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The purpose of this paper is to use social exchange theory (SET) to examine a model where supportive and unsupportive manager behaviors (SMB and UMB) interact to predict employees’ engagement, job satisfaction and turnover intention.

A cross-sectional online survey collected data from 252 UK-based employees of a global data management company.

Factor analysis confirmed manager behaviors to consist of two constructs: supportive and unsupportive behaviors. Structural equation modeling indicated SMB predicted job satisfaction and turnover intentions, but not engagement. Job satisfaction, but not engagement, mediated the SMB-turnover intention relationship. UMB only predicted job dissatisfaction. Neither job satisfaction nor engagement mediated the UMB-turnover intention relationship. UMB undermined the positive relationship between SMB and turnover intention.

The behaviors assessed can be integrated into various stages of a manager’s development process to serve as guidelines of good practice. Crucially, findings suggest managers can exhibit both supportive and unsupportive behaviors, and that consistency in behaviors is important. The study also provides evidence that supportive managers can help reduce turnover intention through job satisfaction.

SET was used as a framework for SMB, UMB and engagement. To the authors’ knowledge this is the first study to examine the interaction between SMB and UMB.

The patient-side manipulator (PSM) achieves high torque capability by combining harmonic servo system with high reduction ratio and low torque motor. However, high reduction ratio can increase inertia and decrease compliance of the manipulator. To enhance the backdrivability of the minimally invasive surgical robot, this paper aims to propose a resistance torque compensation algorithm.

A resistance torque compensation algorithm based on dynamics and Luenberger observer is proposed. The dynamics are established, considering joint flexibility and an improved Stribeck friction model. The dynamic parameters are experimentally identified by using the least squares method. With the advantages of clear structure, simple implementation and fast solution speed, the Luenberger observer is selected to estimate the unmeasured dynamic information of PSM and realize the resistance torque compensation.

For low-speed surgical robots, the centrifugal force term in the dynamic model can be simplified to reduce computational complexity. Joint flexibility and an improved Stribeck friction model can be considered to improve the accuracy of the dynamic model. Experiment results show that parameter identification and estimated results of the Luenberger observer are accurate. The backdrivability of the PSM is enhanced in ease and smoothness.

This algorithm provides potential application prospects for surgical robots to maintain high torque while remaining compliant. Meanwhile, the enhanced backdrivability of the manipulator helps to improve the safety of the preoperative manual adjustment.

Large-scale mobile radars are still erected manually by using lifting equipment, which often fails to meet the requirements on precision, quality and efficiency in the erecting process. This paper aims to introduce techniques for automatic assembly of large mobile radar antenna.

A large-scale metrology system for accurate identification of the positions and orientation of the radar antenna components is presented. A novel three-degree-of-freedom parallel mechanism is designed to realize orientation adjustment of three axes synchronous, and, thus guarantees the efficiency and accuracy of positioning process.

The system described in this paper is practicable in outdoor environment and provides a holistic solution that gives full consideration of the operation conditions and the environmental influences. In performance evaluation tests, the measured absolute accuracy is less than ±1 mm and repeatability is less than ±0.5 mm in the positioning task for 10 × 3 m large antenna.

This paper presents a new concept of an automatic assembly technology for the large radar antenna application.

Supply chain integration (SCI) is one of the most distinctive dimensions in achieving long‐term competitive advantage in the business world. Although considerable state‐of‐the‐art studies regarding the SCI concept and its dimensions have been conducted, empirical research by using the data from agri‐food firms in China to examine the relationship between SCI and firm performance attract little attention. The purpose of this paper is to investigate the effects of SCI on firm performance in pork supply chains in China.

The study follows a causal research approach and survey methodology to collect data from 229 pork processors. The SCI‐firm performance link is examined in two relationships: the pork processors with their upstream pig (meat) suppliers and with their downstream customers. Partial least squares method was used to test the causal relationships.

The results suggest that internal integration and buyer‐supplier relationship coordination are significantly related to firm performance in both relationships. Information technology integration is not significantly related to both upstream and downstream relationships. Logistics integration significantly contributes to pork processors' performance in relationships with downstream customers.

The extension of the SCI construct contributes to supply chain management theory in the context of China.

The soft stabilized slab and pile-supported (SSPS) embankment is an improvement technique to increase the efficiency of resources in road construction. To capture the effects of stabilized slabs on the stress transfer mechanism, the differential settlements and the lateral displacement of the embankment completely. A theoretical model of SSPS is proposed by considering the effect of soil arching and the interaction between the embankment fill, stabilized soil, pile, foundation soil and bearing stratum.

In the theoretical model, the stress and strain coordination relationship of the system was analyzed in view of the minimum potential energy theory and equal settlement plane theory. Subsequently, the theoretical method was applied to field tests for comparison. Finally, the influence of the elastic modulus and the thickness of the stabilized slab on the stress concentration ratio and foundation settlement were examined.

In addition to the experimental findings, the method has been revealed to be reasonable and feasible, considering its ability to effectively exploit the stabilized slab effect and improve the bearing capacity of soil and piles. An economical and reasonable arrangement scheme for the thickness and strength of stabilized slabs was obtained. The results reveal that the optimum elastic modulus was chosen as 28 MPa–60 MPa, and the optimum thickness of the stabilized slab was selected as 1.5 m–2.1 m using the parameters of field tests, which can provide guidance to engineering design.

An optimization calculation method is established to analyze the load transfer mechanics of the SSPS embankment based on a double-equal settlement plane. The model’s rationality was analyzed by comparing the settlement and stress concentration ratios in the field tests. Subsequently, the influence of the elastic modulus and the thickness of the stabilized slab on the stress concentration ratio and settlement were examined. An economical and reasonable arrangement scheme for the thickness and elastic modulus of stabilized slabs was obtained, which can provide a novel approach for engineering design.

Since China initiated its “go global” policy that promotes its overseas investment, China’s Outward Foreign Direct Investment (OFDI) has increased almost twenty times during the last 10 years, reaching $55.9 billion in 2008. The issue of internationalization of Chinese OFDI has attracted increasing attention of researchers from a business perspective. This article systematically reviews the previous studies on overseas investments by Chinese MNEs and discusses the characteristics of Chinese internationalization behavior at both firm level and country level. The internationalization of Chinese companies cannot be understood as a simple game of “catch up” with established MNEs, and more firm‐level empirical studies should be carried out on how these characteristics influence firms’ strategic decisions.

This study aims to investigate the relationship between COVID-19 impacts and auxiliary police officers’ mental health as well as the moderating role of supervisor procedural justice.

Based on the role theory and a police officer survey from China, this quantitative study investigates the relationship between COVID-19 impacts and mental health status among auxiliary police, a rarely examined police type. We also examine the moderating role of supervisor procedural justice.

Auxiliary police officers reported both negative and positive impacts from COVID-19, while the negative impacts were mainly in the work domain, but the positive impacts were primarily in the life area. OLS regression results indicate that negative impacts, especially work-related negative impacts, are significantly related to depression and anxiety, and supervisor procedural justice moderates the relationship between positive impacts and depression and anxiety.

Firstly, we adopted the role theory to examine how public health emergencies affect police officers in their work and life domains. Secondly, we advance the organizational justice literature by assessing whether supervisor procedural justice can moderate the relationship between COVID-19 impacts and their mental health. Thirdly, this research extends the literature on depression and anxiety of auxiliary police officers in China, who attracted less attention in current literature and policies.

In today’s digital era, talent recruitment can help address the growing shortage of skilled labor in the construction industry and promote sustainable growth. While existing research has explored the association between talent acquisition and local labor productivity or economic progress, the impact on construction growth deserves further study. This study aims to (1) explore the influence of talent recruitment on the growth of the construction industry and (2) analyze whether different regional characteristics shape the differential impact of talent acquisition on construction growth.

This research employs a quantitative approach, focusing on 35 major cities in China. A panel data regression model is utilized to analyze annual data from 2013 to 2018, considering variables like the construction talent recruitment index, value added in construction, gross regional product per capita and others. The study also examines regional heterogeneity and conducts robustness tests to validate the findings.

The results reveal a positive and significant correlation between talent recruitment and construction industry growth. This correlation is more pronounced in economically advanced and infrastructure-rich regions. The study also finds that factors like capital investment, educational attainment and housing prices significantly contribute to industry growth. Talent recruitment not only transforms local labor market dynamics but also drives demand for construction services, promoting industry growth through economies of scale.

This research constructs a new measurement for talent recruitment and provides new insights into the pivotal role of talent recruitment in the sustainable growth of the construction industry. It underscores the need for construction firms to tailor talent acquisition policies to their specific circumstances and regional developmental conditions. The findings offer practical guidance for driving regional growth within the sector, emphasizing the importance of talent recruitment as a key yet previously underappreciated factor in industry development.

Project scheduling plays an essential role in the implementation of a project due to the limitation of resources in practical projects. However, the existing research tend to focus on finding suitable algorithms to solve various scheduling problems and fail to find the potential scheduling rules in these optimal or near-optimal solutions, that is, the possible intrinsic relationships between attributes related to the scheduling of activity sequences. Data mining (DM) is used to analyze and interpret data to obtain valuable information stored in large-scale data. The goal of this paper is to use DM to discover scheduling concepts and obtain a set of rules that approximate effective solutions to resource-constrained project scheduling problems. These rules do not require any search and simulation, which have extremely low time complexity and support real-time decision-making to improve planning/scheduling.

The resource-constrained project scheduling problem can be described as scheduling a group of interrelated activities to optimize the project completion time and other objectives while satisfying the activity priority relationship and resource constraints. This paper proposes a new approach to solve the resource-constrained project scheduling problem by combining DM technology and the genetic algorithm (GA). More specifically, the GA is used to generate various optimal project scheduling schemes, after that C4.5 decision tree (DT) is adopted to obtain valuable knowledge from these schemes for further predicting and solving new scheduling problems.

In this study, the authors use GA and DM technology to analyze and extract knowledge from a large number of scheduling schemes, and determine the scheduling rule set to minimize the completion time. In order to verify the application effect of the proposed DT classification model, the J30, J60 and J120 datasets in PSPLIB are used to test the validity of the scheduling rules. The results show that DT can readily duplicate the excellent performance of GA for scheduling problems of different scales. In addition, the DT prediction model developed in this study is applied to a high-rise residential project consisting of 117 activities. The results show that compared with the completion time obtained by GA, the DT model can realize rapid adjustment of project scheduling problem to deal with the dynamic environment interference. In a word, the data-based approach is feasible, practical and effective. It not only captures the knowledge contained in the known optimal scheduling schemes, but also helps to provide a flexible scheduling decision-making approach for project implementation.

This paper proposes a novel knowledge-based project scheduling approach. In previous studies, intelligent optimization algorithm is often used to solve the project scheduling problem. However, although these intelligent optimization algorithms can generate a set of effective solutions for problem instances, they are unable to explain the process of decision-making, nor can they identify the characteristics of good scheduling decisions generated by the optimization process. Moreover, their calculation is slow and complex, which is not suitable for planning and scheduling complex projects. In this study, the set of effective solutions of problem instances is taken as the training dataset of DM algorithm, and the extracted scheduling rules can provide the prediction and solution of new scheduling problems. The proposed method focuses on identifying the key parameters of a specific dynamic scheduling environment, which can not only reproduces the scheduling performance of the original algorithm well, but also has the ability to make decisions quickly under the dynamic interference construction scenario. It is helpful for project managers to implement quick decisions in response to construction emergencies, which is of great practical significance for improving the flexibility and efficiency of construction projects.

The Chinese construction industry is experiencing a rapid growth these days. Due to the requirements of energy conservation, emission reduction and construction waste management, the development of prefabricated buildings (PBs) has attracted much attention in the Chinese construction industry. However, the development of PBs are still in their infancy in China, which have been negatively impacted by many obstacles. It is of great significance to clarify and analyze these obstacles for the purpose of promoting the development of PBs in China. Due to the wideness and complex features of obstacles, the existing literature exploring the research topic lacks comprehensiveness. The purpose of this paper is to systematically identify and discuss the obstacles that hinder the development of PBs in China.

This paper adopts the method of news report analysis based on the news reports retrieved from China National Knowledge Infrastructure (CNKI) and nine major portals in China. The Term Frequency-Inverse Document Frequency (TF-IDF) method of content analysis was used to rank the obstacles according to their importance.

A total of 79 obstacles to the development of PBs in China are identified, and the 79 obstacles are divided into 8 dimensions. Among the Top 20 obstacles, the government dimension accounted for the highest number of 5, the market and consumer dimension and development organization dimension were 4, Manufacturing Enterprise of Prefabricated Components (PCs) dimension, construction organization dimension and design organization dimension were 2, logistics enterprise dimension was 1, and industry association dimension was 0. Among them, the biggest obstacle is the high transportation costs.

First, data collection may not be very comprehensive. Second, this paper is only based on the obstacles in the development of PBs in China, and the universality of the management conclusions needs to be further strengthened.

The research results help the stakeholders in the Chinese PBs industry to better understand the barriers hindering the industry development in a systemic way, which will help propose appropriate strategies to address these barriers.

This paper clarifies the obstacles of China's PBs and makes an analysis, which is of great value to the development of China's PBs.