Innovation Efficiency Research Articles

Banking competition, credit financing and the efficiency of corporate technology innovation

Based on the data spanning 2010 to 2022, this study delves into how banking competition impacts the efficiency of enterprise science and technology innovation by lowering credit costs, enhancing credit availability, optimizing credit allocation, and offering empirical evidence for the significant role of banking competition in influencing corporate technology innovation efficiency. This paper concludes that increased competition in the banking sector notably impacts corporate technology innovation efficiency. Banking competition alters the traditional relationship-based lending model, enhancing banks' ability to assess risks and support innovative projects by enterprises, encouraging enterprises to enhance innovation quality and boost research and development investments, leading to a learning curve effect on innovation and enhancing the efficiency of technology innovation. Mechanism analysis reveals that credit financing plays an intermediary role. Competition in the banking sector leads to lower costs and increased availability of bank credit for research and development in enterprises. It helps address the issue of limited finance for innovation in enterprises, encourages larger-scale innovation, and enhances innovation efficiency. Banking rivalry has a role in enhancing corporate technology innovation efficiency, which is influenced by the environment to a certain extent.

Efficiency gains from reallocating innovation resources between China’s manufacturing sectors

ABSTRACT This paper proposes a new framework for quantifying the misallocation of innovation resources and is among the first to estimate innovation efficiency gains brought by the reallocation in China’s manufacturing industry from 2012 to 2021. Our results show that the misallocation of innovation resources between manufacturing sectors has significantly alleviated. The misallocation of innovation manpower is more serious than that of innovation capital stocks. The study provides theoretical guidance and policy implications for the government to adjust the allocation of innovation resources.

Evaluating the efficiency of green innovation and marketing strategies for long-term sustainability in the context of Environmental labeling

In the contemporary landscape, as environmental concerns take center stage, consumers are increasingly urged to make ecologically friendly choices, facilitated by the prevalence of environmental labeling. This study undertakes a comprehensive investigation into the influence of environmental labeling on customer purchasing behavior, with a specific emphasis on evaluating the effectiveness of green marketing and innovation initiatives. Using the Fuzzy Analytical Hierarchy Process (AHP) and Fuzzy Weighted Aggregated Sum Product Assessment (WASPAS) methodologies, the research pinpoints the elements and tactics able to influence consumer behavior in connection to environmental labeling. Therefore, seven factors, twenty-one sub-factors, and six strategies are identified. The results of Fuzzy AHP show the prominent role of product attributes, marketing and promotion strategies, and sustainability practices while seeking to change consumer behavior with regard to environmental labeling. In addition, the findings from the Fuzzy WASPAS approach suggest that environmentally friendly packaging, product labeling, and partnerships and collaboration are the most successful green innovation and marketing strategies. The findings of this study can help shape the design of more effective environmental labeling programs and marketing plans for encouraging sustainable purchases.

Digitalization and firms’ innovation efficiency: Do corporate social responsibility and irresponsibility matter?

Digitalization and firms’ innovation efficiency: Do corporate social responsibility and irresponsibility matter?

AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies

The advent of artificial intelligence (AI) technology has led to transformative shifts in the human landscape. Moreover, as a potent driving force behind the evolution of energy companies, green innovation has the potential to be supported by advanced technologies such as AI. However, academic research exploring the association between the AI adoption rate and green innovation in energy companies is scarce. This study analyzes data on Chinese listed energy companies from 2010 to 2020. Our findings indicate that energy companies with extensive AI adoption exhibit higher green innovation efficiency. This finding is particularly pronounced among firms that report substantial participation in environmental, social, and governance activities. However, our findings reveal that executives who focus on short-term benefits can undermine the positive influence of AI adoption on green innovation. These main findings are notably significant for energy companies where the roles of chief executive officer and board director are unified, state-owned enterprises, and companies that do not hold bank shares. This study offers novel insights and valuable guidance for policymakers regarding the strategic development of energy companies, thereby bridging a significant gap in the literature.

Digital economy's impact on green innovation efficiency: bottom-up or top-down?

Digital economy's impact on green innovation efficiency: bottom-up or top-down?

Fast style transfer for ethnic patterns innovation

Minority ethnic patterns in China, reflecting diverse cultures, serve as symbols of ethnic identity and cultural heritage. However, the current artistic domain of minority ethnic patterns faces dual challenges: limited artistic styles and insufficient innovation efficiency. In addressing these issues, this study proposes a novel approach for ethnic pattern innovation, named Fast Style Transfer for Ethnic Pattern Innovation (FST-EPI), aiming to enhance innovation efficiency and diversify artistic styles. FST-EPI comprises three key modules: background generation, background fusion, and fast transfer. Firstly, the background generation module utilizes the Visual Geometry Group network (VGGNet) to extract features from images, generating a background image with the desired style while preserving the necessary stylistic attributes. Subsequently, textile patterns are fused with the stylized background image, forming a content-background fusion image. Finally, the selected stylistic patterns, along with the content-background fusion image, are input into the fast transfer module to produce the ultimate innovative pattern. Experimental results demonstrate that the generated images not only fully retain the core features and cultural elements of minority ethnic patterns but also successfully integrate the unique styles from one or more reference images. This proposed method exhibits outstanding efficiency and feasibility in a broad range of experiments related to ethnic pattern style transfer, as evidenced by thorough comparisons with state-of-the-art methods. Ultimately, the processing speed of this method achieves a real-time output at the level of seconds, reducing processing time by nearly 50% compared to traditional approaches.

The impact of the free trade zones construction on green technological innovation efficiency ——evidence from 288 cities in Chinese

We measure the green technology innovation efficiency of 288 cities in China from static and dynamic dimensions using the super−SBM model and Malmquist−Luenberger index, and employ "Difference in Difference" (DID) model to evaluate the impact of FTZs construction on green technology innovation efficiency using panel data from 288 prefecture-level cities from 2008 to 2020. The findings show: (1) The FTZs significantly improve green technology innovation efficiency. The decomposition indexes promote the green technology innovation efficiency more from the dynamic productivity dimension (GTFP) functioning on technological advancement. (2) The FTZs can boost the efficiency of green technology innovation through industrial agglomeration, digital economy, and government financial support; (3) The effect of FTZs on the efficiency of green technology innovation differs based on the size and location of the city. Green technology innovation will reach maximum potential when promoting FTZ policy in less developed central, western, and interior regions. This study addresses whether FTZ policies can genuinely support regional green innovation and policy insights to expand opening up and enhance high-quality economic growth.

A multi-skilled staff scheduling and team configuration optimisation model for artificial intelligence project portfolio considering competence development and innovation-driven

This paper emphasises the pivotal role of enhancing research and development (R&D) staff competence and boosting team innovation efficiency in configuring R&D project teams for artificial intelligence (AI) product development. Diverging from traditional studies primarily focused on time, quality, and cost objectives, this study proposes prioritising the skill increments of staff and team diversity, aligning with the overarching goals of the R&D cycle. Targeting multi-skilled R&D personnel for scheduling and configuration, a three-objective tradeoff optimisation model is established. The nonlinear mixed-integer constrained programming model incorporates a learning effect for calculating employee skill value and employs a heterogeneity efficiency formula for assessing team diversity, particularly emphasising the diversity of R&D personnel research backgrounds. An algorithm based on Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is designed to obtain the approximate Pareto optimal solution. Furthermore, it compares the algorithm with the multi-objective particle swarm optimisation (MOPSO), explores practical decision-making methods for Pareto solutions, and conducts sensitivity analyses on the learning rate and diversity level. Our research is relevant to enterprises seeking to enhance R&D capabilities with a certain degree of homogeneity among R&D employees. This paper exemplifies and validates the proposed model and solution approach using a new AI product from a healthcare company.

Can the environmental trading enhance corporate green innovation efficiency?

This paper examines how environmental trading affects corporate green innovation efficiency. Based on data from 2010 to 2022, this paper adopts carbon trading pilots policy as a quasi-natural experiment and employs a difference-in-difference model to explore the effects and underlying mechanisms. The findings indicate that implementing a carbon trading pilots policy can effectively improve green innovation efficiency, and the impact is achieved by alleviating financing constraints and stimulating the number of green innovation applications. The findings help to adapt environmental policies, leading to increased green innovation efficiency, resulting in a win-win situation for economic growth and environmental conservation.

Scientific and technological innovation efficiency in Chinese provincial higher education institutions: a three-division network DEA approach

Scientific and technological (S&T) innovation in higher education institutions (HEIs) has become a major driving force behind China’s development. The Chinese government has attached great importance to S&T innovation in HEIs, creating the need for efficiency evaluation that can test the effectiveness of S&T policies and provide decision support for S&T innovation. The operational process of S&T innovation in HEIs can be decomposed into three divisions: research and development (R&D), technology transfer (TT), and technical service (TS). Furthermore, the intermediate products produced by the R&D division may be wasted in the TT division. Based on the internal structure and the utilization of intermediate products, this paper proposes a three-division network DEA to explore the efficiencies of S&T innovation in Chinese provincial HEIs. Based on empirical data from 2011 to 2020, the main findings are as follows. (1) The efficiencies of the S&T innovation in HEIs can be improved when the R&D and TT divisions cooperate to avoid wasting intermediate products. (2) The TT division is not only the main source of the overall inefficiency but also the main cause of the efficiency differences among areas. (3) The TT efficiencies of four areas tend to converge to the same steady state.

Can CSR effectively promote corporate green innovation efficiency?

Can CSR effectively promote corporate green innovation efficiency?

The impact of the digital economy on creative industries development: Empirical evidence based on the China.

Digital economy has become a "new engine" that driving global economic growth. Nevertheless, numerous controversies persist regarding whether and how digital economy can facilitate the development of emerging industries. Thus, this paper investigates how digital economy affects creative industries development in China and whether innovation efficiency mediates this relationship. Drawing upon a panel data set containing 29 Chinese provinces from 2012 to 2019, an econometric model is constructed for empirical analysis. We find that digital economy significantly promotes creative industries development, and innovation efficiency plays a partial mediating role between digital economy and creative industries development. According to the influence mechanism, the digital economy of various regions could promote the creative industries development by improving the innovation efficiency. Finally, relevant suggestions were put forward from the expanding application paths, improving regional innovation efficiency, and creating an innovative environment.

Green bonds and sustainable development: theoretical model and empirical evidence from Europe

ABSTRACT As a novel financial instrument, green bonds require further research to understand their causal effects and theoretical mechanisms on sustainable development fully. This paper constructs a theoretical model that characterizes the issuance of green bonds as the extent to which social planners prioritize environmental benefits in bond markets. In this model, we define sustainable development as the geometric mean of environmental factor inputs and final production output. By maximizing consumer utility, this model elucidates the direct and non-linear relationship between green bonds and sustainable development. The paper empirically investigates this proposition using data from 19 European countries between 2018 and 2022. The results indicate that: (1) Green bonds significantly promote sustainable development. This financial instrument, designed to raise funds for environmental projects, can indeed promote sustainable development through clean and green resource allocation. (2) The promotional effect of green bonds on sustainable development increases significantly with improvements in innovation efficiency, industrialization rates, and savings rates. This finding elaborates on the conditions under which the positive impact of green bonds on sustainable development is enhanced. (3) Green bonds only promote sustainable development when a country’s factor endowment structure reaches a specific threshold. Beyond this threshold, as the factor endowment structure becomes very high, the country’s sustainable development gains sufficient momentum, diminishing the role of green bonds. This finding suggests that the positive impact of green bonds on sustainable development is contingent upon certain properties reflecting the economic basis.

The Impact of Environmental Regulation on Collaborative Innovation Efficiency: Is the Porter Hypothesis Valid in Chengdu–Chongqing Urban Agglomeration?

Under the advocacy of sustainable and innovation-driven development, the potential impact of environmental regulation on collaborative innovation has become a controversial issue. This article uses panel data from 16 cities in the Chengdu–Chongqing urban agglomeration from 2011 to 2021 to analyze the impact of environmental regulation on collaborative innovation efficiency. First, this study uses the two-stage DEA model to analyze each city’s industry–university–research collaborative innovation efficiency. Then, the impact of environmental regulation on collaborative innovation is analyzed using the Tobit model. The results show that in the temporal dimension, the collaborative innovation efficiency of each city shows an upward trend. This demonstrates the outstanding effectiveness of transforming knowledge into technology for economic development. In the spatial dimension, the collaborative innovation efficiency of this urban agglomeration shows a “high in the center and low in the surroundings” pattern. The Tobit regression model shows that environmental regulation significantly impacts collaborative innovation in the Chengdu–Chongqing urban agglomeration. Command-and-control environmental regulation policies have a threshold effect on collaborative innovation, verifying the Porter hypothesis that appropriate environmental regulation promotes innovative activities. The results provide an initial basis for formulating regional environmental policies to achieve a win–win situation for innovation and sustainability in underdeveloped regions.

Does internal whistleblowing enhance firm innovation?

This paper examines whether and how internal whistleblowing enhances innovation. We have discovered that the establishment of an internal whistleblowing system help to increase firms' innovation output, in terms of patent application and citation. Furthermore, our paper draws on the monitoring effect of whistleblowing on CEO, and the evidence shows that whistleblowing reduces executives' misconduct and therefore increases investment in R&D. Besides, we also find that such monitoring effect between employees also improves firms' innovation efficiency. Finally, we find that whistleblowing has a positive impact on firm's profits among more innovative firms. This paper aims to investigate how employee monitoring enhances firm innovation, making a contribution to the growing literature on innovation.

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

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

Excess control of family board seats and corporate innovation

AbstractWe examine the impact of board‐level control on corporate innovation in family firms. We find that excess control of family board seats (ECFBS) is negatively correlated with innovation investment, innovation output and innovation efficiency. Our findings suggest that ECFBS exacerbates type II agency problems. Mechanistic analyses show that ECFBS reduces firms’ risk‐taking level, increases their financing constraints and damages channels for acquiring innovative professional knowledge. We also observe that effect of ECFBS on innovation is associated with family origin, familiarization time and family management characteristics. Our findings should be of interest to family firm manager investors and lenders who are interested in family governance mechanisms.

Strengthen the governance and utilization of scientific data, and enhance the efficiency of scientific data-driven innovation and development

Strengthen the governance and utilization of scientific data, and enhance the efficiency of scientific data-driven innovation and development

Research on the impact of environmental regulations on green technological innovation in China from the perspective of digital transformation: a threshold model approach

The digital transformation in developing countries is crucial in determining whether environmental regulations can better facilitate green technological innovation. This paper constructs a theoretical model to deduce the relationships among digital transformation, environmental regulations, and green technological innovation. Empirical research is conducted using a two-way fixed-effects model and a threshold regression approach, based on provincial panel data from China spanning the years 2013 to 2020. The results indicate that environmental regulation inhibits green technological innovation. However, digital transformation, by reducing cost pathways, can promote the efficiency of green technological innovation under environmental regulation. This moderating effect exhibits a nonlinear threshold characteristic. Regarding dimensions of digital transformation, the level of digital investment shows no threshold, while both the level of digital application and the scale of digital integration exhibit threshold effects. Presently, in China, digital transformation effectively incentivizes green technological innovation under environmental regulation. Therefore, increasing digital investment, advancing digital applications, and fostering digital integration are inevitable choices to drive green technological innovation under the pressure of environmental regulation.