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This study aims to determine how and through what mechanisms the outward foreign direct investment (OFDI) promotion effect of the Belt and Road initiative (BRI-OFDI) affects domestic investment. It is motivated by the context that China is fostering a new development pattern, as well as by the impetus from the Belt and Road initiative for the new pattern.

Drawing on data of Chinese-listed companies, this study uses a difference-in-difference method to explore the effect of the BRI-OFDI on domestic investment and a mediation model to illustrate the mechanisms.

The BRI-OFDI has a significantly positive effect on domestic investment, meaning that the Belt and Road initiative's OFDI promotion effect crowds in domestic investment. The results are heterogeneous: the crowding-in effect mainly exists in non-state-owned and technology-intensive enterprises, while a crowding-out effect is seen in state-owned and labor-intensive enterprises. The easing of corporate financing constraints and the expansion of market demand are two important mechanisms.

This study uses the Belt and Road initiative as an exogenous shock to investigate the impact of the initiative-induced OFDI promotion effect on domestic investment. It addresses the potential endogeneity issue confronting the studies on the relationship between OFDI and domestic investment in the literature. The authors focus on the possible spillover effects of the Belt and Road initiative discussing the impact of the BRI-OFDI on domestic investment from the micro-firm perspective. It offers a new perspective to objectively assess the initiative's policy effect.

Given that the current sustainability assessment in higher education institutions primarily relies on qualitative methods with relatively limited quantitative tools, the purpose of this study is to design a tool that could be used to comprehensively assess the overall state of higher education institutions’ sustainability.

The authors based the “Model to Assess the Sustainability of Higher Education Institutions” on the Triple Bottom Line (TBL) framework of economic, environmental and social factors, and established its primary dimensions as educational level, research capacity, community outreach, campus operations, campus experience and assessment reports. They designed the College Organisational Sustainability Scale (CO-SS) based on this research model, drawing their inspiration from the qualitative research tool, the Sustainability Assessment Questionnaire, and taking the following validation steps: expert review (n = 10), pilot testing (n = 150) and formal experiments (n = 1108). These steps were taken to optimise the scale items, test the model’s validity and assess its reliability.

After undergoing rigorous scientific validation, CO-SS was unequivocally confirmed as an effective and reliable tool, demonstrating its accurate reflection of the level of sustainability in higher education institutions.

The authors took an industry-specific approach by relying on the TBL and the Sustainability Assessment Questionnaire to construct and validate the CO-SS. Furthermore, the CO-SS has the potential to evolve into a self-assessment tool for higher education institutions, and a reliable foundation for data-driven decision-making in the realm of organisational sustainability at universities.

This paper aims to present an associated methodology to evaluate the initial stress of coal-rock masses in steeply inclined coal seams.

On the basis of the real-time monitoring data in the field, the corresponding analytical analysis is carried out in consideration of the characteristics of topography and geology, so as to deduce the value of the initial stress in the study area and also give the analytical model of the initial stress field.

The authors identified feasibility of the initial stress level of coal-rock masses in steeply inclined coal seams, and revealed that exact acquisition on the displacement of surrounding rock was feasible to analyze the initial stress level of coal-rock masses by the back analytical method in the steeply inclined coal seams as a two-dimensional plane problem.

The calculation results including vertical stress, minimum horizontal principal stress and shearing stress were 7.057, 8.085 and 0.057 MPa, respectively. The KJ743 coal mine initial stress monitoring system was used to collect real-time initial stress data, which were used to check the accuracy of the analytical back results. The value of the vertical stress varied from 6.8 to 7.0 MPa, which is slightly smaller than the result of the back calculation. The minimum principal horizontal stress varied from 7.6 to 8.4 MPa, which is similar to the result of the back calculation.

The purpose of this study is to analyse the role of the clean development mechanism (CDM) established by the Kyoto Protocol in channelling foreign technology to China. Appraising the experience of CDM remains of key importance when drawing lessons for the post-2012 climate regime.

Descriptive analysis of the sources and the determinants of foreign technology transfer based on the examination of 1,355 registered projects. Econometric analysis of the probability of having a foreign supplier of technology in any project.

The prominence of German firms as technology providers and the absence of a strong relationship between technology suppliers and credit buyers. The econometric analysis finds that project size and cost, project location, credit buyers’ and consultants’ characteristics, as well as technology diffusion are all relevant factors in determining the probability of having a foreign supplier of technology.

China is a particularly interesting case for analysing technology transfer in CDM projects since, after a slow start, the country has become the largest and most dynamic CDM recipient worldwide. Furthermore, the analysis of CDM projects may offer some insights into the complex web of technological links between Chinese and foreign firms.

The transfer of emission-saving technologies to developing countries is expected to play a major role in addressing environmental problems worldwide.

This study analyses the sources and determinants of international technology transfer in CDM projects in China, and offers some insights into how the characteristics of the major players and the links between them affect this phenomenon.

The purpose of this study is to establish an assembly accuracy analysis model of deployable arms based on Jacobian–Torsor theory to improve the assembly accuracy. Spacecraft deployable arm is one of the core components of spacecraft. Reducing the errors in assembly process is the main method to improve the assembly accuracy of spacecraft deployable arms.

First, the influence of composite connecting rod, root joint and arm joint on assembly accuracy in the tandem assembly process is analyzed to propose the assembly accuracy analysis model. Second, a non-tandem assembly process of “two joints fixed-composite rod installed-flange gasket compensated” is proposed and analyzed to improve the assembly accuracy of deployable arms. Finally, the feasibility of non-tandem assembly process strategy is verified by assembly experiment.

The experiential results show that the assembly errors are reduced compared with the tandem assembly process. The errors on axes x, y and z directions decreased from 14.1009 mm, 14.2424 mm and 0.8414 mm to 0.922 mm, 0.671 mm and 0.2393 mm, respectively. The errors round axes x and y directions also decreased from 0.0050° and 0.0053° to 0.00292° and 0.00251°, respectively.

This paper presents an assembly accuracy analysis model of deployable arms and applies the model to calculate assembly errors in tandem assembly process. In addition, a non-tandem assembly process is proposed based on the model. The experimental results show that the non-tandem assembly process can improve the assembly accuracy of deployable arms.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

This study aims to explore the potential impact of country-level governance in corporate financing structures.

A two-step system generalized method of moment was used due to the endogeneity issue. The whole sample comprises 3,761 firms in five economies – China, India, Pakistan, Singapore and South Korea – from 2007 to 2016.

The results indicate that the debt option for financing is not favorable under governments with an adequate governance arrangement. However, there is a direct and significant link between country governance and equity financing because in adequate governance arrangements, the possibilities of information asymmetry are minimal and businesses consider equity a more appropriate and safer financing instrument. In contrast, firms prefer to trade-credit financing in poor governance economies, which confirms an adverse link between trade credit and adequate governance.

The country’s governance should be considered a sensitive matter when deciding about corporate financing.

This arrangement of variables has not been previously analyzed in the literature, suggesting the study’s novelty.

This study aims to investigate the effect of immigration on housing prices in Australia both at the national and regional levels.

Data for eight Australian states on a quarterly basis from 2004–2017 is used. To study the possible dynamic and endogenous relationship between housing prices and immigration, a panel vector autoregressive error correction model (PVECM) is adopted.

Analysis of the results indicates that in the short run immigration positively and significantly affects housing prices, whereas in the long run no significant relationship was observed between the two variables. From the regional breakdown and analysis, it is discerned that in some states there is a significant and positive effect of immigration on residential real estate prices in the long run. Causality analysis confirms that the direction of causation is from immigration to housing prices.

The study illustrates that immigration and interstate migration, as well as high salaries, have been causing a rise in housing demand and subsequently housing prices. To monitor exceedingly high housing prices, local authorities should be controlling migration and salary levels.

Past research studies had highlighted the importance of native interstate migration in explaining the nexus between immigration – housing prices. In this study, it has been empirically verified how immigration has been affecting the locational decisions of natives and subsequently how this has been affecting housing prices.

This study aims to streamline and enhance the assembly defect inspection process in diesel engine production. Traditional manual inspection methods are labor-intensive and time-consuming because of the complex structures of the engines and the noisy workshop environment. This study’s robotic system aims to alleviate these challenges by automating the inspection process and enabling easy remote inspection, thereby freeing workers from heavy fieldwork.

This study’s system uses a robotic arm to traverse and capture images of key components of the engine. This study uses anomaly detection algorithms to automatically identify defects in the captured images. Additionally, this system is enhanced by digital twin technology, which provides inspectors with various tools to designate components of interest in the engine and assist in defect checking and annotation. This integration facilitates smooth transitions from manual to automatic inspection within a short period.

Through evaluations and user studies conducted over a relatively long period, the authors found that the system accelerates and improves the accuracy of engine inspections. The results indicate that the system significantly enhances the efficiency of production processes for manufacturers.

The system represents a novel approach to engine inspection, leveraging robotic technology and digital twin enhancements to address the limitations of traditional manual inspection methods. By automating and enhancing the inspection process, the system offers manufacturers the opportunity to improve production efficiency and ensure the quality of diesel engines.

When dealing with simple functional functions, traditional reliability calculation methods, such as the linear second-order moment and quadratic second ordered moment, Monte Carlo simulation method, are powerful. However, when the functional function of the structure shows strong nonlinearity or even implicit, traditional methods often fail to meet the actual needs of engineering in terms of calculation accuracy or efficiency.

To improve the reliability analysis efficiency and calculation accuracy of complex structures, the reliability analysis methods based on parametric and semi-parametric models are analyzed.

This paper proposes a reliability method that combines the Kriging model and the importance sampling method to improve the calculation efficiency of traditional reliability analysis methods.

This method uses an active learning function and introduces an importance sampling method to screen sample points and shift the center of gravity, thereby reducing the sample size and the amount of calculation.