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The purpose of this paper is to understand the subjects contained in the Dunhuang mural images as well as their relation structures.

This paper performed content analysis based on Panofsky’s theory and 237 research papers related to the Dunhuang mural images. UNICET software was also used to study the correlation structures of subject network.

The results show that the three levels of subject have all captured the attention of Dunhuang mural researchers, the iconology occupy the critical position in the whole image study, and the correlation between iconography and iconology was strong. Further analysis reveals that cultural development, production, and power and domination have high centralities in the subject network.

The research samples come from three major Chinese journal databases. However, there are still many authoritative monographs and foreign publications about the Dunhuang murals which are not included in this study.

The results uncover the subject hierarchies and structures contained in the Dunhuang murals from the angle of image scholarship which express scholars’ intention and contribute to the deep semantic annotation on digital Dunhuang mural images.

As the carrier of knowledge, intellectual capital plays a crucial role in technology capability. However, most of the previous studies focus on technological capability from a static perspective, rather than take dynamic technology capability into consideration. Based on this research gap, the purpose of this paper is to investigate the effects of intellectual capital and its sub-dimensions on dynamic technology capability, measuring by the factor scores of five technological input and output variables.

The authors combine the system dynamic method and empirical study to guarantee the internal and external validity. Specifically, the authors design the system dynamic model and simulation to analyze the system mechanism of intellectual capital and its sub-dimensions on dynamic technology capabilities from four cause and effect feedback loops. Then, the authors propose eight hypotheses based on this system dynamic model. In the empirical test phase, the authors employed a panel data set pertaining to Chinese manufacturing firms from 2007 to 2017, and adopted the fixed effect panel model according to Hausman test.

The authors find that intellectual capital efficiency (ICE) and its sub-dimensions (i.e. human capital efficiency, organizational capital efficiency and capital employed efficiency (CEE) have significantly positive impacts on dynamic technology capability. The results also show that the positive effects of ICE and OC on dynamic technology capability would be strengthened in state-owned enterprises compared with non-state-owned enterprises, while this moderation effect is weakened on the relationship between CEE and dynamic technology capability.

In this study, the authors first introduce the system dynamic method to explore the relationship of intellectual capital and dynamic technology capability, which is a valuable trial on combining system science and empirical study. Additionally, the authors continue to expand the dynamic technology capability from the intellectual capital perspective, and also find the moderating effect from the ownership aspect. It is beneficial to the theoretical development of intellectual capital and dynamic technology capability. Furthermore, the authors provide significant inspirations and implications for enterprise’s managers.

The purpose of this paper is to use difference-in-difference method (DID) to study the influences of independent directors’ political connection on firm value.

File No. 18 by the Organization Department of the Communist Party of China Central Committee requires that the leading cadres in party and government offices are not allowed to act as independent directors; this restriction applies to retired officials as well. As a result, many listed companies lose the political connections of officers as independent directors. This paper takes it as an exogenous shock to evaluate the influence of the political connection of independent directors on firm value, effectively alleviating the endogeneity problem existing in previous studies.

The research finds the following: under the policy of compelled resignation, the loss of political connection of independent directors has a prominent negative impact on firm value; and compared to state-owned enterprises, the firm value of private enterprises receives a greater negative impact. However, the political advantage of state-owned enterprises is not obviously influenced. In the regions with worse external market environments, due to a greater reliance on resources brought about by political connection, the policy has a much greater influence on their listed companies.

The study faces several limitations, each of which represents a potential research direction. First, our analysis is based on the policy effects on the firm’s current Tobin’s Q and finds a negative effect of losing political connections. However, the long-term effects are still unclear, as some studies find a negative effect of political connections. Second, the paper focuses on one channel in which political connections may affect firm value. Other channels, such as subsidies and loans from state-owned banks, which need more granular data, should be explored in the future.

The use of DID model can better objectively evaluate the implementation effects of ban policies and alleviate endogenous problems, which is also enlightening for further perfection of the system of independent directors in the A-share market.

It enriches existing researches of the value of independent directors from the perspective of political connection, which is conducive to understanding the influence and channel on the firm value after the loss of political connection and the value of independent directors in the corporate governance in a more comprehensive and accurate manner.

This paper extends the relevant research on the value of the political connection of independent directors from the perspective of political connection and enlightens the evaluation of the effect of ban policies.

This paper aims to study the influence of microparticles on the surface cavitation behavior of 2Cr3WMoV steel; microparticle suspensions of different concentration, particle size, material and shape were prepared based on ultrasonic vibration cavitation experimental device.

2Cr3WMoV steel was taken as the research object for ultrasonic cavitation experiment. The morphology, quantity and distribution of cavitation pits were observed and analyzed by metallographic microscope and scanning electron microscope.

The study findings showed that the surface cavitation process produced pinhole cavitation pits on the surface of 2Cr3WMoV steel. High temperature in the process led to oxidation and carbon precipitation on the material surface, resulting in the “rainbow ring” cavitation morphology. Both the concentration and size of microparticles affected the number of pits on the material surface. When the concentration of microparticles was 1 g/L, the number of pits reached the maximum, and when the size of microparticles was 20 µm, the number of pits reached the minimum. The microparticles of Fe3O4, Al2O3, SiC and SiO2 all increased the number of pits on the surface of 2Cr3WMoV steel. In addition, the distribution of pits of spherical microparticles was more concentrated than that of irregularly shaped microparticles in turbidity.

Most of the current studies have not systematically focused on the effect of each factor of microparticles on the cavitation behavior when they act separately, and the results of the studies are more scattered and varied. At the same time, it has not been found to carry out the study of microparticle cavitation with 2Cr3WMoV steel as the research material, and there is a lack of relevant cavitation morphology and experimental data.

Based on social exchange theory (SET), the current research aims to investigate the relationship between illegitimate tasks (ITs) and employees’ knowledge-hiding behavior (KHB), incorporating the mediating role of psychological contract violation (PCV) and the moderating role of optimism.

A two-wave time-lagged survey was conducted to collect data from 196 adult Chinese full-time employees.

ITs were positively related to KHB, and this relationship was mediated by PCV. Furthermore, optimism buffered the connection between ITs and PCV as well as the mediating effect of PCV on the relationship between ITs and KHB.

For managers, this study made them aware of the hidden costs of ITs; that is, employees may respond by concealing knowledge in the organization.

This study provides a more nuanced understanding of the relationship between ITs and employees’ subtle deviant behavior, KHB and hitherto unspecified mediating and moderating factors that explain this process.

Cooperative driving refers to a notion that intelligent system sharing controlling with human driver and completing driving task together. One of the key technologies is that the intelligent system can identify the driver’s driving intention in real time to implement consistent driving decisions. The purpose of this study is to establish a driver intention prediction model.

The authors used the NIRx device to measure the cerebral cortex activities for identifying the driver’s braking intention. The experiment was carried out in a virtual reality environment. During the experiment, the driving simulator recorded the driving data and the functional near-infrared spectroscopy (fNIRS) device recorded the changes in hemoglobin concentration in the cerebral cortex. After the experiment, the driver’s braking intention identification model was established through the principal component analysis and back propagation neural network.

The research results showed that the accuracy of the model established in this paper was 80.39 per cent. And, the model could identify the driver’s braking intent prior to his braking operation.

The limitation of this study was that the experimental environment was ideal and did not consider the surrounding traffic. At the same time, other actions of the driver were not taken into account when establishing the braking intention recognition model. Besides, the verification results obtained in this paper could only reflect the results of a few drivers’ identification of braking intention.

This study can be used as a reference for future research on driving intention through fNIRS, and it also has a positive effect on the research of brain-controlled driving. At the same time, it has developed new frontiers for intention recognition of cooperative driving.

This study explores new directions for future brain-controlled driving and wheelchairs.

The driver’s driving intention was predicted through the fNIRS device for the first time.

Prior literature indicates conflicting effects of online product information, which may complicate or simplify consumer purchase decisions. Therefore, the purpose of this paper is to investigate how different online product information (i.e. the choice set size and the popularity information and its presentation) affect consumers’ decision making and the related market outcomes.

This research relies on information-processing theories and social learning theory. By stepwise conducting two 2×2 within-subject factorial design experiments, this research examines the effects of the choice set size, product popularity information and product presentation on consumers’ decision making and the aggregated market outcomes.

The results show that product popularity information led consumers to either simplify or complicate their decision strategy, depending on the size of the choice sets. Additionally, presenting products by their popularity in descending order resulted in consumers making decisions with a larger decision bias. The results also show that the presence of product popularity was more likely to forge a “superstar” structure in a large market.

The research suggests that e-retailers and e-marketplace operators should carefully utilize product popularity information. Multiple mechanisms that shape different shopping environments with different orders are necessary to create a long-tailed market structure.

This study found the mixed effects of product popularity information when it is presented in different environments (i.e. the large/small choice set and the sorted/randomized product presentation). The overuse of popularity information may induce consumers’ decision bias.

Against the background of the popularity of social media and heritage tourism, this study aims to focus on world heritage sites, proposing a method to examine and compare the digital spatial footprints left by tourists using geographic information systems.

By analyzing user-generated content from social media, this research explores how digital data shapes the destination image of WHS and the spatial relationships between the components of this destination image. Drawing on the cognitive-affective model (CAM), it investigates through an analysis of integrated data with more than 20,000 reviews and 2,000 photos.

The creativity of this research lies in the creation of a comprehensive method that combines text and image analytics with machine learning and GIS to examine spatial relationships within the CAM framework in a visual manner.

The results reveal tourists' perceptions, emotions, and attitudes towards George Town and Malacca in Malaysia, highlighting several key cognitive impressions, such as history, museums, churches, sea, and food, as well as the primary emotions expressed. Their distributions and relationships are also illustrated on maps.

Tourism practitioners, government officials, and residents can gain valuable insights from this study. The proposed methodology provides a valuable reference for future tourism studies and help to achieve a sustainable competitive advantage for other heritage destinations.

The purpose of this paper is to examine the direct and indirect effects of destination image on destination loyalty. Indirect effects are measured via tourists’ satisfaction.

A reliable conceptual framework was developed through a mixed methods research methodology. A three-pronged approach was used to cross-validate the results from a literature review, expert interviews, and exploratory study. Structural equation modeling was used in conceptual model development and hypotheses testing.

Exploratory dimensions of destination image, satisfaction and destination loyalty of Indian cities were revealed from Thai tourists’ perception. The positive indirect effects of destination image on destination loyalty via satisfaction is supported.

This study is limited to tourists of Thai nationality who visited India’s travel destinations. Future research should include further generalization of the research methodology to specific travel destination.

This study provides useful information for India’s tourism industry, specifically for the marketing of historical cities as travel destinations.

By proposing a reliable conceptual model based on a mixed methods research methodology, this study is among the first to explore destination image, satisfaction and destination loyalty in India’s tourism context. The mediating role of satisfaction on destination image and destination loyalty was also recognized as an extension of, and contribution, to the theoretical foundation for the destination image concept.