1. Introduction
Since the financial crisis, global economic growth has shown a persistent downward trend [
1,
2]. How to sustain economic growth has become a universal challenge for nations worldwide and a focal topic across disciplines [
3,
4]. As policy practices evolve, there is growing recognition of the importance of incorporating technological innovation and total factor productivity into economic development frameworks, with increasing emphasis on the quality of economic growth. In recent years, new-quality productivity (NQP) has garnered significant attention, with its development being regarded as an effective pathway to achieve qualitative leaps in economic development. Conceptually, NQP represents a form of productivity characterized by qualitative transformations in labor forces, means of production, and their optimal combinations, with total factor productivity improvement as its core indicator. It serves as a hallmark of high-quality development grounded in productivity practices and the new technological revolution [
5,
6]. However, the existing literature, although rich in conceptual definitions and macro-policy discussions, often remains at a descriptive or correlational level, with limited critical examination of methodological limitations or empirical biases. For example, while Pan et al. [
7] emphasize the role of the digital economy, and Wang et al. [
8] focus on carbon emission reduction, most studies treat these as parallel drivers without clarifying their relative explanatory power or interaction effects. Moreover, climate policy uncertainty has been examined [
9], but often through aggregated national-level data, which may mask micro-level heterogeneity and firm-level behavioral dynamics [
10,
11].
The accelerated iteration and evolution of digital technologies, particularly big data, cloud computing, and blockchain, have positioned digitalization as an effective solution for enhancing economic growth momentum and sustainable development worldwide [
12,
13,
14]. Concurrently, corporate digital transformation has gained increasing emphasis from shareholders and managers [
15,
16]. Taking China as an example, Accenture’s 2022 Report on the Digital Transformation Index of Chinese Enterprises reveals that the average digital transformation score of Chinese firms surged from 38 in 2015 to 52 in 2022. This empirical evidence demonstrates that even in developing economies like China, corporate digital transformation practices have become increasingly widespread, with continuous breakthroughs in effectiveness. Existing literature has extensively examined the micro-level consequences of corporate digital transformation, demonstrating its significant value in technological innovation [
17], organizational restructuring [
18], investment efficiency [
19], and sustainable performance [
20]. Nevertheless, most empirical studies adopt either single-industry samples or short cross-sectional datasets, which restrict the ability to capture temporal dynamics and heterogeneous effects across regions, ownership structures, or competition intensity. Methodologically, the reliance on simple OLS or panel regressions without robust endogeneity controls raises concerns about causal inference, particularly when examining complex constructs like NQP [
21,
22]. This creates a research gap for studies employing richer panel data, multi-dimensional measurement frameworks, and quasi-natural experimental designs. Despite the broadening impact of digital transformation on firms, few studies have evaluated its economic effects from the perspective of NQP. Given that NQP serves as a critical indicator of corporate excellence, establishing the intrinsic relationship between digital transformation and NQP carries substantial theoretical and practical significance. This study addresses this gap by not only estimating the direct effect of digital transformation on NQP, but also unpacking the underlying mechanisms (green innovation), boundary conditions (digital financial inclusion), and heterogeneous impacts across ownership types, industry competition levels, and regional development stages. In doing so, it provides a more nuanced understanding of whether the influence of digitalization is primarily driven by innovation capacity enhancement, market connectivity, cost efficiency, or other firm-level capabilities.
Theoretically, corporate digital transformation exerts significant influence on new-quality productivity through three fundamental mechanisms. Primarily, the implementation of digital transformation strategies enables enterprises to reconfigure products, organizational structures, and business models, thereby enhancing production efficiency and productivity levels to generate greater value [
20,
23]. A compelling illustration is Inspur Group’s adoption of the Joint Design-Manufacturing (JDM) model, which through intensive collaboration with customers and partners achieved a 3–10 fold improvement in R&D efficiency, reduced new product development cycles from 1.5 years to 9 months, and enabled prototype delivery within just 3 months, thereby consolidating its technological leadership in both domestic internet infrastructure and global server markets. Concurrently, digital transformation strengthens enterprise-stakeholder connectivity and enhances market responsiveness, facilitating accelerated product iteration and upgrading [
24]. Moreover, digital technologies empower enterprises to achieve green transition through pollution reduction and environmental performance improvement, consequently boosting green total factor productivity and advancing new-quality productivity development. Drawing upon empirical evidence from China, this study addresses three pivotal research questions: Does corporate digital transformation effectively enable new-quality productivity development? Through which specific channels does this effect materialize if confirmed? And do heterogeneous effects exist across regions, industries, and enterprise characteristics?
This study selects China as its research context for three compelling reasons. First, as a representative emerging market economy, China has prioritized digital transformation through its national “Digital China” strategy. The government has substantially invested in digital infrastructure, creating favorable conditions for corporate digital transformation [
25]. By May 2024, China had deployed 3.837 million 5G base stations, accounting for over 60% of the global total, while its fixed broadband networks achieved rapid upgrades from 10 Mbps to 100 Mbps and then to gigabit speeds. These developments provide an ideal setting to examine digital transformation’s effects while offering valuable insights for other digitalizing economies. Second, mirroring global trends, China’s economic growth has slowed significantly in recent years [
25,
26,
27,
28]. In response, policymakers have introduced the novel concept of new-quality productive forces, emphasizing total factor productivity growth and technological innovation as pathways to high-quality development. As the world’s largest developing economy, China’s approach to cultivating new-quality productive forces offers valuable policy lessons for other developing nations facing growth momentum challenges.
This study establishes the causal relationship between digital transformation and corporate NQP through rigorous empirical analysis of China’s non-financial A-share listed companies from 2013 to 2022, utilizing data from corporate annual reports, CNRDS, and CSMAR databases. We employ Python’s (version 3.10.12) Jieba (version 0.42.1) text segmentation tool to extract digital transformation-related keywords from annual reports, constructing a comprehensive firm-level digitalization index. The measurement of NQP is achieved through a multidimensional indicator system encompassing both labor and production tools factors, with weights determined by the entropy method. Baseline regression results demonstrate that digital transformation exerts a statistically significant positive effect on NQP enhancement. The robustness of this finding has been thoroughly verified through alternative model specifications, including reconstructed digitalization indices (Dig) and total factor productivity-based NQP measures, with all tests consistently supporting our primary conclusion.
A potential endogeneity concern is that firms with strong technological innovation capabilities, economic efficiency, and high-quality development may be more inclined to prioritize digital transformation and thus possess greater capacity for digitization. To mitigate this reverse causality issue, this study leverages the “Broadband China” pilot policy as an exogenous shock and employs a multi-period difference-in-differences (DID) approach to estimate the policy’s impact on firm-level NQP. Our findings demonstrate that the “Broadband China” policy exerted a positive effect on NQP. Furthermore, to address additional endogeneity issues such as omitted variable bias, we construct instrumental variables (IVs) and implement a two-stage least squares (2SLS) estimation. After implementing these robustness checks, the causal relationship between digital transformation and NQP is strongly supported.
In the mechanism analysis, we identify two key channels through which digital transformation enhances firm-level NQP: green technology innovation capability and green management innovation. Furthermore, employing a moderation effects model, we demonstrate that digital financial inclusion significantly amplifies the positive impact of digital transformation on NQP. Finally, cross-sectional heterogeneity tests reveal that the productivity-enhancing effects of digitization are more pronounced for state-owned enterprises (SOEs), non-manufacturing firms, firms located in developed regions, and those operating in industries with higher competition intensity.
Compared with existing studies, this paper makes three key contributions. First, this study examines how technological progress affects firms’ new-quality productivity (NQP). Recent literature has mainly focused on defining NQP and discussing its drivers [
5]. Previous studies have explored various factors behind NQP, including the digital economy [
7], international trade [
29], and entrepreneurship [
30]. However, most of these studies rely on single productivity measures, overlooking NQP’s multidimensional nature. Few provide quantitative evidence on how technological progress—especially digital technologies—shapes NQP. Additionally, many studies use short timeframes [
31], making it difficult to assess long-term effects. This limited approach may lead to biased results and underestimate the role of innovation. To address these gaps, we construct a multidimensional NQP index using the entropy method and analyze ten years of firm-level panel data. Our findings help clarify the causal relationship between digital transformation and NQP, contributing to research on NQP’s key drivers.
Second, this study extends research on the microeconomic consequences of digital technologies. In the digital economy era, technologies such as artificial intelligence, blockchain, cloud computing, big data, and the Internet of Things are being widely adopted in the real economy, driving firms to seek transformative pathways [
23]. However, existing studies often overlook the precision and quality of innovation outputs—particularly green innovation, which is critical for sustainable growth—and rarely distinguish between its technological and managerial forms [
10,
11,
17]. They also neglect micro-level enabling conditions, relying instead on broad institutional indicators and overlooking the role of digital financial ecosystems. Unlike prior literature, our findings show that digital transformation significantly enhances firms’ NQP. Furthermore, we identify the mediating role of green innovation capabilities and the positive moderating effect of digital financial inclusion, thereby deepening the understanding of how digital transformation empowers the development of NQP.
Finally, our study, based on empirical data from China, confirms the important role of digital transformation in driving new-quality productivity, which is an important implication in the context of sluggish growth and increasing risks of uncertainty prevailing globally [
32]. In particular, the new-quality of productivity emphasized in this paper implies the need to focus on quality and efficiency in the development process, which is a new and more futuristic concept of productivity [
5], and can bring new insights and reflections for the sustained growth of the world economy.
The paper is organized as follows: The paper is structured as follows:
Section 2 develops the theoretical analysis, research hypotheses, and baseline model;
Section 3 reports the empirical findings, including robustness checks and endogeneity tests;
Section 4 provides further analysis comprising mechanism tests, moderating effects, and heterogeneity analysis; and
Section 5 concludes with research implications and policy recommendations.
5. Conclusions
This section synthesizes key findings on how digital transformation drives new-quality productivity through dual pathways of green innovation. It positions these findings within the existing literature to demonstrate both convergence with established theories and novel contributions to the field. Building on empirical evidence, we derive policy implications for advancing sustainable digitalization and green growth. The section concludes by addressing methodological limitations and proposing future research directions to investigate alternative mechanisms and contextual factors.
5.1. Deliberations
As the global economy enters a new phase of structural transition, countries are facing varying degrees of growth slowdown. In this context, the concept of New-Quality Productivity (NQP) has gained increasing prominence as a driver of sustainable development, demonstrating significant value for economic, ecological, and social progress [
2,
5,
6]. The empirical findings of this study demonstrate that digital transformation serves as a critical driver of NQP, operating through the dual channels of green innovation and amplified by digital financial inclusion. To systematically elucidate the theoretical implications of these findings, this section situates our conclusions within the existing literature, clarifying their alignment with and extension of prior research.
Our core finding—that digital transformation significantly enhances NQP—reinforces the established consensus in existing research while providing micro-level evidence. Consistent with Pan, Xie, Wang and Ma [
7], our study confirms that digital technologies enhance productivity by optimizing information flows and factor allocation. Similarly, our results align with Li and Tian [
11], who demonstrated that digitalization promotes green innovation, which subsequently improves productivity—thereby validating the synergistic relationship between digital transformation and environmental innovation. Furthermore, our finding that digital financial inclusion (DFI) positively moderates the digital transformation–NQP relationship corroborates Hu, Fang and DiGiovanni [
52], who established that digital finance alleviates financing constraints and facilitates the translation of innovation potential into realized performance. This further supports the view that digital finance serves as a key enabler of technological diffusion and sustainable productivity growth.
Despite these alignments, our study introduces critical distinctions that refine existing understanding. First, while prior studies typically treat productivity as a monolithic construct measured by total factor productivity [
33], we conceptualize NQP as a multidimensional construct grounded in the Dual-Factor Theory. This approach captures qualitative improvements in labor and production tools that are essential for sustainable development but often obscured in conventional productivity measures. Second, unlike studies that treat green innovation as an aggregate construct [
11], we disentangle its dual dimensions—green technological innovation and green managerial innovation—revealing distinct yet complementary mediation pathways. This granular analysis demonstrates how digital transformation simultaneously reshapes technological systems and managerial practices to generate sustainable productivity gains. Third, we establish that DFI’s positive effect is conditional on firms’ digital transformation level, suggesting a synergistic relationship wherein external digital finance yields maximum benefits only when firms possess sufficient internal digital capabilities to effectively absorb and deploy resources—a nuance overlooked in earlier work [
61]. Finally, our heterogeneity analysis reveals that the productivity-enhancing effects of digital transformation are more pronounced in state-owned enterprises, non-manufacturing sectors, and firms in developed regions, indicating that institutional context, industry characteristics, and regional development jointly shape the realization of digital dividends.
By delineating these theoretical consonances and distinctions, our study not only validates core propositions in the digital transformation literature but also advances a more nuanced framework for understanding NQP emergence in the sustainable digitalization era.
5.2. Key Findings
This study focuses on the Chinese market and, based on empirical data from Chinese A-share listed companies from 2013 to 2022, systematically reveals the impact of digital transformation on enterprises’ new productive forces and its underlying mechanisms. The main conclusions are as follows.
Firstly, digital transformation significantly improves the new-quality productivity level of enterprises, which is still supported under mitigating endogeneity and has withstood many robustness tests. In doing so, we establish an intrinsic link between digital technology and productivity and contribute to economic growth theory. Second, we identify two plausible mechanisms of action; i.e., digital transformation improves firms’ new-quality productivity level mainly by promoting firms’ green technological innovation and green management innovation, deepening the understanding of the way in which digital technology works to improve productivity. In addition, digital inclusive finance plays a positive moderating role in the relationship between digital transformation and firms’ new-quality productivity. Finally, the results of the cross-sectional analysis show that the impact of digital transformation on firms’ new-quality productivity exhibits an asymmetric impact effect; specifically, firms in state-owned, non-manufacturing, and developed regions as well as those with a high degree of competition in the industry are more affected.
5.3. Practical Applications
Based on key research findings, this study aims to translate empirical research into concrete strategies for advancing sustainable development. First, policymakers should adopt integrated planning to construct a supportive ecosystem for digital–green synergistic development. The robust connection between digital transformation and new-quality productivity necessitates a comprehensive policy framework that extends beyond digital infrastructure to deeply align digitalization with green transition goals. This requires designing composite policy instruments—such as innovation subsidies, tax incentives, and green finance guidelines—to incentivize firms in achieving verifiable environmental benefits through digital technologies. Concurrently, cultivating talent with dual expertise in digital and green domains through education reform and vocational training is critical to bridge skill gaps and provide human capital support for new-quality productivity. Furthermore, asymmetric regulation should be implemented in less-developed regions by adopting differentiated digital transformation support policies, assisting vulnerable firms in overcoming initial barriers and preventing the expansion of “productivity divides.”
Second, corporate managers should strategically reinvest digital dividends into green innovation to amplify productivity returns by directing digital outcomes toward environmental performance enhancement. Specifically, firms should pursue integrated investment by channeling digital budgets into green R&D projects, such as utilizing data analytics for energy management or applying artificial intelligence to optimize resource circulation in a circular economy. Environmental performance indicators—including the carbon footprint and resource productivity—should be incorporated into management systems and decision-making processes to ensure the effective implementation of green management innovation. Additionally, fostering an eco-innovation culture by encouraging employee participation in environmental initiatives and establishing internal innovation incubators focused on addressing sustainability challenges through digital means is essential.
Finally, leveraging the positive moderating role of digital financial inclusion, financial institutions should develop tailored financial products and services to support the digital–green transition. This includes innovating customized financial instruments such as “digital transformation dedicated credit,” “green supply chain finance,” and “sustainability-linked loans” to precisely meet the needs of SMEs in digital and green upgrading while utilizing big data and artificial intelligence for dynamic risk assessment. Simultaneously, collaborative efforts with technology firms and policymakers are needed to build a robust financial ecosystem by improving digital payment systems and credit infrastructure to reduce transaction costs and expand financing channels for sustainable projects.
5.4. Limitations and Future Prospects
This study acknowledges several limitations that warrant consideration and suggest productive avenues for future research. The most critical limitation lies in the measurement of digital transformation. Our firm-level digital transformation index, constructed through textual analysis of keyword frequency in annual reports, primarily captures discursive emphasis rather than actual technology adoption or integration. This methodological approach may introduce measurement bias, as firms could strategically overstate their digital engagement for signaling purposes, while others implementing substantive digital upgrades might underreport their efforts. We therefore explicitly frame our findings as reflecting the relationship between reported digital transformation and new-quality productivity, rather than establishing causal effects from fully implemented digital technologies.
Second, while this study elucidates the positive impacts of digital financial inclusion (DFI) on the relationship between digital transformation and new-quality productivity, it also acknowledges its potential countervailing effects and negative implications. Digital transformation may incur transition costs, intensify internal organizational resistance, and lead to labor displacement in the short to medium term due to automation and skill mismatches [
82]. Similarly, the rapid expansion of DFI could introduce challenges such as algorithmic discrimination, data privacy concerns, and over-indebtedness risks, particularly in contexts where regulatory frameworks are underdeveloped [
83]. These limitations do not invalidate our core findings but underscore the necessity of implementing complementary policies—such as robust social safety nets and digital ethics guidelines—to mitigate risks.
Future research should prioritize developing comprehensive measurement frameworks that integrate discursive indicators with objective metrics—such as IT investment from financial statements, software implementation rates, and digital infrastructure—to more accurately capture the scope and depth of digital transformation. Furthermore, researchers need to systematically investigate the contextual factors and governance mechanisms that may mitigate the potential negative impacts of digital transformation and digital financial inclusion across different institutional environments, including transition costs, skill mismatches, and algorithmic risks.