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This research clarifies the connotations and dimensions of artificial intelligence (AI) technology stimulation and establishes a stimulus scale to explain the relationship between AI technology stimuli and smart customer experience.

This is an empirical study that uses SPSS 24.0 software to perform hypothesis testing on the path relationships between model elements.

Two dimensions of AI technology stimuli (i.e. passion and usability) have a significant, positive impact on smart customer experience; the moderating effects of contrasting dimensions of technology readiness (i.e. optimism and discomfort) are significantly different; smart customer experience has a significant, positive impact on the word-of-mouth (WOM) intentions of consumers.

There are several limitations. Most importantly, the data collected in this study are only from consumers who use intelligent customer service robots in the catering industry. Future research can consider exploring relevant AI technologies in other sectors.

This study has several implications that guide catering companies to develop various positioning and strategies for remaining competitive effectively.

Based on arousal theory, customer experience theory and WOM marketing theory, this is the first novel research project that empirically discusses the dimensions of AI technology stimuli, smart customer experience and WOM intentions with regard to the moderating effect of the technology readiness of consumers toward AI technology.

Computer vision and deep learning (DL) methods have been investigated for personal protective equipment (PPE) monitoring and detection for construction workers’ safety. However, it is still challenging to implement automated safety monitoring methods in near real time or in a time-efficient manner in real construction practices. Therefore, this study developed a novel solution to enhance the time efficiency to achieve near-real-time safety glove detection and meanwhile preserve data privacy.

The developed method comprises two primary components: (1) transfer learning methods to detect safety gloves and (2) edge computing to improve time efficiency and data privacy. To compare the developed edge computing-based method with the currently widely used cloud computing-based methods, a comprehensive comparative analysis was conducted from both the implementation and theory perspectives, providing insights into the developed approach’s performance.

Three DL models achieved mean average precision (mAP) scores ranging from 74.92% to 84.31% for safety glove detection. The other two methods by combining object detection and classification achieved mAP as 89.91% for hand detection and 100% for glove classification. From both implementation and theory perspectives, the edge computing-based method detected gloves faster than the cloud computing-based method. The edge computing-based method achieved a detection latency of 36%–68% shorter than the cloud computing-based method in the implementation perspective. The findings highlight edge computing’s potential for near-real-time detection with improved data privacy.

This study implemented and evaluated DL-based safety monitoring methods on different computing infrastructures to investigate their time efficiency. This study contributes to existing knowledge by demonstrating how edge computing can be used with DL models (without sacrificing their performance) to improve PPE-glove monitoring in a time-efficient manner as well as maintain data privacy.

Automatic segmentation of brain tumor from medical images is a challenging task because of tumor's uneven and irregular shapes. In this paper, the authors propose an attention-based nested segmentation network, named DAU-Net. In total, two types of attention mechanisms are introduced to make the U-Net network focus on the key feature regions. The proposed network has a deep supervised encoder–decoder architecture and a redesigned dense skip connection. DAU-Net introduces an attention mechanism between convolutional blocks so that the features extracted at different levels can be merged with a task-related selection.

In the coding layer, the authors designed a channel attention module. It marks the importance of each feature graph in the segmentation task. In the decoding layer, the authors designed a spatial attention module. It marks the importance of different regional features. And by fusing features at different scales in the same coding layer, the network can fully extract the detailed information of the original image and learn more tumor boundary information.

To verify the effectiveness of the DAU-Net, experiments were carried out on the BRATS 2018 brain tumor magnetic resonance imaging (MRI) database. The segmentation results show that the proposed method has a high accuracy, with a Dice similarity coefficient (DSC) of 89% in the complete tumor, which is an improvement of 8.04 and 4.02%, compared with fully convolutional network (FCN) and U-Net, respectively.

The experimental results show that the proposed method has good performance in the segmentation of brain tumors. The proposed method has potential clinical applicability.

The precise segmentation of brain tumors is the most important and crucial step in their diagnosis and treatment. Due to the presence of noise, uneven gray levels, blurred boundaries and edema around the brain tumor region, the brain tumor image has indistinct features in the tumor region, which pose a problem for diagnostics. The paper aims to discuss these issues.

In this paper, the authors propose an original solution for segmentation using Tamura Texture and ensemble Support Vector Machine (SVM) structure. In the proposed technique, 124 features of each voxel are extracted, including Tamura texture features and grayscale features. Then, these features are ranked using the SVM-Recursive Feature Elimination method, which is also adopted to optimize the parameters of the Radial Basis Function kernel of SVMs. Finally, the bagging random sampling method is utilized to construct the ensemble SVM classifier based on a weighted voting mechanism to classify the types of voxel.

The experiments are conducted over a sample data set to be called BraTS2015. The experiments demonstrate that Tamura texture is very useful in the segmentation of brain tumors, especially the feature of line-likeness. The superior performance of the proposed ensemble SVM classifier is demonstrated by comparison with single SVM classifiers as well as other methods.

The authors propose an original solution for segmentation using Tamura Texture and ensemble SVM structure.

The purpose of this study is to systematically analyze the evolution of health tourism development, identify relevant themes and segments of health tourism research and offer future research directions and practical implications for academic researchers and tourism practitioners worldwide using China as an example.

Using a bibliometric analysis, the present study comprehensively analyzes the theme, segments and the evolution of health tourism research over the past 40 years in China.

Major findings show that health tourism research in China could be divided into four stages with different characteristics, and three segments, including wellness tourism, health and wellness tourism and medical tourism. Findings also reveal the trend of health tourism development tends to be industrialized, diversified and systematic under the guidance of recent policies. Theoretically, based on the theoretical framework developed by Hall (2011), the present study contributes to the establishment and extension of the framework for health tourism within the context of China. Practically, findings can provide health tourism-related policy implications for the future development of health or health sector-integrated tourism.

The study proposes possible collaboration between government and academia in terms of health tourism-related policy formulation.

Through 40-year bibliometric analysis of health tourism evolution in China, the present study explores the main themes of health tourism development, identifies the segments of health tourism and analyzes the development stages of health tourism. Findings should be of use to international readers to better understand the uniqueness of health tourism development and find out possible future health tourism development research directions. As a result, major contributions of this paper are the comprehensive analysis of the evolution of health tourism research and the implications on other countries and regions to adopt a pragmatic approach to explore the trend and unique characteristics of health tourism for future development.

本研究旨在系统地分析中国健康旅游的演变过程, 探索健康旅游研究的相关主题及细分领域, 并为全球学术研究人员及旅游从业者提供未来的研究方向。

此研究通过文献计量学的研究方法, 全面分析了中国近40年健康旅游研究的主题、细分以及演变。

中国健康旅游研究根据其发展特点可以分为四个阶段及三个细分主题：分别是养生旅游, 康养旅游及医疗旅游。调查结果还表明, 在近期政策的引导下, 健康旅游发展趋于产业化、多元化和系统化。从理论意义来说, 本研究基于Hall (2011) 提出的理论框架, 构建了中国背景下的健康旅游框架。从实践意义来说, 研究结果可以为健康和旅游业相关部门提供政策建议。

此研究还有助于促进政府和学术界在健康旅游政策制定方面的合作。

此研究通过对中国近40年健康旅游的研究进行文献计量分析, 探索了健康旅游发展的主题, 分析了健康旅游的细分市场以及发展阶段。研究结果有助于学术界及旅游业更好地了解健康旅游发展的独特性及未来健康旅游的研究方向。因此, 本研究的主要贡献是全面地分析了健康旅游研究的演变, 并有助于其他国家/地区探索未来健康旅游的发展趋势和其独特特征。

El propósito del presente estudio es analizar sistemáticamente la evolución del desarrollo del turismo de salud, identificar temas y segmentos relevantes de la investigación en turismo de salud y ofrecer direcciones de investigación futuras e implicaciones prácticas para investigadores académicos y profesionales del turismo en todo el mundo utilizando a China como ejemplo.

Mediante un análisis bibliométrico, el presente estudio analiza exhaustivamente la temática, los segmentos y la evolución de la investigación sobre turismo de salud en los últimos 40 años.

Los principales hallazgos muestran que la investigación del turismo de salud en China podría dividirse en cuatro etapas con diferentes características y tres segmentos, incluido el turismo de bienestar, el turismo de salud y bienestar y el turismo médico. Los hallazgos también revelan que la tendencia del desarrollo del turismo de salud tiende a ser industrializado, diversificado y sistemático bajo la guía de políticas recientes. El presente estudio hace aportes tanto teóricos como prácticos. Teóricamente, basado en el marco teórico desarrollado por Hall (2011), el presente estudio contribuye al establecimiento y extensión del marco para el turismo de salud en el contexto de China. En la práctica, los hallazgos pueden proporcionar implicaciones políticas relacionadas con el turismo de salud para el desarrollo futuro de la salud o el turismo integrado en el sector de la salud.

El estudio también propone una posible colaboración entre el gobierno y la academia en términos de formulación de políticas relacionadas con el turismo de salud.

A través del análisis bibliométrico de 40 años de la evolución del turismo de salud, el presente estudio explora los temas principales del desarrollo del turismo de salud, identifica los segmentos del turismo de salud y analiza las etapas de desarrollo del turismo de salud. Los hallazgos deberían ser de utilidad para los lectores internacionales para comprender mejor la singularidad del desarrollo del turismo de salud y descubrir posibles direcciones futuras de investigación sobre el desarrollo del turismo de salud. Como resultado, las principales contribuciones de este documento son el análisis exhaustivo de la evolución de la investigación en turismo de salud y las implicaciones en otros países y regiones para adoptar un enfoque pragmático para explorar la tendencia y las características únicas del turismo de salud para el desarrollo futuro.

City wall is an important symbol of ancient Chinese cities with unique geographical and cultural characteristics. Thus, the preservation of this historic landmark is considered significantly important. However, numerous residential construction activities and changes in ecological environment have destructed a great portion of the city walls in recent years. This study looks into the preservation of the ancient city walls from the systematic perspective and in line with the actual characteristics of Longdong Region to provide guideline measures for the protection and restoration of such landmark. Cognition and preservation are adopted extensively to investigate the specific situation of and the factors that influence the ancient city walls in this region. Preservation strategies for the city walls, including the “Axis-Point” system, planning control, and authenticity readability, are presented. The ancient city walls in Longdong Region can be preserved by protecting the entire region, the city, and the main wall body. The systematic method and preservation strategies at the “macro perspective,” “medium perspective” and “micro perspective” levels can solve the preservation problems of the ancient city walls in Longdong Region effectively.

Asks on whose behalf the black woman poet in the USA speaks, what type of language she uses and what audience she has. Points out that an earlier lack of tradition meant that originally white styles of language were used and aimed at the white audience. Looks at the rise of the blues era and the “blueswoman”. Considers the work of Phillis Wheatley, Alice Dunbar Nelson, Anne Spencer and Angelina Grimke together with Margaret Walker and singers such as Ma Rainey and Bessie Smith. Finally, outlines the development of a political era and the growing sexual freedom of black women and the impact their writings.

This paper aims to compare the Greek and Chinese rhetorical traditions and explore their influences on today’s business and marketing communication across relevant cultures. In particular, it uses the Aristotelian persuasive orientations as reference points to introduce the Chinese rhetoric, and interpret cultural differences in persuasion from a historical and sociocultural perspective. It has been found that Greek and Chinese rhetoric and persuasion were developed to meet the needs of the social and cultural environments and this rule still applies to today’s business communication. The logical approach has been emphasised in the English rhetorical tradition while both qing (emotional approach) and li (logical approach) are the focus of persuasion in the Chinese tradition. This difference is also the root of cultural differences in modern business communication. Findings from both English and Chinese texts and data are examined to substantiate our focal argument.

This study attempts to document the impact of financial leverage on corporate innovation in the Chinese nonfinancial public firms listed on Shenzhen and Shanghai stock exchanges.

The firm-level data are collected from CSMAR database for ten years, ranging from 2007 to 2016. The authors have employed the panel fixed effects model and further system GMM approach for analysis. The sample is segregated on the basis of state (SOE) and nonstate ownership (NSOE) to check for the diverse effects. In total, three different proxies of financial leverage are used to unearth the varying impact of short-time and long-term leverage separately. Further, corporate innovation is divided into input innovation (R&D/Sales and R&D/Assets) and output innovation (patents and inventions).

The results suggest that financial leverage is detrimental to the input innovation while conducive for the output innovation when measured by the number of patents. Contrarily, leverage has a negative influence over the output innovation when measured by the number of inventions. This implies that leverage is more damaging for the highest form of innovativeness (inventions) in China. Input innovation is more sensitive to the changes in long-term leverage versus short-term leverage. Further, the authors find that innovation in SOEs is more sensitive to the changes in the leverage as compared to the NSOEs. The results are free from the threat of endogeneity and identification problems, as reported by the system GMM model.

The authors did not segregate the sample on the basis of industry/sector.

The firms pursuing a strategy of radical innovation should try to keep their debt levels lower in order to achieve a higher innovation performance. Although, a rise in the leverage may mean an increased access to finance for a firm but such an access comes at a cost in the form of damage to the corporate innovation. However, increased debt financing may not be so bad for the firms that want to achieve a moderate and not the highest level of innovation. Such firms can produce recurring and synergic effects with debt financing and moderate innovation, once they achieve a level of innovation performance that satisfies their financiers.

To the best of authors’ knowledge, this is probably the first study to check the impact of firm-level financial leverage on both input and output innovation in the Chinese public-listed nonfinancial firms' panel data perspective till now.

This study aims to establish a reliable index to identify interdisciplinary breakthrough innovation effectively. We constructed a new index, the D_Div index, for this purpose.

The D_Div index incorporates the degree of interdisciplinarity in the breakthrough index. To validate the index, a data set combining the publication records and citations of Nobel Prize laureates was divided into experimental and control groups. The validation methods included sensitivity analysis, correlation analysis and effectiveness analysis.

The sensitivity analysis demonstrated the D_Div index’s ability to differentiate interdisciplinary breakthrough papers from various categories of papers. This index not only retains the strengths of the existing index in identifying breakthrough innovation but also captures interdisciplinary characteristics. The correlation analysis revealed a significant correlation (correlation coefficient = 0.555) between the interdisciplinary attributes of scientific research and the occurrence of breakthrough innovation. The effectiveness analysis showed that the D_Div index reached the highest prediction accuracy of 0.8. Furthermore, the D_Div index outperforms the traditional DI index in terms of accuracy when it comes to identifying interdisciplinary breakthrough innovation.

This study proposed a practical and effective index that combines interdisciplinary and disruptive dimensions for detecting interdisciplinary breakthrough innovation. The identification and measurement of interdisciplinary breakthrough innovation play a crucial role in facilitating the integration of multidisciplinary knowledge, thereby accelerating the scientific breakthrough process.