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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.

A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic principle for intelligent crowds in an attempt to show that crowd wisdom could help in making accurate judgments and proper decisions. This further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

Efforts to support the critical role of crowd wisdom in intelligent manufacturing involve theoretical explanation, including a discussion of several prevailing concepts, such as consumer-to-business (C2B), crowdfunding and an interpretation of the contemporary Big Data mania. In addition, an empirical study with three business cases was conducted to prove the conclusion that our ideas could well explain the current business phenomena and guide the future of manufacturing.

This paper shows that crowd wisdom could help make accurate judgments and proper decisions. It further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

The paper highlights the importance of crowd wisdom in manufacturing with sufficient theoretical and empirical analysis, potentially providing a guideline for future industry.

This paper explores how the student movement in Taiwan transformed after the abolition of martial law. After democratization, there were three large-scale student protests, in 1990, 2008 and 2014. This paper explores the development through this period of student movement organizations, issues and interrelations between organizations and individuals.

The study of the process of transformation and development is based on an analysis of newspaper and magazine articles and books about the student movement. To provide an insider's view, magazines, statements and meeting memos written by activists are also included.

As a legacy of the student movement in the 1980s, the 1990 Wild Lily protest advocated democratization and organized a cross-school alliance. This pattern declined, however, because it proved hard to recruit participants after democratization. Instead, student activists returned to education-related issues, and the scale of student organizations remained small. The 2008 Wild Strawberry protest was carried out by autonomous, self-organized groups, which reflected the emergence of individuals as activists. Afterward, student movement organizations attempted to create multiple networks consisted of various issues and participants. These groups built solidarity by cooperating on education and political issues and became the base for the 2014 Sunflower protest.

This paper explores the rarely described historical context for the student movement between large-scale student protests in Taiwan and provides a more comprehensive understanding of the interrelation of organizations and individuals in contemporary social movements.

Poor medication adherence leads to high hospital admission rate and heavy amount of health-care cost. To cope with this problem, various electronic pillboxes have been proposed to improve the medication adherence rate. However, most of the existing electronic pillboxes use time-based reminders which may often lead to ineffective reminding if the reminders are triggered at inopportune moments, e.g. user is sleeping or eating.

In this paper, the authors propose an AI-empowered context-aware smart pillbox system. The pillbox system collects real-time sensor data from a smart home environment and analyzes the user’s contextual information through a computational abstract argumentation-based activity classifier.

Based on user’s different contextual states, the smart pillbox will generate reminders at appropriate time and on appropriate devices.

This paper presents a novel context-aware smart pillbox system that uses argumentation-based activity recognition and reminder generation.

In the context of crowdsourced new product development (NPD), the purpose of this paper is to investigate the optimal level of community involvement (CI) (e.g. zero, limited, and high) when creating products from the perspectives of both ordinary and advanced users. The authors also investigate the influence of design interest and need for social affiliation on users’ attitudes toward and willingness to use community co-design.

The authors conducted two survey studies using ordinary (Study 1, n=199) and advanced users (Study 2, n=131) to evaluate the co-designed T-shirts reflecting varying levels of CI (i.e. zero, limited, and high). The stimuli for both studies were the same and included ten sets of T-shirt co-designs generated from a CI crowdsourced website, Threadless. Fishbein’s (1963) multi-attribute attitude model was used to compute subjects’ overall attitude score toward the T-shirt co-designs.

Results showed both ordinary and advanced user groups rated the design quality of products reflecting limited CI lower than those of zero CI. Advanced users also rated the design quality and sales potential of products from limited CI lower than those of high CI. Further, advanced users indicated that products resulting from high CI reflected significantly better designs with regard to color, shape/line, size, general theme, and overall design as compared to products from limited CI. Design interest as well as need for social affiliation influenced users’ willingness to use community co-design and their attitudes toward a community co-design experience.

The research made an important differentiation between zero, limited, and high CI during the co-design process as well as between ordinary users and advanced users contributed to the extant literature addressing crowdsourcing in NPD.

The study aims to find potential method to enhance the stability and antioxidant activity of vitamins.

Vitamin E (VE) and β-cyclodextrin (CD) were used to prepare the VE-β-CD inclusion complex via a solution method. The yielded VE-β-CD obtained from optimal experimental conditions was characterized. The mechanism of complex formation and the properties of the complex was investigated by steady-state and time-resolved fluorescence techniques. The antioxidant activity of VE-β-CD was evaluated using 1,1-diphenyl-2-picrylhydrazyl (DPPH) and compared with pure VE.

Three experimental factors – reaction temperature (T), molar ratio of VE to β-CD (rm) and inclusion time (t) – were studied for the preparation of VE-β-CD. At experimental conditions of T = 60°C, rm = 1:3 and t = 3 h, a maximum inclusion rate of VE (78.62%) was obtained. The Fourier-transform infrared spectroscopy (FTIR) shows that VE molecule was physically encapsulated by β-CD in the yielded product. Subsequentially, the steady-state fluorescence intensity of VE was found to increase upon encapsulation by β-CD due to the hindrance of fluorescence quenching of VE molecules inside the hydrophobic cavity of β-CD, and an inclusion constant K was determined to equal 3.58 × 103 L/mol from the fluorescence results. The fluorescent observation was confirmed by time-resolved fluorescence experiment as the lifetime of VE increased with an increase in β-CD concentration.

The ability of removing radicals by VE was significantly enhanced after the formation of inclusion complex with β-CD.

This study aims to explore how tourists construct destination images in the context of dark tourism and reveals the relationships between on-site experience, destination image and behavioural intention.

The earthquake-ravaged county town of Beichuan in China was chosen as the study site. The study collected 298 viable questionnaires from tourists. Partial least squares structural equation modelling was performed to explore the relationships between the variables of on-site experience, destination image and behavioural intention.

The study identified four dimensions of dark tourism destination image (TDI) from its attribute and functional perspective. It found that “image of memorial place” and “image of educational place” were the most perceptual images and positively related with most subdimensions of on-site experience and behavioural intention. “Image of leisure place” and “image of landscapes of fear” were less perceived by tourists and negatively related with some subdimensions of on-site experience and behavioural intention.

To our knowledge, this study is the first attempt to explore the complex mechanisms of dark TDI formation with the framework of “on-site experiences–destination images–behavioural intentions”. By identifying tourists’ most and least perceptual images and their effective antecedents and consequences help to reconcile and manage the controversial and contradictory images of a dark tourism destination.

本文探讨了游客如何建构黑色旅游目的地形象, 进一步研究了游客现场体验、目的地形象、行为意愿之间的作用关系。

以汶川地震重灾区北川老县城遗址为案例地, 本研究收集了游客结构化问卷298份, 采用偏最小二乘结构方程模型（PLS-SEM）分析了游客现场体验、目的地形象和行为意愿各维度之间的作用关系。

从目的地属性和功能角度, 本文区分了黑色旅游目的地形象四个维度。研究发现“纪念地形象”和“教育地形象”是游客感知最强的两大维度, 与绝大多数游客现场体验和行为意愿的维度呈显著正向影响关系。 “休闲地形象”和“恐惧景观形象”, 游客感知较弱, 与现场体验和行为意向的一些维度呈负向影响关系。

本文首次利用“现场体验-目的地形象-行为意愿”这一研究框架, 揭示黑色旅游目的地形象的复杂生成机制。通过识别游客感知最强和最弱的形象维度, 揭示其前因与后果, 有助于调和与管理有争议和矛盾的黑色旅游目的地形象。

Este estudio explora cómo los turistas construyen la imagen del destino en el contexto del turismo oscuro, revelando las relaciones entre experiencias en el lugar, imágenes del destino e intenciones de comportamiento.

El terremoto que devastó la ciudad del condado de Beichuan en China fue elegido lugar de estudio por sus peculiaridades para el desarrollo del destino oscuro. El estudio recopiló 298 cuestionarios viables de turistas. Se planteo un modelo de ecuaciones estructurales (PLS-SEM) para explorar las relaciones entre las variables de experiencias en el lugar, imágenes de destino e intenciones de comportamiento.

El estudio identificó cuatro dimensiones de la imagen del destino turístico oscuro desde su atributo y perspectiva funcional. De igual forma, se encontró que la “imagen del lugar conmemorativo” y la “imagen del lugar educativo” eran las imágenes más perceptivas y estaban relacionadas positivamente con la mayoría de los subdimensiones de las experiencias en el lugar e intenciones de comportamiento. Los turistas percibieron menos la “imagen de un lugar de ocio” y la “imagen de paisajes de miedo” y se relacionaron negativamente con algunos subdimensiones de las experiencias en el lugar e intención de comportamiento.

Hasta donde sabemos, este estudio es el primer intento de explorar el complejo mecanismo en la formación de TDIs oscuros con el marco de “experiencias en el lugar- imágenes de destino – intenciones de comportamiento”. Al identificar las imágenes más o menos perceptivas de los turistas, y sus antecedentes y consecuencias efectivos, ayuda a conciliar y gestionar las imágenes controvertidas y contradictorias de un destino turístico oscuro.

The aim of this paper is to present a comprehensive analysis of risk management in East Asia from 1998 to 2021 by using bibliometric methods and tools to explore research trends, hotspots, and directions for future research.

The data source for this paper is the Web of Science Core Collection, and 7,154 publications and related information have been derived. We use recognized bibliometric indicators to evaluate publications and visually analyze them through scientific mapping tools (VOS Viewer and CiteSpace).

The analysis results show that China is the most productive and influential country/region. East Asia countries have strong cooperation with each other and also have cooperation with other countries. The study shows that risk management has been involved in various fields such as credit, supply chain, health emergency and disaster especially in the background of COVID-19. We also found that machine learning, especially deep learning, has been playing an increasingly important role in risk management due to its excellent performance.

This paper focuses on studying risk management in East Asia, exploring its publication's fundamental information, citation and cooperation networks, hotspots, and research trends. It provides some reference value for scholars who are interested or further research in this field.

This paper aims to investigate adolescent English as a foreign language (EFL) learners’ digitally mediated multimodal compositions across different genres of writing.

Three Korean high school students participated in the study and created multiple multimodal texts over the course of one academic semester. These texts and other materials were the basis for this study’s qualitative case studies. Multiple sources of data (e.g. class observations, demographic surveys, interviews, field notes and students’ artifacts) were collected. Drawing upon the inductive approach, a coding-oriented analysis was used for the collected data. In addition, a multimodal text analysis was conducted for the students’ multimodal texts and their storyboards.

The study participants’ perceptions of multimodal composing practices seemed to be positively reshaped as a result of them creating multimodal texts. Some participants created multimodal products in phases (e.g. selecting or changing a topic, constructing a storyboard and editing). Especially, although the students’ creative processes had a similarly fixed and linear flow from print-based writing to other modalities, their creative processes proved to be flexible, recursive and/or circular.

This study contributes to the understanding of adolescent English language learners’ multimodal composing practices in the EFL context, which has been underexplored in the literature. It also presents the students’ perspectives on these practices. In short, it provides theoretical and methodological grounds for future L2 literacy researchers to conduct empirical studies on multimodal composing practices.