Search results

This study investigates the link between board compensation and corporate philanthropy, in which the financial incentives given to board members are considered as a factor that affects a firm's philanthropic activities. The sample of publicly listed companies from 2014 to 2020 is adopted to conduct a multiple regression on the impact of board compensation on corporate philanthropic contributions. Our study results indicate that board compensation, especially when it is tied to long-term performance indicators, is positively related to greater levels of corporate philanthropy. This relationship demonstrates the direction that the financial motivations of board members take in shaping the agenda of social responsibility of a company. This research incorporates the views of agency theory and stakeholder theory into the literature on corporate governance and corporate social responsibility (CSR), thus offering practical implications for policymakers, shareholders, and corporate executives who want to develop a culture of philanthropy in their organizations. Along with that, the study outlines possible directions for further research such as the impact of nonmonetary incentives and the role of board diversity on philanthropic results.

The objective of this study is to provide a systematic review of the literature on artificial intelligence (AI) in customer-facing financial services, providing an overview of explored contexts and research foci, identifying gaps in the literature and setting a comprehensive agenda for future research.

Combining database (i.e. Scopus, Web of Science, EBSCO, ScienceDirect) and manual journal search, the authors identify 90 articles published in Australian Business Deans Council (ABDC) journals for investigation, using the TCCM (Theory, Context, Characteristics and Methodology) framework.

The results indicate a split between data-driven and theory-driven research, with most studies either adopting an experimental research design focused on testing the accuracy and performance of AI algorithms to assist with credit scoring or investigating AI consumer adoption behaviors in a banking context. The authors call for more research building overarching theories or extending existing theoretical perspectives, such as actor networks. More empirical research is required, especially focusing on consumers' financial behaviors as well as the role of regulation, ethics and policy concerned with AI in financial service contexts, such as insurance or pensions.

The review focuses on AI in customer-facing financial services. Future work may want to investigate back-office and operations contexts.

The authors are the first to systematically synthesize the literature on the use of AI in customer-facing financial services, offering a valuable agenda for future research.

The purpose of this paper is to discover the most important genes generated by the gene expression arrays, responsible for the recognition of particular types of cancer.

The paper presents the analysis of different techniques of gene selection, including correlation, statistical hypothesis, clusterization and linear support vector machine (SVM).

The correctness of the gene selection is proved by mapping the distribution of selected genes on the two‐coordinate system formed by two most important principal components of the PCA transformation. Final confirmation of this approach are the classification results of recognition of several types of cancer, performed using Gaussian kernel SVM.

The results of selection of the most significant genes used for the SVM recognition of seven types of cancer have confirmed good accuracy of results. The presented methodology is of potential use in practical application in bioinformatics.

The purpose of this paper is to explore the changes of the scale of urban tourists in mainland China under the impact of COVID-19 and, specifically, the following questions: how did the scale of domestic tourists change nationwide and in the seven geographic regions? What are the differences in the changes among the seven geographic regions? What are the changes in the hot spot areas and spatial clustering of domestic tourists across the country?

Using the data of domestic tourist arrivals in 337 cities in mainland China from 2018 to 2021, this research analyzes the absolute differences and relative differences in the scale of domestic tourists nationwide and in seven geographic divisions with the help of indicators such as range analysis, standard deviation, coefficient of variation and Herfindahl–Hirschman Index and explores the changes in the hot spot areas and spatial concentration degree of the spatial scale of domestic tourists nationwide under the influence of the epidemic using kernel density analysis and spatial auto-correlation analysis.

The absolute differences in all seven geographical divisions continue to increase during 2018–2021. The domestic tourism in southwest China is extremely uneven. Absolute differences in the northwest and northeast regions are relatively small, and the development in attracting domestic tourists is more balanced. Relative differences in southwest China are comparatively large, with the trend of uneven development being obvious. The northeast, northwest and eastern regions of China are small, and the development is more balanced. The popularity of domestic tourism in the Beijing–Tianjin–Hebei region, as well as the Yangtze River Delta region, continues to decline and then pick up in 2021. The inland southwest region became a new domestic tourism hot spot in 2021. The size of domestic tourists from 2018 to 2021 in mainland China cities shows a significant positive spatial correlation, and there is a spatial agglomeration phenomenon, but some regional agglomeration types change from 2018 to 2021.

The impact of the epidemic on the number and spatial scale of domestic tourism in China has been clarified, which makes up for the comparison of domestic tourism changes before and after the epidemic. A clear understanding of the changes in the number and spatial scale of domestic tourists in different regions after the epidemic is conducive to the development of domestic tourism revitalization strategies in accordance with the actual situation of each province and promotes the internal circulation of Chinese tourism.

This paper tries to clarify the quantitative scale of domestic tourism in different regions after the epidemic, which is conducive to the development of domestic tourism revitalization strategies in cities in different regions according to regional characteristics and the actual situation of each province and to promote the healthy operation of the internal circulation of tourism in China. This paper also tries to show the changes of domestic tourism market hot spots, agglomeration conditions changes before and after the outbreak and the clarity of tourists’ preference space changes.

Scale of domestic tourists; Absolute difference; Relative difference; Spatial hot spot distribution; Spatial agglomeration change

本文旨在探寻疫情影响下中国大陆城市游客规模演化规律, 具体而言, 疫情影响下, 全国及七大地理分区的国内游客量规模变化如何？七大地理地区的变化有何差异？以及疫情影响下, 全国国内游客空间规模的热点区域和空间集聚程度有何变化？

利用2018-2021年中国大陆337各城市的国内游客量数据, 借助极差、标准差、变异系数、赫芬达尔指等指标分析全国及七大地理分区国内游客规模的绝对差异和相对差异; 借助核密度分析、空间自相关分析等ArcGIS分析工具, 探寻疫情影响下全国国内游客空间规模的热点区域和空间集聚程度的变化情况。

①绝对差异方面, 七大地理分区的绝对差异均持续增大。西南地区的游客量的绝对差异巨大, 国内游发展极不均衡。西北地区、东北地区绝对差异相对较小, 在吸引国内游客方面发展较为均衡。②相对差异方面, 西南地区的国内游发展相对差异较大, 发展不均衡趋势明显; 东北地区、西北地区、华东地区的国内游发展相对差异较小, 发展较为均衡。③热点区域变化方面, 京津冀地区、长三角地区的国内旅游热度持续下降, 在2021年有所回升; 内陆西南地区在2021年成为新的国内游热点区域。④2018年至2021年城市国内游客量规模均呈现出显著的空间正相关的关系, 存在着空间集聚现象, 但部分区域集聚类型在2018到2021年间发生变化。

①理论意义：明晰了疫情对中国国内旅游人次的数量规模和空间规模的影响, 弥补了当前疫情前后国内旅游业变化对比的研究; 阐明了疫情前后中国城市国内游客空间格局的变化, 拓展了研究情景, 丰富了中国旅游业时空变化的相关研究。②实践意义：明晰了疫后不同地区国内旅游人次的数量规模和空间规模变化情况, 以及国内旅游市场热点变化和游客空间偏好变化, 有利于各地区城市对症下药, 制定符合各省份实际情况的国内旅游业振兴策略, 促进中国旅游业内循环。

Unhealthy diets are associated with an increased risk of non-communicable diseases and present a significant public health challenge. When developing effective interventions and policies, consideration must be given to the unique social culture in which food choice is embedded. Health vulnerabilities to poor nutrition exist throughout life but may be influenced by socio-cultural factors such as age. This study aimed to assess the attitudes of older or younger Chinese consumers towards healthy eating and explore the factors influencing their food choices.

Semi-structured interviews were conducted in Wuhan, China, with 20 consumers aged 18–25 (Group A) and 20 consumers aged 65 and over (Group B).

Thematic analysis revealed that the two groups had positive attitudes towards healthy eating, although Group A participants were more knowledgeable. Time pressure, food prices and social networks differentially influence healthy eating practices across age groups.

Given China’s economic and cultural context, healthy eating interventions should consider the individual characteristics and food preferences of the different age groups. This approach can optimize targeted healthy eating interventions, and media communications related to healthy eating.

This paper aims to address a distributed assembly permutation flow-shop scheduling problem (DAPFSP) considering budget constraints and factory eligibility. The first stage of the considered production system is composed of several non-identical factories with different technology levels and so the factories' performance is different in terms of processing time and cost. The second stage is an assembly stage wherein there are some parallel work stations to assemble the ready parts into the products. The objective function is to minimize the maximum completion time of products (makespan).

First, the problem is formulated as mixed-integer linear programing (MIP) model. In view of the nondeterministic polynomial (NP)-hard nature, three approximate algorithms are adopted based on variable neighborhood search (VNS) and the Johnsons' rule to solve the problem on the practical scales. The proposed algorithms are applied to solve some test instances in different sizes.

Comparison result to mathematical model validates the performance accuracy and efficiency of three proposed methods. In addition, the result demonstrated that the proposed two-level self-adaptive variable neighborhood search (TLSAVNS) algorithm outperforms the other two proposed methods. Moreover, the proposed model highlighted the effects of budget constraints and factory eligibility on the makespan. Supplementary analysis was presented by adjusting different amounts of the budget for controlling the makespan and total expected costs. The proposed solution approach can provide proper alternatives for managers to make a trade-off in different various situations.

The problem of distributed assembly permutation flow-shop scheduling is traditionally studied considering identical factories. However, processing factories as an important element in the supply chain use different technology levels in the real world. The current paper is the first study that investigates that problem under non-identical factories condition. In addition, the impact of different technology levels is investigated in terms of operational costs, quality levels and processing times.

The implications of metallic biomaterials involve stress shielding, bone osteoporosis, release of toxic ions, poor wear and corrosion resistance and patient discomfort due to the need of second operation. This study aims to use additive manufacturing (AM) process for fabrication of biodegradable orthopedic small locking bone plates to overcome complications related to metallic biomaterials.

Fused deposition modeling technique has been used for fabrication of bone plates. The effect of varying printing parameters such as infill density, layer height, wall thickness and print speed has been studied on tensile and flexural properties of bone plates using response surface methodology-based design of experiments.

The maximum tensile and flexural strengths are mainly dependent on printing parameters used during the fabrication of bone plates. Tensile and flexural strengths increase with increase in infill density and wall thickness and decrease with increase in layer height and wall thickness.

The present work is focused on bone plates. In addition, different AM techniques can be used for fabrication of other biomedical implants.

Studies on application of AM techniques on distal ulna small locking bone plates have been hardly reported. This work involves optimization of printing parameters for development of distal ulna-based bone plate with high mechanical strength. Characterization of microscopic fractures has also been performed for understanding the fracture behavior of bone plates.

This paper aims to focus on the preparation of Kevlar fiber (KF) and alkaline hydrolyzed KF (KF-H) to improve the dispersed condition of polyaniline (PAn), as the aggregation of PAn would lead to some adsorption sites buried. And then the materials were used to enrich anionic dye Congo red (CR) from aqueous solution.

The materials (KF@PAn and KF-H@PAn) were designed by means of “diffusion-interfacial-polymerization” under mild condition as high affinity due to the structural properties of PAn, KF and KF-H. The dispersed degree of PAn on the surface of KF and KF-H was validated according to adsorption efficiency for CR.

The content of PAn introduced was not beyond 20 wt.%, while adsorption capacity for CR was significantly enhanced by 4–8 times (on the basis of kinetic data) according to the calculation only by the content of PAn due to KF and alkaline hydrolyzed KF exhibited almost no adsorption for CR, indicating dispersed situation of PAn coating was greatly enhanced and more active sites exposed, which was favorable for the adsorption process. Presence of NaCl would exhibit a more or less positive effect on CR uptake, suggesting the materials could be used for high salt environment.

The investigated means of dispersed degree of PAn on the surface of KF and KF-H are the further and future investigation.

This study will provide a method to improve the dispersed situation of PAn and a theoretical support to treat anionic dyes from aqueous solution especially for salt environment.

The results showed that the dispersed condition of PAn on the surface of KF and KF-H was greatly improved. According to the adsorption capacities for CR, it can be concluded that part of adsorption sites were buried due to the aggregation of PAn, and introduction of KF and KF-H, buried adsorption sites decreased greatly. This study will provide a method to decrease buried adsorption sites of PAn and a contribution for their convenient application in wastewater treatment especially for high salt environment.

Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to experiment with different printing settings. The current study aims to propose a regression-based machine learning model to predict the mechanical behavior of ulna bone plates.

The bone plates were formed using fused deposition modeling (FDM) technique, with printing attributes being varied. The machine learning models such as linear regression, AdaBoost regression, gradient boosting regression (GBR), random forest, decision trees and k-nearest neighbors were trained for predicting tensile strength and flexural strength. Model performance was assessed using root mean square error (RMSE), coefficient of determination (R²) and mean absolute error (MAE).

Traditional experimentation with various settings is both time-consuming and expensive, emphasizing the need for alternative approaches. Among the models tested, GBR model demonstrated the best performance in predicting both tensile and flexural strength and achieved the lowest RMSE, highest R2 and lowest MAE, which are 1.4778 ± 0.4336 MPa, 0.9213 ± 0.0589 and 1.2555 ± 0.3799 MPa, respectively, and 3.0337 ± 0.3725 MPa, 0.9269 ± 0.0293 and 2.3815 ± 0.2915 MPa, respectively. The findings open up opportunities for doctors and surgeons to use GBR as a reliable tool for fabricating patient-specific bone plates, without the need for extensive trial experiments.

The current study is limited to the usage of a few models. Other machine learning-based models can be used for prediction-based study.

This study uses machine learning to predict the mechanical properties of FDM-based distal ulna bone plate, replacing traditional design of experiments methods with machine learning to streamline the production of orthopedic implants. It helps medical professionals, such as physicians and surgeons, make informed decisions when fabricating customized bone plates for their patients while reducing the need for time-consuming experimentation, thereby addressing a common limitation of 3D printing medical implants.

The purpose of this paper is to investigate the morphology evolution and the composition transformation of Au-Sn intermetallic compounds (IMCs) of the new Au/Sn-5Sb-1Cu-0.1Ni-0.1Ag/(Au)Ni solder joint during the high temperature aging.

Sn-5Sb-1Cu-0.1Ni-0.1Ag solder balls (500 µm in diameter), heat sink with structure of 7.4 µm Au layer on 5 µm Ni-plated Cu alloy and Si chip with 5.16 µm plated Au were used to fabricate micro-solder joints. The joints were performed in a furnace at 150°C for 150, 250 and 350 h aging. The samples were polished and deep etched before analyzed by metallographic microscope and scanning electron microscopy, respectively. Energy dispersive x-ray spectroscopy was used to identify the composition of the IMCs.

ß-(Au,Ni,Cu)₁₀Sn phase is formed during the soldering process. The IMCs evolution has two periods during the aging. The first is the ξ-(Au,Ni,Cu)₅Sn, ξ-(Au,Cu)₅Sn and δ-AuSn were formed and grew to form a full-compound joint after about 150 h aging. The second is the conversion of the full-compound joint. The IMCs converted to ξ′ phase when the aging time extends to 250 h, and transformed to ε-(Au,Ni,Cu)Sn₂ and η-(Au,Ni,Cu)Sn₄ after 350 h aging. The thicker gold layer and thinner solder joint can promote the growth of the IMCs. ß-(Au,Ni,Cu)₁₀Sn emerged in Au/SnSb-CuNiAg/(Au)Ni in this research, which is not usually found.

The results in this study have a significant meaning for the application of the new Sn-5Sb-1Cu-0.1Ni-0.1Ag in harsh conditions.