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This paper aims to clarify the spatial connection characteristics and organization mode of logistics economy of 21 cities in Guangdong Province under the background of the integrated development of Guangdong, Hong Kong and Macao Bay area, and explore the spatial development characteristics and influencing factors of logistics economy in Guangdong Province.

This paper constructs the development level model of urban logistics economy in Guangdong Province from three aspects: demand level, supply level and support level, and uses the entropy weight method to measure the development level index of urban logistics economy in Guangdong Province. Then, the traffic accessibility index model is used to measure the traffic accessibility index between cities in Guangdong Province. Finally, using the social network analysis method, combined with the development level index of urban logistics economy in Guangdong Province and the urban traffic access index in Guangdong Province, this paper analyzes the spatial connection characteristics and influencing factors of logistics economy network in Guangdong Province.

There are regional differences in the development level of logistics economy in Guangdong Province; The overall network density of its logistics economic connection is large, but there is an imbalance in the network structure, and the core edge phenomenon is obvious; Logistics economic space presents the characteristics of double core development.

Because the research object is the spatial connection characteristics of logistics economy in Guangdong Province, the research results may lack universality. Therefore, researchers are encouraged to put forward further tests.

By studying the spatial connection mode of logistics economy in 21 cities in Guangdong Province, China, this paper promotes the original methods and empirical contributions, and constructs the research framework of spatial relationship of logistics economy. This research framework is universal to a certain extent.

This paper is conducive to promoting the integrated development of logistics economy in Guangdong Province and improving the balance of regional development of logistics economy.

Firstly, this study provides a new perspective to understand the spatial relationship and spatial spillover of logistics economy from relational data rather than attribute data. Secondly, This study enriched and broadened the research topic of spatial correlation of logistics economy. Thirdly, this research aims to promote the original methods and empirical contributions. Specifically, this study establishes a comprehensive research framework on the spatial network structure of logistics economy.

The study aimed to analyze the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong Province.

A conceptual model of the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong province is established, which takes the business model as the mediating variable and political association as the moderating variable. Multivariate statistical analysis and the MacKinnon confidence interval method were used to analyze 418 questionnaires.

The results show that both relational embeddedness and structural embeddedness have significant positive effects on the innovation performance of high-tech enterprises in Guangdong Province. The business model has a partial mediating effect between relationship embeddedness, structure embeddedness, and innovation performance of high-tech enterprises in Guangdong Province, respectively. Political relevance has a significant negative moderating effect on the relationship between the relationship embeddedness and innovation performance of high-tech enterprises in Guangdong Province, but the moderating effect on structural embeddedness and innovation performance of high-tech enterprises in Guangdong province has not been verified.

The study of this paper also has some shortcomings: very few data research samples exist; the external factors affecting the performance of high-tech enterprises in Guangdong Province need to be further refined. The research scale needs further improvement.

In this paper, embedding theory, transaction cost theory, resource dependence theory, rent-seeking theory, new institution theory and uncertainty management theory were integrated by system attempt to reveal the mediating and moderating roles of business model and political relevance, respectively, between network embeddedness behavior and entrepreneurial innovation performance of high-tech enterprises. The research conclusions expand the relevant research in the field of entrepreneurial innovation. At the same time, the research results provide theoretical support and reference for the innovative growth of high-tech enterprises and government behavior decision-making in Guangdong province.

Network embeddedness will have a profound impact on the entrepreneurial innovation performance of high-tech enterprises. Existing research has overlooked discussing this issue from the perspective of internal and external influencing factors within the enterprise. Therefore, this study addresses this issue by (1) introducing the business model as the mediating variable from an internal perspective of the enterprise, (2) introducing political association as the moderating variable from an external perspective of the enterprise and (3) 418 original questionnaires of high-tech enterprises in Guangdong Province were used to test the effect of the study variables.

This study investigates the mediating role of wage and workforce adjustments, along with the moderating influence of collective bargaining system and employees’ localization, in elucidating the relationship between the COVID-19 shock and workplace employee relations (ER) tension.

Survey data from 1,483 enterprises across 21 prefectural cities in China’s Guangdong Province are collected. The hypotheses are tested by logistic regression.

The study reveals a positive correlation between the COVID-19 shock and workplace ER tension across crisis-hit enterprises, irrespective of their size or industrial sector. Wage reduction and mass layoffs emerge as significant mediators, while the collective bargaining system (CBS) and employees’ localization act as moderators.

The measurement of ER is limited in a single-item scale. Representation of China is also limited since the study exclusively focuses on Guangdong province. The study offers some contributions that firm-level data reveal the pathway through which COVID-19 creates ER tension.

On the one hand, the authors recommend the establishment of an effective communication system between employers and employees. On the other hand, managers should consider the role of informal institutions. Furthermore, the authors suggest implementing tailored strategies at the enterprise level.

Intense external shocks result in widespread layoffs and increased wage reductions within workplaces, and under such circumstances, formal or informal institutions may be insufficient to alleviate ER tension. In this case, the state authorities – including governments and other public agencies or bodies – are necessary to intervene in to organize tripartite dialogue.

While numerous emerging studies on COVID-19 explore how different countries manage industrial relations tension at the national level, few focus on ER at workplace level, particularly in developing countries. Understanding how workplace ER evolve during external shocks and identifying institutional measures to mitigate their negative impact is crucial for future crisis management.

Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic points on the dynamic objects in the image in the mapping can have an impact on the observation of the system, and thus there will be biases and errors in the position estimation and the creation of map points. The aim of this paper is to achieve more accurate accuracy in SLAM algorithms compared to traditional methods through semantic approaches.

In this paper, the semantic segmentation of dynamic objects is realized based on U-Net semantic segmentation network, followed by motion consistency detection through motion detection method to determine whether the segmented objects are moving in the current scene or not, and combined with the motion compensation method to eliminate dynamic points and compensate for the current local image, so as to make the system robust.

Experiments comparing the effect of detecting dynamic points and removing outliers are conducted on a dynamic data set of Technische Universität München, and the results show that the absolute trajectory accuracy of this paper's method is significantly improved compared with ORB-SLAM3 and DS-SLAM.

In this paper, in the semantic segmentation network part, the segmentation mask is combined with the method of dynamic point detection, elimination and compensation, which reduces the influence of dynamic objects, thus effectively improving the accuracy of localization in dynamic environments.

This paper aims to summarize the conditions under which participatory art museums and local commercial traditions can have positive and sustained interactions.

The methods include studying the quantity and content of exhibitions in the four cities of the Bay Area, Guangzhou, Shenzhen, Hong Kong and Shunde, to compare their academic positioning and influence on local commercial production. Through interviewing curators, artists and university scholars who are active in the Bay Area and are invited by the museums on a regular basis, it will let us understand the attitudes from the government, public and capital towards the regional art museums and how these attitudes influence the choice of theme in the participatory art museum practice.

To summarize the findings, the author concludes that a participatory art gallery with commercial production in the Bay Area requires the following: a long tradition of local business and wealth accumulation; a local area is of a size where the community of acquaintances can interact on a regular basis; continued interest of a diverse local elite, including a mix of businessmen and gentry, government officials and various sectors of the public; and museums serving as intermediaries to coordinate the effective integration of the commercial and traditional resources.

Participatory approaches and their impacts are a shared area of interest across urban planning, heritage studies and the creative arts. Crucially, solely relying on either the Latin bottom-up community-oriented approach (Barnes, 2003) or the British top-down policy-oriented approach (Heijnen, 2010) did not maximize benefits, though these distinctive two approaches were convinced that museums should play a larger role in becoming agents of contemporary social change. By contrast, in focusing on Chinese Art Museums, this study will explore participatory practice in the Asian context. In doing so, it will not only diversify the emerging literature on the social and economic impacts of arts and heritage organizations but also challenge the Western lens through which participatory approaches are viewed in the interdisciplinary literature. As Lefebvre acknowledged his lack of non-Western regions in his research, this study will offer new perspectives on museology and its contributions to the Production of Space.

This study aims to explore the connection between travel content consumption in social networks and social comparison, envy as well as travel intention. It analyzes whether tourists’ travel intention is affected by travel content consumption in social networks, and more importantly, whether social comparison and envy play a mediating role in this process.

Data was collected through intercept in four popular tourist spots in Guangzhou and Zhuhai in South China. A self-administered questionnaire was used. A total of 400 participants were recruited, and 291 valid questionnaires were obtained. Bias-corrected nonparametric percentile bootstrap mediation variable test method was used to test hypotheses.

The study yielded three results. First, travel content consumption in the social networks positively influences travel intention. Second, travel content consumption in social networks indirectly affects travel intention through social comparison and envy. Third, the control variables, such as gender, age, education and income, mainly affect envy.

This study constructs a theoretical framework of stimulus–cognitive appraisal–emotion–behavioral responses. To the best of the authors’ knowledge, it is the first study to reveal that the internal psychological mechanism of travel content consumption affects travel intention. It also discloses that envy of seemingly negative emotions can encourage positive behaviors in certain situations.

Despite the growing research interest in gender diversity, the presence of female executives and organizational outcomes, the relationship between female executives and employment relations outcomes remains under-researched. This study aims to examine the potential relationship between female executives and employment relations outcomes, with the gender gap as a focus.

A cross-sectional survey was used to collect data from 2,682 workers from 119 manufacturing firms in Guangdong Province, southern China.

Results show that firms with female executives are more likely to comply with labor laws and promote staff development. The association between female executives and promotion opportunities is stronger for female employees than for male employees. However, there is no significant association between female executives and employee salaries.

This research contributes to employment relations literature and extends the application of social role theory to studies of employment relations in particular societal contexts. This study also provides possible boundary conditions for the existence of queen bee behavior by using data from Chinese factories.

This study aims to empirically examine the relationships among perceived environmental uncertainty (EV), the level of knowledge distance (KD) and the impact of value network on firm performance.

The quantitative analysis is based on data from 243 Chinese companies with engineering, procurement and construction (EPC) business in the context of the COVID-19 pandemic.

The two dimensions of value network [network centrality (NC) and network openness (NO)] have a different impact on firm performance [financial performance (FP) and market performance (MP)]. NC has a positive impact on FP, but not on MP. NO has a positive effect on MP, but not on FP. A reduced KD mediates the relationship between value network and firm performance. Moreover, it fully mediates the relationship between NC and MP, NO and FP. Finally, during the COVID-19 pandemic, only EV has a moderating effect on KD and MP.

This study is limited in terms of data set because it relies on a limited amount of cross-sectional data from one specific country. Therefore, researchers are encouraged to test the proposed propositions further.

The present findings suggest that EPC professionals should pay more attention to the EV, which may be impacted by policy, technology and the economy. This research has actionable implications for the reform of EPC in the construction industry, and practical recommendations for EPC firms to improve their corporate performance.

The results measure the complementary effects of both dimensions of value network (NC and NO) on two distinct aspects of firm performance (MP and FP) and assess the moderating effect of EV and KD in the context of the COVID-19 pandemics.

For online experiential products, tactile attributes are important but hard-to-achieve features. This research aims to explore consumers' emotional experiences by incorporating tactile attributes into the online clothing shopping scenario.

This paper presents two online shopping experiments by consumers who purchase online clothing: one experiment involves subjects browsing clothing products on a computer screen; the other one involves subjects touching the clothing fabric while browsing a corresponding product on a computer screen. Based on the stimulus–organism–response (S-O-R) model, a physiological polygraph was used to record the emotional experience of subjects under the stimuli of “sight” and “sight + touch.”

(1) Subjects had a more positive emotional arousal under the stimuli of “sight + touch”; (2) the visual merchandising of clothing and expected touch task affect subjects' overall emotional experience with clothing, and with a good visual experience and expected tactile experience, the subjects showed a more positive emotional valence under the stimuli of “sight + touch”; (3) differing from previous research, this experimental data only supports the hypothesis that the skin conductance indicator is related to the level of emotional arousal, without supporting its correlation with emotional valence. However, the heart rate indicator is correlated with emotional valence but not with emotional arousal.

This work proposes a way to study the tactile attributes of online clothing and enriches the theoretical framework of polygraph and the S-O-R model for the research of online experiential products, and in terms of application, it sheds light on sales strategies of online experiential products for retailers and brand owners.

Fire smoke detection in petrochemical plant can prevent fire and ensure production safety and life safety. The purpose of this paper is to solve the problem of missed detection and false detection in flame smoke detection under complex factory background.

This paper presents a flame smoke detection algorithm based on YOLOv5. The target regression loss function (CIoU) is used to improve the missed detection and false detection in target detection and improve the model detection performance. The improved activation function avoids gradient disappearance to maintain high real-time performance of the algorithm. Data enhancement technology is used to enhance the ability of the network to extract features and improve the accuracy of the model for small target detection.

Based on the actual situation of flame smoke, the loss function and activation function of YOLOv5 model are improved. Based on the improved YOLOv5 model, a flame smoke detection algorithm with generalization performance is established. The improved model is compared with SSD and YOLOv4-tiny. The accuracy of the improved YOLOv5 model can reach 99.5%, which achieves a more accurate detection effect on flame smoke. The improved network model is superior to the existing methods in running time and accuracy.

Aiming at the actual particularity of flame smoke detection, an improved flame smoke detection network model based on YOLOv5 is established. The purpose of optimizing the model is achieved by improving the loss function, and the activation function with stronger nonlinear ability is combined to avoid over-fitting of the network. This method is helpful to improve the problems of missed detection and false detection in flame smoke detection and can be further extended to pedestrian target detection and vehicle running recognition.