Search results

This study examined the impact of environmental factors on consumers’ intention to use buy online in-store returns (BORS) services. Specifically, it investigates how integrating environmental knowledge and consequence awareness into the theory of planned behavior (TPB) influences consumers’ intention to adopt BORS services.

Data were collected through a structured questionnaire and analyzed using statistical methods to explore the relationships between attitude, subjective norm, perceived behavioral control, environmental factors and intention to use BORS services.

The findings indicate that attitude, subjective norm and environmental knowledge significantly increase consumers’ intention to use BORS services. Additionally, the interaction of attitude and environmental knowledge further enhances consumers’ intention to use BORS services.

This study contributes to the limited literature on the drivers of consumers’ adoption of BORS services by integrating environmental factors with TPB. It provides new insights into how targeted environmental education and promotion activities can influence consumers’ behavior toward sustainable practices, providing valuable strategies for retailers to support sustainable development goals.

This paper aims to study the effect of microcrystalline cellulose (MCC) on the mechanical property and shape memory property of water-borne epoxy (WEP).

In the present study, the MCC/WEP composites were successfully prepared by melt-blending, freeze-drying and hot-pressing. The mechanical property tests were performed using a tensile test instrument (Instron Corp, Norwood, Massachusetts, USA). dynamic mechanical analysis Q800 was performed to analyze the sample’s dynamic mechanics. The thermal–mechanical cycle tests performed on a thermal mechanical analysis (TMA) Q400 in dynamic TMA mode enabled to analysis of the shape memory properties of the MCC/WEP composites.

The results showed that the inclusion of 2 wt.% MCC led to significant improvements in tensile strength and modulus of the composites, with tensile strength increasing by 33.2% and modulus expanding by 65.0%. Although the inclusion of the MCC into WEP enhanced the shape memory property, the MCC/WEP composites still maintained good shape memory fixity and shape memory recovery ratio of more than 95.0%.

This study has a significant reference value for improving the mechanical properties of WEP and other water-borne shape memory polymers.

Propaganda is a prevalent technique used in social media to intentionally express opinions or actions with the aim of manipulating or deceiving users. Existing methods for propaganda detection primarily focus on capturing language features within its content. However, these methods tend to overlook the information presented within the external news environment from which propaganda news originated and spread. This news environment reflects recent mainstream media opinions and public attention and contains language characteristics of non-propaganda news. Therefore, the authors have proposed a graph-based multi-information integration network with an external news environment (abbreviated as G-MINE) for propaganda detection.

G-MINE is proposed to comprise four parts: textual information extraction module, external news environment perception module, multi-information integration module and classifier. Specifically, the external news environment perception module and multi-information integration module extract and integrate the popularity and novelty into the textual information and capture the high-order complementary information between them.

G-MINE achieves state-of-the-art performance on both the TSHP-17, Qprop and the PTC data sets, with an accuracy of 98.24%, 90.59% and 97.44%, respectively.

An external news environment perception module is proposed to capture the popularity and novelty information, and a multi-information integration module is proposed to effectively fuse them with the textual information.

The prevalence of artificial intelligence (AI) has considerably affected management and society. This paper aims to explore its potential impact on hospitality industry employees, bringing enlightenment to both employees and managers.

Data were collected from a survey of 432 employees who worked in full-service hotels in China. Structural equation modeling (SEM) was used to analyze the data.

Results presented a positive relationship between AI awareness and job burnout. No significant direct relationship was found between AI awareness and career competencies. Organizational commitment mediated the relationship between AI awareness and career competencies, as well as the relationship between AI awareness and job burnout.

This study contributes to human resource management in the hospitality industry to theoretical and practical aspects. Theoretically, it enriched both career theory and fit theory. Practically, this study reminds managers to pay attention to the adverse effect of AI on human capital. It also enlightens the manager to think of the positive effects that AI may bring. Managers should provide proper support to overcome AI’s threat to human resources.

Practically, this study reminds managers to pay attention to the adverse effect of AI on human capital. It also enlightens the manager to think of the positive effects that AI may bring. Managers should provide proper support to overcome AI’s threat to human resources.

The study aims to analyze the impact of AI from a career perspective. It provided theoretical support and evidence for hotel managers for the effects of AI awareness on hotel employees. The study conveys a potential topic of concern that the hospitality industry may face in the future.

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

The purpose of this paper is to investigate the relationships between business risks and credit choices of 400 farm households surveyed in Shaanxi province in October 2007 in the Yangling district. More specifically, this paper investigates whether or not rural farm households in China balance business risks from agricultural production with financial risk from the use of debt.

The data were collected through a survey of 400 farm households in Shaanxi province conducted in October 2007. Four separate regressions are run using a credit measure as the dependent variable and measures of profitability, risk, risk aversion, and demography, and debt source (formal versus informal lending) as independent variables.

The model shows evidence of risk balancing. That is, there is strong evidence that Chinese farmers reduce credit use and financial risk, as business risks increase.

The results suggest that Chinese policy makers could encourage the use of finacial leverage and prudent debt use by offering risk reducing programs such as crop insurance, weather insurance, or price insurance.

This paper uses a unique survey form to collect production risk data as well as gather information on credit use and sources. Data were collected so that risk measures could easily be computed using a triangular distribution. Furthermore, this is believed to be the first empirical validation of the risk balancing hypothesis.

The discrepancy between the content of an article and its title is a key characteristic of fake news. Current methods for detecting fake news often ignore the significant difference in length between the content and its title. In addition, relying solely on textual discrepancies between the title and content to distinguish between real and fake news has proven ineffective. The purpose of this paper is to develop a new approach called semantic enhancement network with content–title discrepancy (SEN–CTD), which enhances the accuracy of fake news detection.

The SEN–CTD framework is composed of two primary modules: the SEN and the content–title comparison network (CTCN). The SEN is designed to enrich the representation of news titles by integrating external information and position information to capture the context. Meanwhile, the CTCN focuses on assessing the consistency between the content of news articles and their corresponding titles examining both emotional tones and semantic attributes.

The SEN–CTD model performs well on the GossipCop, PolitiFact and RealNews data sets, achieving accuracies of 80.28%, 86.88% and 84.96%, respectively. These results highlight its effectiveness in accurately detecting fake news across different types of content.

The SEN is specifically designed to improve the representation of extremely short texts, enhancing the depth and accuracy of analyses for brief content. The CTCN is tailored to examine the consistency between news titles and their corresponding content, ensuring a thorough comparative evaluation of both emotional and semantic discrepancies.

This paper examines the pre-factors of college students’ entrepreneurial behaviors and how their background characteristics affect corporate financial performance in high-tech businesses.

About 67 high-tech businesses in China focusing on technical innovation from the Guotai’an database are selected to carry out empirical analysis.

It is observed that the age, educational and professional backgrounds of college entrepreneurs profoundly influence their ventures geared toward high-tech innovation. Moreover, the transformation abilities, managerial proficiency and growth capabilities, which characterize these ventures, notably affect business performance. They further serve as a moderator in the relationship between the entrepreneurial backgrounds of college students and the overall business performance of their enterprises.

It insinuates novel strategic avenues for collegiate entrepreneurs’ entrepreneurial mindset and industrial positioning. Moreover, our findings will not only augment the practical research in the realm of collegiate entrepreneurship but also enhance the study of technological innovation theories, thereby offering further insight and guidance for collegiate entrepreneurs’ innovative endeavors and entrepreneurial pursuits.

Adding Pd element to Au wire can improve the reliability of Au-Al bonding, but the mechanism of Pd element has not been well revealed so far. The purpose of this study is to reveal in more detail the mechanism of the role of Pd elements in Au/Al bonding.

In this paper, the microstructure changes and tensile data of 99.99% (4N) gold wire and 99% (2N) gold wire with 1 at % Pd were compared through high-temperature thermal aging treatment of the specimens, so as to explore the influence mechanism of Pd element on Au-Al bonding reliability.

The addition of Pd element effectively reduces the thickness of intermetallic compounds (IMCs) layer and strengthens the fracture tension and reliability. Compared with the 4N specimen, the average thickness of the IMCs layer of the 2N specimen under the same conditions is reduced by 1 µm, and the tensile value of the 2N specimen is increased by 1−3 g. Stored at 200°C for 200 h, the failure rate of bond point of 4N specimen reached 94.64%, and that of 2N specimen was 20%, with a difference of 4.73 times.

Through comparative analysis of the data, this study found that the doping of Pd element in Au-Al IMCs in the early stage slowed down the growth rate of the IMCs, and the precipitation of Pd element in the late stage to form a better Pd-rich layer hindered the element mutual diffusion behavior between Au and Al.