Industrial Technological Innovation Research Articles

Study on urban green development efficiency of Jiangsu, Zhejiang and Fujian in China: a mixed network SBM approach

PurposeBy studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.Design/methodology/approachFirst, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.FindingsSubsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.Originality/valueThis study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.

How Does Environmental Protection Tax Affect Urban Energy Consumption in China? New Insights from the Intensity Difference-in-Differences Model

Against the backdrop of accelerating environmental protection and resource conservation, it is of great significance to achieve energy conservation and sustainable growth. In this context, by collecting panel data from 284 cities in China from 2009 to 2021, this paper constructs an intensity difference-in-differences (I-DID) model, using the implementation of China’s environmental protection law in 2018 as an event shock, to explore the impact of environmental protection tax (EPT) on urban energy consumption. The results indicate that EPT significantly reduces urban energy consumption. After several robustness tests, the estimation results shown above still hold. The mechanism test reveals that EPT mainly reduces energy consumption by promoting urban industrial upgrading, economic openness, and technological innovation. In addition, the heterogeneity test shows that EPT has a greater impact on energy consumption in central and western cities, small and medium-sized cities, non-resource-based cities, and non-old industrial bases. Therefore, to fully improve the positive effect of EPT on urban energy consumption, we suggest increasing energy efficiency, promoting the green transformation of energy structures, enhancing the ability to open-up and innovate, and improving a differentiated regional EPT management system.

Can green finance reduce carbon emission? A theoretical analysis and empirical evidence from China.

As an important way for China to achieve its dual-carbon goal, green finance has become the foundation for promoting high-quality economic development in China. In order to clarify the mechanism of green finance on carbon emissions, this paper puts green finance into the economic model and deduces the relationship between green finance and carbon emission reduction. This paper is based on the panel data of 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2008 to 2019, using the individual fixed effect model, dynamical model, mediator model, and SDM model to study the impact of green finance on carbon emissions and its impact path of upgrading of the industrial structure and the development of science and technology based on the measurement of the green finance development index of each province by the entropy method. The findings show that the development of green finance can reduce carbon emission significantly, which can be sustained until at least the third phase and generates spatial spillover effects; regional heterogeneity analysis finds that the development of green finance shows geographical discrepancies: compared with the eastern and western regions, the development of green finance in central region can reduce carbon emissions more significantly; not only can the development of green finance directly reduce carbon emission, but also through the upgrading of industrial structure and technological innovation. The research not only provides a new perspective and supplementary empirical evidence for understanding the carbon emission reduction effect of green finance, but also offers some useful references for green finance to contribute to carbon emission reduction.

Unlocking Economic Resilience: A New Methodological Approach and Empirical Examination under Digital Transformation

Economic resilience is crucial for urban sustainability as it ensures stability and growth in the face of external shocks, promotes social cohesion and inclusivity, fosters environmental sustainability, and enhances cities’ adaptability to future challenges. This study expands the conventional perspective on economic resilience beyond the context of shocks, focusing on the inherent resilience of regional economic systems. A novel method for quantifying economic resilience is introduced, emphasizing system sensitivity and adaptability. Using Chinese prefecture-level city data and an econometric model, we empirically examine how Fintech, a major digital transition in current urban systems, affects economic resilience. The findings reveal that Fintech has a substantial positive effect on economic resilience, primarily through the upgrading of industrial structures and technological innovation. Furthermore, there is significant regional heterogeneity in the impact of Fintech on economic resilience, with more pronounced contributions in the east, central, and western regions of China, as opposed to the northeast. Additionally, the impact of Fintech on economic resilience is more substantial in large-scale cities. The promotion of economic resilience through digital transformation serves as a potent risk prevention measure. Understanding the role of economic resilience in urban systems holds valuable implications for countries worldwide.

Coupling coordination and spatial–temporal evolution between high-quality development of construction industry and scientific and technological innovation

Coupling coordination and spatial–temporal evolution between high-quality development of construction industry and scientific and technological innovation

The path of green finance to promote the realization of low-carbon economic transformation under the carbon peaking and carbon neutrality goals: Theoretical model and empirical analysis

In 2020, China proposed the Carbon Peaking and Carbon Neutrality Goals, promoting low-carbon economy and the related green financial market environment. The introduction of relevant policies means that China's green financial service system is undergoing transformation. This is not only a manifestation of China's active commitment to environmental protection obligations, but also a major responsibility for China to actively respond to global climate change. It also directly puts forward higher requirements for China to accelerate the implementation of low-carbon economic transformation. Based on the panel data of 30 provinces (cities) from 2006 to 2020, this article realistically uses panel data information as the most fundamental basis, and adopts the Mediating Effect and GMM model to empirically analyze and verify the implementation path of green finance to assist in the low-carbon transformation of the economy. The study found that green finance could assist in the low-carbon transformation of the economy: there are paths of green finance →upgrading industrial structure → GDP carbon emission intensity and green finance →technological innovation→ GDP carbon emission intensity. Heterogeneity analysis showed that, in high-carbon emission areas, the upgrading of industrial structure has played a negative mediating effect in the process of green finance assisting in the low-carbon transformation of the economy. In addition, both the technological innovation paths in high-carbon emission areas and the upgrading industrial structure and technological innovation path in low-carbon emission areas have played a positive mediating effect in the process of green finance assisting in the low-carbon transformation of the economy. The research in this article enriches and develops the theory of finance and economic growth, providing a reference basis for achieving the Carbon Peaking and Carbon Neutrality Goals and coping with the difficulties encountered in the low-carbon transformation of the economy. It is of positive significance in the field of low-carbon development.

Forecasting Emerging Technologies in Intelligent Machine Tools: A Novel Framework Based on Community Analysis

Having emerged as strategic focal points in industrial transformation and technological innovation, intelligent machine tools are pivotal in the field of intelligent manufacturing. Accurately forecasting emerging technologies within this domain is crucial for guiding intelligent manufacturing’s evolution and fostering rapid innovation. However, prevailing research methodologies exhibit limitations, often concentrating on popular topics at the expense of lesser-known yet significant areas, thereby impacting the accurate identification of research priorities. The complex, systemic, and interdisciplinary nature of intelligent machine tool technology challenges traditional research approaches, particularly in assessing technological maturity and intricate interactions. To overcome these challenges, we propose a novel framework that leverages technological communities for a comprehensive analysis. This approach clusters data into specific topics which are reflective of the technology system, facilitating detailed investigations within each area. By refining community analysis methods and integrating structural and interactive community features, our framework significantly improves the precision of emerging technology predictions. Our research not only validates the framework but also projects key emerging technologies in intelligent machine tools, offering valuable insights for business leaders and scholars alike.

Low-carbon governance, fiscal decentralization, and enterprise green development: Evidence from China.

Simultaneously achieving economic development and environmental protection is a shared global challenge. While the positive effect of environmental regulations on protecting the environment has been widely recognized, the attention paid to low-carbon governance and corporate green transformation remains insufficient. Based on the two-stage least square regression model (2SLS) of instrumental variables, this paper utilizes panel data from China to identify the influence mechanism of government low-carbon governance on enterprise green development. It explores the effect of low-carbon governance on enterprise green development from the perspective of fiscal decentralization. The findings show that (1) Low-carbon governance significantly promotes corporate green development, primarily through improving industrial structure and technological innovation; (2) Low-carbon governance notably promotes the green development of private enterprises but has little effect on state-owned enterprises. There are also geographical differences, and the results are better in Eastern China than in the Central and Western parts of China; (3) Fiscal decentralization at both central and local levels inhibits the effect of low-carbon governance on driving corporate green development by causing a mismatch of human resources. Therefore, to promote corporate green development, low-carbon governance must prioritize green development, actively guide industrial structural upgrading and enterprise technological innovation, implement differentiated low-carbon governance measures tailored to different ownership enterprises, and optimize the assessment indicators for fiscal decentralization. This paper helps deepen the understanding of the relationship between government low-carbon governance and enterprise green development in developing countries. It can be used as a reference for government departments to formulate relevant policies.

Research on evaluation of Wuhan air pollution emission level based on entropy weight method

For the lack of precise monitoring and accurate assessment models for air quality, this paper fully considers such constraints and establishes an evaluation model of air pollution emission level to evaluate the air pollution emission level of Wuhan—a city in central China. The model uses entropy weight method including important indicators of air pollution into the integrated optimization of air quality assessment, laying the basis for sources of pollution and the reasonable and effective city development. The total emissions of air pollution for Wuhan shows a gradual upward trend over time, mainly coming from industrial pollution. The government can reduce air pollution by focusing on detecting major polluting industries, promoting industrial technological progress and innovation, and strengthening the effective implementation of emission trading system.

Urban green land use efficiency of resource-based cities in China: Multidimensional measurements, spatial-temporal changes, and driving factors

The green use of urban land has become a key for the sustainable transformation of resource-based cities. This paper selects 116 Chinese resource-based cities to construct an evaluation system for urban green land use and measure its efficiency. Secondly, it identifies driving factors affecting urban green land use efficiency (UGLUE) and comprehensively analyze the heterogeneity of these factors. The important findings of this paper include: (1) The UGLUE of resource-based cities in China has experienced a trend of first fluctuating and then improving. However, there are obvious regional differences. The UGLUE in the eastern and western regions are higher than those in the central and northeastern regions. (2) Industrial upgrading, financial development and technological innovation are key factors affecting UGLUE in resource-based cities. (3) There is significant heterogeneity in the impact of different factors in different city types, different regions and different time periods. The land use in resource-based cities should transform from blind expansion in pursuit of short-term economic benefits to a green development that pursues the coordination of economic, social, and ecological benefits based on the local conditions.

Impact of the coupling relationship between marine industry and regional development on the marine economy

To investigate the relationship between the marine industry and regional development, and assess its impact on the marine economy. The study creates an evaluation index system for the coupling relationship between the marine economy and regional development. It applies coupling theory and combines the hierarchical analysis method with the entropy weight method to determine the weight of each index. By constructing the coupling degree and coupling coordination degree model, this paper quantitatively analyzes the coupling relationship and applies the coefficient of variation to assess the coordinated development differences between different regions. The study utilized data from the official China Marine Statistical Yearbook. The analysis revealed an upward trend in the coupling degree of the marine economy and regional development during the study period, increasing from 0.58 to 0.72. This indicated a significant strengthening of the interaction and synergistic development between the two. In typical coastal areas, the coupling degree increased from 0.62 to 0.78, indicating the significant contribution of the marine industry to the region's comprehensive economic development. The study proposes policy recommendations to enhance the adjustment of the marine industrial structure and technological innovation, promote inter-regional cooperation and resource sharing, and strengthen marine environmental protection and sustainable resource utilization. These measures aim to promote the development of the marine economy while safeguarding marine resources.

Blockchain=better food? The adoption of blockchain technology in food supply chain

Purpose This study aims to investigate the integration of blockchain technology into the food supply chain within the restaurant industry. It focuses on how blockchain can be applied to enhance transparency and trust in tracking food sources, ultimately impacting customer satisfaction. Design/methodology/approach A service design workshop (Study 1) and three between-subjects experiments (Studies 2–4) were conducted. Findings Results indicate that blockchain adoption significantly improves traceability and trust in the food supply chain. This improvement in turn enhances customer satisfaction through perceived improvements in food safety, quality and naturalness. This study also notes that the effects of blockchain technology vary depending on the type of restaurant (casual or fine dining) and its location (tourist destinations or residential areas). Practical implications The findings offer practical insights for restaurant owners, technology developers and policymakers. Emphasizing the benefits of blockchain adoption, this study guides decision-making regarding technology investments for enhancing customer service and satisfaction in the hospitality sector. Originality/value This research contributes novel insights to the field of technology innovation in the hospitality industry. It extends the understanding of signaling theory by exploring how blockchain technology can serve as a tool for signal transmission in restaurant food supply chains.

Path to sustainable development: Can industrial intelligence and technological innovation balance economic growth and environmental quality in China?

AbstractIntelligent industrial transformation and technological innovation fuel China's sustainable development. We examine whether industrial intelligence and technological innovation improve economic growth and environmental quality using provincial data from China from 2006 to 2020. We used panel co‐integration techniques (fully modified OLS and dynamic OLS) for analysis. The results showed that industrial intelligence drives economic growth and environmental quality, whereas technological innovation primarily promotes economic growth. We also found that green technological innovation improves economic growth and environmental quality. The Granger causality technique based on the vector error‐correction model showed a strong interrelationship among industrial intelligence, technological innovation, economic growth, and environmental quality. Furthermore, a heterogeneity analysis shows that the effects and interrelationships of the variables of interest vary significantly by region in China. To achieve sustainable development, the government should accelerate the transformation of industrial intelligence, invest in environment‐friendly technological innovation activities, and focus on the co‐development of industrial intelligence, technological innovation, economic growth, and environmental quality.

Research on the impact of China's reform to delegate power, streamline administration, and optimize government services on the technology innovation efficiency of the pharmaceutical manufacturing industry.

The government has recently implemented reforms aimed at delegating power, streamlining administration, and optimizing government services. This reform has eliminated barriers that impede the growth of various industries, thereby unleashing innovative potential. Additionally, there have been several medical policies, including changes to medical insurance and centralized volume-based procurement. China's pharmaceutical market has undergone significant changes, leading to increased demands for innovation technology efficiency in pharmaceutical manufacturing. The three-stage BCC theory was employed to assess the effectiveness of technology innovation in the industry under this reform. Calculate precise comprehensive technical efficiency values, pure technical efficiency values, and scale efficiency values for technological innovation in the pharmaceutical industry across 30 provinces from 2018 to 2020, after removing environmental factors. In 2020, Jiangsu and Shandong and nine other provinces reached the comprehensive technical efficiency frontier surface, joining Tianjin, Zhejiang, and Guangdong provinces. However, Gansu, Qinghai, Ningxia, and Xinjiang still need to catch up due to their smaller industrial scale and lack of technology. To ensure the effectiveness of reforms, it is crucial to fully consider provincial differences. Articulating national and provincial policies is necessary to allow efficient provinces to continue and allocate resources toward less efficient provinces to improve overall efficiency.

Retracted: Identification of Driving Factors of Scientific and Technological Innovation in the New Material Industry Based on the Theory of Complex Adaptive System: Taking the Construction of Green Innovation System as an Example

Retracted: Identification of Driving Factors of Scientific and Technological Innovation in the New Material Industry Based on the Theory of Complex Adaptive System: Taking the Construction of Green Innovation System as an Example

Transformation in Organizational and Human Resource Management in the Digital Intelligence Age

This article explores the revolutionary impact of digital technology and artificial intelligence on organizational and human resource management in the era of digital intelligence. Confronted with challenges in industrial evolution, technological innovation, and customer-centric dynamics, businesses are urged to embrace innovation and instill a culture of transformation. The pivotal focus lies in propelling the transformation of organizational and human resource management in six key dimensions. Firstly, organizational systems evolve to become more open, interconnected, flexible, and adaptive. Secondly, human resource allocation diversifies, emphasizing collaborative synergy among team members. Thirdly, performance management methods underscore alignment with organizational strategy and culture, emphasizing the improvement of employees’ perspective and competence. Fourthly, values management signifies a shift towards intrinsic motivation and cultural consistency in personnel management. Fifthly, leadership styles stress motivation, empowerment, and support, prioritizing an employee-centric approach. Sixthly, it underscores the value of human capital as the cornerstone of innovative incentive strategies, advocating for sustained investment in key talent. In summary, the framework advocates for innovation as a strategic imperative, recognizing the intrinsic value of individuals as the driving force behind organizational success and underscoring human resources as a pivotal driver of organizational development in the era of digital intelligence.

To Construct a Stronger Spiritual and Cultural Support for Advancing New Industrialization—Review of Industrial Technology Innovation in the Past 10 Years and Future Prospects

To Construct a Stronger Spiritual and Cultural Support for Advancing New Industrialization—Review of Industrial Technology Innovation in the Past 10 Years and Future Prospects

Spatial association network of carbon emission performance: Formation mechanism and structural characteristics

To enhance regional carbon emission performance (CEP), understanding the spatial association characteristics of CEPs in cities has emerged as a pivotal strategy for the Chinese government to address climate issues. In this study, the formation mechanism of the CEP spatial network is illustrated and a super-efficient SBM model used to measure the CEP of each city in the Yangtze River Delta (YRD) from 2003 to 2018. Subsequently, the structural characteristics and influencing factors of the CEP network were explored using a macro-micro-individual analysis framework. The results showed that the CEP of regional cities exhibited clear network structural characteristics, with a continuous strengthening of spatial association. The motif structure type with reciprocity and agglomeration played a decisive role in the network. The low-carbon development of the YRD mainly depended on the driving effect of the core cities; however, there was a noticeable disparity in individual centrality between the core cities and the others. Geographic proximity and differences in economic agglomeration, open policy, and transportation had a significant positive impact on the CEP network. Conversely, disparities in industrial structure, population agglomeration, and technological innovation were not conducive to network formation. Based on these findings, policies to promote the low-carbon transition in the YRD have been proposed.

Spatial correlation network structure of energy-environment efficiency and its driving factors: a case study of the Yangtze River Delta Urban Agglomeration

Improving energy-environment efficiency is not only a requirement for constructing China’s ecological civilization but also inevitable for achieving sustainable economic and social development. Studies on energy-environment efficiency based on relational data and network perspectives are limited, which hinders the development of collaborative regional emission reduction activities. This study uses the SBM-Undesirable model to measure the energy-environment efficiency of the Yangtze River Delta Urban Agglomeration from 2010 to 2020, adopts a modified gravity model and social network analysis to reveal the structural characteristics of its spatial correlation network, and explores its driving factors through the QAP method. The study found (1) an overall upward trend in energy-environment efficiency but with problems of uneven development. (2) The spatial correlation of energy-environment efficiency shows a complex network structure, with increasing network correlation and strong network stability; the network can be divided into four plates: net benefit, net overflow, two-way spillover, and agent. (3) Differences in industrial structure, environmental regulation, economic development, and technological innovation significantly impact the formation of spatial correlation network of energy-environment efficiency. This study provides a reference for the construction of a cross-regional synergistic mechanism to improve energy-environment efficiency.

City size and energy efficiency of Chinese manufacturing firms: An empirical study from a city characteristic perspective

The nexus between city size expansion and energy issues has caused heated academic and policy debates. This study empirically investigates the effects of city size on manufacturing firms' energy efficiency in China. Results suggest that the relationship between city size and energy efficiency is inverted U-shaped. City size impacts energy efficiency through its effects on industrial agglomeration and technological innovation. The heterogeneous analysis reveals the differential effects, where firms in energy-intensive sectors, being small and growing, are more affected. Finally, city characteristics, represented by urban sprawl and economic density, significantly moderate the relationship between city size and energy efficiency. These findings provide some insightful references for future urban planning and energy conservation.