Technological Innovation Factors Research Articles

Research on the coupling mechanism and influencing factors of digital economy and green technology innovation in Chinese urban agglomerations

This paper examines the coupling coordination degree between digital economy and green technology innovation in 19 urban agglomerations across China from 2011 to 2020. Through the analysis of the coupling coordination degree model, spatial autocorrelation, multi-distance spatial clustering analysis, kernel density analysis and grey correlation model, this study uncovers the mechanism of coupling between digital economy and green technology in Chinese urban agglomerations. Data analysis revealed a significant increase in the coupling coordination between the digital economy and green technology innovation within urban agglomerations. However, there are noticeable spatial imbalances in this trend. Additionally, the multi-distance spatial distance analysis highlights a shift from a random distribution to a clustered distribution of spatial characteristics. The polarization features vary among each urban agglomeration and exhibit a significant positive spatial correlation. Factors such as economic sustainability, creative talent, policy support, digital impetus, and technological support will affect the coupling mechanism of green technology innovation and the digital economy in China's urban agglomerations. Policy recommendations are proposed to foster the development of the digital economy, promote coordinated growth within and beyond urban clusters, and ultimately build a digital ecological civilization that is both green and intelligent.

Technological Composition and Innovation Factors in Inventive Yangtze River Delta: Evidence from Patent Inventions

Patents as proxy for technological trends is well noted. The rapid increase of patents in China, however, has aroused debates on its technological progress: ‘few original innovations’ are produced in advanced areas, and true ‘breakthroughs’ are disproportionate to the quantity of the applications. As different technological fields contributions vary to technological progress, a nuanced understanding towards technological composition is in need to help reveal China’s strength in technological innovation. This research takes the Yangtze River Delta (YRD), one of China’s most inventive city-regions, as an epitome to examine the issue via three steps: (1) valid patent inventions applied from 2010 to 2018 are sorted to capture the concentration and colocation features of 35 technological fields defined by the World Intellectual Property Organization (WIPO); (2) four types (intensive, extensive, distinctive, and supportive) of technologies exemplifying technology intensity and interactivity are identified by the cross-classification method and further analyzed by spatial autocorrelation; (3) how urban factors relate to innovation of these four types of technologies are explored. This research unveils a mixed but polarized structure of technological composition in the YRD where the spatial concentration of technologies is as analogous to the nation’s but colocation is not; though quite a few technologies fall into the intensive (usually high-tech) category which assumes to be more likely to breed ‘breakthroughs’, their numbers are limited and far less than extensive (usually labor intensive) or supportive. Knowledge exchange is frequent in core inventive cities where economic performance measured by GDP is most eminently linked to patent inventions of categorized technologies, the exception is intensive technology for which the significance of university students overrides other factors.

Enhancing firms’ innovation persistence in the circular economy through government-supported green supply chain demonstrations: cost leadership or differentiation?

ABSTRACT Government support is pivotal in guiding firms towards adopting green supply chain (GSC) practices aligned with the circular economy. Our study addressed this critical issue through a quasi-natural experiment of GSC demonstration in China. We conducted a difference-in-differences estimation to assess the variation in the persistent innovation capabilities between the treatment and control groups. The results indicate that the GSC demonstration, as an external policy change, stimulated the development of firms’ persistent innovation capabilities. These capabilities have positive effects on both innovation input and output dimensions. Additionally, we explored the interaction between firms’ competitive strategies and government support. Findings indicate that differentiation strategies have a stronger positive impact on innovation persistence, while cost leadership strategies weaken this link. These results emphasize the government's critical role in fostering GSC adoption, offering implications for effective government-business collaboration towards a circular economy and sustainable planning across social, environmental, and technological innovation factors.

The spatial and temporal situation of China's digital technology innovation and its influencing factors.

Digital technology innovation is the core driving force for the high-quality development of the digital economy, and in-depth exploration of the regional distribution pattern and formation mechanism of digital technology innovation in China is conducive to the rational layout and coordinated development of the inter-provincial digital economy. Based on the Reference Relationship Table of the Classification of Core Industries of Digital Economy and the International Patent Classification (2023), the patent authorization data of digital technology from 2012 to 2022 were obtained, and the spatiotemporal situation of China's digital technology innovation was analyzed by using ArcGIS software, Dagum's Gini coefficient, and Moran's I index, and the spatial Dubin panel model was used to explore the influencing factors of digital technology innovation. It is found that: (1) the scale and vitality of China's digital technology innovation have increased significantly, and there are obvious spatial differentiation characteristics, and the innovation level of "eastern coastal-central and western interior" is decreasing, forming a cluster distribution pattern in the Yangtze River Delta region, Beijing, Guangdong, and other places, and the degree of agglomeration is decreasing. (2) The overall regional differences in China's digital technology innovation are large, the differences between the East and the West dominate the interregional differences, and the net differences between regions are the main factors leading to regional differences. (3) There is a significant positive spatial correlation between the scale and vitality of digital technology innovation, which has a significant spatial spillover effect. (4) The results confirm that the level of economic development, digital access, financial scientific and technological support, technology market development level, and R&D intensity have a significant positive impact on the scale and vitality of digital technology innovation; The investment in scientific and technological talents has a significant positive impact on the scale of digital technology innovation, but has no significant impact on the vitality of digital technology innovation.

Spatial pattern evolution and driving factors of urban green technology innovation in China

Spatial pattern evolution and driving factors of urban green technology innovation in China

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

Rural housing-jobs synergy at the county level in mountainous and hilly areas of China: Spatio-temporal pattern and driving mechanism

Rural decline is a severe global problem. The sustainable development of rural areas is in jeopardy due to rapid migration out of rural areas and the separation of rural housing and jobs. Rural housing-jobs synergy (RHJS) is conducive to promoting high-quality and sustainable development of rural areas. Based on rural permanent population, rural employment population, and rural working-age population data from 2007 to 2020, this study applied spatial autocorrelation analysis and Geodetector model to explore the spatio-temporal pattern and driving factors of RHJS at the county scale in Chongqing. Results showed that RHJS in Chongqing demonstrated a steady upward trend and showed spatial heterogeneity. The spatial layout of RHJS was characterized by spatial agglomeration. RHJS hotspots are all located in the yuzhong district and has advantages in terms of its natural resource environment and market placement, while the coldspots are concentrated in the northeast of Chongqing with generally poor conditions. The internal drivers of county RHJS have gradually shifted from a mix of resource-environmental factors and economic factors to a combination of economic factors and social public service factors, with the influence of social public service factors increasing. Market location was the main external driving factor for RHJS, and the influence of technological innovation factors is growing. The degree of influence of the selected variables in each driver on RHIS varies spatially and temporally, and improving RHIS can be accomplished by optimizing the industrial structure, boosting investment in science and technology, and improving the quality of social public services such as healthcare. The proximity of provincial capital cities, the income ratio of urban and rural residents, and the altitude have a significant negative effect on the regional divergence, they are the main variables affecting the RHJS divergence. These findings will assist decision-makers in developing future rural sustainable development policies for the construction of livable and employable villages and optimize rural areas spatial structures by RHJS situation and its driving factors in various regions of counties in mountainous and hilly ecologically fragile areas, and also serve as a useful reference for sustainable a rural development research in other developing countries.

Research on the Performance Path of Industrial Green Total Factor Productivity in the Context of High-Quality Development—Based on Fuzzy-Set Qualitative Comparative Analysis

Improving industrial green total factor productivity (GTFP) is essential for achieving high-quality industrial development in China. To explore this perspective, we examined 30 provinces as case samples and applied a fuzzy-set qualitative comparative analysis in order to analyze the factors of technological innovation, human capital, green consumption, environmental regulation, the Internet, and external openness in relation to industrial GTFP. The findings of this study show that the configuration path of industrial GTFP has multiple concurrencies. Specifically, three paths were identified as leading to high industrial GTFP, namely, the “total factor type”, “open-technology drive type”, and “technology-human drive type”. Meanwhile, the two configuration paths of non-high-industrial GTFP displayed an asymmetric relationship. Overall, these findings are crucial in revealing the path to improving industrial GTFP and achieving high-quality industrial development in China. The “total-factor-type” and “open-technology-drive-type” paths were the most prevalent in the eastern region, while the central area leaned more towards the “technology-human drive type”. This study offers valuable recommendations and insights for policymakers and scholars interested in promoting the development of industrial GTFP.

Modelling the factors of technological innovation in the healthcare sector: A fuzzy-TISM-MICMAC approach

ABSTRACT Healthcare (HC) sector has witnessed the growing proliferation of technological innovation to enhance the quality of life, increased life expectancy, diagnostic options, and cost-effectiveness of HC services. Therefore, the present study aims to identify and analyse the critical factors of technological innovations catering to HC service delivery. The study has implemented fuzzy-total interpretive structural modelling (F-TISM) approach to develop hierarchical inter-relationships among the identified factors. Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis is implemented to classify factors into autonomous, dependent, linkage, and independent groups. The findings of the study placed all the factors of technological innovation in the HC sector at six levels of the developed hierarchical F-TISM model. The factors at the bottom levels are independent variables, which lead to the top-level dependent variables and in the middle of the hierarchical structure are the linkage variables. The most influential factors in the F-TISM model are public-private partnerships, integrated HC information systems, health 4.0 in HC services, organizational culture, and consumer demand. The study distinctly highlighted the importance of HC innovation achieved through the strong foundations laid down by organizational culture and the prolonged need of consumers bridged through integrated HC systems and state-of-the-art technological advancements.

Technological innovation toward sustainability in manufacturing organizations: A circular economy perspective

Technological innovation has been widely recognized both as a trigger and catalyzer towards sustainability. However, hardly ever manufacturing companies are ready and mature enough to employ technological innovations in their processes and business. Given the relevance of technological innovation in pursuing sustainability, it is hard to comprehend what are the prominent factors affecting the role of technological innovation to address sustainability and prioritize them. Therefore, the prime purpose of this study, applied to an emerging economy, is to analyze the contributions of technological innovation toward sustainability in manufacturing organizations with a circular economy (CE) perspective. To address this objective, a questionnaire has been developed and conducted, also using the Grey VIKOR method and a sensitivity analysis. The findings from the study illustrate that entrepreneurship direction towards innovation and market direction towards innovation are the two potential factors of technological innovation towards sustainability. The implications highlight that CE, sustainable education and stakeholder engagement solutions can be crucial to the competitiveness of a developing country's manufacturing businesses.

Research into the Spatiotemporal Characteristics and Influencing Factors of Technological Innovation in China’s Natural Gas Industry from the Perspective of Energy Transition

Promoting technological innovation in the natural gas industry is a feasible means of achieving energy transition. Guided by the geographic innovation theory, this article carries out research on the scale, technical fields, capabilities, and influencing factors of technological innovation in the natural gas industry of 312 Chinese prefecture-level cities, making use of the cusp catastrophe model, the center of gravity and standard deviational ellipse, exploratory spatial data analysis, and geographically and temporally weighted regression (GTWR). The research shows the following: (1) Technological innovation in China’s natural gas industry has continuously expanded in terms of scale, with the number of participating cities increasing, showing a spatially uneven pattern of local agglomeration and national diffusion. (2) There have been significant innovation achievements in natural gas equipment and engineering, but natural gas utilization is lagging in comparison, with drilling, new materials, environmental protection, pipe network engineering, and digital services becoming frontier fields, and collaborative innovation with the thermoelectric, metalworking, automotive, and other related industries having been initially established. (3) The unevenness of technological innovation capabilities is obvious, with the core advantages of Beijing–Tianjin being continuously strengthened and Sichuan–Chongqing, the Yangtze River Delta, the Pearl River Delta, Shandong Peninsula, and Liaodong Peninsula forming high-level technological innovation capability agglomerations. (4) The spatiotemporal pattern of technological innovation capability is the result of multiple factors, with northeastern cities mainly being affected by natural gas demands, northwestern cities being highly sensitive to capital strength, eastern cities mostly relying on urban development, and cities in North China mainly being bolstered by the strength of talent. (5) It is necessary to carry out further multi-agent and multi-scale future research on technological innovation in the natural gas industry and its relationship with the energy transition and to explore the interactivity of the influencing factors. This study may provide strategies for technological innovation in the natural gas industry from the perspective of the energy transition.

Understanding technological innovation and evolution of energy storage in China: Spatial differentiation of innovations in lithium-ion battery industry

China has attached great importance to technology innovation of lithium battery and expects to enhance its efficiency in distributed energy storage systems. The driving factors of technological innovation are often closely related to regional resources, spatial elements and intellectual factors. This has been confirmed by previous research such as in smart grid, but the exploration of lithium battery, an important field, has not been carried out. Based on the industrial location and spatial theory, this study obtained the patent data of lithium-ion batteries (LiB) and technology information. Based on spatial methods such as standard deviation ellipse and Moran index, this paper visually analyses the spatial patterns that influence the technological innovation of LiB in China, and discusses its driving factors in different development periods. The results show that: (1) The LiB innovation space in China is dominated by the Pearl River Delta, supplemented by the Yangtze River Delta and the Beijing-Tianjin-Hebei region, forming a multipolar pattern. (2) The driving force of innovation space evolution is different. Research institutions and enterprises occupy different leadership positions in different regions. (3) The concentration index of the LiB innovation indicates that innovation in neighbouring provinces of China is spatially dependent and increasingly significant. The market structure has a positive impact on the innovation efficiency of the lithium battery industry, and this positive impact also has characteristics of spatial heterogeneity.

Research on Influencing Factors of Technological Innovation in Industrial Clusters Based on Data Mining and Artificial Intelligence Technology

At present, realizing the upgrading and sustainable development of industrial clusters has become an urgent problem. Based on this, based on data mining and artificial intelligence technology, this paper combines the actual needs of industrial clusters and technological innovation to construct an analysis model of the influencing factors of technological innovation in industrial clusters. Based on the complex network foundation, this paper regards the activity of the innovation network as the result of the joint influence of the presence index, closeness index, betweenness index, agglomeration index and path length index. Moreover, this paper combines the actual situation of the cluster to construct an evaluation system for the activity of the innovation network. In addition, this paper uses the PROMETHEE method based on the cloud model to evaluate the activity of the innovative network to be studied in this paper. Finally, this paper designs experiments to verify the performance of the algorithm model constructed in this paper. The research results show that the system model constructed in this paper has a certain effect.

The Impact of Human Capital on Green Technology Innovation—Moderating Role of Environmental Regulations

Green technology innovation can bring about dual benefits, i.e., technological progress and energy conservation, as well as emission reduction, which are regarded as effective means to achieve economic development and environmental protection. The influencing factors of green technology innovation have been studied from multiple angles. In order to promote the level of green technology innovation in China from a new perspective, this paper selected human capital as the independent variable, and empirically investigated the direct impact of educational and healthy human capital on green technology innovation, based on the panel data of 30 Chinese provinces (excluding Hong Kong, Macao, Taiwan and Tibet) from 2006 to 2016. Meanwhile, considering the current environmental policy system in China, this paper took environmental regulations as moderating variables, and analyzed the moderating role of three environmental regulations, namely, command-and-control environmental regulations, market-incentivized environmental regulations, and public voluntary environmental regulations, in the impact of human capital on green technology innovation. It was found that (1) educational human capital, with a three-period lag, and healthy human capital significantly promotes green technology innovation; (2) command-and-control environmental regulations, with a one-period lag, and market-incentivized environmental regulations promote green technology innovation, while public voluntary environmental regulations have an insignificant impact on green technology innovation; (3) the moderating effect of command-and-control and market-incentivized environmental regulations in the impact of human capital on green technology innovation is not significant. For public voluntary environmental regulations, the moderating effect between educational human capital and green technology innovation is significantly negative, while the moderating effect of healthy human capital on green technology innovation is not significant.

Evolution and Influencing Factors of Manufacturing Production Space in the Pearl River Delta—Based on the Perspective of Global City-Region

Evolution and influencing factors of manufacturing production spaces in the global city regions of China are diverse from the West, attracting attention to accurately identify and analyze the real and continuous distribution of manufacturing production spaces on the basis of the actual situation of the region. The 18th National Congress of the Communist Party of China proposed that the production spaces should be intensive and efficient, but the existing studies focus less attention on the manufacturing entity spaces in city regions. Taking the Pearl River Delta as an instance, combined with the POI data of manufacturing enterprises, this study interprets the spatial information of manufacturing production spaces in 1987, 1997, 2007 and 2017 by means of high-resolution remote sensing images. Using various models to quantitatively explore the distribution pattern and evolution characteristics of manufacturing production spaces in the Pearl River Delta in dissimilar periods, and then providing policy guidance for the accurate planning and regulation of manufacturing production spaces in China’s global city regions, on the basis of comparing the evolution mechanism of manufacturing space in Western countries’ global city regions. The results show that: Under the coupling effect of the stage of time series and the heterogeneity of spatial distribution, the manufacturing production spaces in the Pearl River Delta has evolved from the scattered distribution of the core area to the complex and diversified spatial pattern. The hot spots of manufacturing production space expansion in distinct stages also exhibit stage differences. At the current stage, the factors of globalization, technological innovation and policy are becoming increasingly significant. The evolution characteristics of manufacturing production spaces in global city regions in China and Western countries are dissimilar, but the driving factors are similar, which involves the level of urbanization and industrialization, the local government-level infrastructure investment, etc. Instead of simply promoting or restraining the optimization control of manufacturing production spaces, the local governments conduct precise regulation in line with the actual space distribution and development mechanism of manufacturing production spaces in diverse cities. In this process, we can learn from but not copy the experience of the Western countries.

Green Technology Innovation of Energy Internet Enterprises: Study on Influencing Factors under Dual Carbon Goals

In order to help Energy Internet (EI) enterprises develop sustainably, promote the transformation and upgrading of energy systems and achieve the goal of carbon peaking and carbon neutrality, a study on the influencing factors of green technology innovation (GTI) in EI enterprises was conducted using the Decision-making Trial and Evaluation Laboratory-Adversarial Interpretive Structure Modeling Method (DEMATEL-AISM). Through a literature review and field research, the DEMATEL-AISM-based model of the GTI influencing factors of EI enterprises was constructed on the basis of summarizing the system of GTI influencing factors of EI enterprises, visualizing the interrelationship and hierarchical structure among GTI influencing factors of EI enterprises and finally proposing relevant countermeasures and suggestions. This study shows that the proximity-level factors such as R&D investment and external cooperation directly affect the GTI of EI enterprises; the essential-level factors such as environmental regulation and development strategy are the root causes of the GTI of EI enterprises. The transition-level factors such as market competition and business model are the key nodes of the GTI of EI enterprises, and the above factors should be focused on.

Using Machine Learning With Technological Innovation Factors to Predict the Transferability of University Patents

Using Machine Learning With Technological Innovation Factors to Predict the Transferability of University Patents

Effects of ICT in Hotel Industry in South Africa

Purpose: The purpose of this study was to investigate the role of Information and Communication Technology (ICT) in creating competitive advantage in selected hotels in Johannesburg.
 Methodology: Descriptive research design was adopted by the study while stratified random sampling was used to stratify the 104 respondents into 4 categories which included: Operations, reservations, Marketing and ICT managers. Questionnaires were used to collect primary data while descriptive statistics were used to analyze the data.
 Findings: The results showed that there was significant uptake of ICT in all categories of the hotels.
 Conclusion: The study concluded that organizational, environmental and technological innovation factors significantly influenced ICT uptake of Johannesburg Hotels.
 Recommendation: The study recommends engagement in online marketing and diversification of the types of online marketing in order to optimize on visibility, enhance marketing funnel and ultimately increase profitability.

Research on the Correlation and Influencing Factors of Digital Technology Innovation in the Guangdong–Hong Kong–Macao Greater Bay Area

We investigated the digital technology innovation association’s spatial distribution characteristics and influencing factors using social network analysis and a negative binomial gravity regression model. The model was based on the transfer of digital technology patent rights among cities in the Guangdong–Hong Kong–Macao Greater Bay Area from 2010 to 2020. The following are the paper’s main findings: First, the digital technology innovation association among cities in the Guangdong–Hong Kong–Macao Greater Bay Area is strengthening, and the accessibility and agglomeration of each city node are improving, as are small-world characteristics. Second, for a long time, the four cities of Guangzhou, Shenzhen, Dongguan, and Foshan have been at the epicenter of digital technology innovation. Third, in a more peripheral position, Zhongshan, Huizhou, and Zhaoqing have gradually increased the number of digital technology innovation linkages with other cities. Fourth, technological and institutional proximity positively impact digital technology innovation associations in the Greater Bay Area, whereas geographical distance has a negative impact. The study’s findings can be used to help promote digital technology innovation linkages and develop policies for innovation development in the Greater Bay Area.

Research on the Driving Factors of Technological Innovation of Technology-based Small and Medium-sized Enterprises in the Context of Energy Conservation and Emission Reduction

Energy conservation and emission reduction is an important measure to implement the Scientific Outlook on Development, promote economic restructuring and change the development mode. It is an unshirkable social responsibility of technology-based small and medium-sized enterprises (SMEs) to require the joint efforts of all citizens. Based on the current situation, this paper analyzes the influencing factors of the technological innovation ability of China's energy conservation and emission reduction enterprises from both external and internal aspects, and puts forward some suggestions.