Search results

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.

Extensive macro- and micro-economics research has been conducted on China's tax reform, which replaced business tax with value-added tax (VAT). However, existing studies have not clarified the reform's impact on firm-level investment decisions. Hence, this study explored the effect of replacing business tax with VAT on firms' investment efficiency.

The study used 2010–2018 data from China's A-share listed companies and a difference-in-differences (DID) model to explore the effect of the reform on firm-level investment decisions.

The authors found that China's tax reform has improved investment efficiency in underinvested firms, increased liquidity and decreased the level of reliance on external financing. The tax reform had a greater effect on investment efficiency in firms with lower liquidity and higher external financing reliance. Its effect was also more significant among non-state-owned and small companies.

This study fills the aforementioned research gap by exploring the effects of China's tax reform, thus providing a theoretical reference and a basis for policymaking.

Broiler meat is the most commonly used meat product worldwide. Although China is regarded as one of the three largest broiler producers, the per capita chicken consumption remains low. Consumers' cognitive bias and the information acquisition channels are believed to be the main factors contributing to this. This paper aims to discuss the aforementioned issue.

To explore the phenomenon empirically, the current study uses the survey data of 1,056 consumers from China and analyses them using ordered logistic regression.

The results revealed that consumers' cognitive bias significantly affects their behaviour toward broiler products, and the order of influence is cognitive bias regarding industry cognitive > product nutrition and taste > food safety. The study further revealed that the more diverse the information acquisition channels, the more likely they are to promote consumer behaviour toward broiler chickens. The order of influence of the channels was self-organising > new media > traditional media.

Overall, the findings suggest that the government and enterprises should strengthen and upgrade information channels to boost both the broiler industry and consumer consumption behaviour regarding poultry products.

Rather than the usual focus on the impact of consumer cognition on consumer behaviour, this study examines the impact of cognitive bias on consumer behaviour. Further, centring on broiler products with high protein, low fat and feed-to-meat ratios, this study explores the reasons the per capita consumption of broiler products in China is far lower than the national average.

This research addresses the diverse characteristics of existing railway steel bridges in China, including variations in construction age, design standards, structural types, manufacturing processes, materials and service conditions. It also focuses on prominent defects and challenges related to heavy transportation conditions, particularly low live haul reserves and severe fatigue problems.

The study encompasses three key aspects: (1) Adaptability assessment: It begins with assessing the suitability of existing railway steel bridges for heavy-haul operations through comprehensive analyses, experiments and engineering applications. (2) Strengthening: To combat frequent crack defects in the vertical stiffener end structure of girder webs, fatigue performance tests and reinforcement scheme experiments were conducted. These experiments included the development of a hot-spot stress S-N curve for this structure, validating the effectiveness of methods like crack stop holes, ultrasonic hammering and flange angle steel. (3) Service life extension: Research on the cruciform welded joint structure (non-fusion transfer type) focused on fatigue performance over the long life cycle. This led to the establishment of a fatigue S-N curve, enhancing Chinese design codes.

The research achieved several significant outcomes: (1) Successful implementation of strengthening and retrofitting measures on a 64-m single-span double-track railway steel truss girder on an existing heavy-duty line. (2) Post-reinforcement, a substantial 26% to 32% reduction in live haul stress on bridge members was achieved. (3) The strengthening and retrofitting efforts met design expectations, enabling the bridge to accommodate vehicles with a 30-ton axle haul on the railway line.

This research systematically tackles challenges and defects associated with Chinese existing railway steel bridges, providing valuable insights into adaptability assessment, strengthening techniques and service life extension methods. Furthermore, the development of fatigue S-N curves and the successful implementation of bridge enhancements have practical implications for improving the resilience and operational capacity of railway steel bridges in China.

The study employs two independent experimental studies to collect data. It focuses on the matching effect between advertising appeals and product types. The Elaboration Likelihood Model serves as the theoretical framework for understanding the cognitive processing involved in consumers' responses to these advertising appeals and product combinations.

This paper aims to investigate the impact of advertising appeals on consumers' intentions to purchase organic food. We explored the interaction between advertising appeals (egoistic vs altruistic) and product types (virtue vs vice) and purchase intention. The goal is to provide insights that can enhance the advertising effectiveness of organic food manufacturers and retailers.

The analysis reveals significant effects on consumers' purchase intentions based on the matching of advertising appeals with product types. Specifically, when egoistic appeals align with virtuous products, there is an improvement in consumers' purchase intentions. When altruistic appeals match vice products, a positive impact on purchase intention is observed. The results suggest that the matching of advertising appeals with product types enhances processing fluency, contributing to increased purchase intention.

This research contributes to the field by providing nuanced insights into the interplay between advertising appeals and product types within the context of organic food. The findings highlight the importance of considering the synergy between egoistic appeals and virtuous products, as well as altruistic appeals and vice products. This understanding can be strategically employed by organic food manufacturers and retailers to optimize their advertising strategies, thereby improving their overall effectiveness in influencing consumers' purchase intentions.

Being an efficient mechanism for the value of money, public–private partnership (PPP) is one of the most prominent approaches for infrastructure construction. Hence, many controversies about the performance effectiveness of these delivery systems have been debated. This research aims to develop a novel performance management perspective by revealing the causal effect of key performance indicators (KPIs) on PPP infrastructures.

The literature review was used in this study to extract the PPPs KPIs. Experts’ judgment and interviews, as well as questionnaires, were designed to obtain data. Copula Bayesian network (CBN) has been selected to achieve the research purpose. CBN is one of the most potent tools in statistics for analyzing the causal relationship of different elements and considering their quantitive impact on each other. By utilizing this technique and using Python as one of the best programming languages, this research used machine learning methods, SHAP and XGBoost, to optimize the network.

The sensitivity analysis of the KPIs verified the causation importance in PPPs performance management. This study determined the causal structure of KPIs in PPP projects, assessed each indicator’s priority to performance, and found 7 of them as a critical cluster to optimize the network. These KPIs include innovation for financing, feasibility study, macro-environment impact, appropriate financing option, risk identification, allocation, sharing, and transfer, finance infrastructure, and compliance with the legal and regulatory framework.

Identifying the most scenic indicators helps the private sector to allocate the limited resources more rationally and concentrate on the most influential parts of the project. It also provides the KPIs’ critical cluster that should be controlled and monitored closely by PPP project managers. Additionally, the public sector can evaluate the performance of the private sector more accurately. Finally, this research provides a comprehensive causal insight into the PPPs’ performance management that can be used to develop management systems in future research.

For the first time, this research proposes a model to determine the causal structure of KPIs in PPPs and indicate the importance of this insight. The developed innovative model identifies the KPIs’ behavior and takes a non-linear approach based on CBN and machine learning methods while providing valuable information for construction and performance managers to allocate resources more efficiently.

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.

The present study aims to verify whether there is a positive (negative) role being played by the institutional investors on the loss-making companies' performance.

The authors employ panel data regression and two-step system generalised method of moments (SYS-GMM) to test the above objective.

The empirical results clearly show that no positive relation is found between institutional investors and loss-making companies' performance.

The findings of the study might have significant implications for firms to improve the firms' operational performance [return on assets (ROA)]. Also, the firm's financial performance [return on equity (ROE)] could be improved by increasing profitability which will reflect in the share prices of the firms whereby the performance can build the investors' confidence over the firm. Market performance (Tobin's Q) could be increased by providing more attractive offers and discounts to customers to capture the business opportunities available in the market.

The overall findings might have for reaching implications in the manufacturing sector with regard to allowing (disallowing) institutional investors.

The results of the study may help both companies and institutional investors.

This is the maiden attempt to study whether loss-making companies could be positively (negatively) impacted by the arrival of sophisticated institutional investors [foreign institutional investors (FIIs) and domestic institutional investors (DIIs)]. Further, this study is largely different from previous studies in terms of using new variables which are related to firm characteristics and valuation multiples. Further, seeing if the institutional investors tend to enhance the firm performance is curious.

This study intends to explore the relationship between digital finance and the vertical specialization of firms. The following questions are discussed: (1) As a representative new financial development model, what is the role of digital finance in the vertical specialization of firms? (2) If digital finance improves the level of vertical specialization of firms, what is the mechanism behind such improvement? (3) How does digital finance impact the vertical specialization of firms in different regions, industries, and firms?

A two-way fixed-effect model of panel data is proposed to verify the relationship between digital finance and the vertical specialization of firms. This model is constructed by matching the city-level data of digital finance with the data of China's A-share listed companies from 2011 to 2018. Meanwhile, the instrumental variable (IV) method and difference-in-difference (DID) method are adopted to deal with the endogeneity problem of the model.

The authors' study finds that digital finance has significantly improved the level of vertical specialization of firms. The result is robust under the endogeneity consideration and a series of robustness tests. After the dimensionality of the index is reduced, the depth of digital finance usage is more conducive to the improvement of the vertical specialization of firms compared with the width of digital finance coverage and the level of financial digitization. Digital finance mainly improves the level of vertical specialization of firms by reducing transaction costs and increasing the market thickness of the intermediate products. Moreover, digital finance has certain heterogeneity in promoting the vertical specialization of firms, an effect that is more significant in the eastern region, manufacturing industry and state-owned enterprises (SOEs).

The first limitation is the mechanism test. This research only analyzes the mechanism from transaction cost and the market thickness of the intermediate products. With the rapid development of information technology, digital finance will be further integrated into people's production and life. There will then be more mechanisms that should be explored between digital finance and the vertical specialization of firms. Another limitation is the data sample of this paper. The conclusions of this research are based only on the data of listed companies. However, in the authors' opinion, the specialization level of small and medium-sized enterprise (SMEs) should be higher. Therefore, the conclusions of this work are underestimated, which can be considered as the lower limit of digital finance for enterprise specialization.

As a favorable financing channel to supplement traditional financial service functions, digital finance plays a critical role in the operating efficiency of enterprises and the effective allocation of macro resources. The authors' research shows that digital finance has significantly improved the vertical specialization of firms. This conclusion provides guides to improve the production efficiency of enterprises and the quality of economic development.

This paper has three main contributions. (1) The relationship between financial development and the vertical specialization of firms is innovatively discussed from the perspective of digital finance, which implies that digital finance can effectively promote the level of vertical specialization of firms. (2) This paper provides new perspectives and ideas to reveal the impact mechanism of digital finance on the real economy by systematically analyzing the mechanism of digital finance on the vertical specialization of firms from the perspectives of transaction costs and financing constraints. (3) The regional differences in the development of digital finance, industry differences in the vertical specialization of firms and differences in the nature of enterprise property rights are all under consideration, which improves the effectiveness and pertinence of digital finance in promoting the vertical specialization of firms.

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.