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Despite the growing body of empirical research on leader anger expressions, the issue of how and when leader anger expressions shape newcomers’ proactive career behavior and work alienation in the construction industry has been largely overlooked. Building upon social information processing theory, this research identifies newcomers’ organization-based self-esteem as a mediator, and suggests that newcomers’ performance goal orientation could moderate the relationship.

A questionnaire study was conducted on the construction industry in China, and the PROCESS program developed by Hayes was used to test the hypothetical model with 215 valid cases.

The results suggest that leader anger expressions are negatively associated with newcomers’ organization-based self-esteem, and organization-based self-esteem mediated the link between leader anger expressions and newcomers’ proactive career behavior and work alienation. Furthermore, the newcomers’ performance goal orientation moderates the negative impact of leader anger expressions on newcomers’ organization-based self-esteem.

Due to the cross-sectional nature of this study, causal implications are difficult to draw. Moreover, all data we received was based on participant self-reports, which may raise concerns about common method variance.

In this paper, we contribute to a deeper understanding of the mediating mechanisms and boundary conditions by which leader anger expressions influence newcomers’ proactive career behavior and work alienation from social information processing perspective, in addition to providing valuable insights for management of newcomers in the construction industry.

Despite the increasing importance of boundary-spanning behaviors in construction projects, the research on how leader anger expressions impact employees’ boundary-spanning behaviors remains unclear. This study aims to investigate the impact of leader anger expressions on employees’ boundary-spanning behaviors in construction projects while exploring the mediating effect of work hope and the moderating effect of power distance orientation through the lens of social information processing theory.

The empirical data were collected from a questionnaire survey of 235 employees in construction projects, and the hypotheses were tested using the PROCESS program developed by Hayes.

This study demonstrated that leader anger expressions negatively affect employees’ work hope, and work hope mediates the relationship between leader anger expressions and employees’ boundary-spanning behaviors. Besides, the stronger the employees’ power distance orientation, the stronger the negative relationship between leader anger expressions and employees’ work hope, and the above mediating effect was also stronger.

The use of cross-sectional data was unable to entirely infer a causal relationship between leader anger expressions and employees’ boundary-spanning behaviors. Additionally, the reliance on self-reported data inevitably introduced some common method bias.

Applying social information processing theory, this paper enriches the discourse on factors influencing employees’ boundary-spanning behaviors in construction projects. It also offers valuable insights for leaders in construction projects to manage their teams effectively.

This paper aims to explore the influencing factors of public perceived efficacy of emergency infrastructure projects based on the triadic interactive determinism, and analyze the relationship among these factors.

Based on the triadic interactive determinism, we explored the factors influencing public perceived efficacy of emergency infrastructure project and empirically verified the relationship among these factors and perceived efficacy by using data drawn from a questionnaire survey of 491 residents near Leishenshan Hospital, Jiangxia District, Wuhan, China.

Prior experience, emotional response, personal expectation, public trust, context message and interactivity level, namely behavior, individual and environment, affect the perceived efficacy of public emergency infrastructure projects.

The results offer an insight into public perceived efficacy of emergency infrastructure project from the perspective of antecedents in a triadic reciprocal determinism, which provides a reference basis for the sustainable development of the emergency infrastructure projects. This study also suggests valuable practical implications to government departments to improve the quality of administrative decision-making effectively.

Although existing studies have found some influencing factors of public perceived efficacy in general infrastructure, there is still a lack of systematic carding and quantitative description of influencing factors of public perceived efficacy of emergency infrastructure projects. This study bridges this gap by exploring the determinants and their influencing relationship of public perceived efficacy especially for emergency infrastructure projects.

The manufacturing industry and the producer service industry have a high degree of industrial correlation, and their integration will cause changes in the complex industrial network topology, which is an important reason for the synergistic effect. This paper describes the topology of industrial systems using complex network theory; further, it discusses how to identify the criticality and importance of industrial nodes, and whether node characteristics cause synergistic effects.

Based on the input-output data of China in 2007, 2012 and 2017, this paper constructs the industrial complex network of 30 Chinese provinces and cities, and measures the regional network characteristics of the manufacturing industry. The fixed-effect panel regression model is adopted to test the influence of agglomeration degree and centrality on synergies, and its adjustment mechanism is explored.

The degree of network agglomeration in the manufacturing industry exerts a negative impact on the synergistic effect, while the centrality of the network exerts a significant promoting effect on the synergistic effect. The results of adjustment mechanism test show that enhancing the autonomous controllable ability of the regional industrial chain in the manufacturing industry can effectively reduce the effect of network characteristics on the synergistic effect.

Based on input-output technology, this paper constructs a complex industrial network model, however, only basic flow data are used. Considerable in-depth and detailed research on the economic and technological connections within the industry should be conducted in the future. The selection of the evaluation index of the importance of industrial nodes also needs to be further considered. For historical reasons, it is also difficult to obtain and process data when carrying out quantitative analysis; therefore, it is necessary to make further attempts from the data source and the expression form of evaluation indicators.

In a practical sense this has certain reference value for the formulation of manufacturing industrial policies the optimization of regional industrial layout and the improvement of the industrial development level. It is necessary to formulate targeted and specialized industrial development strategies according to the characteristics of the manufacturing industry appropriately regulate the autonomous controllable ability of the industrial chain and avoid to limit the development of industries which is in turn limited by regional resources. Industry competition and market congestion need to be reduced industry exchanges outside the region encouraged the industrial layout optimized and the construction of a modern industrial system accelerated.

The above research results hold certain reference importance for policy formulation related to the manufacturing industry, regional industrial layout optimization and industrial development level improvement. Targeted specialized industrial development strategies need to be formulated according to the characteristics of the manufacturing industry; the autonomous controllability of the industrial chain needs to be appropriately regulated; limitation of regional resources needs to be avoided as this restricts industrial development; and industry competition and market congestion need to be reduced. Agglomeration of production factors and optimization of resource allocation is an important part of a beneficial regional economic development strategy, and it is also an inevitable choice for industrialization to develop to a certain stage under the condition of a market economy. In alignment with the research conclusions, effective suggestions can be put forward for the current major industrial policies. In the process of promoting the development of the manufacturing industry, it is necessary for regional governments to carry out unified planning and guidance on the spatial layout of each manufacturing subsector. Regional governments need to effectively allocate inter-industry resources, better share economies of scale, constantly enhance the competitive advantages and competitiveness of development zones and new districts and promote the coordinated agglomeration and development of related industries with input industries. Industrial exchanges outside the region should be encouraged, the industrial layout should be optimized and the construction of a modern industrial system should be accelerated.

Complex network theory is introduced to study the industrial synergy effect. A complex industrial network of China's 30 regions is built and key network nodes are measured. Based on the dimensionality of the “industrial node – industrial chain – industrial complex network”, the research path of industrial complex networks is improved.

In public health emergencies, seeking confirmed cases’ activity trajectory information (CCATI) is crucial to the public’s efforts to combat the epidemic. The public can stabilize their sentiments and mitigate the risk of cross-infection by obtaining CCATI. We investigated the factors influencing users' intentions to seek CCATI to enhance the government’s risk communication capabilities and improve information platform services.

We analyzed how information ecological factors affect the intention to seek CCATI through perceived value. Data was collected from 429 Chinese citizens during the fourth wave of the coronavirus disease 2019 (COVID-19) pandemic. We used the structural equation model technology and bootstrap mediation effect test to examine the model.

Information understandability, information relevance, perceived severity and perceived vulnerability directly and positively affect the intention of seeking CCATI. While, the above relationships are also partially mediated by emotional value and functional value. Social support directly and negatively affects the intention of seeking CCATI, while the relationship is also partially mediated by emotional value and functional value. Curiosity directly and positively affects the intention of seeking CCATI, while the relationship is also partially mediated by emotional value. The relationship between the quality of the search service and the intention of seeking CCATI is not significant, instead, it is fully mediated by functional value. The influence effect of information relevance on the intention of seeking CCATI is the greatest, followed by perceived vulnerability. The mediating effect of functional value is higher than emotional value.

The findings may help governments enhance their risk communication capabilities and improve epidemic prevention and control measures, enhancing the appeal of information platforms.

We focused on CCATI, an area with limited scholarly attention. We analyzed CCATI-seeking factors using an information ecology theory, introducing perceived value as a mediator, thus offering novel perspectives and models.

Doctor–medical institution collaboration (DMIC) services are an emerging service mode in focal online health communities (OHCs). This new service mode is anticipated to affect user satisfaction and doctors' engagement behaviors. However, whether and how DMIC occurs is still ambiguous because the topic is rarely examined. To bridge this gap, this study explores doctors' participation in DMIC services and its effects on their online performance, as well as its effect on patients' evaluation of them on OHC platforms.

The authors propose hypotheses based on structural holes theory. A unique dataset obtained from one of the most popular OHCs in China is used to test the hypotheses, and difference-in-differences estimation is adopted to test the causality of the relationship.

The results demonstrate that providing DMIC services improves doctors' online consultation performance and patients' evaluations of them but has no significant effect on doctors' knowledge-sharing performance on OHC platforms. Doctors' knowledge-sharing performance and consultation performance mediate the relationship between participation in DMIC services and patients' evaluation of doctors. Regarding doctors' participation in DMIC services, its impact on doctors' consultation performance and patients' evaluation of them is weaker for doctors with higher professional titles than for doctors with lower professional titles.

The findings clarify the value creation mechanisms of online collaboration between doctors and medical institutions and thereafter facilitate doctors' participation in DMIC services and enhance the sustainable development of OHCs.

While prior studies predominantly focus on the overall impact of digital transformation on environmental, social and governance (ESG) performance, this study employs dynamic capability theory to examine two different dimensions of digital transformation, namely digital transformation quantity and digital transformation structure, and how they influence the ESG performance of enterprises. The mediating roles of social attention and green innovation are investigated to further explore the underlying mechanisms.

The authors apply fixed effects models and empirically test the hypotheses using samples of Chinese A-share listed companies from 2011 to 2020. In addition, difference-in-differences and instrumental variable methods are used in the robustness test.

When digital transformation is categorized into quantity and structure, the impact mechanisms are found to be distinct. Externally, digital transformation quantity attracts social attention, aiding enterprises in evolutionary adaptability and acquiring resources to support ESG practices. Internally, digital transformation structure fosters green innovation, enabling enterprises to overcome technical obstacles and harness technology’s potential to enhance their ESG performance.

This study contributes to the current knowledge by differentiating digital transformation into quantity and structure, which helps to further explore the mechanism of digital transformation on ESG and address the research gap. Meanwhile, the concept of adaptability in the dynamic capability theory is employed to construct the model, offering a deeper perspective and expanding the theory. This nuanced investigation of the mediating effects of social attention and green innovation elucidates how different dimensions of digital transformation contribute to the development and utilization of dynamic capabilities, thereby enhancing enterprises’ ESG performance.

The purpose of this study is to make property price forecasts for the Chinese housing market that has grown rapidly in the last 10 years, which is an important concern for both government and investors.

This study examines Gaussian process regressions with different kernels and basis functions for monthly pre-owned housing price index estimates for ten major Chinese cities from March 2012 to May 2020. The authors do this by using Bayesian optimizations and cross-validation.

The ten price indices from June 2019 to May 2020 are accurately predicted out-of-sample by the established models, which have relative root mean square errors ranging from 0.0458% to 0.3035% and correlation coefficients ranging from 93.9160% to 99.9653%.

The results might be applied separately or in conjunction with other forecasts to develop hypotheses regarding the patterns in the pre-owned residential real estate price index and conduct further policy research.

This study aims to explore the spatial impact of an increase in the minimum wage on the labor productivity of star-rated hotels in China.

The impact is analyzed by using the dynamic spatial Durbin model.

The authors find a U-shaped link between the increase in minimum wage and labor productivity of star-rated hotels. The long-term impact of a minimum wage increase has a greater influence on labor productivity than its short-term effects. While there is no notable spatial spillover impact observed in the sample of 31 provinces in China, the authors do identify a spatial spillover effect of the minimum wage rises on the labor productivity of star-rated hotels in the central area. Furthermore, they observe heterogeneity across China. The eastern and western regions exhibit a U-shaped relationship, whereas the central region exhibits an inverted U-shaped relationship.

The findings of this study allow government agencies to get a more comprehensive comprehension of the actual consequences of minimum wage hikes on the tourism and hospitality sector, thereby establishing a solid basis for them to develop appropriate policies. Moreover, it offers a variety of suggestions aimed at enhancing the quality and efficiency of hotel management.

Research on the effects of minimum wage standards is scant in the hospitality industry. Based on human capital investment theory, this study examines the effect of the minimum wage standard hikes on labor productivity of star-rated hotels from the spatial perspective, filling the existing research gap.

This study aims to investigate the cause of high-order wheel polygonization in a plateau high-speed electric multiple unit (EMU) train.

A series of field tests were conducted to measure the vibration accelerations of the axle box and bogie when the wheels of the EMU train passed through tracks with normal rail roughness after re-profiling. Additionally, the dynamic characteristics of the track, wheelset and bogie were also measured. These measurements provided insights into the mechanisms that lead to wheel polygonization.

The results of the field tests indicate that wheel polygonal wear in the EMU train primarily exhibits 14–16 and 25–27 harmonic orders. The passing frequencies of wheel polygonization were approximately 283–323 Hz and 505–545 Hz, which closely match the dominated frequencies of axle box and bogie vibrations. These findings suggest that the fixed-frequency vibrations originate from the natural modes of the wheelset and bogie, which can be excited by wheel/rail irregularities.

The study provides novel insights into the mechanisms of high-order wheel polygonization in plateau high-speed EMU trains. Futher, the results indicate that operating the EMU train on mixed lines at variable speeds could potentially mitigate high-order polygonal wear, providing practical value for improving the safety, performance and maintenance efficiency of high-speed EMU trains.