This paper examines whether Open Government Data (OGD) can improve urban air quality in China. Using the staggered rollout of city-level OGD platforms as a quasi-natural experiment, it estimates the effect of platform launches on annual average PM2.5 concentration at the prefecture-city level. The results show that OGD significantly reduces PM2.5 concentration. This finding remains robust after replacing the dependent variable, conducting event-study tests, applying the Goodman–Bacon decomposition, using a heterogeneity-robust estimator, and carrying out a placebo test. The analysis also shows that controlling for the prior influence of provincial platforms is important, because ignoring this factor may lead to an underestimation of the city-level policy effect. Further analysis suggests that OGD may improve air quality by promoting green innovation, strengthening the government’s orientation toward high-quality development, and increasing public environmental attention. The effect is stronger in cities with better digital infrastructure and stronger government governance capacity, and is generally more pronounced in major urban agglomerations. Overall, the findings suggest that OGD is not only a tool for information disclosure, but also a policy instrument with broader value for environmental governance.

Bridging divides with data: Open government data and ESG rating divergence

Public adoption of open government data: A game theoretical approach

ABSTRACT Open government data (OGD) is essential for advancing digital governance, but its influence on corporate resilience remains insufficiently explored. Based on a panel data from China’s A-share listed manufacturing firms during 2007 and 2023, this paper employs a staggered difference-in-differences model with the imputation estimator to examine the impact of OGD on corporate resilience from a signal transmission perspective. The baseline results show that OGD significantly increases firms’ return on assets (ROA) by 0.07 and reduces bankrupt risk (RC) by 0.005, indicating improvements both in corporate operational and recovery resilience. These findings remain robust after various robustness tests. Mechanism analysis reveals that OGD strengthens corporate resilience by improving the business credit environment and promoting a fair and competitive market. Heterogeneity analysis shows that OGD strengthens resilience more in non-SOE enterprises, enhances operational resilience in capital- and technology-intensive sectors, and improves recovery resilience among small and labour-intensive firms. Further analysis demonstrates that firms with lower digital viability benefit more from OGD, and that improvements in marketization and digital infrastructure amplify the effect of OGD on operational resilience. This paper offers valuable insights for improving digital governance in developing countries.

Open government data and entrepreneurship: Evidence from China

Purpose Although there is much research about Open Government Data (OGD), comprehensive evaluations of OGD policy impacts remain sparse. This study addresses this gap by empirically examining the alignment between OGD policy objectives and real-world outcomes across 337 Chinese municipalities. Design/methodology/approach A typology of OGD policy objectives is developed and used to evaluate OGD policies and their impact in different geographical regions. Findings The analysis revealed a hierarchy of outcomes where “technical support” goals yield higher impacts than “innovative value”, whereas the latter is often the goal of OGD initiatives. Regional disparities also emerge, with Eastern cities outperforming traditional industrial areas. Originality/value These findings underscore that policy design does not guarantee expected outcomes, especially under varying regional contexts. Policy-makers should better address local characteristics and develop targeted policy strategies and effective resource allocation. Highlights

ABSTRACT Despite extensive research on open government data and political trust in Western contexts, less is known about how such reforms shape trust across different levels of government in non-Western countries. We argue that governments in these settings may strategically use open data reforms to signal transparency and thereby enhance political trust, with higher-level governments that lead these reforms more likely to benefit. Using data from China, we find that open government data increases trust in central and county governments, but not in township governments, and that perceived transparency mediates this relationship.

Abstract In this study, we analyzed the transformation of coworking geography before and after COVID-19 across 335 locations in Pune and used kernel density to select two clusters for this research. This paper presents an empirical investigation of socioeconomic determinants and lifestyle factors in conjunction with Coworking spaces, along with the behavioral choice factors of coworking spaces as identified in the literature and primary surveys. Empirical investigations using Geographically Weighted Regression (GWR) and Ordinary Least Squares (OLS) are conducted for two knowledge clusters in Kalyani Nagar and Baner, using variables from Census data, OpenStreetMap (OSM), Open Government data, and PCMC data. The analysis reveals that "Lifestyle choice factors", "Hotel Locations", and "Urban built growth rate" have significant impacts on Coworking spaces. Lastly, the paper proposes various recommendations that serve as an impetus for a better, more conducive environment for a prospering knowledge economy through effective and efficient policy measures.

ABSTRACT This paper examines the impact of public data open platforms (PDOP) on the digital and intelligent transformation of enterprise in China, addressing the research gap regarding the causal effectiveness of open government data initiatives. Using a balanced panel dataset of 16,365 Chinese A-share listed enterprises from 2009 to 2023, we apply a synthetic difference-in-differences approach to verify it. In contrast to previous findings, our results suggest that the PDOP had no significant impact on enterprises digitalization and intelligent transformation. The null effect highlights the challenges of open government data and offers insights for future improvement, particularly in reducing implementation distortions, improving the applicability of data, and better aligning government data provision with the actual needs of enterprises.

As data emerge as a new production factor, unlocking their value hinges on effective circulation and sharing mechanisms. Exploiting panel data for 279 prefecture-level cities in China from 2011 to 2023, this study employs Staggered Difference-in-Differences and Double Machine Learning methods to examine the causal impact and underlying mechanisms of public data openness on digital financial inclusion development. The findings reveal that the establishment of government open data platforms significantly promotes digital financial inclusion. Public data openness operates through two distinct channels: enhancing information matching efficiency and facilitating industrial collaborative agglomeration. The former reduces financial institutions’ information search costs and enables the construction of alternative credit assessment systems, while the latter catalyzes fintech ecosystems and generates knowledge spillover effects. Furthermore, policy effects manifest more prominently in regions characterized by higher marketization levels, well-developed digital infrastructure and abundant human capital endowments.

Citizen participation is a vital component of public administration in the 21st century. This study compares Thailand and South Korea to examine how digital governance frameworks influence civic engagement, focusing on policy design, administrative structures, and political culture. The findings reveal that South Korea has effective- ly utilized digital platforms, such as e-participation systems and Open Government Data, to strengthen transparency and enable citizens to engage substantively in au- diting, administrative appeals, and policymaking. In contrast, although Thailand has developed platforms such as the 1111 Complaint System and Damrongtham Online Center, citizen participation remains limited because of structural, legal, and trust barriers. This contrast illustrates that South Korea has reached an advanced stage of digital governance, whereas Thailand is still in its formative phase. Therefore, this study proposes policy recommendations for Thailand, including sustained investment in digital infrastructure, development of integrated platforms, and enhancement of transparency to foster public trust. These measures would expand opportunities for citizen engagement and serve as a pathway to advance public administration toward greater democracy and sustainability.

Purpose Chinese government documents require sensitivity reviews to detect and protect sensitive personal information before public release. However, this process is often time-consuming and labor-intensive due to the lack of robust automated detection and classification systems, especially considering the complexities of Chinese morphology, grammar and semantics, which challenge existing solutions. Design/methodology/approach This study proposes a parallel dual-channel hybrid neural network model for the detection and classification of sensitive information. The model leverages Bidirectional Encoder Representations from Transformers (BERT) for text vector representation, combined with Text Convolutional Neural Networks (TextCNN) and Bi-directional Long Short-Term Memory (BiLSTM) networks to extract both local and global semantic features. The integration of an attention mechanism further enhances the model’s capacity by emphasizing critical terms, thereby improving the precision of sensitive information classification. Findings The effectiveness of the proposed model, CGDSClass, was validated through comparative analysis with nine existing models across two datasets. The results demonstrate that CGDSClass significantly outperforms these models, indicating a superior capability in handling the specific challenges of sensitive information detection in Chinese government documents. Originality/value As the first study to address sensitive information detection and classification in the context of Chinese government open data, this research offers a novel theoretical and technical foundation. CGDSClass not only improves the accuracy of classification but also enhances early warning and monitoring capabilities, thereby reducing the risk of data breaches and advancing the openness of government data practices.

How much data: measuring quantity, visibility and topics of Indian open governmental data using machine algorithm approaches

This study evaluates India's open data ecosystem through data.gov.in by analysing sector-wise and state-wise data production, usability, and major content topics. Using 6,907 datasets (2012-2023) extracted via a Python-based API, the analysis highlights key areas of interest: primary healthcare data (health), crop production statistics (agriculture), and demographic data (census). States like Tamil Nadu and Assam focus heavily on health-related data, while Andhra Pradesh and Bihar prioritise census abstracts. Tamil Nadu leads contributions to transport data (75.44%) and livestock census data (16.53%). Comparisons with USA and UK portals reveal India's strength in regional datasets but emphasise gaps in technical infrastructure and user engagement. Despite disparities between displayed and actual catalogues, India's tailored local data fosters transparency and data-driven governance. This first-of-its-kind study benchmarks India's portal globally, providing insights into sectoral focus, identifying best practices, and addressing socio-economic governance challenges.

This article examines how countries move beyond the traditional model of publishing open government data by integrating AI-driven surveys, blockchain-based verification and participatory feedback forums to co-create higher-quality, more trustworthy datasets. In this regard, the study analyzes user feedback mechanisms across various national open data platforms and particularly investigates three specialized e-participation initiatives: the U.S. Challenge.gov crowdsourcing ecosystem, Sweden’s NOSAD open data and open-source collaboration network, and Vienna’s blockchain-driven data verification system. The cross-national content analysis identifies a diverse set of mechanisms, including interactive forms, social media integration, dataset request systems, metadata automation and community discussion boards that e-government platforms increasingly deploy to enhance data quality, usability and civic participation. Findings show that context-aware feedback, AI-tailored user interactions and decentralized metadata verification significantly strengthen transparency, trust and citizen engagement. The case studies further illustrate how incentives, collaborative resource exchange and distributed ledger technologies shape new models of participatory data governance. The article concludes by proposing a conceptual framework for evolving OGD portals into citizen-centric, innovation-driven ecosystems and offers policy recommendations to support more responsive, secure and collaborative open data infrastructures.

ABSTRACT Information asymmetry fundamentally drives corporate financing constraints; yet traditional firm-level disclosures frequently fail to mitigate it due to their susceptibility to strategic manipulation and credibility deficits. This paper identifies open government data (OGD) as a pivotal solution that is an exogenous and institutionally validated information infrastructure, transcending the limitations of firm-controlled mechanisms. Leveraging China’s staggered provincial OGD platform launches in a quasi-natural experiment, we deploy a multi-period difference-in-differences (DID) design to identify causal effects. Results show OGD reduces financing constraints by 3.4% on average, primarily via two democratizing pathways: (i) expanding bank credit availability through increased unsecured lending, reducing reliance on traditional collateral; and (ii) strengthening non-bank financing via enhanced supply chain trade credit access, a critical yet policy-neglected channel. Heterogeneity analyses show that OGD most significantly alleviates financing constraints for informationally marginalized firms: SMEs and digitally mature firms by mitigating “thin-file” disadvantages; low-quality disclosers by offsetting credibility gaps; and firms with concentrated ownership by facilitating external monitoring. Crucially, for firms with robust internal controls, OGD complements governance through independent validation, highlighting its role as a governance amplifier rather than a substitute. This study provides empirical evidence that public data sharing can offer scalable solutions for enhancing financial inclusion.

ABSTRACT Foreign direct investment (FDI) firms face significant information barriers and costs in host countries. Whether open government data (OGD) policy can help FDI firms access information and attract inflows has become a crucial issue. This study uses panel data for 286 Chinese cities from 2007 to 2021 to assess whether OGD has promoted FDI inflows. The study finds that OGD significantly promotes FDI inflows. The mechanism analysis reveals that OGD facilitates FDI inflows by mitigating transaction costs and liabilities of foreignness, enhancing governmental governance efficiency, and curbing government intervention. Additional findings indicate that the effect of OGD on promoting FDI inflows is more potent in regions with higher economic policy uncertainty and higher levels of digital development. These results suggest that OGD can effectively enhance governance efficiency and curb government intervention, providing valuable policy implications for leveraging OGD to promote FDI inflows.

Open Government Data (OGD) has become a key driver of transparency, innovation, and sustainable development. By making public sector information accessible, OGD fosters economic growth, improves public services, and strengthens democratic governance. This paper explores the role of OGD in promoting innovation and advancing the Sustainable Development Goals (SDGs), particularly in urban planning, environmental protection, and public health. It also examines challenges in data accessibility, interoperability, and usability, highlighting the need for standardized formats and open APIs. A case study of the JakDojade transport planning application demonstrates how OGD can enhance smart mobility, reduce environmental impact, and create business opportunities. However, limitations in data availability and licensing practices hinder full utilization. This paper calls for improved data-sharing policies and IT infrastructure to maximize the societal benefits of open data.

ABSTRACT Information is crucial to capital flows. This study exploits open government data (OGD) as an exogenous shock to information disclosure and employs a staggered difference-in-differences approach to examine its impact on foreign direct investment (FDI). We find that: (1) OGD significantly increases FDI inflows, robust to multiple sensitivity tests; (2) OGD attracts FDI by promoting digital financial inclusion, reducing institutional transaction costs, and fostering innovation; and (3) The effect of OGD on FDI varies by entry mode and industry. Specifically, OGD primarily promotes FDI through joint ventures rather than wholly owned subsidiaries and mainly stimulates investment in the producer services sector, while having no significant effect on living services or manufacturing. These results highlight the importance of data sharing in overcoming local information barriers and sustaining openness to FDI.

Open government data (OGD) initiatives, in Switzerland and elsewhere, are increasingly promoted in the name of economic value. In this context, the European Union (EU) introduced the concept of high-value datasets (HVDs), consisting of datasets whose reuse is expected to generate particularly high economic benefits. In the EU, HVDs are identified based on thematic categories and are to be prioritised for publication with minimal legal and technical barriers, with particular emphasis on data quality. While the identification of HVDs has been discussed in literature, given the recent introduction of the HVD concept, the relationship between the adoption of the HVDs prioritisation strategy and dataset quality has yet to be empirically measured. To address this question, we analyse metadata from 318,696 OGD datasets across six national portals: five from EU countries implementing the HVD approach and one from Switzerland, which does not. Using an index measuring adherence to good practice standards for OGD publishing, which is necessary to ensure data quality, we find that while HVDs tend to score higher on best practices compliance metrics, prioritisation alone does not resolve persistent quality issues and may introduce new risks.   Zusammenfassung Initiativen für offene Verwaltungsdaten (OGD) rücken zunehmend den wirtschaftlichen Nutzen in den Vordergrund. Diese Studie untersucht, ob die von der EU geförderte Priorisierung von High-Value-Datensätzen (HVDs) zur Steigerung der Datenqualität führt. Anhand von Metadaten zu 318 696 Datensätzen in sechs Ländern zeigt sich: HVDs schneiden bei Qualitätsstandards besser ab, doch Priorisierung allein behebt bestehende Qualitätsprobleme nicht unbedingt und kann neue Risiken mit sich bringen.   Résumé Les initiatives de données gouvernementales ouvertes (OGD) mettent de plus en plus l’accent sur leur potentiel économique. Cette étude analyse le rapport entre la stratégie de priorisation de certaines données, les ensembles de données de forte valeur (HVD) promus par l’UE, et la qualité des données. En examinant les métadonnées de 318 696 ensembles dans six pays, nous constatons que les HVD respectent mieux les bonnes pratiques de publication en moyenne, mais que la priorisation seule ne résout pas les problèmes de qualité et peut engendrer de nouveaux risques.   Schlagworte: Offene Regierungsdaten; hochwertige Datensätze; Datenqualität; Datenverwaltung Mots-clés: Données gouvernementales ouvertes; ensembles de données de forte valeur; qualité des données; gouvernance des données