) the EDAS and CSM technique was extended to SFSs; (2) the CRITIC technique is used to derive weight based on CSM technique under SFSs. (3) the SFN-CSM-EDAS technique is founded to manage the MAGDM under SFSs; (4) a numerical case study for enterprise technological innovation capability evaluation from a low carbon perspective and some comparative analysis is supplied to validate the SFN-CSM-EDAS technique.

Artificial intelligence-driven photovoltaic building materials industry: Greenization and digitization innovation conversion of photovoltaic technology based on a novel interval fuzzy field theory decision-making model

Digital technologies, such as big data, the Internet, and artificial intelligence, are rapidly advancing. Photovoltaic building materials enterprises (PBMEs) have been leveraging digital transformation to enhance their technological innovation capabilities and gain a competitive edge. In the global context of transitioning towards a low-carbon economy, the deep integration of digital technology offers a new solution for the green transformation of PBMEs. The synergy between green traction digitalization and digitalization enables green practices, making collaborative integration crucial for the far-reaching development of PBMEs. Within the framework of China’s “double carbon” policy, domestic PBMEs are experiencing exponential growth, where digital green innovation (DGI) has become their primary objective. In this DGI context, selecting the right partners is the first step that significantly impacts the efficiency and effectiveness of DGI implementation. Therefore, the purpose of this study is to assist PBMEs in selecting high-quality partners, promoting the DGI process, enhancing technological innovation capabilities, and gaining a competitive advantage. To achieve this, the paper proposes constructing a theoretical framework for evaluating the DGI cooperation ability of PBMEs using the theory of ecological reciprocity. Based on this framework, an evaluation index system is established to assess the DGI cooperation ability of potential partners The interval intuitionistic fuzzy evaluation method, combined with a double combination weighting approach, is employed to evaluate the DGI ability of selected partners. Furthermore, by applying field theory, a dynamic selection model for strategic alliance partners is developed to aid PBMEs in selecting high-quality partners for DGI and facilitating the DGI process. The research findings indicate that: i) The evaluation standard framework for DGI cooperation ability of PBMEs encompasses “symbiosis,” “mutualism,” and “regeneration,” along with the crucial environmental element of mutual trust. ii) The evaluation method based on double combination weighting effectively assesses the comprehensive DGI capabilities of selected PBME partners. The application of field theory enables scientific and effective dynamic partner selection for PBMEs through resource complementarity. iii) The proposed framework and partner selection model can be employed in real partner selection scenarios for PBMEs, allowing them to choose high-quality partners, enhance their DGI capabilities, and attain practical selection outcomes. This paper presents novel partner selection model that integrates decision rules and resource complementarity, enabling PBMEs to efficiently select DGI partners from a pool of potential candidates and improve their innovation efficiency. The utilization of the double combination weighting method and field theory in the partner selection paradigm of D extends the theoretical foundation, while the establishment of the DGI capability evaluation index system for PBME partners contributes to empirical applications.

How green industrial policy affects the constancy of green technology innovation: a fresh proof from the innovation motivation perspective

Green industrial policy is an important means to achieve coordinated development of the environment and industry. Enterprises are the primary bodies involved in the green transformation of the market. Thus, it is important for governments and policymakers to recognize the micro-effects of policy implementation on enterprise innovation. From the perspective of the green-tech innovation motivation of enterprises, this study distinguishes green enterprises using text mining analysis methods. Based on propensity score matching (PSM) samples and using panel data from 1,391 listed enterprises in China for the period of 2008–2019, a log log survival analysis model was constructed, and the effectiveness of green industrial policy on the green-tech innovation constancy of enterprises was dynamically analyzed. The results demonstrate that enterprises supported by the green industrial policy can significantly reduce the risk rate of stopping green-tech innovation constancy. Green industrial policy can significantly improve the constancy of the green technological innovation capabilities of enterprises. The innovation constancy of state-owned enterprises is higher than that of private enterprises. Furthermore, intermediary effect tests indicate that different types of green industrial policies stimulate enterprises to generate different innovation motivations. Command-control policies can promote substantive innovation constancy through the industrial competition effect and exert a significantly positive effect. Market-oriented policies can induce enterprises to perform strategic innovation constancy through fiscal incentives and financial investment effects and can produce significant negative effects. Based on these findings, this study proposes improvements in the policy construction of a long-term mechanism to strengthen the substantive innovation of enterprises. This study provides a theoretical basis and policy reference for improving the incentive efficiency of green industrial policies and promoting constant enterprise innovation under the Green and High-Quality Development Goals of China.

Technological cooperation relationships among supply chain enterprises under the perspective of technological blockade: A tripartite evolutionary game model

In the era of accelerated globalization, the issue of technology blockade in complex product supply chains has taken centre stage, making the resilience and security of these chains a focal point in the strategic manoeuvres of major nations. This paper presents a tripartite evolutionary game model encompassing main manufacturers, domestic suppliers, and foreign suppliers. The aim is to delve into the internal mechanisms of transnational supply chain enterprises dealing with complex products, utilizing the “double cycle” framework to address technological blockade. The study's findings reveal a progression in the evolutionary system linked to the technological innovation capabilities of domestic suppliers. The system evolves from the independent innovation of domestic suppliers to cooperative innovation within domestic enterprises and ultimately culminates in joint ventures and cooperation involving multinational suppliers. Additionally, a noteworthy technology gap exists between domestic and foreign countries, suggesting that introducing foreign advanced technology initially and mimicking innovation can effectively mitigate research and development risks. Furthermore, the study underscores the role of Chinese government subsidies in incentivizing technological innovation among domestic suppliers, particularly pronounced when facing significant technology gaps. Simultaneously, the foreign government's imposition of penalties on premium sales by foreign suppliers serves as a catalyst for internal innovation within Chinese enterprises. These actions also motivate multinational enterprises to invest and cooperate, fostering the development of an international cycle. This study provides a fresh perspective on overcoming foreign technological blockades. Its positive implications extend to the advancement of technology in China's complex product landscape and the bolstering of supply chain resilience.

Research on the Evaluation of Regional Scientific and Technological Innovation Capabilities Driven by Big Data

Scientific and technological innovation (STI) is an important internal driver of social and economic development. Reasonable evaluation of regional scientific and technological innovation (RSTI) capability helps discover shortcomings in the development of urban development and guides the allocation of scientific and technological resources and the formulation of policies to promote innovation. This paper analyzes new opportunities created by big data and artificial intelligence for the evaluation of RSTI capability, and based on this analysis, the collaborative evaluation schemes of multi-entity participation are investigated. In addition, considering the important value of unstructured data in evaluating STI, the Latent Dirichlet Allocation (LDA) topic model and sentiment analysis method are employed to analyze the construction of an evaluation indicator system that integrates scientific and technological news data. To fully utilize the respective advantages of human experts and machine learning in the field of complex issue evaluation, this paper proposes an RSTI capability evaluation model based on AHP-SMO human-machine fusion. This study promotes the integration of science and technology and economy and has theoretical and practical significance.

The dynamic relationship among green logistics, technological innovation and green economy: Evidence from China

Under the background of “double carbon”, exploring the growth path of green logistics and enhancing the driving force of technological innovation is the urgent need of our country to comply with the green transformation of its economy and realize high-quality economic growth. Taking the panel data of 30 Chinese provinces from 2010 to 2020 as the sample, the green logistics index evaluation system is constructed based on the driver-press-state-impact-response (DPSIR) theoretical framework, and the green economic efficiency of each province in the sample period is measured by using the non-expected output Super- Slacks-based measure (SBM) model, and by constructing the panel vector autoregressive (PVAR) model including technological innovation is used to systematically elaborate the dynamic influence paths among the three. The study found that: China's green economy, technological innovation, and green logistics all have their own mechanisms for growth, which will gradually diminish over time. In the near and long term, green logistics will promote technological innovations and the evolution of a green economy, but there is a lag in the long-term benefits of green logistics on technological progress. In the short term, technological innovation does not lend support to the growth of a green economy, but over time, the impact of technological innovation on the growth of that economy will shift from negative to positive. This shows that improving technological innovation capability is an important path for green logistics to promote green economic efficiency. The findings of the study provide a basis for decision making to achieve the emission reduction target and improve the efficiency of the green economy.

How does the opening of high-speed rail drive energy restructuring? New micro evidence from China

Against the dual backdrop of China vigorously promoting high-speed railways (HSR) construction and establishing an ecological civilization system, HSR as urban transportation infrastructure, is currently gaining growing attention from the academic community due to its environmental benefits as well as its effects in energy conservation and emission reduction. In this context, this research treats the initiation of HSR as a quasi-natural experiment, meanwhile empirically examining the effect of HSR on energy structure restructuring and exploring the micro-level channels through which it operates. The empirical results validate the reduction effect of HSR opening on fuel energy consumption of industrial enterprises, especially the usage of fuel coal. This highlight remains valid across a series of robustness tests. Moreover, it is evident that the “driving effect” of enterprise technological innovation capability and the “industrial upgrading effect” of enterprise relocation are effective transmission pathways in the process of HSR opening influencing the adjustment of energy consumption structure. Moreover, the unique characteristics of enterprise, industry, and region introduce a certain degree of heterogeneity. The low-energy-consumption effect of HSR is more pronounced in high-carbon industry enterprises, technology-intensive enterprises, firms engaged in innovation pilot cities, small to the medium-sized city and resource-based city. This paper provides a new perspective on energy structure adjustment, contributing to offering solid experiences and references for environmental governance in China and other emerging economies.

Research on China's Economic Development under the Background of Anti-economic Globalization

This article combines the China's economic development under the background of deglobalization. Through analyzing the impact of deglobalization on China's economic development, it explores China's strategies to cope with deglobalization. The study found that deglobalization has had a significant impact on China's economic development, mainly including the impact on foreign trade, investment environment, economic structural adjustment, and national economic security. In order to respond to these impacts, this article proposes strategies such as optimizing foreign trade structure, enhancing technological innovation capability, strengthening international economic cooperation, and improving national economic security prevention capabilities. The research results indicate that properly addressing deglobalization can promote the healthy development of China's economy. Based on these findings, this article also looks forward to future research. In conclusion, this study aims to examine the issues of China's economic development under the background of deglobalization and provide reference for relevant decision-making.

Enterprise Digital Transformation, Dynamic Capabilities, and ESG Performance

Digital transformation improves the operational efficiency and perceptual capabilities of businesses and creates a foundation for fulfilling ESG responsibilities. The authors use the theories of technological innovation and dynamic capabilities and select a sample of 4054 listed companies with commercial integration of ESG rating data to explore the mechanisms through which digital transformation affects ESG performance. Dynamic capabilities are further divided into innovation changeability (IT), coordination integration capability (CI), and learning absorption capability (LA) to investigate the mediating effects and summarize the causal path of “digital transformation - dynamic capabilities - ESG performance.” The research focuses on the impact of digital technology on ESG performance with the aim of helping businesses utilize technology more effectively to build dual competitive advantages in digitization and ESG.

A hybrid approach to resolve ambiguity in new product development

Improving technological innovation (TI) capabilities is an integral component of government policies aimed at improving the competitiveness of small and medium enterprises (SMEs). This study aims to address implementation challenges arising from the use of Qualitative Forecasting Method (QFM) in new product development programs and proposes a novel method to aid decision makers (DMs) in their decision-making process. To tackle this issue, a hybrid method is proposed, incorporating Fuzzy Delphi method (FDM), Fuzzy Analytic Hierarchy Process (FAHP), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Multi-Choice Goal Programming with utility function (MCGP-U), while introducing prospect theory as a novel approach. is proposed. The proposed method offers several advantages, including effective early planning, accurate identification of key success factors (KSFs), selection of the most suitable project leader, and estimation of the most reasonable resource investment, all of which are critical factors for success in TI for enterprises. The research results show that (1) the proposed method reduces project execution time by 20% compared to the original manual planning, (2) it facilitates the acquisition of KSFs using a rational approach to ensure project success, and (3) it increases the financial returns of the company by 17% compared to the company’s forecast. In summary, this paper makes a significant contribution to practical applications and additionally contributes to decision-making field by introducing prospect theory into the proposed hybrid method.

The Impact of Private Equity Investment on Technological Innovation in Enterprises: A Case Study of Bloomage Biotechnology

Technological innovation serves as a crucial driving force for the development of enterprises, and the construction of a modern economic system relies heavily on continuous innovation. Private equity investment, with its unique characteristics, provides comprehensive support for enterprise innovation. Private equity firms not only contribute financial investment but also meet the deeper needs of enterprises through profound business cooperation and empowerment. Using Bloomage Biotechnology as a case study, this paper analyzes the impact of private equity investment on technological innovation in enterprises. The study delves into the analysis from the perspectives of research and development investment and innovation output, reaching the conclusion that private equity investment can provide stable capital support and abundant resource integration for enterprises. This effectively promotes the enterprises investment in research and development and innovation output, thereby enhancing their technological innovation capabilities.