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To address challenges such as inadequate funding and inefficiency in public infrastructure construction, PPPs have gained significant global traction. This study aims to comprehensively assess the impacts and mechanisms of PPPs on the SDI and to provide rational policy recommendations based on the findings.

We collated a dataset from 30 Chinese provinces covering the years 2005–2020 as our research sample. The study’s hypotheses are tested using a double fixed-effects model, a chained mediated-effects model and a multidimensional heterogeneity analysis.

Our findings indicate that PPPs have a facilitating effect on SDI in general. This boost usually lags behind policy implementation and is cyclical in the time dimension. In the spatial dimension, PPPs contribute significantly to SDI in the eastern and western regions, but not in the central region. From the perspective of the dynamics of economic, social and industrial development, PPPs in economically backward areas are difficult to promote SDI, promote it the most in economically medium regions and are slightly less in economically developed regions than in medium regions. This promotion effect has an inverted U-shaped relationship with social development and diminishes with industrial structure upgrading. Finally, due to the negative relationship between PPPs and social development and between social development and SDI, PPPs are shown to contribute to SDI and are identified as critical paths. However, PPPs suppress SDI by inhibiting economic and industrial development.

This study makes three novel contributions to the existing body of knowledge: (1) we innovatively introduce the United Nations Sustainable Development Goals (SDGs) into the field of infrastructure research, offering fresh perspectives on SDI enhancement; (2) revealing the mechanisms by which PPPs affect SDI through the three dimensions of economic, social and industrial development enabling policymakers to better understand and optimize resource allocation and improve planning, design and management of PPP projects for sustainable infrastructure and (3) we assess the spatiotemporal variances of PPPs’ effects on SDI and the diversity across regions at different social, economic and industrial structures developmental stages, offering critical insights to global decision-makers to devise tailored policy measures.

The purpose of this paper is to develop a model to analyze the role of exchange rate appreciation expectation in trade invoicing from the perspective of importers, then empirically analyze it using Japanese export data.

Constructing a theoretical model of importer behavior by analyzing the importer's utility function under an assumption such as “menu cost”, then using econometric method to justify the theoretical model's finding.

It was found that under the assumption of “menu cost”, risk neutrality and price rigidity, there are three directions of appreciation expectation's effect: increasing, unchanged and decreasing theoretically; but under common condition, only a large appreciation expectation will cause an importer to reduce the use of exporter's currency, and the role is constricted by exporters' bargaining capacity. The empirical results of Yen's use in Japan's exports justifies the model's conclusion and shows that commercial pressure and political events are the most important signals to form large appreciation expectation.

This paper has important policy implications for Renminbi (RMB)'s exchange rate policy under the context of RMB internationalization, in order to promote RMB's use in exports; China should control the large appreciation expectation of RMB and the best way is to rigorously tackle trade deficit with US and European countries, and to eliminate the explicit appreciation signal.

The paper analyzes the role of exchange rate appreciation in trade invoicing theoretically and empirically for the first time; and reasonably explains the development of currency invoicing in Japanese exports and contemporary Chinese exports, as well as having important policy implications for Chinese exchange rate policy.

The purpose of this paper is to analyze the “following” behavior of six currencies in East Asia to RMB before and after the “financial crisis”.

Using foreign exchange spot rate data from 2005 to 2013, the authors investigate the dynamic relationship of RMB and six East Asia currencies with method of DCC-GARCH and quantile regression.

The authors get such conclusions: first, most currencies indeed “follow” RMB in whole sample period but the correlation is “time-varying”; second, the degree of co-movement increased as a whole, which reflects that the influence of China in East Asia rose continuously; third, the East Asian currencies behaved differently before the crisis, but reveal some similarities after the crisis, and prefer to “follow” when RMB depreciates and reluctant to follow when RMB appreciates at a comparatively large degree. The authors argue that it may be related to the different macroeconomic environment faced by East Asia region before and after the crisis, the rising economic influence of China and the development of RMB internationalization’s practice.

The effort could strength the understanding to the “following” behavior of East Asia currencies to RMB, the authors also point out that RMB has been as regional currency anchor, but the role of anchor is unstable, and is affected by international economic circumstance, China should adapt some methods to strength RMB’s influence to East Asia currency.

The purpose of this paper is to identify most favorable (or quasi-preferred) industry characteristics of remanufacturing industry and most favorable (or quasi-preferred) industry factors which have an effect on these characteristics so as to improve these factors.

Grey system theory has prominent advantage of using few data and uncertainty information to analyze many factors. Therefore, it is more suited for system analysis than traditional statistical analysis methods like regression analysis, variance analysis and principal component analysis, which require massive data, certain probability distribution in the data and few variant factors. So in this paper, grey incidence analysis method, which is an important part of grey system theory, is used to identify industry characteristics and key industry factor of remanufacturing industry in China and then put forward appropriate industrial policies and countermeasures to improve these industry factors.

According to the results of this study, it reveals that there are no most favorable industry characteristics and no most favorable industry factors in remanufacturing industry of China. “Annual sale of remanufacturing industry” is identified as quasi-preferred industry characteristic, and “total number of employees with master degree or above in remanufacturing enterprise” is identified as the quasi-preferred industry factor. “Total building area of remanufacturing enterprise” is referred as the most unfavorable industry factors.

Judging from the findings of this study, four practical implications are summarized as follows: “annual sale of remanufacturing industry” should be given great importance because it is a quasi-preferred industry characteristic. “Total number of employees with master degree or above in remanufacturing enterprise” and “total number of research institution and university participated in remanufacturing” should be further strengthened by establishing an industry-university-research institute collaboration network, due to the fact that they are the top two quasi-preferred industry factors. “Total investment of remanufacturing industry” and “total annual R&D expenditures” have not played their due role in improving remanufacturing industry, so they should be moderately controlled so as to reduce waste of investment. “Total building area of remanufacturing enterprise” must be strictly controlled because of its little impact on remanufacturing industry.

In this research, grey incidence analysis is applied to identify key industry factors of remanufacturing industry for the first time. It helps in finding industry factors which are in urgent need of improvement and assists in making appropriate industrial policies and countermeasures to improve them by studying relationships between industry characteristic and industry factors.

The purpose of this study is to investigate the effects of capital market liberalization on audit reporting and pricing. The authors use the announcement of the Shanghai-Hong Kong Stock Connect program in China as a shock to capital market liberalization.

The authors use the difference-in-differences method to study the difference in changes in the frequency of modified audit opinions and audit fees between the treatment group and the control group.

This study finds that capital market liberalization increases reputational and litigation risks for auditors and leads to more conservative audit reports. In addition, capital market liberalization stimulates the management of eligible firms to improve the information environment, helps to reduce information asymmetry and decreases audit fees. Specifically, the authors identify the channels of active foreign institutional investors as a new governance mechanism through which capital market liberalization impacts eligible firm and auditor decisions.

This study complements the literature by showing that capital market liberalization may bring a new and strong governance mechanism for eligible firms and auditors.

This study may provide new references for active foreign institutional shareholders as a new and strong governance mechanism in weak institutional regimes such as China, auditors’ optimization decisions when litigation risks increase and management’s improvements in the information environment under the monitoring of foreign institutional shareholders.

Overall, this study contributes to the literature by showing that capital market liberalization can bring a new governance mechanism for the management of eligible firms and auditors in a weak institutional environment. Foreign institutional shareholders may be superior to the domestic market forces and other corporate governance in the role of monitoring the management of eligible firms and auditors.

While performance demands in the natural world are varied, graded lattice structures reveal distinctive mechanical properties with tremendous engineering application potential. For biomechanical functions where mechanical qualities are required from supporting under external loading and permeability is crucial which affects bone tissue engineering, the geometric design in lattice structure for bone scaffolds in loading-bearing applications is necessary. However, when tweaking structural traits, these two factors frequently clash. For graded lattice structures, this study aims to develop a design-optimization strategy to attain improved attributes across different domains.

To handle diverse stress states, parametric modeling is used to produce strut-based lattice structures with spatially varied densities. The tailored initial gradients in lattice structure are subject to automatic property evaluation procedure that hinges on finite element method and computational fluid dynamics simulations. The geometric parameters of lattice structures with numerous objectives are then optimized using an iterative optimization process based on a non-dominated genetic algorithm.

The initial stress-based design of graded lattice structure with spatially variable densities is generated based on the stress conditions. The results from subsequent dual-objective optimization show a series of topologies with gradually improved trade-offs between mechanical properties and permeability.

In this study, a novel structural design-optimization methodology is proposed for mathematically optimizing strut-based graded lattice structures to achieve enhanced performance in multiple domains.

The purpose of this paper is to establish a dynamic analysis model of composite cylindrical roller bearings, investigate the effects of different working conditions on the kinematic characteristics of composite bearings and compare the differences between them and solid roller bearings.

This paper establishes a dynamic analysis model for composite cylindrical roller bearings and proves the correctness of the established model by establishing dynamic vibration experiments and contact theory for composite roller bearings. Comparative analysis was conducted on the effects of coupling changes in rotational speed, load, number of rollers and filling ratio on parameters such as bearing static stiffness, contact stress and vibration acceleration.

The composite roller can enhance the bearing’s operational stability and minimize contact stress, but that a higher filling ratio is going to increase the bearing’s stiffness. The acceleration degree of bearing vibration, the load on the outer raceway nodes and the bearing stability all decrease as inner ring speed rises.

A dynamic calculation model of composite cylindrical roller bearings is established, and the influence of multiparameter coupling changes on bearing vibration and contact is studied, which lays a foundation for the structural improvement of the bearings.

Student engagement has become increasingly significant in sustainability education for engineers because it enables future engineers to develop competencies, knowledge and values relevant to acting for sustainability. Therefore, this paper aims to examine characteristics of student engineer engagement with sustainability and to discuss the meanings of this concept.

To build a more holistic picture of student engineer engagement with sustainability, this study followed a literature review approach to search, screen and appraise relevant journal articles on this topic. As a result of this research, 30 articles were identified as eligible.

Based on the theoretical framework for student engagement with sustainability, newly synthesized here, and the content analysis of the 30 papers included in this study, four patterns of engagement were identified: intrapersonal engagement, inter-relational engagement, engagement as connection and disconnection and situated engagement.

This review provides practical recommendations about how to support the engagement of student engineers with sustainability at the levels of the individual, staff, educational programmes and associated curricula. Future research directions are also discussed.

This study contributes a theoretical framework synthesizing student engagement theory with sustainability education. It also describes current characteristics of student engineers’ engagement with sustainability.

Given that Chinese brands and products are widespread in the global market, this paper aims to examine the effect of Chinese brand origin salience (vs not) on brand evaluations by increasing global identity perceptions, and figuring out the moderating role of uncertainty avoidance.

Three experiments were conducted in different product categories to test the effect of Chinese brand origin salience. Study 1 and Study 2 collected data from different countries (i.e. Japan and the USA) with varying levels of uncertainty avoidance. In Study 3, the data were collected from the single-country sample, including participants from cultural backgrounds with high (Asian Americans) and low (Caucasian Americans) uncertainty avoidance.

Chinese brand origin salience positively influences brand evaluations via increased global identity perceptions. In addition, uncertainty avoidance plays a moderating role in the process. Specifically, the favorable effect of Chinese brand origin salience on brand evaluations will be attenuated among consumers with high (vs low) uncertainty avoidance.

This paper demonstrates that Chinese brand origin salience can enhance brand evaluations beyond prior work focusing on the negative stereotypes of Chinese brands and their imitation of Western brands. Importantly, Chinese brands have become an important part of the global community as Chinese brand origin salience can evoke consumers’ global identity.

This research paper aims to establish a comprehensive framework for the barriers to CER in the construction industry, assesses the barriers' relative degrees of hindrance and causal mechanisms.

Firstly, 26 carbon emission reduction (CER) barriers in the construction industry were identified based on a systematic literature review (SLR) and categorized into five dimensions: policy, economy, society, technology and organization (PEST + O model). Secondly, the Best–Worst Method (BWM) was used to clarify the degrees of hindrance of the CER barriers. Then, the Grey-Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL) was used to visualize the directional cause–result relationship network among prominent barriers. Finally, the Boston matrix model was used to propose differentiated strategies to address CER barriers in the construction industry.

The calculated centrality and causality of the prominent barriers indicated that the lack of relevant legal policies and normative guidelines, the poor binding force and enforcement of existing relevant policies, the lack of effective economic subsidies and incentives and the difficulty in the operation, transformation and upgrading of existing construction CER are the key barriers that CER needs to address first in the construction industry. Considering the order of priority and the optimal path, differentiated countermeasures are proposed to address key, driving, independent and effect barriers.

This study develops a BWM–Grey-DEMATEL integrated multi-criteria decision-making model. An innovative C-shaped strategic map for addressing CER barriers in the construction industry is proposed by integrating the dual dimensions of time and space. This will guide practitioners, policymakers and decision-makers in developing CER strategies.