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This study examines the role of digital transformation intentions in enhancing the perceived resilience of firms, with a focus on China’s manufacturing sector. It investigates the mediating role of knowledge sharing and the moderating impact of transformational leadership.

A quantitative approach was employed, collecting data from 347 manufacturing firms. Participants included managers and MBA students involved in digital transformation projects. The study utilized statistical analysis to explore the relationships between digital transformation intentions, knowledge sharing, transformational leadership and perceived firm resilience.

The analysis reveals that knowledge sharing is a critical mediating factor between digital transformation intentions and perceived firm resilience. Additionally, transformational leadership significantly strengthens this relationship, highlighting its importance in the successful implementation of digital initiatives.

The study is geographically and sectorally limited to China’s manufacturing sector, which may affect the generalizability of the findings. Future research could explore other sectors and regions to validate and extend the results.

The findings underscore the necessity of integrating digital transformation initiatives with effective leadership and knowledge management practices. Firms that foster transformational leadership and facilitate knowledge sharing are better equipped to enhance their resilience in the face of global disruptions.

This research offers a deep understanding of how digital transformation intentions, mediated by knowledge sharing and supported by transformational leadership, contribute to perceived firm resilience. It provides valuable insights for both academic research and practical applications in the field of management.

This paper aims to objectively present the research dynamics of China in the field of information behavior and its development trends. Firstly, it incorporates China’s research in the field of information behavior into the global research network of information behavior, analyzing the changes in the status of Chinese scholars and their research institutions in the global research network from 1991 to 2022, the trends in publication volume and the cooperation relationships with other countries. Then, it conducts a detailed analysis of China’s research categories, groups, theoretical models and hot topics in different information contexts in the past five years (2018–2022).

The study retrieved research literature related to information behavior in China from 1991 to 2022 in the Web of Science database. It then utilized a national/institutional cooperation network map to analyze the changes in the status of Chinese scholars/institutions in the global research network during this period, publication volume trends and cooperation relationships with other countries. Furthermore, it employed keyword co-occurrence network maps to analyze the key categories, groups, theories and models of China’s research in different information contexts in the past five years. Based on this, it used keyword clustering network maps to analyze the hot topics of China’s research in different information contexts in the past five years.

(1) China’s research in the field of information behavior started relatively late, but the volume of publications has grown rapidly since 2004, currently ranking second globally in cumulative publication quantity. However, the influence of the literature published by China is limited, and there is a lack of research institutions with global influence. (2) In the last five years, China has conducted extensive research in various information contexts. Among these, most research was conducted in work contexts, followed by healthcare contexts, especially studies related to epidemics. (3) Current research on information behavior in China is characterized by expanded and refined research groups, diversified research categories, continuous expansion and enrichment of research contexts, increased interdisciplinary nature of research and continuous innovation in research methods and theoretical models.

This study, utilizing a scientific knowledge map, elucidates China’s position in global information behavior research, with a specific emphasis on analyzing China’s research hot topics and trends in this field over the past five years. It aims to provide valuable resources for scholars interested in understanding the status of information behavior research in China and to offer some guidance for scholars currently or intending to engage in information behavior research.

The purpose of this paper is to develop a transform method and a deep learning model to identify the inner surface shape based on the measurement temperature at the outer boundary of the pipe.

The training process is assisted by the finite element method (FEM) simulation which solves the direct problem for the data preparation. To avoid re-meshing the domain when the inner surface shape varies, a new transform method is proposed to transform the shape identification problem into the effective thermal conductivity identification problem. The deep learning model is established to set up the relationship between the measurement temperature and the effective thermal conductivity. Then the unknown geometry shape is acquired by the mapping between the inner shape and the effective thermal conductivity through the inverse transform method.

The new method is successfully applied to identify the internal boundary of a pipe with eccentric circle, ellipse and nephroid inner geometries. The results show that as the measurement points increased and the measurement error decreased, the results became more accurate. The position of the measurement point and mesh density of the FEM model have less effect on the results.

The deep learning model and the transform method are developed to identify the pipe inner surface shape. There is no need to re-mesh the domain during the computation progress. The results show that the proposed method is a fast and an accurate tool for identifying the pipe inner surface.

The visible time window (VTW) calculation of satellites to ground targets is significant for Earth observation satellites' operation management and control. With the improvement of satellite maneuvering capability and the complexity of on-orbit observation tasks, the traditional VTW calculation methods can no longer meet the demands of satellite operation management and control due to a large amount of calculation and low efficiency. The purpose of this study is to propose a fast VTW calculation method based on map segmentation named map segmentation method (MSM), to improve the calculation efficiency, and further solve this problem.

The main feature of the MSM method is to segment the map and subsatellite trajectories and traverse the subsatellite points within a specific range around the target, significantly reducing the search space and the amount of computation and improving computational efficiency.

Numerical simulations for two satellite orbits are implemented to verify the feasibility of the proposed VTW calculation method, and the traditional traversal method (TM) is also performed for comparative analysis. The results show that the proposed method can obtain the same VTW, using less calculation time than the TM. The computational efficiency is significantly improved, especially for many tasks. The calculation time of observing 500 targets is saved by more than 70%, indicating a broad application prospect.

This paper proposes an original VTW calculation method based on map segmentation to improve the calculation efficiency. The simulation scenarios are designed to verify the accuracy and effectiveness of the proposed method, and the observation targets are randomly distributed on the map. For comparative analysis, the TM is also performed under the same simulation conditions.

The aim of this study was (1) to investigate the relationship between destination image (DI), destination personality (DP) and behavioral intention (BI) in the context of ski tourism and (2) especially the role of DP in the relationship between DI and BI among ski tourists.

We collected data using WJX.CN (N = 400) to test the hypothesized model. Confirmatory factor analysis (CFA) was used to examine the psychometric properties of the measurement model and partial least squares structural equation modeling (PLS-SEM) was used to test the hypotheses.

The results show that DI directly affects DP and partially affects BI, while DP directly affects ski tourists' BI. In addition, the indirect effect of DP between affective image and BI was significant, showing full mediation, and the indirect effect of DP between cognitive image and BI was significant, showing a partial mediation effect.

The findings enrich the ski tourism literature, contribute to the development of ski tourism in destination cities and the strategic marketing of ski resorts and provide recommendations for ski tourism researchers and marketers.

Since the limited growth of enterprises has been identified as a deliberate choice of women entrepreneurs, the purpose of this paper is to illustrate how the institutional environment of an entrepreneurial ecosystem (EE) fosters the gender gap in entrepreneurial growth intention. The mediating role of the perceived institutional environment in the gender effect on entrepreneurial growth intention is tested in the Chinese context. As individuals’ cognitions are usually influenced by their cultural orientations, the gender difference in perceptions of the institutional environment is considered to be contingent on entrepreneurs’ self-construal.

Using a multiregional sample of 206 Chinese entrepreneurs who completed the questionnaire, the study obtained results by adopting a structural equation modelling analysis with a partial least squares approach.

There are significant gender gaps in perceptions of the institutional environment and growth intention among Chinese entrepreneurs. Due to their limited political ties and lower legitimacy in economic activities in the country, Chinese women entrepreneurs have more negative perceptions of the regulative and cognitive institutional environment than their male counterparts, which accounts for the lack of growth ambition among Chinese women entrepreneurs. Independent self-construal enlarges the difference in environmental perceptions between male and female entrepreneurs.

This research enriches the discussion in the emerging area of EEs by adequately responding to the highlighted target to advance ambitious entrepreneurship and offering an interpretation of its evolutionary thinking. Given the increasing calls for a focus on high-growth women’s entrepreneurship, this study provides an explanation for how the institutional environment engenders the absence of women in growth-oriented entrepreneurial activities. It also uncovers the overlooked deficiency in institutional practice by highlighting the gender inequality in the implementation process of entrepreneurial support policies and the distribution of entrepreneurial capabilities in society.