Innovation Ability Of Enterprises Research Articles

Philosophical Research on Enterprise Innovation Ecology Based on a Human–Computer Interaction Mental Model

Enterprise innovation ecology plays a vital role in the operation and development of enterprises. It can enable enterprises to have benign and sustainable progress space in action. At the same time, it can also make the innovation ability of enterprises grow unprecedentedly, which is a crucial factor related to the survival and lifeline of enterprises. However, enterprise managers are often too immersed in concept innovation and structural optimization in the actual innovation and ecological construction of enterprises. Still, they do not pay attention to the problems in actual construction. This would cause the actual operation of the system to be restricted by key influencing factors such as environmental protection policies, making it difficult to achieve effective progress. In this regard, the purpose of this paper is to analyze and discuss the enterprise innovation ecological philosophy based on the human–computer interaction mental model. Therefore, this paper comprehensively considers four key factors that affect the construction of enterprise innovation ecology, namely, the promotion of enterprise technology, the competitiveness of enterprise market, the innovation characteristics of enterprises, and the environmental constraints of innovation ecology, and improves and perfects the innovation ecosystem from these factors. Finally, an efficient ecological model of enterprise innovation was designed, and the scientific construction was carried out through the human–computer interaction mental model combining human–computer interaction technology and cognitive psychology. At the same time, the model is applied to the actual enterprise operation, and the naive Bayesian algorithm is adopted to optimize the relevant performance of the algorithm model. The experimental results showed that the highest sample accuracy of the algorithm reaches 92.9%, which greatly improved the operation efficiency of enterprise innovation ecological construction.

The influence of collaborative innovation network characteristics on firm innovation performance from the perspective of innovation ecosystem

PurposeThis study is aimed at making an inspection of the effects of collaborative innovation network characteristics on firm innovation performance, and the intermediary roles of knowledge transfer efficiency is taken into account.Design/methodology/approachThis study used a convenient sampling method to obtain population and samples. Using data obtained by publishing online and paper questionnaires, and using on-site interviews in Anhui Province in the Yangtze River Delta region of China, descriptive analysis, regression analysis and correlation analysis are utilized to study the direct influence of collaborative innovation network characteristics on knowledge transfer efficiency as well as firm innovation performance, and the intermediary roles of knowledge transfer efficiency on firm innovation performance, respectively. In this study, 3,000 questionnaires were distributed to the employees of enterprises engaged in research and development (R&D) activities, of which 2,560 were valid. With the help of SPSS24.0 software, the reliability and validity of the questionnaire was analyzed.FindingsThe results are indicative of that network centrality and relationship strength positively affect knowledge transfer efficiency and firm innovation performance. Nevertheless, network scale has no significant correlation with knowledge transfer efficiency and enterprise innovation performance. In addition, knowledge transfer efficiency is an intermediary between collaborative innovation network characteristics and enterprise innovation performance, and positively affects enterprise innovation performance, which demonstrated that managers should take advantage of collaborative innovation network characteristics to elevate knowledge transfer efficiency because well-realized transferals of knowledge can help accelerate the coordination of resources in knowledge, and finally bring about the advancement of firm's innovation abilities and performance.Research limitations/implicationsThere are few previous studies that fully examined the relationships among collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. This paper developed previous researches on the relationships between collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. The mediation of knowledge transfer efficiency on the relationship between collaborative innovation network characteristics and firm innovation performance is analyzed. Further, studies on collaborative innovation network characteristics using data obtained from employees engaged in R&D activities are very limited in the literature. On account of that, the findings in this study may make sense to the innovation ability of innovative enterprise and expand the literature in the field of enterprise strategic management and knowledge management.Practical implicationsThis analysis shows that collaborative innovation network characteristics have both positive and negative effects on firm innovation performance. Therefore, business managers should pay attention to their position in the collaborative innovation network and maintain the relationship strength with other innovation subjects. Special consideration should be given to the knowledge transfer of innovative enterprises, so as to improve firm innovation performance practically.Originality/valueThe study may provide additional understandings for researchers, government managers, universities and enterprises with regard to strategic management from the visual angle of innovation ecosystems. It is instrumental in the exploration of the mechanisms enabling firm innovation performance.

Influence of Enterprise’s Factor Inputs and Co-Opetition Relationships to Its Innovation Output

In the context of economic globalization, innovation has become a major drive for the sustainable development of enterprises, which emphasizes the importance of studying the influencing factors of enterprise innovation output. The purpose of this study is to clarify the influence mechanism of different indicators on enterprise innovation output, and then provide relevant suggestions for improving enterprise innovation ability. This paper takes 562 enterprises in Chaoyang Sub-park and Fengtai Sub-park of Zhongguancun in Beijing within the time span between 2015 and 2016 as the research objects, and constructs a comprehensive indicator system of influencing factors for enterprise innovation output from the perspective of enterprise co-opetition relationship, factor input and environmental factors. A quantitative model of innovation output and influencing factors was built and then solved, via spike-and-slab sparse function and stepwise regression, aiming at analyzing the influence of different indicators on enterprise innovation output. In addition, this paper also classifies enterprises according to their innovation level and explores the influence of indicators on different types of enterprises. The innovation of this study lies in the modeling of competition and cooperation between enterprises and the establishment of a relatively comprehensive indicator system of influencing factors for enterprise innovation output. The results show that the degree of technological collaboration between enterprises, the level of financing and the degree of capital and labor input in innovation activities have significant positive effects on enterprise innovation output. On the contrary, product and service competition, as well as capital competition, tends to have a negative impact, which urges enterprises to pay heed to the intensity of competition faced by products and services as well as the diversity of financing sources and investment targets to reduce the negative impacts. In addition, enterprises with different levels of innovation should take customized measures in terms of factor input and co-opetition relationships, in that some indicators such as network structure indicators negatively influence the innovation output of enterprises with lower levels of innovation, but has positive impacts on those with higher levels of innovation.

Recommendation Research of Science and scientific and technological reports for the Needs of Science and Technology Enterprises

To improve the scientific research and innovation ability of science and technology enterprises, we recommend science and technology reports for the individual demandss of science and technology enterprises, and provide scientific theory and technical support. This paper proposes a technology report recommendation method that integrates feature value and time value for the demandss of science and technology enterprises. Firstly, the TF-IDF algorithm and word2vec language model are used to construct the feature vector of technology enterprise demand. Secondly, LDA, TF-IDF and word2vec are used to construct the feature vector of scientific and technological reports, and the time value of scientific and technological reports is calculated by referring to the negative exponential equation of literature aging and the half-life index of downloads. Finally, the similarity is calculated between the technology enterprise demand feature vector and the technology report vector, and the final recommendation results are obtained by sorting and comparing with other methods. The empirical results show that the scientific and technological reports recommended by this paper’s methodology not only meet the demandss of science and technology enterprises, but are also novel and cutting-edge.

Research on the evaluation of green innovation ability of resource-based enterprises based on digital technology

In order to improve the evaluation effect of resource-based enterprises' green innovation ability, this paper studies the evaluation of resource-based enterprises' green innovation ability based on digital technology, and gives an idealized algorithm of MIIC with two variables. This paper points out the shortcomings and defects of the existing MIC approximation algorithms through further analysis. Moreover, in view of the disadvantage of high time complexity of the existing two-variable MIC approximation algorithm, this paper proposes a two-variable MIC clustering algorithm. In addition, this paper uses the K-Means clustering algorithm to replace the core of the maximum information coefficient MIC algorithm, which simplifies the optimization process when searching for the optimal grid division. The experimental research results show that the evaluation research model of the green innovation capability of resource-based enterprises based on digital technology proposed in this paper can play a certain role in the green innovation of resource-based enterprises.

Research on the Path of Digital Economy Promoting Export Trade under the Background of High-quality Development

Digital economy is an economic form based on information. It focuses on the role of value chain and industrial chain in many factors affecting the high-quality development of export trade. At the same time, based on the main characteristics of the digital economy, the paper analyzes the mechanism of the digital economy on the high-quality development of export trade, and the role of digital industrialization and industrial digitalization is more obvious. At this stage, if China wants to promote the high-quality development of export trade, it should promote the development of digital industrialization and stimulate the innovation ability of foreign trade enterprises. Improve the digitalization level of export trade industry and create a sound ecology for the development of international trade; Improve the basic services of the digital economy and expand the development space of export trade; Build a good development environment for export trade with the help of digital economy; Promote the diversification of export trade products, the diversification of main bodies, and the development of low-carbon.

Environmental Regulation, Corporate Social Responsibility (CSR) Disclosure and Enterprise Green Innovation: Evidence from Listed Companies in China.

The resource and environmental constraints on China's economic development have become more prominent; thus there is an urgent need for enterprises to achieve green innovation transformation to promote high-quality economic development. We obtained data on 655 on Chinese A-share companies listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2020, a total of 7205 samples, and explored the influencing mechanism of environmental regulation on corporate green innovation and the moderating mechanism of CSR disclosure by constructing a nonlinear fixed-effect regression model. The results showed: (1) the overall level of green innovation of listed companies is low, and the relationship between environmental regulation and enterprise green innovation presents the U-shaped characteristic of changing from cost effect to innovation compensation effect; (2) non-state-owned enterprises have less tolerance and more sensitive response to environmental regulation than state-owned enterprises; (3) social responsibility information disclosure has a positive regulatory effect on environmental regulation and enterprise green innovation, and non-state-owned enterprises are more significant. It provides references for the government to adjust the intensity of environmental regulation, and, meanwhile, for enterprises to improve the level of environmental protection and the CSR disclosure, and enhance the green innovation ability of enterprises in emerging market.

Sustainable collaborative innovation capability enhancement paths of marine ranching: Supernetwork analysis perspective

In order to solve the problem of weak innovation ability of marine ranching enterprises, it is necessary to establish a collaborative innovation system involving multiple subjects to break the innovation boundary of enterprises. At the same time, because the collaborative innovation system of marine ranching is a complex network system, this paper designs the supernetwork model of collaborative innovation in marine ranching based on supernetwork theory, by analyzing the operation mechanism of relationship coordination network, resource sharing network and cooperative innovation network in supernetwork, solving the network equilibrium conditions and the path to realize supernetwork equilibrium based on variational inequality. Through numerical examples, this paper draws the following conclusions: (a) When the relationship coordination network, resource sharing network and cooperative innovation network all reach equilibrium, the marginal total cost of the three networks is equal to the marginal total value, the cooperative innovation super network of marine ranching reaches equilibrium state; (b) the supernetwork model of collaborative innovation in marine ranching needs to go through two states: “initial-intermediate” and “intermediate-equilibrium” to achieve equilibrium. Finally, this paper puts forward suggestions on the behavior of the participants to ensure the stable operation of the marine ranching collaborative innovation system.

Driving Path and System Simulation of Green Innovation Capability of Science and Technology Enterprises in Yangtze River Delta

Green innovation integrates innovation-driven and green development strategies, which helps to realize the green transformation of production and life in the Yangtze River Delta region, and promote high-quality economic development. Based on the multidisciplinary cross attribute of system dynamics (SD), the boundary and influencing factors of the green innovation system are defined, and the system dynamics model of green innovation ability of science and technology enterprises is constructed. With the help of statistical data from 2010 to 2020, the model is simulated to explore the change trend and law of elements. The results show that: (1) The green innovation ability of science and technology enterprises is composed of three stages, knowledge innovation, technological innovation, and innovation application, which are interconnected and progressive. The change trend of each variable is conducive to the improvement of green innovation competitiveness, and the green innovation benefits are significant. (2) Green innovation is driven by multidimensional factors such as R&D investment, technological innovation investment, knowledge innovation ability, and the conversion rate of scientific research achievements. The improvement of the conversion rate of scientific research achievements has the greatest impact on the enterprise’s green innovation ability, and the change trend is more obvious. (3) Positive and negative two-direction sub-mode regulation of R&D investment, technological innovation investment, and scientific research achievement conversion coefficient will affect the speed of green innovation accumulation of enterprises, and this increment is marginally increasing with the increase of the coefficient in the short term. Finally, some suggestions are put forward to promote the green innovation ability of science and technology enterprises in the Yangtze River Delta.

The Influence of Entrepreneur's Social Capital and Resource Acquisition on Enterprise's Innovation Ability -- A Case Study of Guangdong Entrepreneurs

The Influence of Entrepreneur's Social Capital and Resource Acquisition on Enterprise's Innovation Ability -- A Case Study of Guangdong Entrepreneurs

Environmental Regulation and the Innovation Performance of Chinese Export Firms: A Quasi-Natural Experiment based on the Law of Promoting Cleaner Production

As China’s export products have been pollution-intensive in recent decades, stringent environmental regulations have been applied to export products. Environmental regulation will squeeze out a firm’s expense on innovation and impact its productivity through the cost effect and innovation offset effect. However, the overall impact on productivity change is uncertain because of the trade-off between the two effects. This study explores the relationship between the innovations of export firms and environmental regulation using the panel data of export firms in 18 industrial industries. The impact of the implementation of the Law of Promoting Cleaner Production on the innovation of export firms in industries with different pollution intensities has been studied using the difference-in-differences method. The findings show that environmental regulation has a negative impact on the innovation of export firms. Export destinations create a difference in innovation performance. Environmental regulation tends to have a positive impact on the innovation of firms whose major markets are developed countries. Compared with light pollution-intensive industries, the Law of Promoting Cleaner Production has reduced the innovation ability of export firms in heavy and medium pollution-intensive industries. Therefore, when formulating environmental policies, regulators should consider the impact of such policies on the innovation of export enterprises and formulate a reasonable intensity of environmental regulations to achieve a win–win situation vis-à-vis improving the ecological environment and enhancing the innovation ability of export enterprises.

The Influence of the Third Distribution on the Innovation Ability of Enterprises

Facing the vigorous development of the third distribution, its supporting mechanism is gradually improving. Therefore, combining the development of the third distribution, this paper analyzes the factors that affect the innovation ability of enterprises from the aspects of market mechanism, government capacity, legal system and social ethics, and proposes the path to enhance the innovation ability of enterprises. Applying the proposed innovation path to the actual development will enable enterprises to effectively improve their innovation ability and competitiveness in the face of the third wave of distribution development, so as to achieve the innovative development of the entire market.

Influence of Management Education on Enterprise Scientific and Technological Innovation Based on K-Means Clustering Algorithm

Scientific and technological innovation is the source of the survival and development of enterprises and the key to the realization of the goal of prosperity. In recent years, more and more companies have begun to focus on technological innovation, but the results are not significant, so companies have begun to explore the factors that affect their technological innovation. The management is the helm of the development of the enterprise, the main body of the company’s actual production activities, and the direct person in charge of the company’s management. Its influence on the innovation of the enterprise is self-evident, and the education level of the management directly determines the manager’s ability and vision. However, the current research on management mainly focuses on the position change of management and the rights of management and does not involve the level of education of management. Based on this, this article started from the management education and subdivided it with the K-means clustering algorithm, so as to explore the impact of management education on the technological innovation of enterprises. The experiment showed that there was a significant positive correlation between the educational level of management and the technological innovation ability of enterprises, and the correlation coefficient was 1.521. It fully shows that the management with a higher education background will promote the enterprise to carry out scientific and technological innovation practice and continuously improve the enterprise’s innovation ability.

How to Evaluate College Students’ Green Innovation Ability—A Method Combining BWM and Modified Fuzzy TOPSIS

Currently, enterprises are paying more and more attention to green innovation in order to reduce the negative impact on the environment and achieve sustainable development. Different from evaluating the green innovation ability of enterprises, how to evaluate a person’s green innovation ability from the perspective of open innovation is a new direction. This study aims at proposing a novel framework to evaluate college students’ green innovation ability. First, a set of criteria to evaluate college students’ green innovation ability is determined by experts using the panel consensus approach. Second, the best worst method (BWM) is used to calculate the weights of criteria. Lastly, modified fuzzy technique for order of preference by similarity to ideal solution technique (TOPSIS) technique is adopted to rank college students’ green innovation ability. Moreover, a case study is presented to verify the validity of the proposed method. The results provide implications for academic, industry, and policymakers. Specifically, through the evaluation of college students’ green innovation ability, universities can find the inadequacies in culturing students’ green innovation ability and strengthen education in the aspects corresponding to the criteria with high global weights. Companies can select the talented internship students with green innovation ability as employees and should realize that it is good for them to cultivate college students with universities. Policymakers of the education department can trace the quality of education in college senior students’ green innovation ability every year. In addition, they should pay more attention to establish policies regarding those criteria with high global weights.

Research on the cultivation of green competitiveness among chinese heavily polluting enterprises under country/district environmental regulations

The development of the world economy has caused serious environmental pollution, which has resulted in an ecological crisis. With the acceleration of economic development, China’s ecological crisis is becoming more serious. Green technology innovation is an important driving force in realizing green economic development, and heavily polluting enterprises are the key link to cultivating green technology innovation. The Porter hypothesis holds that environmental regulation has a promoting effect on enterprises’ green technology innovation, but this is not reflected in the context of China. As a basic administrative unit, the implementation of environmental regulations in counties and districts determines the effectiveness of environmental policies. Utilizing structural equation modeling, this study analyzes the cultivation of the green technology innovation ability of heavily polluting enterprises under environmental regulations. The results show that command-based environmental regulation can effectively promote enterprises’ green technology innovation ability. Incentive-based environmental regulation needs to be strengthened to drive the development of enterprises’ “three wastes” treatment innovation ability. Voluntary environmental regulation does not effectively promote green process innovation and “three wastes” treatment innovation. In addition, enterprises’ current “three wastes” treatment innovation capacity is not enough to promote the improvement of enterprises’ green competitiveness. The results of this article show that environmental regulation is conducive to the green innovation ability of enterprises, and this promotion effect needs to be further strengthened. Moreover, the highlighted research limitations will contribute to the subsequent research work.

Can high-speed train improve the innovation ability of enterprises?

ABSTRACT This paper analyzes the impact of high-speed train construction on enterprise innovation and its specific mechanisms by establishing high-speed train-city-firm level panel data and constructing a multi-period DID model in China. The results show that, firstly, the construction of a high-speed train significantly improves the innovation level of enterprises, and the construction of the first high-speed train can increase the number of patents of local listed enterprises by about 11.5%. Second, the impact of high-speed train construction on the innovation level of listed enterprises is mainly through the internal human capital and external marketization of enterprises. Specifically, the high-speed train construction affects innovation by weakening the transportation distance; on the other hand, it improves the external market environment and enhances the market competition, making firms seek innovation actively.

INCENTIVE EFFECT AND EMOTION REGULATION OF INFORMATION TECHNOLOGY ON INNOVATION BEHAVIOR

INCENTIVE EFFECT AND EMOTION REGULATION OF INFORMATION TECHNOLOGY ON INNOVATION BEHAVIOR

Digital transformation, green innovation and the Solow productivity paradox.

To provide evidence at the micro level for cracking the Solow productivity paradox, this paper deeply studies the impact of enterprise digital transformation on green innovation. In terms of theoretical research, three potential mechanisms are excavated for the first time; considering empirical research, a series of strict causal effect identification strategies are carried out. The results show that enterprise digital transformation can significantly promote green innovation, and it passes a series of robustness tests and endogenous tests. According to the theoretical and empirical results, the policy suggestions mainly include five points: helping enterprises to accelerate digital transformation; strengthening the green innovation ability of enterprises; reducing internal and external costs and promoting the professional division of labor; piloting the digital transformation policy; enhancing corporate social responsibility. It provides a reference of experience and a path for other countries to follow in implementing a digital transformation strategy and green sustainable development strategy.

Does the Upgrading of Provincial Development Zones Improve the Cities’ Economic Efficiency? Evidence from a Quasi-experiment of Heterogeneous Development Zones

The expansion of China's development zones has already made significant contributions to economic development, as well as provided practical guidance for other developing countries to implement development zone practice. This paper analyzes how industry characteristics, high-technology zone hierarchy differences, regional differences, and openness differences affect the causal relationship between high-tech zones (HTZ) establishment and innovation of information service enterprises. The study constructs a complete empirical analysis framework with the help of the difference-indifference model (DID) and interaction term model. The empirical results show that, compared with the control group, HTZ establishes more innovation intentions and increases the innovation scale, thus significantly enhancing innovation levels. Compared with the non-high-tech zone sample, the HTZ has a significant positive effect on the innovation ability of technology service enterprises in the cities. Meanwhile, through a comparison of the regression results of different regions, it is found that the establishment of high-tech zones has the best effect on enterprise innovation ability in the eastern region, followed by the northeastern, central, and western regions. The following policy recommendations are proposed for optimizing the construction and management of high technology zones and promoting enterprise innovation development.

Innovation Service Platform of Small and Medium-Sized Microenterprises Based on Social Perception and Neural Network Algorithm.

In recent years, the number and scale of small, medium-sized, and micro enterprises have continued to increase, which is the main force to promote the development of China's national economy, the guarantee of China's rapid and stable economic development, and has a direct impact on social stability and people's livelihood. In China's economic growth, small, medium-sized, and micro businesses play a critical role. However, several limitations limit their current growth stage, preventing them from expanding their size, such as resource and environmental limits, an inappropriate industrial structure, and institutional issues, such as severe market rivalry. To address this issue, this paper develops a micro innovation service platform for small and medium-sized businesses, offers a variety of services to small and medium-sized businesses, fully realizes data sharing and transmission in all aspects using social perception and neural network algorithms, and effectively utilizes social attributes on mobile nodes to assist each node. Also, it investigates the impact of the innovation service platform for small and medium-sized micro firms in practice. After the construction of the innovation service platform for small and medium-sized micro enterprises in 2018, it analyzes the number of transaction projects of platform technology transfer, technology development, technical consultation, and technical services from 2018 to 2020 and analyzes the transaction volume of projects in four aspects. The results show that they have significantly improved, which plays an important role in realizing the transformation of achievements and improving the innovation ability of small and medium-sized micro enterprises in China. At the same time, according to the investigation and analysis of 8 innovative service platforms in the western region, 25% of them have developed well.