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The information used for supervision by regulatory departments in public-private partnership (PPP) projects is primarily transmitted and processed by the PPP implementation department, which negatively impacts the information quality, leading to information asymmetry and undermining the overall effectiveness of supervision. This study aims to explore how to use blockchain to anchor the information used for supervision in PPP projects to the original information, to strengthen the oversight.

This paper adopts the principles of design science research (DSR) to design a conceptual framework that systematically organizes information along the information dissemination chain, ensuring the reliable anchoring of original information. Two-stage interviews involving experts from academia and industry are conducted, serving as formative and summative evaluations to guide the design.

The framework establishes a weak-centralized information organizing mode, including the design of governance community and on-chain and off-chain governance mechanisms. Feedback from experts is collected via interviews and the designed framework is thought to improve information used for supervision. Constructive suggestions are also collected and analyzed for further development.

This paper provides a novel example exploring the inspirations blockchain can bring to project governance, like exercising caution regarding the disorderly expansion of public sector authority in addressing information disadvantages and how to leverage blockchain to achieve this. Technical details conveyed by the framework deepen understanding of how blockchain benefits and the challenges faced in successful implementation for practitioners and policymakers. The targeted evaluation serves as rigorous validation, guiding experts to provide reliable feedback and richer insights by offering them a more cognitively convenient scenario.

China has been going through a “museum boom” paralleling the domestic tourism boom since 2000; such growth changed the cultural landscape; museums became a vital characteristic of some Chinese cities for both residents and tourists. Encouraged by this growth, the more ambitious “All-for-one Museum (全域博物馆)” was proposed. The physical boundary between museums and living spaces is infinite ambiguity, challenging the idea of museums as “heterotopias.” This study aims to explore the musealization of urban spaces in the context of anthropology and museology, scrutinizing the cultural-political intentions and meanings of these developments, and seeks to ignite further investigation into the reconstruction of historical imaginaries for tourists and urban populations across related disciplines.

This paper examines two cases in Chinese metropolises, Beijing and Shanghai, to illustrate this development of musealization, that is, how the cities actively leverage museological values and methods to connect with their past. In the Beijing case, the authors explore how the local government is leading the effort to musealize the city; in the Shanghai case, they will see how tourists, especially dweller-tourists, navigate through a curated past story in the city and connect their own experience, memory and identity with the place.

The all-for-one museum creates a museal layer projected onto the bigger urban space, even though the authenticity of the “past” is challenged by the modernization development of the city. The authors also find out that for some tourists (especially dweller-tourists), an existential sense of authenticity plays a more significant role as they not only seek to sightsee the past of the city but also to take part in its creation.

This paper discusses two kinds of musealization in cosmopolitan cities of Beijing and Shanghai: top-down and bottom-up. It approaches questions about the musealization of urban spaces from the perspectives of anthropology and museology, and discusses musealization in the specific historical context of China’s modernization process.

Mega construction projects (MCPs), which play an important role in the economy, society and environment of a country, have developed rapidly in recent years. However, due to frequent social conflicts caused by the negative social impact of MCPs, social risk control has become a major challenge. Exploring the relationship between social risk factors and social risk from the perspective of risk evolution and identifying key factors contribute to social risk control; but few studies have paid enough attention to this. Therefore, this study aims to systematically analyze the impact of social risk factors on social risk based on a social risk evolution path.

This study proposed a social risk evolution path for MCPs explaining how social risk occurs and develops with the impact of social risk factors. To further analyze the impact quantitatively, a social risk analysis model combining structural equation model (SEM) with Bayesian network (BN) was developed. SEM was used to verify the relationship in the social risk evolution path. BN was applied to identify key social risk factors and predict the probabilities of social risk, quantitatively. The feasibility of the proposed model was verified by the case of water conservancy projects.

The results show that negative impact on residents’ living standards, public opinion advantage and emergency management ability were key social risk factors through sensitivity analysis. Then, scenario analysis simulated the risk probability results with the impact of different states of these key factors to obtain management strategies.

This study creatively proposes a social risk evolution path describing the dynamic interaction of the social risk and first applies the hybrid SEM–BN method in the social risk analysis for MCPs to explore effective risk control strategies. This study can facilitate the understanding of social risk from the perspective of risk evolution and provide decision-making support for the government coping with social risk in the implementation of MCPs.

This paper aims to examine the impact of corporate governance mechanisms on forward-looking corporate social responsibility (CSR) disclosure (FCSRD).

The authors use the manual content analysis to measure FCSRD for a sample of 94 companies listed on the Amman Stock Exchange from 2010 to 2016. Data on companies' FCSRD are manually collected from annual reports. The authors also use regression analyses to test the research hypotheses.

The authors find that board size positively affects FCSRD, while CEO duality and family ownership negatively impact FCSRD.

To the best of the authors’ knowledge, this is the first evidence of how governance mechanisms affect FCSR information in corporate annual reports in a developing country.

This study aims to practically determine the optimum proportion of aggregates to attain the desired strength of geopolymer concrete (GPC) and then compare the results using established analytical particle packing methods. The investigation further aims to assess the influence of various amounts of recycled aggregate (RA) on properties of low-calcium fly ash-based GPC of grade M25.

Fine and coarse aggregates were blended in various proportions and the proportion yielding maximum packing density was selected as the optimum proportion and they were compared with analytical models, such as Modified Toufar Model (MTM) and J. D. Dewar Model. RAs for this study were produced in laboratory and they were used in various amounts, namely, 0%, 50% and 100%. 12M NaOH solution was mixed with Na₂SiO₃ in the ratio of 1:2. The curing of concrete was done at the temperatures of 60° and 90 °C for 24, 48 and 72h.

The experimentally obtained optimum proportion of coarse to fine aggregate was 60:40 for all amounts of RA. Meanwhile, MTM and Dewar Model resulted in coarse aggregate to fine aggregates as 40:60, 45:55, 55:45 and 55:45, 35:65, 60:40, respectively, for 0% 100% and 50% RAs. The compressive strength of GPC elevated with the increase in curing regime. In addition, the ultrasonic pulse velocity also displayed a similar trend as that of strength.

The GPC with 50% RAs may be considered for use, as it exhibited superior properties compared to GPC with 100% RAs and was comparable to GPC with natural aggregates. Furthermore, compressive strength is correlated with split tensile strength and ultrasonic pulse velocity.

In the context of innovation-driven development strategy, open innovation has become an important way for enterprises to gain competitive advantages on the path of innovation and development. However, with the increasing competition, enterprises' open innovation is restricted by some constraints. How to promote open innovation in the restricted situations has become an existing research gap. Based on the perspective of digital transformation, this paper discusses how to promote the open innovation of enterprises under the restricted situations and find its breakthrough path, and analyzes the moderating effect of innovation persistence and political relevance.

Due to the complexity and confidentiality of military–civilian integration enterprises, they have become typical innovation-restricted enterprises. In this study, it selects a-share listed companies in the field of military–civilian integration in China in 2016–2020 as the research sample, and uses the two-way fixed-effect model to analyze the proposed variables. Finally, the robustness of the results in this paper is verified by a series of robustness tests and endogeneity tests.

The results show that digital transformation facilitates open innovation in military–civil integration enterprises, and that innovation persistence and political relevance positively moderate the relationship between the two. Further, digital transformation can promote open innovation in military–civil integration enterprises by easing the financing constraints and reducing information asymmetry. Innovation persistence has a more pronounced positive moderating effect among civilian-to-military and SMEs, and digital transformation of firms in the South has a negative effect on open innovation, but innovation persistence and political relevance dampen this negative effect.

Previous studies on the restrictions of open innovation or its dark side are mostly case studies and qualitative research. In contrast, the superiority and novelty of this study is in the form of a typical innovation-restricted enterprises “civil-military integration enterprise” as the research sample, based on the perspective of digital transformation, through empirical analysis method to explore how to better implementation of open innovation in the restricted situations. The findings of the study can not only enrich the application of digital transformation and open innovation theory, but also provide practical guidance for military–civil integration innovation in restricted situations.

This study aims to determine whether the stock holdings of equity mutual funds are informative for predicting future stock performance in the Chinese market. It is a puzzle that actively managed mutual funds underperform passive benchmarks, whereas retail investors still delegate investment decisions to the fund managers. The present study sheds light on whether mutual fund managers possess security selection skills in their top ten holdings.

By regression analysis and portfolio sorting, this study focuses on 830 Chinese A-share stocks in the industry research reports from the Guotai Junan Securities Company. It collects mutual fund's top ten holdings data from the Wind Financial Terminal between 2019Q1 and 2021Q1. As robustness checks, the result holds for the fixed-effect model, an additional measure of ranks in the top ten holdings, the predictability test based on the confusion matrix and two stage least square (2SLS) regression.

The authors find that the top ten holdings by equity mutual funds are informative for predicting stock performance and can provide valuable information for investors to support their decision-making.

The findings of this study provide insightful guidance for retail investors in making investment decisions and support the hypothesis that active fund management adds value.

Firstly, the authors find that the top ten holdings of Chinese mutual funds show significantly positive signals for future stock excess returns, indicating the selection skills of fund managers. Secondly, the above positive relationship exhibits a diminishing marginal effect with more funds holding this stock. Thirdly, the authors find that the predictability horizon of the number of overweighing funds is up to three quarters and then diminishes in the fourth quarter. Finally, investors have a 59% prediction accuracy for the whole stock sample and an 85% precision conditional on the predicted positive subsample to outperform the market. The authors also address the endogeneity and reverse causality issues.

This study aims to empirically analyze how the quality of alternatives influences the commitment level in the relationships between companies in supply chains. It also studies how this ultimately influences the associated satisfaction level and logistics performance.

For this purpose, the authors adopted an extended investment model based on interdependence theory. The authors explored the relationships between logistics outsourcing partners based on the components of the investment model. To examine the correlations between variables, the authors surveyed workers in domestic supply chain–related departments and used a total of 300 valid questionnaires for statistical analysis. The hypotheses were verified through structural equation modeling using SPSS 18.0 and AMOS 18.0.

The quality of alternatives had a positive influence on the commitment level. Additionally, the commitment level had a positive influence on the satisfaction level but did not have a significant influence on logistics performance. Finally, the satisfaction level exhibited a proportional relationship with logistics performance.

First, this study examined the effects of the relationships between supply chain parties and psychological factors on logistics outsourcing. Second, this study applied the investment model to a logistics outsourcing-related topic. Finally, under the COVID-19 and the trade war, this study is significant as it shows that the existing commonly accepted hypotheses can be overturned.

This study differs from other studies in that it applied the investment model to a logistics outsourcing-related topic.

This study aims to investigate the influence of digital transformation on the overall financial performance of firms, with a specific focus on Chinese-listed companies from 2010 to 2021. It seeks to understand the impacts on various accounting and financial indicators in emerging economies such as China.

This study employs a text-mining approach to construct a digital transformation index based on the data sample of 11,814 firm-year observations from China’s A-share listed companies. This index serves as a proxy to measure the extent of digital transformation and its impact on financial performance and health.

The findings indicate that digital transformation significantly enhances overall financial performance and health, as evidenced by increased profitability, reduced operational costs, and lowered financial risks. The study reveals a time-lagged effect, where the benefits of digital transformation become more apparent after about one year. Further analysis shows that the value of digital transformation is more evident in a firm’s asset items. This raises the possibility of recognising the by-product, such as data resources, in the digital transformation process.

This research offers a unique contribution by linking digital transformation to financial performance using a large dataset from China's A-share listed firms. Doing so enhances our understanding of the tangible effects of digital transformation on corporate performance. Furthermore, this research provides valuable insights for the advancement of future accounting practices and the development of standards.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.