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Based on the density dependence theory, this paper attempts to explore how two types of interdependence among firms located in the same national high-tech zones (NHTZs) – mutualism and competition – affect entrepreneurship in the NHTZs. The authors suggest that increasing firm density can help enhance legitimacy and form mutual networks. However, as the competition becomes fierce, the above positive relationship will weaken when the firm density exceeds a certain level. In addition, the authors are interested in whether the age of NHTZs would affect their sensitivity to legitimacy and competition and whether firm density affects entrepreneurship.

This article formulates two hypotheses from the theoretical deduction. The hypotheses are examined using the ordinary least squares (OLS) regression with a unique, unbalanced panel dataset of Chinese NHTZs spanning from 2014 to 2021. Considering potential endogeneity risk among the variables, the authors attempt to lag variables and ultimately find the results are still robust.

Drawing upon the density dependence theory, the empirical results show firm density is conducive to promoting entrepreneurship, while the positive relationship between community density and NHTZs' entrepreneurship gradually weakens as the firm density surpasses a certain level. The dynamics between mutualism and competition have different impacts on NHTZs' entrepreneurship. In addition, the results demonstrate that the linkage between firm interdependence and entrepreneurship is stronger for younger NHTZs. Firm density has an impact on entrepreneurship through legitimacy and excessive competition effects.

On the one hand, the research period of this paper is 2014–2021, as the China Torch Statistical Yearbook only started to publish operating revenues in 2014, so the data period of this paper is relatively short. More research can be done in the future when more data is disclosed. On the other hand, the qualitative analysis cannot be conducted because of the limited data and materials. In future research, the qualitative analysis of entrepreneurial activities in NHTZs, such as questionnaires or case studies, needs to be supplemented, which will be an interesting direction.

Most existing research has not distinguished the differences between NHTZs (Wang et al., 2019), especially the differences in legitimacy and access to resources caused by the age of NHTZs. This article considers the heterogeneity between NHTZs, which helps to provide theoretical and practical evidence for a transition economy like China to make trade-off decisions on balancing absorbing new entrants with promoting the efficient allocation of resources based on the density and age of NHTZs.

Drawing upon density dependency theory, this paper enriches the literature on agglomeration and entrepreneurship with a new perspective and extends the study to NHTZs.

First, this paper provides new evidence on how agglomeration affects entrepreneurship from an ecological perspective with the help of mutualism and competition interdependence. Most studies have explored the role of agglomeration in entrepreneurship, focussing on social networks, knowledge spillovers or resource endowments (Acs et al., 2013; Capozza et al., 2018; Yu, 2020). Drawing upon density dependency theory, this paper enriches the literature on agglomeration and entrepreneurship with a new perspective and extends the study to NHTZs. Second, the emphasis of science parks has been primarily on qualitative or case studies (Salvador et al., 2013; Guo and Verdini, 2015; Xie et al., 2018). We have diversified the quantitative research between agglomeration and entrepreneurship by using panel data from Chinese NHTZs from 2014 to 2021. Third, most existing research has not distinguished the differences between NHTZs (Wang et al., 2019), especially the differences in legitimacy and access to resources caused by the age of NHTZs. This article considers the heterogeneity between NHTZs, which helps to provide theoretical and practical evidence for a transition economy like China to make trade-off decisions on balancing absorbing new entrants with promoting the efficient allocation of resources based on the density and age of NHTZs. Finally, this paper meticulously investigates the profound influence and underlying mechanisms of firm density within NHTZs on entrepreneurship. It discerns two distinct mechanisms at play: the legitimacy effect and the impact of excessive competition resulting from firm density. This comprehensive analysis significantly contributes to our comprehension of the intricate interplay between firm density and entrepreneurship, shedding light on the dynamics of competition and mutual benefits.

Under oil interruption, lubricant supply in the high-speed bearing cavity is interrupted, which reduces the bearing lubrication and cooling ability, thus leading to degradation of bearing performance or even its failure. This paper aims to study the effect of grooves at the noncontact outer ring area on the flow and thermal performance of high-speed bearings under oil interruption, which is expected to improve the resistance of existing bearings to oil interruption.

The groove was added to the noncontact outer ring area of the bearing, and a method of combining volume of fluid and MRF was adopted to systematically study and analyze the oil-gas flow field structure and the temperature field distribution in the bearing cavities.

Results show that the lubricating oil could be stored and guided by the grooves of the bearing outer ring into the key lubrication area inside the bearing cavity, which increased the oil content near the inner ring and made the oil distribution more uniform. As a result, lubrication cooling and heat dissipation performance of the bearing cavity was improved. Compared with the original bearing, the bearing with a V-shaped groove had the optimal lubrication and cooling performance.

A rolling bearing model of the noncontact outer ring area with grooves under oil interruption is established in the paper. The simulation results provide theoretical guidance for the research and development of high-speed bearings with stronger oil interruption resistance ability.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0199/

This study aims to present a novel hydrostatic squeeze film-metal mesh journal bearing (HS-MMJB), which uses both hydrostatic squeeze film damper (HSFD) and metal mesh damper (MMD), to suppress the vibration of rotor-bearing systems.

The lubrication equations were introduced to calculate the dynamic characteristics of HS-MMJB, and the response analyses of rotor systems were carried out. Experiments were conducted to study the vibration reduction of a rotor system with HS-MMJB. In addition, experiments for different oil supply pressures in the HS-MMJB were conducted.

The theoretical and experimental results show that the HS-MMJB exhibits excellent damping and vibration attenuation characteristics. Moreover, the stability of the rotor system can be improved by controlling the oil supply pressure.

There is a dearth of research on vibration characteristics of rotor system support by journal bearing combining HSFD and MMD. Moreover, the active oil pressure control is implemented to improve the stability of rotor system.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

Achieving sustainability and sustainable performance has emerged as a critical area of focus for both academic research and practice. However, this pursuit faces challenges, particularly concerning the inadequacy of supply chain information. To address this issue, our study employs the organizational information processing theory to explore how adopting blockchain technology enables firms to learn from and collaborate with their supply chain partners, ultimately facilitating their sustainable performance even in the presence of organizational inertia.

Underpinned by the organizational information processing theory and drawing data from 220 manufacturing firms in China, we use structural equation modeling to test our conceptual model.

Our results demonstrate that blockchain technology adoption can significantly enhance sustainable performance. Furthermore, supply chain learning acts as a mediator between blockchain technology adoption and sustainable performance, while organizational inertia plays a negative moderating role between blockchain technology adoption and supply chain learning.

These findings extend the existing literature on blockchain technology adoption and supply chain management, offering novel insights into the pivotal role of blockchain in fostering supply chain learning and achieving sustainable performance. Our study provides valuable practical implications for managers seeking to leverage blockchain technology to enhance sustainability and facilitate organizational learning.

Using the Shanghai pilot free trade zone (SPFTZ) as the testing ground for further reform and opening up,the links between global value chain (GVC) and pilot free trade zone (PFTZ) programs are mutually reinforcing. GVC creates opportunities for companies to use PFTZ to reduce their costs and increase their competitiveness, while PFTZ can facilitate the movement of goods within GVC and promote the development of GVC by attracting foreign investment. Overall, in SPFTZ, the industrial structure is promoted due to trade and investment facilitation, innovation promotion, and comprehensive service platform inside SPFTZ.

This study examined industrial upgrading in GVC (IUGVC) using five indicators under three quantitative dimensions: product, process, and skill upgrading. Difference-in-Differences (DID) model is employed for the impact assessment of SPFTZ. Parallel trend analysis and Granger causality analysis are performed to check the reliability of DID outcome. Finally, robustness test using exogenous control variables are carried out.

A positive impact of SPFTZ is found on IUGVC, which is due to promoting effect of SPFTZ on foreign direct investment and technological innovation. Based on the study's findings, policy recommendations are given, such as providing business support to enterprises operating inside a PFTZ.

From a GVC perspective, the impact of theSPFTZ establishment on IUGVC cannot be ignored, and is so far missing in the literature.

Expatriate management is a popular topic in international human resource management (IHRM) because expatriates play a critical role in a firm’s international business operations. The purpose of this paper is to discuss the existing studies that often examine the expatriate management of developed country multinational enterprises (MNEs), aiming to help them identify, employ, prepare and retain expatriates and address challenges these MNEs may face, while how MNEs from emerging countries manage their expatriates is understudied.

The knowledge of expatriate management from emerging market MNEs (EMNEs) may help us understand whether there is anything new for IHRM theory and practice. This conceptual paper aims to address this research gap by selecting China, a leading emerging economy, and reviewing the existing literature in both English and Chinese to examine the status quo of the expatriate management in Chinese MNEs to highlight challenges facing these MNEs in managing their expatriates when conducting outward foreign direct investment (FDI).

This paper aims to make theoretical contributions by generating research propositions to address an under-researched area, i.e., how EMNEs manage their expatriates and the role of their expatriates in the outward FDI.

No other person’s work has been used in the main text of the paper. This paper has not been submitted for the award of any other degree or diploma in this or any other tertiary institution.

In the field of steel defect detection, the existing detection algorithms struggle to achieve a satisfactory balance between detection accuracy, computational cost and inference speed due to the interference from complex background information, the variety of defect types and significant variations in defect morphology. To solve this problem, this paper aims to propose an efficient detector based on multi-scale information extraction (MSI-YOLO), which uses YOLOv8s as the baseline model.

First, the authors introduce an efficient multi-scale convolution with different-sized convolution kernels, which enables the feature extraction network to accommodate significant variations in defect morphology. Furthermore, the authors introduce the channel prior convolutional attention mechanism, which allows the network to focus on defect areas and ignore complex background interference. Considering the lightweight design and accuracy improvement, the authors introduce a more lightweight feature fusion network (Slim-neck) to improve the fusion effect of feature maps.

MSI-YOLO achieves 79.9% mean average precision on the public data set Northeastern University (NEU)-DET, with a model size of only 19.0 MB and an frames per second of 62.5. Compared with other state-of-the-art detectors, MSI-YOLO greatly improves the recognition accuracy and has significant advantages in computational cost and inference speed. Additionally, the strong generalization ability of MSI-YOLO is verified on the collected industrial site steel data set.

This paper proposes an efficient steel defect detector with high accuracy, low computational cost, excellent detection speed and strong generalization ability, which is more valuable for practical applications in resource-limited industrial production.

This study aims to provide empirical evidence on the relationship between formal institutions and stock price crash risk from a global perspective.

This paper uses data of 35,468 firms globally over the years 1987–2019 and address the endogeneity issue by employing the Mundlak random effects estimator.

The authors find a significant negative impact of institution quality on stock price crash risk (i.e. better institutions reduce crash risk), after controlling for common determinants of crash risk such as leverage, return on asset, firm size, investment, etc. as well as macro factors such as GDP growth. This effect is robust to different measures of crash risk and sub-indicators of institutions quality. In addition, the authors also find this effect to be universally present in economies characterized by different levels of income.

To the best of the authors' knowledge, there's no known study that explores the potential causal relationship between institution quality and stock price crash risk. Therefore, the research topic in this study is original and can contribute significantly to the existing literature.

The purpose of this paper is to propose an on-line iterative compensation method combining with a feed-forward compensation method to enhance the assembly accuracy of a metrology-integrated robot system (MIRS).

By the integration of a six degrees of freedom (6DoF) measurement system (T-Mac), the robot’ movement can be tracked with real-time measurement. With the on-line measured data, the proposed iterative compensation for absolute positioning and the feed-forward compensation for relative linear motion are integrated into the assembly process to improve the assembly accuracy.

It is found that the MIRS exhibits good performance in both accuracy and efficiency with the application of the proposed compensation method. With the proposed assembly process, a component can be automatically aligned to the target in seconds, and the assembly error can be decreased to 0.021 mm for position and 0.008° for orientation on average.

This paper presents a 6DoF MIRS for high-precision assembly. Based on the system, a novel on-line compensation method is proposed to enhance the assembly accuracy. In this paper, the assembly accuracy and the corresponding distance parameter are given by a series of experiments as reference for assembly applications.