Search results

Three-dimensional (3D) food printers are revolutionizing food production with personalized, sustainable and efficient meal creation. This study aims to explore the factors driving consumer intentions to purchase three-dimensional (3D) food printers. These innovative devices are gaining popularity for their ability to produce intricate, customizable food designs with remarkable precision and convenience. By leveraging the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, the research examines key variables such as performance expectancy, effort expectancy, social influence, facilitating conditions (FCD), hedonic motivation and perceived product value. The aim is to understand how these factors shape consumer behavior and decision-making, providing insights into the adoption dynamics of 3D food printers for professional and domestic use.

This study collected 973 valid responses through an online survey. The data were analyzed using partial least squares structural equation modeling.

Performance expectancy, social influence and perceived product value significantly enhance consumers’ intention to purchase 3D food printers. In contrast, effort expectancy, FCD and hedonic motivation show no statistically significant impact on their usage intention.

Companies in the 3D food printing industry should prioritize improving product performance and leveraging social influencers to spark consumer interest. Educating the public about the benefits of 3D food printing is essential for building market acceptance and demand. Governments should contemplate implementing policies and regulations encouraging companies to invest in research and development in this field. This study acknowledges its limitations and recommends directions for future research.

This study establishes its originality by integrating hedonic motivation and perceived product value with the original UTAUT framework to investigate Chinese households’ intentions to use a 3D food printer.

This research is aimed to examine how environmental pollution affects consumers' preference for self-improvement products.

Through a series of three experimental studies, this research substantiates our hypotheses by employing various manipulations of environmental pollution and examining different types of self-improvement products.

The research demonstrates that environmental pollution enhances consumers' preference for self-improvement products via the mediation of perceived environmental responsibility. And the effect is negatively moderated by social equity sensitivity.

The recurrent incidence of environmental pollution has elicited significant concern among the general public and academic scholars. An overwhelming majority of research examining the impact of pollution on consumer behavior has concentrated on its influence on environmentally friendly and healthy consumption patterns. Nevertheless, the current research proposes that pollution fosters a preference for products associated with self-improvement, mediated by perceived environmental responsibility, with the effects being moderated by social equity sensitivity.

Political factors play a crucial role in China's initial public offering (IPO) market due to its distinctive institutional context (i.e. “economic decentralization” and “political centralization”). Given the significant level of IPO underpricing in China, we examine the impact of local political uncertainty (measured by prefecture-level city official turnover rate) on IPO underpricing.

Using 2,259 IPOs of A-share listed companies from 2001 to 2019, we employ a structural equation model (SEM) to examine the channel (voluntarily lower the issuance price vs aftermarket trading) through which political uncertainty affects IPO underpricing. We check the robustness of the results using bootstrap tests, adopting alternative proxies for political uncertainty and IPO underpricing and employing subsample analysis.

Local official turnover-induced political uncertainty increases IPO underpricing by IPO firms voluntarily reducing the issuance price rather than by affecting investor sentiment in aftermarket trading. These relations are stronger in firms with pre-IPO political connections. The effect of political uncertainty on IPO underpricing is also contingent upon the industry and the growth phase of an IPO firm, more pronounced in politically sensitive industries and firms listed on the growth enterprise market board.

Local government officials in China usually have a short tenure and Chinese firms witness significantly severe IPO underpricing. By introducing the SEM model in studying China IPO underpricing, this study identifies the channel through which local government official turnover to political uncertainty on IPO underpricing.

The aim of this study is to investigate the factors that influence the readiness to adopt artificial intelligence (AI) tools within Moroccan auditing firms.

A quantitative research design was used, using survey data to examine the influence of perceived usefulness (PU), ease of use (EU) and top management commitment (TMC) on AI adoption readiness (AIAR) in auditing. A conceptual model, drawing from the technology acceptance model (TAM) and supported by findings from previous literature, was proposed. The model was tested using partial least squares – structural equation modelling on data collected from 116 Moroccan respondents.

The study confirmed that PU and TMC do not significantly influence the AIAR in auditing in Morocco, whereas EU is positively and significantly associated to the AIAR.

The study presents findings based on data from a single country, which may limit the broader applicability of the results to other contexts or regions with different regulatory, cultural or economic environments.

The results suggest that TAM is not necessarily adapted to AI adoption within an emerging context like Morocco. The significant role of EU in AIAR suggests that Moroccan firms should prioritize the development and integration of AI tools that are intuitive and user-friendly. AI should be presented not only as a tool for enhancing audit quality but also as a means of reducing workload and improving efficiency. Furthermore, rather than relying solely on top-down mandates, a more decentralized approach to AI adoption could be effective, where individual auditors are empowered to experiment with AI tools and integrate them into their practices. This approach could foster a culture of innovation and gradual adoption, increasing the likelihood of successful AI integration within Moroccan auditing firms.

AI adoption in auditing can promote societal benefits by enhancing transparency, accountability and trust in both public and private sectors. In countries like Morocco, where financial transparency is lacking but vital for stability, AI can help reduce corruption, improve decision-making and foster public trust, ultimately supporting investment and social equity.

This paper offers an original contribution by examining AIAR in Morocco’s auditing sector, focusing on an emerging market and African context. Unlike studies in developed countries, it highlights the unique challenges and opportunities faced by Moroccan auditors, considering factors like PU, EU and TMC. It challenges organizations to assess their readiness and the ability of their employees to effectively integrate AI into their workflows.

This paper aims to focus on the research progress of intelligent self-healing anti-corrosion coatings in the aviation field in the past few years. The paper provides certain literature review supports and development direction suggestions for future research on intelligent self-healing coatings in aviation.

This mini-review uses a systematic literature review process to provide a comprehensive and up-to-date review of intelligent self-healing anti-corrosion coatings that have been researched and applied in the field of aviation in recent years. In total, 64 articles published in journals in this field in the last few years were analysed in this paper.

The authors conclude that the incorporation of multiple external stimulus-response mechanisms makes the coatings smarter in addition to their original self-healing corrosion protection function. In the future, further research is still needed in the research and development of new coating materials, the synergistic release of multiple self-healing mechanisms, coating preparation technology and corrosion monitoring technology.

To the best of the authors’ knowledge, this is one of the few systematic literature reviews on intelligent self-healing anti-corrosion coatings in aviation. The authors provide a comprehensive overview of the topical issues of such coatings and present their views and opinions by discussing the opportunities and challenges that self-healing coatings will face in future development.

This study aims to investigate the effect of different microstructures and its grain boundary character distribution (GBCD) on the corrosion behavior of weathering bridge steel.

The rust layer characteristics and corrosion resistance of specimens with different microstructures in the simulated industrial environment were studied by Electron Probe X-ray Micro-Analyzer, wavelength-dispersive spectrometer and electrochemical techniques. Electron backscatter diffraction technique was used to characterize the GBCD in steels with different microstructures.

Results revealed a significant difference in the corrosion susceptibility among the four microstructures, with corrosion rates decreasing in the following order: ferrite + pearlite > ferrite + bainite > bainite > martensite. The variation in corrosion resistance is primarily influenced by the microstructure type and the proportion of special grain boundaries, rather than the alloying elements. The proportion of Σ3 boundaries within the coincidence site lattice boundaries is positively correlated with improved corrosion resistance. A higher Σ3 boundary fraction resulted in a lower effective grain boundary energy, elevated self-corrosion potential, increased polarization resistance and reduced areas of localized galvanic corrosion; this led to enhanced inhibition of the electrochemical corrosion reaction, consequently reducing the corrosion rate.

This study elucidates and quantifies the intrinsic relationship between microstructure, GBCD and corrosion rate. This understanding is crucial for enhancing the corrosion resistance of weathering bridge steels in industrial atmospheric corrosion environments.

Green banking has evolved in the financial sector to reduce the negative impact of economic progress. However, customers’ behavior remains indifferent towards bank’s green initiatives across nations. Therefore, this study examines the various factors affecting the behavior of Indian banking customers towards green banking by extending the theory of planned behavior (TPB).

The study employed a quantitative research approach and distributed a self-administered questionnaire. Data from the 293 green banking service users in India’s Delhi-National Capital Region (NCR) have been collected using purposive and snowball sampling techniques. SPSS 26 and SmartPLS 3 were used to analyze data.

The findings explained that environmental concern substantially predicts customer attitude, subjective norms and perceived behavior control towards green banking. Moreover, all the constructs within the TPB model were found to substantially impact customers’ inclination to adopt green banking, thereby leading to actual behavior.

Academically, the findings have broadened the TPB model’s application by adding a new construct in the context of green banking while confirming its applicability. Practically, it advises financial regulators and banking personnel to prioritize establishing a conducive environment for customers, characterized by the accessibility of green banking services under favorable conditions and at affordable rates.

The study enhanced the understanding towards green banking by correlating different variables and extending the TPB model using SmartPLS 3 in the domain of green banking.

Drawing upon compensatory ethics theory, this study explored the underlying mechanisms through which gossipers engaged in helping behavior as a form of compensation after initiating negative workplace gossip.

Through a two-wave field study of 394 Chinese employees, this study tests theoretical hypotheses using path analysis and bootstrapping methods.

The findings suggested that negative workplace gossip positively influenced the gossipers’ helping behavior through moral self-image and guilt. Moreover, moral reflectiveness not only positively moderated the impacts of negative workplace gossip on moral self-image and guilt but also positively moderated the mediating effects of moral self-image and guilt in the relationship between negative workplace gossip and helping behavior.

These results enrich the theoretical research on negative workplace gossip, offer new perspectives for studying this phenomenon and provide a theoretical basis and decision-making reference for management practices.

This paper aims to compare the differences between single- and multi-person interactions in virtual tourism, underpinned by the stimulus-organism-response (S-O-R) framework and media richness theory (MRT).

In this study, quantitative data gathered from questionnaires applied to 558 individuals was analyzed by using partial least squares structural equation modeling. The moderating role of interaction type was tested through multigroup analysis (MGA).

The results showed that vividness positively influenced telepresence, perceived attractiveness and authentic experiences; telepresence positively affected authentic experiences and perceived attractiveness; and authentic experiences and perceived attractiveness positively impacted willingness to visit in both interaction groups. A difference was detected between the two groups in that perceptions of media vividness were more easily transformed into a willingness to visit through telepresence in the multi-person interaction group. Interaction type moderated the effect of vividness on telepresence. The vividness of the media had a more significant effect on telepresence among those who participated in virtual tourism together.

In this study, a model was developed to explain how media vividness affected willingness to visit by considering the relationships between telepresence, authentic experiences and perceived attractiveness in virtual reality, as well as the social interaction aspect.

本研究旨在比较虚拟旅游中单人和多人互动的差异, 基于刺激-有机体-反应（S-O-R）框架和媒介丰富度理论（MRT）。

本研究对 558 名受试者的问卷调查数据进行了定量分析, 采用 PLS-SEM 模型分析, 并通过多群组分分析（MGA）测试了互动类型的调节作用。

研究结果显示, 生动性对临场感、感知吸引力和真实体验有正向影响; 临场感对真实体验和感知吸引力有正向影响; 真实体验和感知吸引力对参观意愿有正向影响。两组之间的差异在于, 在多人互动组中, 媒介生动性更容易通过临场感转化为参观意愿。互动类型调节了生动性对临场感的影响, 参与虚拟旅游的多人群体中, 媒介的生动性对临场感的影响更为显著。

本研究构建了一个模型, 解释了在虚拟现实中, 媒介生动性如何通过临场感、真实体验和感知吸引力的关系影响参观意愿, 同时考虑了社会互动的因素。

This study investigates the relationship between digitalization and agricultural carbon intensity from 2006 to 2021.

Utilizing panel data from 30 provinces in China from 2006 to 2021, this study employs a threshold and a spatial Durbin model to investigate the relationship between digitalization and agricultural carbon intensity. In addition, a heterogeneity analysis was conducted to understand variations across regions.

The study used threshold models and spatial Durbin models to reveal that in agricultural production, digitalization can significantly reduce the carbon emission intensity of planting and livestock production. Through the threshold effect, it was found that the effectiveness of digitization in curbing emissions varies by region and is influenced by the level of urbanization, with the inhibitory effect being: western > central > eastern. In addition, through spatial analysis, it was found that the impact of digitalization on carbon emission intensity has significant spatial effects, presenting a “high-high” and “low-low” clustering pattern. Moreover, through the Durbin model, digitization exhibits a significant negative spatial impact on the planting industry, and the development of the local digitalization can significantly reduce the carbon emission intensity of the planting industry in neighboring areas. There is a significant positive spatial effect on livestock production, and the development of local digitalization will, to some extent, increase the carbon emission intensity of livestock production in neighboring areas. This study underscores the critical importance of digitalization in reducing agricultural carbon emissions and highlights the necessity for tailored digital strategies that consider regional characteristics and urbanization levels.

This study shows the critical importance of digitalization in reducing agricultural carbon emissions and highlights the necessity for tailored digital strategies that consider regional characteristics and urbanization levels.

This paper pioneers the investigation of the spatial impact of digitalization on agricultural carbon emissions using provincial-level panel data and classifies agriculture into planting and livestock production. This study contributes to the literature by filling the research gap and enhancing our understanding of the relationship between digitalization and environmental sustainability in rural areas.