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This study aims to fabricate a novel electromagnetic interference (EMI) shielding composite aerogel with both thermal insulation and high temperature warning functions.

An emerging bio-based polypyrrole (PPy) gel/Fe₃O₄/calcium alginate (PFC) EMI shielding composite aerogel was prepared by freeze-drying and in situ polymerization method. First, Fe₃O₄/calcium alginate (CA) aerogel was obtained by freeze-drying the Fe₃O₄/CA mixture. Then, PPy/Fe₃O₄/CA was obtained by synthesizing PPy on the surface of CA/Fe₃O₄ aerogel through in situ polymerization. Finally, PPy/Fe₃O₄/CA was immersed in porphyrin solution (cross-linking agent) to get the final PFC EMI shielding composite aerogel.

Due to the matched impedance between Fe₃O₄ and PPy, the EMI shielding performance of PFC composite aerogel can reach up to −8 dB. In addition, the PFC EMI shielding composite aerogel also shows excellent self-extinguishing and thermal insulation properties. After leaving the flame, the burning PFC aerogel is quickly extinguished. When the PFC aerogel is placed on the heating plate at 230 °C, the temperature on the side of the aerogel away from the heating plate is only 90.3 °C after 5 min of heating. The electrical resistance of the PFC composite aerogel can be reduced from 3.62 × 104 O to 5 × 102 O to trigger the warning light after 3 s of exposure to the alcohol lamp flame. This reversible thermal resistance response characteristic can be used to give an early warning signal when the PFC encounters high temperature or flame.

This work provides a novel strategy for designing a multifunctional EMI shielding composite aerogel with repeatable high temperature warning performance. This PFC composite aerogel shows potential applications in the prevention of material combustion in high temperature electromagnetic environments.

As a distinctive form of communist heritage tourism, the ideology and government-led form of red tourism warrants an in-depth examination of how tourists consume and perceive it. This study aims to reveal tourists’ perception of red tourism through the lens of destination image.

This study collected 9,819 user-generated photographs within four types of red tourism destinations (RTDs) and used a computer visual and semiotic analysis approach to conduct photograph-based cognitive and affective attributes extraction. Network analysis further visualized the co-relations between cognitive images and affective images. ANOVA analysis compared the differences of the four types of destination images.

Ten dimensions of cognitive image and eight categories of affective image of red tourism were identified. It found that monuments, statues, memorial symbols were the distinctive cognitive features, and admiration was the most dominant emotion. Heterogeneity of destination images was identified among the four types of RTDs.

To the best of the authors’ knowledge, the study is one of the first to explore tourists’ consumption of red tourism through the lens of destination image, which reveals the inconsistencies between the officially projected images and tourists’ perceived images of red tourism. Using Plutchik’s model, it validates a series of positive and negative emotions contributing to the affective images of red tourism, which expands the findings of emotions within the extant red tourism research. Through combined applications of computer visual and semiotic analysis, ANOVA, network analysis and model visualization, the study provides an important methodological triangulation for photograph-based destination image studies.

红色旅游作为共产主义旅游的独特形式, 游客如何感知这种国家意识形态植入与政府主导型旅游值得深入研究。本研究旨在从目的地意象视角揭示游客红色旅游感知。

本研究收集四种类型的红色旅游地9819张用户生成照片, 利用计算机视觉-情感析法对照片进行认知和情感元素提取。复杂网络分析揭示了认知意象与情感意象之间的关联。方差分析比较了四种红色旅游地意象的差异。

本研究确定了红色旅游认知意象的十个维度和情感意象的八个类别。研究发现, 纪念碑、雕像、纪念符号是其独特的认知意象元素, 钦佩是其最主要的情感，四种类型红色旅游地意象存在差异性。

本文是同类研究中首次从目的地意象视角探索游客对红色旅游地感知, 揭示了红色旅游官方投射意象与游客感知意象之间的差异。利用Plutchik情感之轮模型, 验证了一系列积极和消极情绪构成红色旅游地情感意象, 拓展了红色旅游的情感发现。综合运用计算机视觉-情感分析、方差分析、网络分析和模型可视化等方法, 为基于照片的旅游目的地意象研究提供了一个重要方法。

Como forma distintiva del turismo del patrimonio comunista, la ideología y la forma gubernamental del turismo rojo justifican un examen en profundidad de cómo lo consumen y perciben los turistas. Este estudio pretende revelar la percepción que tienen los turistas del turismo rojo desde la perspectiva de la imagen del destino.

Este estudio recopiló 9.819 fotografías generadas por los usuarios dentro de cuatro tipos de destinos de turismo rojo, y utilizó un enfoque de análisis visual y semiótico por ordenador para llevar a cabo la extracción de atributos cognitivos y afectivos basados en fotografías. El análisis de redes visualizó además las correlaciones entre las imágenes cognitivas y las imágenes afectivas. El análisis ANOVA comparó las diferencias de los cuatro tipos de imágenes de destino.

Se identificaron diez dimensiones de imagen cognitiva y ocho categorías de imagen afectiva del turismo rojo. Se descubrió que los monumentos, las estatuas y los símbolos conmemorativos eran los rasgos cognitivos distintivos, y la admiración la emoción más dominante. Se identificó una heterogeneidad de imágenes de destino entre los cuatro tipos de destinos de turismo rojo.

El estudio es uno de los primeros en explorar el consumo de turismo rojo por parte de los turistas a través de la lente de la imagen del destino, lo que revela las incoherencias entre las imágenes proyectadas oficialmente y las imágenes percibidas por los turistas del turismo rojo. Utilizando el modelo de Plutchik, valida una serie de emociones positivas y negativas que contribuyen a las imágenes afectivas del turismo rojo, lo que amplía los hallazgos sobre las emociones dentro de la investigación existente sobre el turismo rojo. Mediante aplicaciones combinadas de análisis visual y semiótico por ordenador, ANOVA, análisis de redes y visualización de modelos, el estudio proporciona una importante triangulación metodológica para los estudios de la imagen del destino basados en fotografías.

Financial asset return series usually exhibit nonnormal characteristics such as high peaks, heavy tails and asymmetry. Traditional risk measures like standard deviation or variance are inadequate for nonnormal distributions. Value at Risk (VaR) is consistent with people's psychological perception of risk. The asymmetric Laplace distribution (ALD) captures the heavy-tailed and biased features of the distribution. VaR is therefore used as a risk measure to explore the problem of VaR-based asset pricing. Assuming returns obey ALD, the study explores the impact of high peaks, heavy tails and asymmetric features of financial asset return data on asset pricing.

A VaR-based capital asset pricing model (CAPM) was constructed under the ALD that follows the logic of the classical CAPM and derive the corresponding VaR-β coefficients under ALD.

ALD-based VaR exhibits a minor tail risk than VaR under normal distribution as the mean increases. The theoretical derivation yields a more complex capital asset pricing formula involving β coefficients compared to the traditional CAPM.The empirical analysis shows that the CAPM under ALD can reflect the β-return relationship, and the results are robust. Finally, comparing the two CAPMs reveals that the β coefficients derived in this paper are smaller than those in the traditional CAPM in 69–80% of cases.

The paper uses VaR as a risk measure for financial time series data following ALD to explore asset pricing problems. The findings complement existing literature on the effects of high peaks, heavy tails and asymmetry on asset pricing, providing valuable insights for investors, policymakers and regulators.

This study aims to explore the capabilities, limitations and potential of ChatGPT applicable to online reference services in academic libraries.

This study used the method of qualitative content analytics to assess the general capabilities of ChatGPT applicable in academic libraries. Two experienced academic librarians had face-to-face interactions with ChatGPT by asking ten most common questions often asked by faculty and students at the Georgia Southern University Libraries (https://library.georgiasouthern.edu/). To examine the ChatGPT’s applicability and capability, they also compared the ChatGPT with a popular online chat reference tool called LibChat, which is now widely used in academic libraries in 91 countries worldwide.

It was found that as an artificial intelligence (AI)-powered real-time chatbot ChatGPT could effectively provide faculty and students with general guidance on locating the needed information resources and services in academic libraries, though its responses might not be accurate or truthful all the time. Embedded into the LibAnswers system of the Springshare’s products (www.springshare.com/libanswers/), LibChat serves as a real-time online chat tool used by academic libraries for reference services, but it is only available during the regular librarians' duty hours. This technical limitation does not meet the dynamic needs of faculty, students, staff, and local community users. Only well-optimized AI-driven chat products like ChatGPT could provide 24/7 online services to support uninterrupted academic library services in the future.

This study only examined the general capability and potential of ChatGPT3.5 in specific subject areas. Additional studies are needed to further explore how the latest capabilities of ChatGPT4.0 or newer version, such as its text-to-image, text-to-speech, text-to-text, text-to-video and Web search, could impact future reference services of academic libraries. ChatGPT’s primary optimization and upgrades in the future may also change and impact this study's findings. The comparison between ChatGPT and LibChat presents a significant breakthrough of the generative AI technology in academic libraries. This comparative study encourages more academic experts, faculty, librarians and scholars to track the advance of generative AI applications, including ChatGPT, adopted in academic learning environments. In addition, the ChatGPT's complete capability and potential enhanced and integrated in the future may go beyond what this study evaluated.

This study examined the strengths and weaknesses of ChatGPT applicable to reference services of academic libraries. Through a comparison between ChatGPT and LibChat, this study suggests that optimized AI online chatbots still have a long way to go to meet the dynamic needs of faculty and students in the ever-changing academic learning environments. To contribute to the existing research literature focusing on the rise of generative AI tools such as ChatGPT, this study provides a valuable reference for the applicability of generative AI applications in academic libraries to promote more library creation and innovation in the coming years of the 21st century.

Many studies on entrepreneurial intention have explored the impact of different factors; however, few have examined the relationship between and impact mechanisms of informal social networks and entrepreneurial intention. This study aimed to bridge this research gap.

This study is based on social capital and ambidexterity theories. After surveying the data of 302 college students from different provinces and universities in China, a mediation model for research is constructed.

Informal social networks help enhance college students’ entrepreneurial intentions, whereas entrepreneurial learning (exploratory and exploitative learning) partially mediates this relationship.

This study empirically explores the impact of informal social networks on the entrepreneurial intentions of Chinese college students and indicates the crucial role played by entrepreneurial learning (divided into exploratory and exploitative learning).

This study aims to explore why Chinese consumers pay for digital content products by investigating the experiences of Chinese consumers living in first-tier and second-tier cities regarding paid digital knowledge products.

A total of 19 in-depth interviews were conducted to collect data, and the phenomenological reduction was adopted to analyze data.

This study reveals that Chinese consumers use paid digital knowledge products to alleviate stress and anxiety stemming from real-life competition and the fear of falling behind. While consumers acknowledge the limited assistance that paid knowledge products can offer, their acceptance and expectations of paid digital knowledge products remain positive.

Paid digital knowledge represents an innovative phenomenon, with few scholars outside China having studied it. This study contributes a conceptual framework to understand the motivations of Chinese consumers with high purchasing power residing in first-tier and second-tier cities to invest in digital content.

This study aims to investigate the relationship between individual-level psychological resources and team resilience in the context of expatriate project management teams. It seeks to understand how personal psychological resources contribute to team resilience and explore the dynamic evolution mechanism of team resilience. The goal is to enhance team resilience among expatriates in a BANI (Brittle, Anxious, Nonlinear, and Incomprehensible) world, where organizations face volatile and uncertain conditions.

An online survey was applied for data collection, and 315 valid samples from Chinese expatriates in international construction projects were utilized for data analysis. A structural equation model (SEM) examines the relationships between personal psychological resources and team resilience. The study identifies five psychological factors influencing team resilience: Employee Resilience, Cross-cultural Adjustment, Self-efficacy, Social Support, and Team Climate. The hypothesized relationships are validated through the SEM analysis. Additionally, a fuzzy cognitive map (FCM) is constructed to explore the dynamic mechanism of team resilience formation based on the results of the SEM.

The SEM analysis confirms that employee resilience, cross-cultural adjustment, and team climate positively impact team resilience. Social support and self-efficacy also have positive effects on team climate. Moreover, team climate is found to fully mediate the relationship between self-efficacy and team resilience, as well as between social support and team resilience. The FCM model provides further insights into the dynamic evolution of team resilience, highlighting the varying impact effects of antecedents during the team resilience development process and the effectiveness of different combinations of intervention strategies.

This study contributes to understanding team resilience by identifying the psychological factors influencing team resilience in expatriate project management teams. The findings emphasize the importance of social support and team climate in promoting team resilience. Interventions targeting team climate are found to facilitate the rapid development of team resilience. In contrast, interventions for social support are necessary for sustainable, long-term high levels of team resilience. Based on the dynamic simulation results, strategies for cultivating team resilience through external intervention and internal adjustment are proposed, focusing on social support and team climate. Implementing these strategies can enhance project management team resilience and improve the core competitiveness of contractors in the BANI era.

This study develops and tests a model that explores how human capital impacts micro-business performance through the sequential mediation of new technology adoption and entrepreneurial bricolage.

A cross-sectional study was conducted on 508 women entrepreneurs engaged in micro-businesses in Malaysia. This study used partial least squares structural equation modeling to test the hypotheses.

This study demonstrates the significant impact of human capital on micro-business performance. It establishes a sequential mediation model in which technology adoption and entrepreneurial bricolage mediate the nexus of human capital–micro-business performance.

This study contributes to the theory by innovatively integrating human capital, new technology adoption, entrepreneurial bricolage, and microbusiness performance, drawing on the resource-based view and human capital theory. However, its cross-sectional nature limits causal inference, and focusing solely on women entrepreneurs in Malaysian micro-businesses may constrain novelty. Additionally, the reliance on self-reported data introduces bias, emphasizing the need for future research.

Fostering entrepreneurial bricolage and embracing technology adoption can enhance performance. Business managers can optimize strategies by promoting continuous learning, innovative problem-solving, and technological advancements.

This study highlights the potential social and economic impacts of supporting women-owned micro-businesses in Malaysia. Policymakers can promote economic growth, employment, and community well-being by emphasizing innovation, human capital development, and technology adoption in Malaysia’s diverse ethnic contexts.

This study introduces a distinctive serial mediation framework to understand the impact of human capital on micro-business performance. It explores mediation dynamics, extends the knowledge of serial mediation in the human capital-performance relationship of microbusinesses, and contributes to the unexplored roles of technology adoption and entrepreneurial bricolage in Malaysian micro-businesses.

Sustainability is considered a core trend in the development of the fashion industry. Clarifying the driving factors of consumers’ sharing willingness regarding sustainable image from the perspective of psychology can help fashion brands implement sustainable management and deepen industrial sustainable development.

Based on commitment theory, this paper proposes a conceptual model that includes three antecedents: perception of greenwashing, environmental, social and governance (ESG) and social media content quality. These affect consumers’ sharing willingness regarding sustainable image through affective commitment, continuance commitment and normative commitment. Furthermore, 310 participants reported their tendencies in a formal empirical study.

The results show that unlike green perception, which has a significant negative effect, consumers have a significant positive commitment to high perceived levels of ESG and social media content quality. Besides, all three dimensions under the commitment theory play a partial mediating role between consumer perception and sharing willingness.

This study not only extends the research on the commitment theory to the field of fashion marketing and management but also enriches the research context of brand image sharing willingness, which explains the differential effects of different consumer commitments on their information sharing willingness. Moreover, several management implications applicable to the fashion industry have also been proposed based on the conclusion.

This research is the first to use bibliometric analysis to provide insight into the landscape and forecast the future of customer experience research in the banking sector.

We used bibliographic coupling and co-word analysis to delineate the existing knowledge structure after reviewing 338 articles from the Web of Science database.

The bibliographic coupling analysis revealed five key clusters: customer engagement and experience in digital banking; customer experience and service management; customer experience and market resilience; digital transformation and customer experience; and digital technology and customer experience—each representing a significant strand of current research. In addition, the co-word analysis revealed four emerging themes: customer experience through AI and blockchain, digital evolution in banking, experience-driven ecosystems for customer satisfaction, and trust-based holistic banking experience.

These findings not only sketch an overview of the current research domain but also hint at emerging areas ideal for scholarly investigation. While highlighting the industry’s rapid adaptation to technological advances, this study calls for more integrative research to unravel the complexities of customer experience in the evolving digital banking ecosystem.

This review presents a novel state-of-the-art analysis of customer banking experience research by employing a science mapping via bibliometric analysis to unveil the knowledge and temporal structure.