The implementation of the innovative city pilot policy (ICPP) is conducive to promoting the urban industry–university–research collaborative innovation, but there is no clear answer to how industry–university–research knowledge flow is affected by the policy. Based on the knowledge flow process divided into the knowledge creation stage and knowledge transfer stage, this paper uses the two-stage Data Envelopment Analysis (DEA) model to measure the dual efficiency of urban industry–university–research knowledge creation and knowledge transfer. And the paper also adopts the spatial difference-in-difference (SDID) model to study the impact mechanism of ICPP on the knowledge flow dual efficiency. The results show that there are positive spatial spillover effect of the knowledge creation efficiency (KCE) and knowledge transfer efficiency (KTE). And the effects of ICPP on industry–university–research KCE and KTE are both manifested as the promoting impact. Furthermore, ICPP has a significantly positive impact on the urban innovation atmosphere (UIA), and UIA plays a partial mediating role in the impact mechanism of ICPP on KCE and complete mediating role in the relationship of ICPP and KTE.

Purpose: 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).Design/methodology/approach: 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.Findings: 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.Practical implications: This research enhances understanding of demand-side policies and provides crucial insights for the government to further improve public procurement policies.Originality/value: 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.

The positive impact of data elements on enterprise operation has been confirmed by many scholars, but few studies have paid attention to the effect of data elements on corporate green transformation, especially in the context of global climate change. In this study, we employ panel data from Chinese listing firms to identify the casual impact of data elements on corporate green transformation, using the staggered difference-in-differences method. We show that: (a) Data elements exert a significant positive influence on corporate green transformation. This finding holds up in a series of robustness checks; (b) The promoting effect of data elements on green transformation is mediated by alleviating financing constraints and elevating executive green attention; (c) Green governance resilience and green management innovation can strengthen the positive relationship between data elements and green transformation; and (d) The promoting effect is more pronounced in enterprises with larger boards of directors, those located in the eastern regions, and those characterized by higher carbon emission intensities. Overall, we not only provide empirical evidence of optimizing regional data-factor allocation and promoting green technological innovation but also offer theoretical guidance for refining the pathways of corporate green transformation.