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Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.

This study examines the innovation-efficiency linkage for Indian and Chinese manufacturing and service firms.

We applied the stochastic production and cost frontier approach to determine the output and cost efficiency of the firms surveyed in World Bank enterprise surveys. We then used both unconditional and conditional propensity score matching (PSM) estimation techniques to examine the effects of innovation as well as R&D on output and cost efficiency of the firms surveyed.

The study results suggest that innovation-efficiency linkage varies between countries and sectors. Innovations significantly raise output and cost efficiency of Indian manufacturing firms, whereas innovations in Chinese manufacturing firms are cost-oriented and negatively affect output efficiency. For the service firms of both countries, innovations are significantly positively linked with output and cost efficiency. The study also suggests that R&D acts as a crucial moderator for innovation-efficiency linkage for Chinese manufacturing firms but not for Indian firms, and the interaction effects of innovations are not substantially higher in magnitude than their individual effects. Finally, conditional PSM results suggest knowledge spillover for effective innovations of Indian firms, whereas R&D is a must for substantial innovation-efficiency linkage in Chinese firms.

This study offers quite a few crucial policy decisions concerning the relationship between innovation and efficiency as well as the moderation effect of R&D on innovation-efficiency linkage. It concludes that the effects of innovation on firms' efficiency and the role of R&D as a moderator of the innovation-efficiency relationship differ between India and China across the manufacturing and service sectors.

The purpose of this study is to measure and analyze the national innovation efficiency of organisation for economic co-operation and development (OECD) countries. This is to determine to what extent OECD countries efficiently use the elements that enable innovation activities possible in generating innovation outputs.

An input–output model was constructed to measure efficiency. The inputs and outputs in the research model are the input and output sub-indices of the Global Innovation Index. Data envelopment analysis was used to measure the national innovation efficiency levels of OECD countries.

The results show that national innovation efficiency is generally high in OECD countries. However, some countries lag behind in innovation efficiency. OECD countries’ ability to create and provide the elements that enable innovation activities is higher than their ability to create innovation outputs. OECD countries have a good innovation environment and a high level of resources, but they should focus on how to create more innovation outputs.

This study presents a measurement of national innovation efficiency of OECD countries which contributes “Innovation Strategy” agenda. The results empirically show that overall innovation indices cannot be the only indicator of the performance of national innovation systems. In this study, an innovation efficiency/performance matrix is constructed to present the relative positions of the countries to help in examining countries’ strengths, weaknesses and potentials based on innovation efficiency and innovation performance simultaneously. This study contributes to the literature by presenting a broader perspective and measurement of national innovation efficiency by taking an extensive number of indicators into account.

This paper aims to examine the effect of innovation-driven polices on innovation efficiency of sport firms listed on the new Third Board in China.

Firm innovation efficiency, including comprehensive innovation efficiency, pure technical efficiency and scale innovation efficiency were calculated by using data envelopment analysis (DEA) models. The input variables and output variable in the DEA model were selected through correlation analysis. The effects of several innovation-driven policies on the innovation efficiency of sport firms were analyzed by a series of multiple regression analyses.

Regarding the innovation efficiency evaluation of sport firms, total research and development (R&D) investment and total R&D staff are two suitable input variables, and total profit, sales revenue and new effective patent are three suitable output variables. Income tax relief for high-tech enterprise has a positive effect on comprehensive innovation efficiency and pure technical efficiency, and governmental subsidies have a negative effect on comprehensive innovation efficiency and pure technical efficiency. However, pretax deduction of R&D expenses does not have a significant effect on comprehensive innovation efficiency, pure technical efficiency and scale innovation efficiency, and income tax relief for high-tech enterprise and pretax deduction of R&D expenses also have no effect on scale innovation efficiency. For a large-scale sport firm, the negative effect of “governmental subsidies” and the positive effect of “income tax relief for high-tech enterprise” on its pure technical efficiency are more significant. For a sport firm with more R&D staff, governmental subsides and “income tax relief for high-tech enterprise” have more positive effect on its innovation efficiency.

The study findings could potentially provide practical guidance to both managers and government-industry policymakers in the sports industry.

Firstly, this paper focused on Chinese sport firms from a rising industry in a developing country (China). The related conclusions are conducive to the governmental management of new industries and the innovation management of new enterprises. Second, this paper analyzed the effect of three special innovation-driven policies on three types of innovation efficiency and explored enterprise innovation development in more detail. Third, this paper not only discusses the effect of innovation-driven policies on innovation efficiency, but also the heterogeneity of their effects.

The authors aim to discuss the impact of research and development (R&D) internationalization on emerging market enterprises' (EMNEs') innovation efficiency, as well as the moderating effects of top management team (TMT) human capital.

The authors empirically tested the hypotheses based on Chinese listed manufacturing company data from 2008 to 2017.

R&D internationalization helps to increase EMNEs' innovation efficiency. Incorporating TMT human capital into this framework, the authors found that international experience, education level and technical background would all strengthen the above relationship.

First, the authors contribute to the R&D internationalization literature by providing the first empirical evidence that R&D internationalization will influence EMNEs' innovation efficiency. Second, this study enriches the research results on the driving factors of enterprise innovation efficiency and expands the related research results on the relationship between R&D internationalization and production efficiency. Third, the research highlights the prominent position of TMT human capital in the relationship between R&D internationalization and EMNEs' innovation efficiency, which strengthens the contextual characteristics of the “R&D internationalization-innovation performance” framework.

Introduction – In recent years, there has been a growing interest in innovation, not only in developed countries but also in developing countries. However, there has been limited literature for the developing countries.

Purpose – The literature on national innovation systems (NIS) mainly consists of case studies or qualitative researches aiming to explain the patterns of innovation, while the quantitative analysis are limited in explaining the innovation capability and efficiency of innovation. This study is unique in a sense that it compares the innovation efficiencies of the EECA countries. This chapter aims to measure the efficiency of NIS via data envelopment analysis (DEA) method.

Methodology – DEA is used to consider a sample of 18 Eastern European and Central Asian (EECA) countries and Turkey. One of the main issues is to determine the input and output variables because the available data for some of these countries were limited. Therefore, research and development expenditure (% of GDP), government expenditure on education, total (% of GDP), imports of goods and services (% of GDP) and foreign direct investment, net inflows (% of GDP) were determined as input variables. Output variables were as follows; patent applications both residents and non-residents, high-technology exports (% of manufactured exports) and scientific and technical journal articles.

Findings – Based on the key findings it can be noted that Kazakhstan, Turkey, Latvia and Uzbekistan are more efficient in innovation performance compared to other EECA countries. Throughout the results of the DEA, these countries may develop new policies about their innovation systems to reach out the higher performance.

Which venture capital is more beneficial in the product innovation of entrepreneurial ventures? The authors study the drawbacks and different effects of corporate venture capital (CVC) and independent venture capital (IVC) on the effectiveness and efficiency of product innovation in entrepreneurial ventures to answer this question.

This study uses a panel dataset of 502 high-tech ventures and runs the Heckman model to correct potential endogeneity issues.

The authors find that CVC increases the product innovation effectiveness of entrepreneurial ventures, but decreases their efficiency. IVC reduces innovation effectiveness and enhances efficiency. However, CVC performs less positively, while IVC performs more positively in terms of innovation effectiveness and efficiency in the B2B market than in the B2C market.

This study provides insights into how to leverage venture capital to develop new products effectively and efficiently.

This study moves beyond the current understanding of the finance-marketing interface. It delineates the two faces of venture capital and reveals the joint effects of equity stakes and market stakes between different types of venture capital and transaction markets in product innovation.

This 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.

This 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.

The 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.

There 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.

This 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.

The 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.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

This study aims to analyse the impact of corporate social responsibility (CSR) on corporate innovation efficiency and the mechanism underlying this effect.

Data of non-financial listed companies operating in China from 2010 to 2019 were employed. Dual fixed-effects and dynamic panel models were used to explore the relationship between CSR and corporate innovation efficiency, and analyse its heterogeneity.

The researchers found that CSR reduces innovation efficiency in China. Further, (1) when enterprises conduct CSR to obtain excess returns, it is easy to form excess goodwill; (2) under the pressure of the government and society, enterprises passively assume CSR, thereby crowding out R&D funds; and (3) regardless of whether companies in the high-tech industry actively or passively assume social responsibilities, CSR will not have a significant impact on their innovation efficiency.

The sample of this research is limited to Chinese A-share listed companies and lacks consideration for small and medium-sized enterprises. Therefore, whether the conclusions of this article are applicable to small and medium-sized enterprises or family enterprises needs further verification.

The research explores the intrinsic motivation and possible consequences of CSR from the dual perspectives of corporate active and passive.

The ultimate goal of a firm is to make a profit. In practice, few enterprises pay without any return. Perhaps some companies actively assume social responsibilities in order to obtain greater benefits, while passively assume social responsibilities due to oppression.

This study analyses the impact of CSR on corporate innovation efficiency from both active and passive perspectives. The results have important implications for government officials and entrepreneurs.