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High-tech enterprises, as the national innovation powerhouses, have garnered considerable interest, particularly regarding their technological innovation capabilities. Nevertheless, prevalent research tends to spotlight the impact of individual factors on innovative behavior, with only a fraction adopting a comprehensive viewpoint, scrutinizing the causal amalgamations of precursor conditions influencing the overall innovation proficiency of high-tech enterprises.

This paper employs a hybrid approach integrating necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) to examine the combinatorial effects of antecedent factors on high-tech enterprises' innovation output. Our analysis draws upon data from 46 listed Chinese high-tech enterprises. To promote technological innovation within high-tech enterprises, we introduce a novel perspective that emphasizes technological innovation networks, grounded in a network agents-structure-environment framework. These antecedents are government subsidy, tax benefits, customer concentration, purchase concentration rate, market-oriented index and innovation environment.

The findings delineate four configurational pathways leading to high innovative output and three pathways resulting in low production.

This study thereby enriches the body of knowledge around technological innovation and provides actionable policy recommendations.

This study aims to explore the impact mechanism of the degree of innovation failure on breakthrough innovation in Chinese listed companies, and examines the moderating effect of the company’s own knowledge-based capabilities.

Based on organizational learning theory and using the innovation failure data of invention patents from Chinese A-share listed companies on the main board from 2003 to 2017 as research samples, this study constructs and examines a comprehensive framework and its impact on breakthrough innovation regarding “what kind of innovation failure will promote breakthrough innovation”, focusing on innovation failure, enterprise knowledge base, and breakthrough innovation.

Empirical research has found a U-shaped relationship between innovation failure and breakthrough innovation. In other words, both a low level of failure and an extremely high level of failure can significantly promote breakthrough innovation in enterprises. Furthermore, when the depth of enterprise knowledge is high, it further strengthens the non-linear relationship between innovation failure and breakthrough innovation.

The research results enrich the study of the failure predicament and breakthrough innovation of Chinese technology innovation enterprises, revealing effective paths for Chinese technology innovation enterprises to get rid of the passive situation of innovation failure, and providing theoretical support and practical reference for “breaking new ground and achieving breakthrough innovation”.

A new round of technological revolution is impacting various aspects of society. However, the importance of technology adoption in fostering firm innovation is underexplored. Therefore, this study aims to investigate whether robot adoption affects technological innovation and how human capital plays a role in this relationship in the era of circular economy.

Based on the robot adoption data from the International Federation of Robotics (IFR) and panel data of China's listed manufacturing firms from 2011 to 2020, this study uses regression models to test the impact of industrial robots on firm innovation and the mediating role of human capital.

The results demonstrate that the adoption of industrial robots can significantly promote high-quality innovation. Specifically, a one-unit increase in the number of robots per 100 employees is associated with a 13.52% increase in the number of invention patent applications in the following year. The mechanism tests show that industrial robots drive firm innovation by accumulating more highly educated workers and allocating more workers to R&D jobs. The findings are more significant for firms in industries with low market concentration, in labor-intensive industries and in regions with a shortage of high-end talent.

Due to data limitations, the sample of this study is limited to listed manufacturing firms, so the impact of industrial robots on promoting innovation may be underestimated. In addition, this study cannot observe the dynamic process of human capital management by firms after adopting robots.

The Chinese government should continue to promote the intelligent upgrading of the manufacturing industry and facilitate the promotion of robots in innovation. This implication can also be applied to developing countries that hope to learn from China's experience. In addition, this study emphasizes the role of human capital in the innovation-promoting process of robots. This highlights the importance of firms to strengthen employee education and training.

The adoption of industrial robots has profoundly influenced the production and lifestyle of human society. This study finds that the adoption of robots contributes to firm innovation, which helps people gain a deeper understanding of the positive impacts brought about by industrial intelligence.

By exploring the impact of industrial robots on firm innovation, this study offers crucial evidence at the firm level to comprehend the economic implications of robot adoption based on circular economy and human perspectives. Moreover, this study reveals that human capital is an important factor in how industrial robots affect firm innovation, providing an important complement to previous studies.

This study aims to identify the strategic factors and their effects on the post-cross-border acquisitions (CBA) technological innovation performance of the acquiring firms. It develops a hierarchical model to examine the interrelationship between identified strategic factors such as strategic flexibility, strategic ambidexterity, environmental dynamism, etc.

This study uses modified total interpretive structural modeling qualitative methodology (m-TISM) to develop a hierarchical model and conducts a Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis to show the interrelationship between strategic factors affects the acquirer’s post-CBA technological innovation performance. It determines the autonomous, dependent, linkage and independent strategic factors. It further uses comparative case analysis to empirically examine the strategic factors in real-time CBA situations.

This study shows the m-TISM-based hierarchical model highlighting the interrelation, level of autonomy, dependence and linkage among strategic factors affecting the acquirer’s post-CBA technological innovation performance. It suggests that strategic factors such as environmental dynamism, R&D competence, innovation capability and technological capability are largely autonomous and have significant driving power, whereas strategic ambidexterity and strategic flexibility are the connecting factors. post-M&A integration is the governing factor for technological innovation performance in CBA.

The strategists and practitioners could evaluate the key strategic factors having significant driving power for strategy formulation and implementing efficient policies. By implementing the m-TISM model acquiring a firm’s post-CBA performance can be enhanced. Future researchers might utilize quantitative methods like regression and structural equation modeling in the CBA context.

This study uses a novel m-TISM and MICMAC approach to identify the driving and dependent factors affecting post-CBA technological innovation performance. It further provides a detailed theoretical and conceptual understanding relating to the philosophy and establishes an interrelation amongst these under-researched strategic factors in CBA.

This study aims to test the link between enterprise digital transformation and technological innovation and the mechanisms and channels behind this link.

This study systematically examines whether and how enterprise digital transformation affects technological innovation in China.

Enterprise digital transformation effectively improves technological innovation. This result remains stable in robustness and endogeneity checks. The channel mechanisms of this promoting effect are internal (improvement of internal control quality and alleviation of agency costs) and external (increased attention of analysts and reduction of customer concentration). Moreover, this promoting effect is more significant for state-owned enterprises, small and medium-sized enterprises, enterprises in areas with low marketization and enterprises that do not enjoy digital subsidies from the government.

Enterprises need to attend to the mechanisms behind the link between digital transformation and technological innovation and to the unique effects of different enterprise attributes and capital markets, such as size, the ownership nature, the degree of regional marketization and government subsidies. Doing so will effectively promote digital transformation and technological innovation and strengthen core competitiveness.

This study provides systemic evidence of the link between enterprise digital transformation and technological innovation. The findings enrich the research literature on enterprise digitization and the factors of influencing enterprises’ technological innovation and provide a reasonable explanation for how enterprise digital transformation affects technological innovation.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

Based on the resource orchestration perspective, this paper aims to examine whether family firms are more efficient in their collaboration for innovation process than non-family firms, considering different types of collaboration for innovation depending on the kind of partner.

This study empirically develops and tests the hypotheses based on a panel data sample of 14,937 firm-year observations from 1,867 Spanish manufacturing firms over the period 2007–2014, performing a Propensity Score Matching (Propensity score matching)-based analysis.

Results reveal that family firms outperform non-family firms, despite less collaboration and innovation inputs, thereby extending the ongoing debate surrounding the innovation efficiency of family firms. Family firms obtained better results through vertical collaborations for innovation, both in terms of product and process innovations. For horizontal collaborations, family firms only outperform their non-family counterparts in process innovation. When collaborating with universities and other research centers, there are no significant differences in the innovation outcomes between the two groups.

Recent literature points out that more research is needed to know when, how and under what circumstances family firms show superior innovative efficiency. This work empirically proves that family firms outperform non-family firms in collaboration for innovation. However, not all collaboration partners help family firms to reach this superior innovative efficiency. Family firms obtained better results just through vertical and horizontal collaborations.

Human capital is acquired not only through formal education (e.g. general skills) but also through training at the workplace. Prior studies have ignored the role of government subsidies explicitly for on-the-job training, which may influence firm training decisions and firm innovation performance. Hence, the authors establish a comprehensive theoretical framework to consider these issues and fill these gaps.

Considering the Chinese manufacturing firms listed in the Shanghai and Shenzhen Stock Exchange from 2010 to 2017, the authors investigate the influence of training investment on innovation performance by illustrating the role of human capital updating in enhancing firm innovation. The authors also explore serval mechanisms on how training investment influences innovation performance.

The authors propose that training investment promotes firm innovation performance, whereas government training subsidies negatively moderate this relationship. The authors also reveal how technicists' involvement and corporate culture mediate the relationship between training investment and innovation performance.

This study provides policy implications for stimulating firm innovation by improving learning and absorption ability, strengthening cultural identity and implementing system norms. Effective policies should be adopted to provide subsidies for on-the-job training of enterprises, particularly for firms with technical executives and firms in diversified life-cycle.

This work contributes to the literature on the role of on-the-job training in promoting firm innovation and reveals the crowding-out effect of subsidies. This study also shows the heterogeneous effects of training investment on firm innovation.

The development and evolution of stakeholder collaborative innovation in megaprojects is impacted by various influencing factors. The effect of influencing factors on collaborative innovation performance (CIP) in megaprojects is not a simplistic linear relationship but an iterative and non-linear relationship that requires a dynamic perspective to analyze. Therefore, this paper adopts the system dynamic (SD) approach to investigate the dynamic and interactive relationships between the CIP and the influencing factors.

The study first develops a research framework with the system boundary of “CIP system – organizational collaboration subsystem – knowledge collaboration subsystem – strategic collaboration subsystem”. Then, the causal relationship model, the stock-flow model, and the mathematical equations were determined based on the literature review and the expert interviews. Finally, five performance improvement scenarios were designed according to the practice context of CIP in megaprojects, and simulations were performed using the Vensim PLE software to investigate the CIP from a dynamic perspective.

The findings reveal that the effect of different influencing factors on CIP grows non-linearly, with the cumulative effect becoming more pronounced as time advances. The incentive mechanism has the most significant effect, and the combined effect of multiple influencing factors has a highly significant facilitating effect on improving CIP. Strategic collaboration, organizational collaboration and knowledge collaboration are mutually conditional and reinforcing with each other, which ultimately promotes the improvement of CIP.

This study uncovers the inherent pattern and the interactive dynamic mechanism of factors for improving CIP in the context of megaprojects. It enriches the theoretical research in the area of collaborative innovation in megaprojects and provides practical management strategies for improving CIP.

The purpose of this paper is to explore the integration of business intelligence (BI) systems in the digital transformation context and its impact on management control (MC) and organizational performance by delving into the implementation of a BI pilot project in a multinational Engineering and Construction (E&C) group.

This research adopts a qualitative insider action research approach. The initial stage of a BI system (BIS) is implemented by leveraging the critical success factors (CSFs) framework, based on the organizational, process and technological dimensions.

The results show that the BI solution leverages the capabilities of the reporting process with impacts on MC and overall organizational performance. The study uncovers the intricate dynamics of integrating BI and reports gains that span across streamlined and standardized processes, optimized use of resources, improved data flexibility and nurturing a data-driven culture.

This research adds to the current literature on MC and accounting information systems by providing an in-depth analysis of the early stages involved in implementing a BIS. The approach uses a well-established CSFs framework, which enhances the comprehension of how these factors impact the success of the implementation process. Focusing on the E&C sector, where the adoption of digital transformation is still gaining traction, this study provides practical knowledge and extends the theoretical understanding of BI technology applications with empirical evidence from the accounting field.