Level Of Technological Innovation Research Articles

Characterization of the Innovation Management of the Hotel Portoviejo

Purpose: The purpose of the research is aimed at characterizing the innovative behavior of a city hotel in Portoviejo based on the low level of technological innovation. Theoretical Framework: Innovation transcends all organizations, the traditional interpretation of the concept related to patents and inventions has gone down in history. Today in the business world of high competitiveness and high uncertainty the maxim is: innovate or perish. What this work proposes is related to the management of innovation, but not in manufacturing, but in services, where the technological level also increases dramatically, and high qualifications and careful customer service are required. The applied model is based on the functions of Technology and Innovation Management (GTI), these are: technology inventory, technology enrichment, technology optimization, technological evaluation, and technology protection. Method: The research is qualitative and quantitative with an exploratory and descriptive study with a non-experimental design and the Technology and Innovation management model is supported by the MINGI SOFWARE, which is based on the functions of the GTI and presents tools that characterize and evaluate the process. innovative. In this study, the analysis of business perspectives, the determination of the business model (Traditional or innovative), and the innovative culture of the Hotel are determined as innovative tools. Results and Conclusion: As a result, an innovative characterization of the accommodation, restoration and recreation processes is obtained; concluding that the hotel follows traditional management practices, its business perspective is aimed at sales and not the market and its innovative culture is low, hence to achieve a sustainable service process it must establish an action plan that allows the breaking of the gaps to reach a higher stage with good innovation management practices. Implications of the Research: The main contribution is in the application of the GTI characterizing tools in Ecuador and the projection necessary to increase the innovative intensity in the hotel activity. Originality/Value: The work presents originality, since the model has not been applied in South America and can contribute to good socio-environmental management practices in the hotel business.

CORPORATE FINANCIALIZATION AND GREEN TECHNOLOGY INNOVATION: EVIDENCE FROM CHINESE-LISTED MANUFACTURING COMPANIES

We examine the relationship between corporate financialization and green technological innovation using data on manufacturing companies during 2007–2020. We find that corporate financialization reduces the level of green technology innovation. Heterogeneity analysis demonstrates that financialization’s impact on green technological innovation varies across different enterprise types, especially for private enterprises, high-tech enterprises, and enterprises in eastern and western regions. Moreover, financial constraints will strengthen the influence of financialization on green technological innovation while managerial myopia will weaken the influence of financialization. The empirical insights advance our understanding of the relationship and mechanisms between financial asset investment behavior and green technological innovation in manufacturing enterprises.

Investigating the impact of artificial intelligence development on water pollution in China

Analysing the impacts of AI development on water pollution is of great significance for improving water environment management measures and promoting global sustainable development. In this study, macro and micro panel data of China from 2008 to 2019 were used to measure the development level of AI at the industry and provincial levels in China, and a panel data regression model was constructed to analyse the effects of AI development on water pollution and regional heterogeneity. The measurement results show that the development level of AI is increasing. Among the six industries, the intelligence level of the manufacturing industry has developed the fastest, by approximately 48.74 times compared with the baseline. At the provincial level, Guangdong Province made the greatest progress in intelligence level, increasing by approximately 23.6 times. The regression results show that AI technology is helpful in reducing the level of water pollution, and this conclusion remains valid after the regression of instrumental variables and robustness testing. In terms of regional heterogeneity, AI technology can significantly reduce the degree of water pollution in eastern and western China. However, the development of AI technology in the central region has no significant impact on water pollution, and a risk of increasing the degree of water pollution exists. The reasons may be that the eastern region has high levels of economic vitality and technological innovation and a strong ability to transform AI achievements, which can significantly improve the water environment. Industrial support policies in the western region are strong, and the application of AI can quickly improve production methods and significantly reduce water pollution levels. In comparison, the levels of economic development, technological innovation, and policy support in the central region need to be strengthened, so the environmental effect of AI is not significant.

Uniting FAIR data through interlinked, machine-actionable infrastructures

A new community of research infrastructures has joined forces to provide scientists with seamless access to the plethora of data, services and tools in biodiversity research. New levels of technological innovation and interoperability between infrastructures foster unprecedented access to biodiversity data across all data domains and the entire research lifecycle, thus advancing open science practices and strengthening Europe's position in the global biodiversity research landscape. This policy brief highlights the potential benefits derived from enhanced connectivity and interoperability among various types of biodiversity data, fostering innovation and advancements in biodiversity science, monitoring, conservation, and policy development.

Examining the emission reduction effect of carbon emission trading and carbon tax synergism and their impact mechanisms to reduce the carbon emission of company: based on 247 listed companies of China

ABSTRACT Using the panel data of Shanghai and Shenzhen A-share listed companies spanning from 2007 to 2021, we explore the impact of the synergism of carbon emission trading policy and carbon tax policy on the carbon emission level of enterprises through the difference-in-difference model, intermediary effect model, regulatory effect model. The research results show that: (1) Carbon emission trading and carbon tax both promote enterprises’ carbon emission reduction. (2) There are three paths for carbon emission trading and carbon tax policies to encourage enterprises’ carbon emission reduction actions synergistically: improving enterprises’ green technology innovation level, optimising energy structure, and accelerating industrial structure optimisation. (3) Mediated regulatory effect results show that the greater the company’s government support and R&D investment, the greater the synergism between carbon trading and carbon tax policies to drive green technology innovation and the better the carbon emission reduction effect of the company. (4) The synergism between carbon trading and carbon tax policies positively fosters public ownership companies’ carbon emissions reductions and heavily polluted industry companies.

The Impact of Foreign Direct Investment, Green Technology Innovation and GDP on CO2 Emissions in Western China: A Static Panel Data Analysis

This study investigates the impact of FDI, green technology innovation and GDP on CO2 emissions in the western region of China. This study applies the extended STIRPAT model, selects the relevant data of nine provinces in western China from 2000 to 2019, applies the static panel data analysis method, compares and analyses the estimation methods of Pooled OLS, fixed effect and random effect, and finally adopts the robust standard error estimation method of fixed effect. The results of the robust standard error estimation indicate that, in addition to the negative impact of green technology innovation on CO2 emissions, CO2 emissions are positively impacted by FDI, GDP, population, and the proportion of the secondary and tertiary industries. Therefore, reasonable introduction of FDI and improving green technology innovation levels are crucial in reducing CO2 emissions in the western region of China.

The effects of tourism on economic growth targets achievement

ABSTRACT Exploring the impact of tourism on economic growth targets achievement (EGTA) can not only effectively combine the tourism-induced economic growth hypothesis with political promotion tournament theory but also help guide the economic decisions of local officials. Based on panel data from 277 cities in China, this paper examines the impact of tourism on EGTA. The results show that tourism revenue is not favourable to EGTA, but tourist arrivals are. The significant effect of tourism on EGTA is only found in eastern China. Tourism in cities not driven by tourism often fails to stimulate EGTA. In regions with higher levels of economy and technological innovation, tourism has a greater positive impact on EGTA, but fixed asset investment amplifies tourism’s negative impact on EGTA. In addition, tourist arrivals have a significant spatial spillover effect on EGTA. This paper reveals the theoretical mechanism of tourism-induced EGTA and is also an important attempt to integrate the political promotion tournament theory with the tourism-induced economic growth hypothesis.

The impact of green finance on renewable energy development efficiency in the context of energy security: Evidence from China

The influence of green finance (GF) on renewable energy development efficiency (REDE) has garnered considerable attention from both academia and society. To study the changes in China's REDE in recent years and GF's effect on it, this research first evaluates 30 provinces’ REDE from 2010 to 2019 using a non-radial directional distance function (NDDF) based on global technical assumptions. Second, we evaluate the direct impact of GF on REDE. Finally, we explore the internal mechanism for how GF influences REDE. The results of this study are as follows. (1) GF has a significant promoting effect on REDE. (2) The improvement of renewable energy (RE) technological innovation level and the increase of foreign investment strengthen GE's promoting effect on REDE. (3) The positive effect of GF on REDE is prominent in regions with lower environmental regulations and carbon intensities and higher financial development levels. This paper offers relevant policy suggestions to improve REDE and to enhance GF development.

Spatial network structure and influencing factors of carbon emission intensity in Guangdong-Hong Kong-Macao greater bay area

Introduction: In response to China’s ambitious dual-carbon goals, this study investigates the spatial correlation and influencing factors of carbon emission intensity within the Guangdong-Hong Kong-Macao Great Bay Area (GBA), a region pivotal for the nation’s energy conservation and emission reduction efforts. Through a comprehensive analysis encompassing the period from 2000 to 2020, this research aims to delineate the spatial dynamics of carbon emissions and identify actionable insights for regional low-carbon development.Methods: Utilizing an integrated methodology comprising spatial autocorrelation analysis, Social Network Analysis (SNA), and the Quadratic Assignment Procedure (QAP), the study analyzes carbon emission data alongside socio-economic variables. These methodologies allow for a nuanced exploration of the spatial correlation structure and the determination of factors influencing carbon emission intensity across the GBA.Results: Findings reveal a cyclical fluctuation in the spatial network of carbon emissions from 2000 to 2020, characterized by varying degrees of cohesion among cities, indicating significant opportunities for spatial optimization. A “core-periphery” pattern emerges, with economically robust cities such as Hong Kong and Macao at the core, and less developed cities like Huizhou and Jiangmen on the periphery. Cities like Guangzhou and Shenzhen play crucial mediator roles. The QAP analysis further identifies six major influencing factors: geographic spatial proximity, economic development level, urbanization rate, industrial configuration, level of technological innovation, and environmental protection efforts, with the latter four having a markedly positive impact on spatial relevance.Discussion: The study’s insights underscore the importance of understanding the spatial dynamics of carbon emissions and the role of socioeconomic factors in shaping these patterns. For policymakers and stakeholders in the GBA, these findings highlight the necessity of targeted intervention strategies that consider both the unique position of cities within the spatial network and the broader socio-economic context. This approach can significantly contribute to achieving China’s dual-carbon objectives, promoting energy conservation, and facilitating the transition to a low-carbon economy.

Research on total factor energy efficiency in western China based on the three-stage DEA-Tobit model.

As an essential material basis and power source for economic and social development, Western China's low energy use efficiency has hindered its sustainable economic development. This study aims to evaluate the total factor energy efficiency of the region and identify its influencing factors. A three-stage DEA model was used to measure the efficiency of 11 provinces from 2006 to 2021, and the Tobit model was employed to investigate internal factors. The findings show that (i) external environmental factors and stochastic perturbations have a significant impact on TFEE in the western region, overestimating integrated efficiency and scale efficiency and underestimating pure technical efficiency. (ii) the study of external influencing factors finds that the level of economic development increases input redundancy; the industrial structure increases capital input and labor input redundancy while decreasing energy input redundancy; and the energy consumption structure increases capital input and energy input redundancy while decreasing labor input redundancy. (iii) the study of internal influencing factors finds that the level of scientific and technological innovation, the level of openness to the outside world, and the TFEE have a positive correlation. In contrast, the intensity of environmental regulation has a negative correlation.

The coupling and coordination of digital economy and manufacturing transformation and upgrading for industry 5.0 in Hebei Province

In the context of the widespread application of digital technologies such as the Internet, big data, artificial intelligence, and cloud computing, digital transformation in the manufacturing sector has become an important engine to promote high-quality economic development in Hebei Province. This paper aims to objectively analyze the current situation of industrial integration between the Beijing-Tianjin-Hebei digital economy and the manufacturing industry, and conduct level measurement, so as to promote the in-depth integration and development of the digital economy and manufacturing industry in Hebei Province, so that the manufacturing enterprises in Hebei Province can rebuild their competitive advantages in the future development, finally realize digital transformation, and promote the high-quality development of the manufacturing industry in Hebei Province. Therefore, it is very important to carry out empirical research on the integrated development of digital economy and manufacturing industry in Hebei Province. First of all, this paper constructs the index evaluation system of digital economy and manufacturing industry respectively, takes the relevant data of Beijing-Tianjin-Hebei region in recent five years as data samples, uses entropy weight-TOPSIS method to measure the level of digital economy development and manufacturing industry transformation, and uses the coupling coordination degree model to measure the level of industrial integration of the two. The final results show that: (1) The development level of digital economy in Hebei Province fluctuates greatly, and there is still a certain gap with Beijing and Tianjin, but the future development potential of digital economy is huge. (2) The transformation level of manufacturing industry in Hebei Province shows a trend of fluctuation and rise on the whole, and the development trend is good, and the gap between Hebei Province and developed regions is gradually narrowing. (3) The integration of digital economy and manufacturing industry in Hebei Province has a good development trend, but there is still a certain gap with Beijing and Tianjin, and there are problems of inadequate, unstable and unbalanced industrial integration. Finally, based on the research conclusions, suggestions are put forward to promote the coordinated development of Beijing-Tianjin-Hebei region, improve the level of digital economy and manufacturing integration of industrial convergence development, raise the level of digital infrastructure construction, and raise the level of science and technology innovation. This paper reveals the mechanism of digital economy affecting the high-quality development of manufacturing industry, studies the whole process of digitalization, information technology and intelligence integration into the development of manufacturing industry, and fully releases the positive effect of digital economy driving the high-quality development of manufacturing industry, which has important theoretical and practical significance for promoting the high-quality development of manufacturing industry and formulating relevant industrial policies.

Measurement and influencing factor analysis of the matching degree between agricultural scientific and technology innovation and rural industry integration under the sustainable background

Agricultural scientific and technological innovation and rural industry integration are the key contents of promoting agricultural and rural modernization in China. This study empirically analyzed the matching relationship between the two and its influencing factors, and found that the matching degree between agricultural scientific and technological innovation and rural industry integration in China showed a steady upward trend in the sample period. Both China as a whole and all regions completed the upgrading from moderate to high matching in the sample period, The performance of each region is also excellent. In 2020, the matching degree of 28 regions will enter a high matching range. The implementation of the rural revitalization policy will help to improve the matching degree between China’s agricultural scientific and technological innovation and rural industrial integration. The scale of rural financial development and the matching degree of lagging one period also have a significant positive impact on the improvement of the matching degree. This study further proposes relevant policy recommendations from improving the supply level of agricultural scientific and technology innovation, enhancing the adaptability between supply and demand of agricultural scientific and technology innovation, improving the policy support system, and optimizing the financial security system.

Can the green finance pilot policy promote the low-carbon transformation of the economy？

Based on the panel data of 30 provinces (cities) from 2006 to 2020, this paper selects 2011 and 2017 as the time nodes of the green finance pilot policy, and uses PSM-DID Model and Mediating Effect Model to empirically analyze and verify the promotion effect and mechanism of the green finance pilot policy on the low-carbon transformation of the economy. The study found that both the green finance pilot policies in 2011 and 2017 can promote the low-carbon transformation of the economy, and the policy effect is significant. The Mediation Mechanism Test found that the green finance pilot policy could promote the low-carbon transformation of the economy through two paths: optimization of energy structure and improvement of technological innovation level. The Dynamic Effect Test found that the policy effect of the green finance pilot policy in 2011 to promote the low-carbon transformation of the economy is continuous, while the policy effect of the green finance pilot policy in 2017 to promote the low-carbon transformation of the economy is less continuous. However, the policy effects of the green finance pilot policies in 2011 and 2017 will weaken over time. This paper enriches and develops the relevant research on the green finance pilot policy, providing empirical evidence and research enlightenment for China to further expand the construction scope of the green finance reform and innovation pilot zone, implement green finance policies, and promote the low-carbon transformation of the economy.

How digital government mediate the influence of fossil fuels on green innovation: Evidence from China's a-share industrial enterprises

China's rapid economic growth has resulted in a heavy reliance on fossil fuels, necessitating effective government intervention to facilitate their green transformation within the industrial sector. Therefore, a comprehensive investigation into the impact of mineral resource and fossil fuel dependence (ED) on the green transformation of Chinese enterprises, alongside the role of digital governance systems, holds paramount importance. This study delves into the influence of ED on firms' green technology innovation (FGI) using data sourced from A-share industrial enterprises listed on China's Shanghai and Shenzhen stock exchanges during the period from 2011 to 2021. Additionally, it examines the internal mechanisms facilitated by digital government, and provides insights into the heterogeneity observed from the perspectives of enterprises' industry classifications and sizes. The following conclusions are drawn: (1) ED significantly impedes the enhancement of green technology innovation levels among listed industrial enterprises, and this finding remains robust across multiple testing methods. (2) ED demonstrates varying inhibitory effects on firms' green technology innovation, with the most pronounced impact observed in the energy production and supply industry and the mining industry, and a relatively weaker effect observed in manufacturing enterprises. Furthermore, the inhibitory effect of fossil energy dependence on green technology innovation is observed to be stronger in small-scale enterprises compared to their larger counterparts. (3) The advancement of the digital economy notably mitigates the inhibitory effect of fossil energy dependence on firms' green technology innovation. (4) ED primarily diminishes the level of green innovation by reducing the stringency of government environmental regulations, hindering regional marketization, and impeding the industrial structure's upgrade.

HOW DOES STATE-OWNED EQUITY AFFECT GREEN TECHNOLOGY INNOVATION OF PRIVATE ENTERPRISES

Based on the data of 22368 private listed companies in the CSMAR database from 2010 to 2022, this paper empirically tests the impact of mixed ownership reform of private enterprises on green technology innovation and discusses the mechanisms of financing constraints. The research finds that the introduction of state-owned equity by private enterprises can help enterprises improve their green technology innovation level. Further research reveals that financing constraints significantly limit enterprises' green technology innovation, and the introduction of state-owned equity can enhance this innovation by alleviating financing constraints. The effect of mixed reform in less developed areas is more significant. This paper provides important empirical data for the mixed ownership reform of private enterprises and also provides ideas for the improvement of the green technology innovation level of private enterprises in developing countries.

How can the policy combination promote the development of green buildings? ---Analysis based on stage perspective

The development of green buildings (GBs) relies on the incentives and penalty provided by government policies. Firstly, different development stages of GBs are identified in this study, and an evolutionary game approach is used to explore the stage characteristics and behavioral strategies of key stakeholders at different stages. Thereafter, considering the multidimensional synergistic effects of government incentive and penalty policies at different stages, this study investigates how to set and match incentive and penalty combinations at different development stages of GBs. Research indicates that the “incentive and penalty combinations” in policies is a core element for the benign development of the GBs. In the preliminary stage, the level of green technology innovation significantly influences the direction of the system. The “light incentive and light penalty” policy of government is preferable as it can guide developers and consumers to understand GBs, thus opening up the green building market. In the growth stage, the maturity of green technology plays a significant role. The “heavy incentive and heavy penalty” policy of government is effective, which helps developers compensate for construction costs, actively develop GBs, and effectively avoid deviant behavior. Meanwhile, consumers also change their purchasing preferences based on the benefits of GBs. In the mature stage, the role of industry associations becomes more prominent after the government withdraws from the market. The supervision strategy of “strong supervision and light penalty” effectively manages the green building market. Consumers continue to trust the quality of GBs from developers, and the synergy among the government, developers, and consumers collectively promotes the maturity of the green building market.

Coupled Coordination and Drivers of Green Technology Innovation and Carbon Emission Efficiency

The coupled and coordinated development of green technology innovation and carbon emission efficiency in the Yangtze River Economic Belt is crucial for its realization of green and low-carbon transformation. Based on the panel data of the Yangtze River Economic Belt from 2011 to 2021, the comprehensive evaluation levels of green technological innovation and carbon emission efficiency were measured, and the coupling degree of coordination model and panel Tobit model were constructed to empirically analyze the coupling degree of coordination and driving factors of the two. The results show that, overall, the comprehensive evaluation value of green technology innovation level in the Yangtze River Economic Zone shows an upward trend; the value of carbon emission efficiency first rises and then falls. From the perspective of spatial distribution, both of them present the characteristic of “high in the east and low in the west”. The coupling coordination degree shows a growing trend and initially realizes the basic coordination. The coupling degree of coordination shows a significant negative correlation between the energy structure and the coupling degree of both of them, while urbanization level, environmental regulation, industrial structure, level of economic development, degree of openness, and labor level all show a significant positive correlation.

Agricultural greenhouse gas emissions, fertilizer consumption, and technological innovation: A comprehensive quantile analysis

This paper investigates the asymmetric inter-linkages and causality between agricultural greenhouse gas emissions, fertilizer consumption, and technological innovation in four main agricultural countries i.e., China, the United States, Japan and Canada, by employing monthly data from 1990 to 2019. Accordingly, Quantile-on-Quantile (QQ) regression and two causality-in-quantile approaches are applied to conduct a comprehensive quantile analysis of the asymmetric relationship for all quantiles of the above distribution. Our results exhibit a positive association between agricultural greenhouse gas emissions, fertilizer consumption, and technological innovation in China, the United States and Canada. Besides, the strength of the positive association depends largely on the development level of agricultural greenhouse gas emissions, fertilizer consumption, and technological innovation. However, except for the positive impact between fertilizer consumption and agricultural greenhouse gas emissions, I find a negative nexus between agricultural greenhouse gas emissions and technological innovation in Japan. Compared with the other three sample countries, Japan has done the best in agricultural greenhouse gas emission mitigation. The results also demonstrate that agricultural greenhouse gas emissions, fertilizer consumption, and technological innovation follow a bidirectional quantile-causality relation in all sample countries. Overall, I find that fertilizer consumption does increase agricultural greenhouse gas emissions, and that technological innovation has not played a full role in mitigating greenhouse gas emissions in most countries. Finally, our findings have significant implications for formulating reasonable emission reduction measures in the agricultural sector.

Evaluating the Impact of Urban Digital Infrastructure on Land Use Efficiency Based on 279 Cities in China

The development and application of urban digital infrastructure can alter land use patterns and facilitate the aggregation of factors such as labor and capital, thereby influencing the land use efficiency in cities. Based on statistical data from 279 cities in China spanning from 2004 to 2019, this study employs fixed-effects and mediation models to analyze the impact of urban digital infrastructure on land use efficiency. The findings reveal that the construction of urban digital infrastructure significantly promotes the enhancement of land use efficiency, with technological innovation levels and industrial structural transformation serving as mediators between urban digital infrastructure and land use efficiency. The impact of urban digital infrastructure on land use efficiency exhibits heterogeneity across different city scales, urban tiers, geographic locations, and policy implementation batches. Its effects are more pronounced in larger-scale cities, higher-tier cities, those located in the central and western regions, and the first two batches of pilot cities. The research findings contribute to providing theoretical references and a decision-making basis for enhancing land use efficiency, advocating for increased investment in urban digital infrastructure construction, encouraging technological innovation levels, and facilitating the upgrading of industrial structural transformation.

Nexus between carbon emissions and local debt risk: Evidence from China's prefecture-level cities

Debt risk is an externality of carbon emissions in the greening transformation process. Based on panel data of 171 prefecture-level cities in China from 2012 to 2020, this article empirically analyzed the influence and mechanism of carbon emissions on local debt risk. The results can be concluded as follows: (1) Carbon emissions will significantly induce local debt risk. After considering the endogenous problem and serial robustness tests, the conclusions above are still valid. (2) Local debt risk itself has a cumulative expansion effect stimulate by carbon emissions. And carbon emissions will strengthen the depth of local debt risk with the increase of local debt risk. (3) The moderating impact of carbon emissions on local debt risk has heterogeneous characteristics, with different industrialization processes, developmental level of scientific and technological innovation, and corporate environmental management regulation. This article not only provides a new evidence for carbon emissions externality from local debt risk perspective, but also provides a useful reference for local governments to enhance debt risk governance, and orderly implement reduction action of carbon emissions.