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The 21st century has brought the business model earth-shaking changes, especially since the Corona Virus Disease 2019 (COVID-19) epidemic at the end of 2019. Now, the epidemic normalization is slowing down China's rapid development. However, technological development, like artificial intelligence (AI), is unstoppable and is transforming China's economic growth modes from factor-driven to innovation-driven systems. Therefore, it is necessary to study further the new changes in labor entrepreneurship and innovation business models and their mechanism of action on economic growth.

This work studies how innovative human capital (IHC) uses AI and other scientific and technological (S&T) innovation technologies to promote China's innovation-driven economic growth model transformation from the labor entrepreneurship and innovation perspective.

The research shows that the entrepreneurial innovation ability of IHC can increase marginal return and output multiplier effect. It changes the traditional business model and promotes China's economic growth and innovation development. At the same time, this work analyzes China's inter-provincial panel data through the panel smooth transition regression (PSTR) model. It concludes that there is a nonlinear relationship between IHC and the output of innovative achievements. The main body presents three stages of nonlinear changes: first rising, then slightly declining, and rising so far.

The finding provides a direction for solving the problem of slow economic growth and accelerating the transformation of economic growth mode under epidemic normalization.

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.

Reports on an ongoing empirical study into the characteristics and strategies of “successful” technologically oriented UK firms. Using survey data from samples of winners of the Queen’s Award for Technological Achievement and a comparative group of high‐technology firms, the study establishes that few statistical differences exist between the two groups and between specific sizes of firms in each sample in relation to aspects of their design and innovation strategies. The issues raised in this paper include: the way in which technological success is conceptualised; the usefulness of awards such as the Queen’s Award for Technological Achievement as a benchmark for innovative firms; and, the attitudes and activities of sample firms in relation to design and new product development strategies.

The color TV industry in China has become a mature industry. Its development demonstrates and provides reference implications for how developing industries within a country can achieve a technological leap. This paper aims to address this issue.

An exploratory case study approach is taken to find the key factors in the technological catch‐up of China's traditional industry.

In the study it is found that China's color TV industry, as a mature traditional industry, has four‐dimensional key factors affecting the catch‐up of technology in the flat‐panel stage: market; merger and acquisition; international cooperation innovation for patent; and the roles of internal reform. “Market” is the window of opportunity and challenge; “merger and acquisition” is the key factor for making the patent convert from external mode to internal mode by deviant‐track. The “international cooperation innovation for patent” is also a key factor to ensure achievement of technology catch‐up and sustainable technological innovation. The role of internal reform promoter is the key factor in the technological catch‐up process in which taking entrepreneur as the core.

The article describes Changhong's flat‐panel TV technology catch‐up mode, analyzes four‐dimensional key factors affecting the technology catch‐up of China's color TV industry; the Chinese color TV industry as mature industry; and discusses which developments have demonstrated how to achieve a technological leap in developing industries.

This study aims to explore how stakeholders leverage their guanxi and structural holes to promote knowledge mobilization to increase the performance of sci-tech achievement transformation.

This study conducted questionnaires, a social network analysis and semistructured interviews to examine its hypotheses by gathering data from a university and an enterprise in China.

Structural holes impede knowledge mobilization among stakeholders in their network, but guanxi moderates this impeding effect. In addition, knowledge mobilization promotes transformation performance.

By developing a mechanism to illustrate how stakeholders strategically leverage their guanxi and structural holes to affect the efficacy of knowledge mobilization to increase transformation performance, we reveal how stakeholders interact to co-create values for innovation, thereby contributing to the innovation and knowledge management literature.

The Aviation Division of Smiths Industries at Cheltenham has won a Queen's Award for Export Achievement. Exports and indirect exports from the Cheltenham factory have increased over a three year period by almost £5 million to £11 million each year, representing some 70 per cent of production. Exports are made regularly to almost every country having commercial and military aircraft produced in the western world; while the bulk of export sales are to those countries with an aircraft manufacturing industry.

As a transition economy, China is interested in allocating its limited innovation resources economically, reasonably and efficiently to produce as many outputs as possible with its limited financial and human resources. Nonetheless, what is the efficiency of the allocation of innovative resources for civil–military integration enterprises, and what factors hinder its efficiency improvement? The purpose of this paper is to explore these problems.

The improved two-stage network data envelopment analysis (DEA) method is used to measure the overall efficiency and stage efficiency of the innovation resource allocation of 58 Chinese civil–military integration listed companies from 2010 to 2016. Tobit model is used to analyze the influencing factors of resource allocation efficiency.

The results indicate that the overall efficiency and stage efficiency of innovation resource allocation fluctuate in varying degrees during the period. The optimization of overall efficiency is restricted by lower efficiency of innovation achievement transformation. Enterprise scale was found to have a significant negative impact on both overall and two-stage efficiencies. Proportion of research and development (R&D) personnel had a positive effect on the overall and two-stage efficiency. Government support had a significant positive effect on the stage of innovation resource development and overall efficiency.

Previous research studies have used either the DEA or stochastic frontier analysis method to measure the efficiency of innovation activities as a whole and ignored the stage of initial investment to final output in innovation activities. That is, the process in which initial input of R&D resources becomes innovation output, and then becomes economic benefits. Therefore, this paper studies the efficiency of innovation resource allocation of civil–military integration listed companies. The improved two-stage chain network DEA method and Tobit model were used.

The purpose of this paper is to verify the impacts of the transaction costs rationale on economic agents’ innovative results when they engage in European R & D networks, supplying both firms and policymakers with empirical support for improved decision making toward economic competitiveness and construction of the European research area. Furthermore, unlike many transaction cost economics assessments, the authors evaluate the existence of transaction costs following a dynamic framework of analysis (instead of using solely ex ante governance choice as a driver of inter-firm “friction” management), offering a novel perspective on these phenomena.

Data consist of firm-level information from Eureka’s Final Reports (1995-2006) for Spanish, Italian, French, British and German firms. Empirical assessments were performed through a two-step approach of direct and indirect effects of network management and potential sources of disturbances. Ordinal regressions were applied in order to identify transaction costs’ relevance as drivers of firms’ technological and commercial outcomes, as well as on managerial quality of alliances. Statistical controls include microeconomic and project-specific variables.

Results highlight the role played by transactional aspects as drivers of companies’ outcomes and managerial complexity. Furthermore, the authors find robust evidence that formal ex ante governance structures are incapable of satisfactorily addressing dynamic disturbances that take place within R & D networks. Whereas such findings are directly related to existing transaction costs, the authors find no support for the usual variables attributed to increased complexity in international inter-firm relationships.

Self-selection issues are inherently related to the research instrument (i.e. Eureka’s Reports), while further firm-level data could not be obtained since confidentiality issues protected companies’ names and sectors. Also, network-level data are not available, allowing the evaluation of individual perceptions only.

While literature addresses the issue of transaction costs in R & D networks via theoretical assumptions and rough proxies, this assessment offers an in-depth evaluation of a set of valuable indicators with direct implications for researchers, managers and policymakers. Main contributions concern the identification of dynamic interactions (and their respective disturbances) as a key feature of the overall performance of R & D networks, stressing the non-linearity of economic processes in these hybrid relationships, an issue that has been poorly tackled by previous empirical investigations.

This study examines the differences in the economic stimulus effects, transmission mechanisms, and output multipliers of government consumption, government traditional investment, and government science and technology investment.

This study constructs and estimates a New Keynesian model of endogenous technological progress embedded in the research and development (R&D) and technology transfer sectors. Using Chinese macroeconomic time series data from 1996 to 2019, this study calibrates and estimates the model and analyzes the impulse response function and a counterfactual simulation of expenditure structure adjustment.

The results show that compared with the traditional dynamic stochastic general equilibrium (DSGE) model, the endogenous process of technological progress amplifies the impact of government consumption shock and traditional government investment shock on the macroeconomy, leading to greater economic cycle fluctuations. As government investment in science and technology has positive external spillover effects on firm R&D activities and the application of innovation achievements, it can promote more sustainable economic growth than government consumption and traditional investment in the long run.

This study constructs an extended New Keynesian model with different types of government spending, which includes endogenous technological progress within the R&D and technology transfer sectors, thereby linking fiscal policy, business cycle fluctuations and long-term economic growth. This model can study the macroeconomic impact of fiscal expenditure structure adjustment when fiscal expansion is limited. In the Bayesian estimation of model parameters, this study not only uses macroeconomic variables but also adds a sequence of private R&D investment.

This paper intends to examine the change of R&D fiscal policies in China since 1978 and its impact on China's drive to become an innovation‐oriented country.

This paper adopts an archive approach and undertakes an overview of the policy changes and their implications.

It is found that policy changes have gradually made enterprises the focal point of the national innovation system and that correspondingly a new financial and fiscal mechanism has been created to create incentives for innovation in firms.

This paper provides a comprehensive overview of the changing financial and fiscal policies in support of technological innovation in China.