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This paper employs nationwide, large-scale field survey data to provide the first empirical evidence on the impact of human educational capital on the acquisition of health entitlement among Chinese migrant workers. The findings of this study hold significant practical implications for the formulation of policies aimed at improving the health protection of migrant workers, as well as for socioeconomic policies during China's transitional period.

Using the IVProbit model, this research examines how human educational capital influences the attainment of health entitlement among migrant workers in China by analyzing the impact and mechanism of education on health entitlement. The study is based on the China Migrants Dynamic Survey (CMDS) data from 2018, which include 100,177 observations.

For migrant workers in China, higher levels of education have a significant positive effect on the acquisition of health entitlements, including medical insurance, health records and health education. The positive impact of human educational capital on health entitlements is more significant for non-provincial cities and young-generation migrant workers. The results also show that human educational capital can influence the acquisition of health entitlements through mediators such as financial status, social integration and health status.

This study represents the first empirical attempt to evaluate the influence of human educational capital on the access of migrant workers in China to health rights and interests. Additionally, the study develops a theoretical framework to examine how the impact of human educational capital varies across migrant workers with different characteristics and their access to health entitlements.

This paper aims to examine the different impacts of six variables on firm technological innovation performance in different high-tech industries in China. Through a comparative analysis of data about growth enterprises market board (GEM)-listed companies, this study attempts to get some conclusions, to help firms in different high-tech industries use resources more rationally and to improve technological innovation performance more effectively.

This paper constructs semi-parametric models based on the relevant data of GEM-listed companies during 2010 to 2015 for different high-tech industries. These models can ensure that the influencing factors of firm technological innovation performance are no longer restricted to a particular aspect but can provide a comprehensive comparative analysis of the effects of factors on firm technological innovation performance in different high-tech industries.

The empirical results show that R&D expenditures have a significant positive impact on firm technological innovation performance in most high-tech industries, but not in electronic and communication equipment manufacturing industry; R&D personnel investment and government subsidies have significant positive impacts on firm technological innovation performance in knowledge-oriented industries; technology diversity has a significant positive impact on firm technological innovation performance in technology-oriented industries; the proportion of exports shows an inverted U-shaped relationship with firm technological innovation performance in electronic and communication equipment manufacturing industry, while firm size shows an inverted U-shaped relationship with firm technological innovation performance in general equipment manufacturing industry; and the effect of semi-parametric model fit is superior to the general parameters model.

Drawing on the resource dependence perspective, this paper is the first to consider a comprehensive treatment of differential effects of internal resources (R&D personnel, R&D expenditure), external resources (government subsides) and firm characteristics (firm size, export ratio) on firm technological innovation performance in different high-tech industries in an emerging country, in particular in contrast to previous studies that have focused on a single industry or taken the type of industry as a control variable. In addition, most studies about the determinants of firm innovation performance are based on survey questionnaires, which may introduce large subjective errors. Setting the relationship between variables in advance may also introduce fit error when using a general-parameter model. Semi-parametric regression which is used in this paper is able to prevent this shortcoming effectively. When constructing a regression model, this can be exempted from the formal constraints, thus estimating data more accurately and ensuring superior fit.

We evaluated the best-available evidence for the effects of receiving business-as-usual or naturally delivered special education services in K-12 US schools. Our best-evidence synthesis of 44 empirical studies evaluated which outcome domains and disability types have been investigated and whether findings varied by the rigor of the study design and methods. Regression-based studies comparing students with educational disabilities (SWED) to students without disabilities (SWOD) yielded mostly negative associations of receiving special education with academic achievement, behavior, and long-term or other outcomes. In contrast, regression-based studies that contrasted SWED receiving special education to other SWED not receiving special education produced a pattern of estimates similar to quasi-experimental designs that contrast SWED to SWOD. The most rigorous designs utilized quasi-experimental methods that compared SWED receiving special education services with SWED not receiving special education services, and generally reported more positive than negative evidence of receiving special education services across most outcome domains. Future research that utilizes rigorous quasi-experimental methodology and appropriate comparison groups to investigate the effectiveness of special education is needed, particularly for nonachievement outcome domains.

Hazard warning schemes provide efficient hazard recognition and promote project safety. Nevertheless, these schemes perform poorly because the warning information is calibrated for individual characters and is not prioritized for the entire system. This study proposes a hazard warning scheme that prioritizes hazard characters from the inspection process based on the inspectors' experience.

First, hazard descriptions were decomposed into their characters, forming a double-layer network. Second, warning schemes based on cascading effects were proposed. Third, character-based warning schemes were simulated for various experiences.

The results show that when a specific hazard is detected, the degree centrality is the most effective parameter for prioritization, and hazard characters should be prioritized based on betweenness centrality for experienced inspectors, whereas degree centrality is preferred for novice inspectors.

The warning scheme theoretically supplements the information-processing theory in construction hazard warnings and provides a practical warning scheme with priority for the development of automated hazard navigation systems.

This study aims to explore the social networks and network interactions of bed-and-breakfast (B&B) entrepreneurs in rural China. In addition, it evaluates how such network interactions relate to rural resilience.

In-depth interviews were performed in two locations: Ningbo and Dujiangyan, China. Purposive sampling was combined with snowball sampling to select interviewees. The 154 interviews involved 29 B&B owners and relevant social actors. All codes and data were analyzed using the discourse analysis framework.

The B&B owners’ social networks were identified based on strategic goals, revealing a business operation network, business development network and business citizenship network. Challenges in seeking financial support for rural B&Bs during the pandemic were specified along with network interactions. The institutional adaptation approach was used to evaluate network interaction in rural B&B business. It was argued that other networks would react based on primary network members’ goal compatibility and the effectiveness of the primary network in addressing obstacles.

This study indicates that the rural B&B entrepreneurs’ interactions with various networks could influence on business resilience, community resilience as well as rural resilience.

By combining the institutional adaptation typology with social network theory, this study generates a new typology of network interactions for rural B&Bs. The typology helps to explain how and why B&B entrepreneurs make decisions and provides a broader scope of social networks involved in these business operations.

Thermal stress of the rotor in a squirrel cage induction motor is generated due to the temperature rise, and the structure of the rotor will be destroyed if the stress acted on the rotor exceeds its limits, so the thermal stress is also one of the main causes led to broken bar fault. The purpose of this paper is to report the thermal stress coupled analysis for the induction motor with healthy and faulty rotor, and to find the variation tendency of the temperature and thermal stress due to broken bars, and the part most likely to break in the rotor as a result of the thermal stress load are identified.

The steady temperature and thermal stress of the rotor in the case of the healthy and faulty conditions are calculated by finite element method, and the 3D model of the motor used in the experiments is established and the experimental results are presented for both healthy and faulty machines.

The influence of the broken bars fault on the motor thermal profile and thermal stress can be found, and it explains why the breaking point always appears in the joint of the bars and end rings.

The paper presents the 3D thermal stress coupled model and performance characteristics of induction motor with broken bars. The reasonable constraint is established according to the contact of components each other, and more reasonable fracture location is selected. The results obtained by the simulation model are in a good agreement with practical situation, because the effect of skewed rotor were taken into consideration in the process of simulation.

This paper aims to explore the interaction between investor attention and green security markets, including green bonds and stocks.

This study takes the Baidu index of “green finance” as the proxy for investor attention and constructs several generalized prediction error variance decomposition models to investigate the interdependence. It further analyzes the dynamic interaction between investor attention and the return and volatility of green security markets using the rolling time window.

The empirical analysis and robustness test results reveal that the spillovers between investor attention and the return and volatility of the green bond market are relatively stable. In contrast, the spillover level between investor attention and the green stock market displays significant time-varying and asymmetric effects. Moreover, the volatility spillover between investor attention and green securities is vulnerable to major financial events, while the return spillover is extremely sensitive to market performance.

The conclusion further expands the practical application and theoretical framework of behavioral finance in green finance and provides a new reference for investors and regulators. Besides, this study also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management in green securities.

The purpose of this paper is to investigate manufacturer encroachment and distributor encroachment in a three-echelon supply chain consisting of an upside manufacturer, an intermediate distributor and a downside retailer.

In this paper, the authors use the optimization theory to mathematize the proposed question and build a model. First, the authors consider sequential quantity decisions, where the encroacher decides on the direct selling quantity after determining the retailer's order quantity. Second, the authors relax this sequential decision process assumption by reconsidering a circumstance in which quantity decisions are decided simultaneously.

In contrast to previous studies, this study shows that in three-echelon supply chains, the upside firm is more likely to encroach compared with the downside firm. The “bright side” of encroachment exists for all players only when the encroachment cost is at a moderate level. However, in manufacturer encroachment under simultaneous quantity decisions, the “bright side” skips the distributor but benefits the retailer directly as the encroachment cost increases from zero to a certain level. The main reason lies in that the distributor loses its pricing power because the end-market has been disturbed by the simultaneous quantity decisions. A comparison of the results of sequential and simultaneous quantity decisions reveals the merit of simultaneous quantity decisions. The authors find that the intermediate role (the distributor in our model) in three-echelon supply chains may benefit more from simultaneous quantity decisions. That is, the distributor may achieve a better profit even in a market with intensified competition.

The findings of this paper contribute to the marketing science literature on encroachment. The majority of existing literature has focused on manufacturer encroachment in two-echelon supply chains. This paper innovatively investigates and compares manufacturer encroachment and distributor encroachment in a three-echelon supply chain.

The authors address a two-dimensional (both customer acquisition and retention) incentive in a decentralized service chain consisting of a risk-neutral brand and agent (or averse). 

The authors focus on the relationship between acquisition and retention, that is, retained customers (repeated purchases) are based on and come from the acquired (new) customers in the former period. The authors also design a two-period separate incentive on both dimensions.

The authors found that a targeted incentive strategy should be applied for achieving more revenue when the incentive intensities are relatively small. Otherwise, the brand needs to adjust the targeted incentive strategy into incentivizing the opposite dimension, particularly on acquisition. Under the optimal contract, the brand needs to be very careful with deciding the fixed part of the incentive salary and the incentive intensities on both dimensions. For example, the fixed salary initially decreases and then increases in the incentive intensities. For the optimal incentive policies, the brand should incentivize acquisition but outsource retention if the agent is risk-neutral. When the agent is becoming risk-averse, the brand should lower its incentive intensity as the risk degree and variances become larger. Interestingly, the brand may benefit from introducing risks.

The study contributes to the literature by considering the following points. First, the authors extend the principal-agent incentive model by considering two-period decisions of customer acquisition and retention. Second, based on the two-period principal-agent problem, the authors design separate incentive intensities on acquisition and retention, respectively. While, most of the literature focused on acquisition incentives. Third, different from other works focusing on either risk-neutral or risk-averse environments, the authors consider both and compare the cases of risk-neutral and risk-averse to analyze the impact of risk on the optimal decisions and the brand's expected profit.