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Environmental, social and governance (ESG) greenwashing is a form of social responsibility response that appears compliant but is substantively oppositional. As an abnormal social behavior, existing research has rarely focused on the deep-seated strategic logic behind ESG greenwashing. Business strategy emerges as the linchpin for companies undertaking a series of decision-making actions. Consequently, this research seeks to provide new insights into the strategic drivers behind corporate greenwashing and the role of institutional investors in mitigating these practices.

The research utilizes empirical analysis based on data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2010 to 2022. ESG performance data is sourced from the Bloomberg ESG Disclosure Ratings and Thomson Reuters’ Asset4 database. Business strategy is assessed using six key indicators. The study employs institutional theory as the analytical framework, examining the impact of business strategy on ESG greenwashing and investigating the internal mechanisms driving these behaviors.

The study finds that compared with defender strategies, prospector strategies are more likely to lead to ESG greenwashing behavior. Specifically, aggressive business strategies tend to facilitate corporate ESG greenwashing. Mechanism analysis indicates that, compared to defenders, prospectors induce ESG greenwashing by increasing information asymmetry (reputation effect) and being constrained by financing limitations (profit-seeking effect). From an external governance perspective, this study finds that institutional investor ownership can mitigate the impact of business strategy on ESG greenwashing. Furthermore, additional research confirms that in heavily polluting industries, the positive effect of business strategy on ESG greenwashing is more pronounced, whereas implementing the Environmental Protection Tax Law curtails the impact of business strategy on ESG greenwashing.

This study analyzes the role of business strategy in ESG greenwashing, particularly in the context of emerging economies such as China, contributing uniquely to the literature on corporate decision-making and green management. The research extends the application of institutional theory to the field of corporate environmental strategy and introduces the concepts of reputation and profit-seeking effects, offering fresh perspectives on understanding ESG greenwashing behavior. It also provides empirical evidence of the governance role of institutional investors in addressing managerial opportunism related to ESG greenwashing, enriching the existing theoretical framework. Finally, the study highlights the need to establish stronger institutional and managerial mechanisms to effectively tackle corporate greenwashing, offering valuable insights for future research and practice.

The purpose of this paper is to examine the influence of the innovation ability of universities (IAU) on the efficiency of University–Industry knowledge flow and investigate whether the level of provincial innovative agglomeration (PIA) moderates the relationship between IAU and the efficiency of the University–Industry knowledge flow.

This study uses the super-efficiency data envelopment analysis model to measure knowledge research efficiency (KRE) and knowledge transformation efficiency (KTE) and then studies the influencing mechanism of the two kinds of efficiency using the spatial Tobit model with panel data from 2008 to 2017.

The results show that the overall KRE in Chinese universities is higher than the KTE. IAU has a significantly positive impact on KRE and KTE. PIA has a significantly inverted U-shaped influence on KRE and KTE and positively moderates the promoting effect of IAU on KRE and KTE.

Due to the limitations of the data, this paper only selects several secondary indicators to measure KRE and KTE with reference to previous studies.

This study enriches the future research of University–Industry cooperation and knowledge flow and it is conducive to promoting the efficiency of University–Industry knowledge research and transformation from the perspective of universities, enterprises and local governments.

This study proposes the concept of University–Industry knowledge flow and divides the knowledge flow into the knowledge research stage and the knowledge transformation stage based on the knowledge supply chain theory. Moreover, the paper expands the theoretical framework of the impact of IAU on the efficiency of University–Industry knowledge flow and provides findings on the moderating effect of PIA.

This paper aims to examine the influence of individual and combined effects of the mode focused on scientific and technological-based innovation (STI) and the mode based on learning by doing, by using and by interacting (DUI) on firms’ innovation performance and whether information technology (IT) moderates the relation between different innovation modes and firms’ innovation performance.

A conceptual model linking innovation modes, IT (including IT infrastructure and the frequency of IT usage) and firms’ innovation performance was developed, and the proposed hypotheses were tested empirically using World Bank’s micro survey data collected from manufacturing firms in an emerging market (China).

The results show that individually both STI mode of innovation and DUI mode of innovation have a significant positive effect on firms’ innovative performance, whereas the combined STI and DUI mode of innovation has a negative impact. IT infrastructure moderates the relation between STI (or STI and DUI) mode of innovation and firms’ innovation performance, while the frequency of IT usage has no moderating effects on the relationship between any kind of innovation modes and firms’ innovation performance.

Although some results are quite different from what is expected, these are insightful for both academics and policymakers. The use of cross-sectional data has its limitations. Therefore, future studies based on longitudinal data should be conducted. This study points toward the need to conduct the meta-analysis to better explain the existing inconsistencies in the findings of relevant quantitative studies.

This study provides firm managers with practical implications. The conclusions of this study imply that the impact of the combined STI and DUI mode of innovation is likely to be contextual, so firms should make contingent decisions on whether to engage in STI mode of innovation and DUI mode of innovation simultaneously according to their own organizational conditions. Moreover, face-to-face contacts are particularly important when a firm engages in DUI mode of innovation. In addition, the focus of IT strategy of firms engaged in STI mode of innovation should be on perfecting their IT infrastructure rather than increasing the frequency of IT usage.

This paper provides new evidence for the relation between business innovation modes and firms’ innovation performance, and it is one of the few empirical studies that focus on emerging markets. More importantly, this paper proposes a persuasive explanation framework for understanding the heterogeneous impacts of the combined STI and DUI mode of innovation on firms’ innovation performance. This is the first study that examines the moderating effect of IT on the relationship between business innovation modes and a firm’s innovation performance.

This paper aims to investigate the impact of open innovation (OI) in Chinese enterprises on enterprise value (EV). At the same time, this research explores the effects of OI in environmental, social and governance (ESG) and also reveals the intermediary role of ESG in the impact of OI on improving EV.

This study builds a theoretical framework to define a set of hypotheses verified in empirical research. Based on the panel data of Chinese listed companies removing missing data from 2011 to 2020, a two-way fixed effect model is used to study the relationship between OI, ESG and EV.

The research shows that OI of enterprises has effectively improved their value. At the same time, OI can also improve the ESG of enterprises. That OI increases EV is partly by the mediating path of ESG.

This study determines the influence of OI on EV from a stakeholder and sustainable development perspective, clarifying the mediating pathway of ESG in the relationship. Doing so could inspire companies to improve their OI and desire to enhance competitiveness. It will also prompt enterprises to pay attention to social responsibility activities.

The purpose of this article is to explore the impact of open innovation on international revenues, as well as the moderating role of digital transformation and strategic differentiation in the relationship.

This study develops a theoretical framework to specify a group of hypotheses. A two-way fixed effect model is used to analyze the relationship between open innovation and international revenues, as well as the moderating effects of digital transformation and strategic differentiation, using panel data of Chinese multinational firms.

Results revealed that open innovation is statistically significantly positive when related to international revenues. Based on the quantitative analysis, the correlation is stronger in sample enterprises with higher digital transformation and strategic differentiation.

This study highlights how open innovation drives international revenues for Chinese listed firms, advancing resource-based view theory in emerging market countries. Introducing digital transformation and strategic differentiation as boundary conditions addresses research gaps and offers practical insights for supporting open innovation for practitioners.

Team learning is critical to interdisciplinary research teams (IDR teams) to use heterogeneous knowledge effectively. Nevertheless, team learning is rarely addressed in the IDR team literature. Also, few studies investigate the antecedents and consequences of team learning in IDR teams, leading to a lack of guidance for management practices. This study aims to investigate how team learning can be developed and how team learning influences team outcomes in IDR teams.

A questionnaire survey on 304 members of 37 IDR teams in a research university in China is conducted. Data are analyzed using a partial least square structural equation modeling.

The results support most hypotheses in general. For the antecedent variables, task interdependence, trust and constructive conflict positively affect team learning. For the outcome variables, team learning improves shared mental models, coordination quality and team performance significantly. Additionally, task uncertainty positively moderates the team learning-coordination quality relation and team learning-team performance relation. However, this paper does not find support for the moderating role of task uncertainty on the team learning-shared mental models relation.

To the best of the knowledge, this is the first study investigating the antecedents and consequences of team learning in IDR teams. A multidimensional measurement of team learning for the IDR team context is developed. This study investigates how team behavioral factors influence team learning and the effect of team learning on shared mental models, coordination quality and team performance. This study also explores the contingency role of task uncertainty in the effects of team learning.

Technology innovation in enterprises is a powerful driver of national competitiveness and sustainable corporate development. At the same time, the regional innovation policy mix serves as a core factor at the macro level, guiding and influencing enterprise technology innovation. Therefore, this paper addresses a critical question in innovation studies: the impact of the regional innovation policy mix complexity on enterprise technology innovation. Additionally, we also investigated the internal mechanisms and boundary conditions within this framework.

A dual-mode network model of local government-regional innovation policy is developed to capture the complexity of the regional innovation policy mix. The complexity index is calculated iteratively using the R language. The paper employs quantitative and empirical analysis, drawing on a sample of 622 regional innovation-related policy documents from 31 Chinese provinces (municipalities and autonomous regions).

The results reveal an inverted U-shaped relationship between policy mix complexity and enterprise technological innovation. The analysis further shows that university-industry cooperation intensity mediates this relationship, while regional knowledge absorptive capability moderates the impact of regional innovation policy mix complexity on enterprise technological innovation.

This paper highlights the influence of regional innovation policy mix complexity on enterprise technological innovation and underscores the role of university-industry cooperation intensity and regional knowledge absorptive capability. The findings offer valuable insights into the dynamics of enterprise innovation and inform effective government policy governance for fostering innovation.

This paper aims to explore the nexus between family involvement and environmental, social and governance (ESG) performance based on socioemotional wealth theory, and it also analyzes the potential influence mechanism.

Based on the categorization of China Stock Market & Accounting Research database, this study divides the Chinese listed firms into family and nonfamily firms and applies multiple regression methods to test the theoretical hypotheses.

Family involvement can incentivize corporations to enhance corporate transparency, which can in turn enhance their ESG performance. The role of family involvement in bolstering corporate ESG performance is negatively contingent on external financing constraints.

There are insufficient studies on the nexus between family ownership and ESG performance. The findings provide insights into helping policymakers formulate targeted measures to encourage corporations to be more active in promoting ESG initiatives.

This study attempts to uncover the nonlinear relationship between public procurement and corporate total factor productivity (CTFP), and investigates the mediating roles of R&D investment and rent-seeking cost. Additionally, it conducts a heterogeneity analysis for firms with varying levels of political connections and corporate social responsibility (CSR).

Employing Ordinary Least Squares (OLS) and Olley-Pakes (OP) methods, the authors gauge CTFP and manually identify government customers to quantify public procurement. Leveraging panel data from Chinese listed companies, this study explores the relationship between public procurement and CTFP.

This study unveils a U-shaped relationship between public procurement and CTFP, highlighting R&D investment and rent-seeking costs as potential mechanisms. Furthermore, it identifies heterogeneous effects among companies with varying levels of political connections and CSR on the relationship between public procurement and CTFP, including their mediating effects.

This research enhances understanding of demand-side policies and provides crucial insights for the government to further improve public procurement policies.

By offering empirical evidence of how public procurement impacts CTFP, this paper enriches the literature on the behavioral repercussions of public procurement and the determinants of CTFP. It also overcomes the “black box” of the mechanism between public procurement and CTFP, based on the government’s dual role as a pathfinder and customer of enterprises. It broadens the application scenarios of institutional theory and principal-agent theory. Additionally, the heterogeneity analysis of firms with varying political connections and CSR extends the frontiers of related research.

Effective knowledge integration is vital for decision making in interdisciplinary research (IDR) teams. However, there is a lack of knowledge about the antecedents of knowledge integration. This study aims to examine how social capital at different levels and their interaction influences knowledge integration in IDR teams. Specifically, this study explores the moderating role of team social capital in the relationship between individual social capital and knowledge integration.

A survey on 346 individuals from 46 IDR teams in a research university in China is conducted. A multilevel analysis of the hierarchical linear model is used to process the sociometric data.

Results reveal that team social capital interacts with individual social capital by influencing knowledge integration. At the individual level, tie strength and structural equivalence have a positive influence on knowledge integration. There is an inverted U-shaped relationship between betweenness centrality and knowledge integration. Furthermore, team cohesion negatively moderates the positive effect of tie strength and structural equivalence on knowledge integration. No support is found for the moderating role of team cohesion on the effect of betweenness centrality.

First, different from previous research on social capital at single levels, this study links the individual-level and the team-level views to explore the effects of social capital on knowledge integration. Second, this study enriches research on inducing factors of knowledge integration. Third, this study extends social capital research and knowledge integration research to the IDR team context.