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This study aimed to examine the effects of curiosity on expatriates' innovative work behaviour and job satisfaction in a cross-cultural setting, with the sequential mediating effects of cultural intelligence (CQ) and knowledge-sharing behaviour.

Data were collected by distributing an online survey to 465 Taiwanese expatriates living and working abroad. Structural equation modelling was used to test the hypotheses via AMOS v.22.

The results indicate that curiosity is an antecedent of an individual's CQ and both CQ and knowledge-sharing behaviour are sequential mediators in the relationships between curiosity and innovative work behaviour and between curiosity and job satisfaction.

The study expands the existing body of research to analyse personal traits as meaningful factors that enhance CQ and the mechanisms of CQ and knowledge sharing behaviour in the relationship between curiosity and innovative work behaviour and between curiosity and job satisfaction. It offers novel empirical evidence for the important role of curiosity, CQ and knowledge-sharing behaviour in enhancing an individual's innovative work behaviour and job satisfaction in a cross-cultural setting.

Podcasting is a new mobile technology application for language learning. Drawing upon the stimulus–organism–response model and the interest driven creator (IDC) theory from e-learning, this study aims to develop and test an integrative conceptual framework. This study investigates contextual and environmental stimuli effects (content richness [CR], self-directed learning [SDL] and situational interest [SI]) from a podcast English learning context on learners’ experience states (cognitive absorption [CA], pleasure [PL] and arousal [AR]) and their subsequent responses (continuance learning intention [CLI]).

Using 416 valid responses from five universities located in North Taiwan, data analysis is performed using a structural equation model.

The results show that most of the interest factor stimuli (CR, SDL and SI) have significant impacts on learners’ experiences (CA, PL and AR), which in turn affect their CLI.

The findings provide useful insights for English show podcasters and operators to invest in establishing learners’ interest factor and stimulating experiences to improve their CLI.

This paper contributes to a better understanding of students who use contextual factors of podcast English learning and how these factors influence their CLI via a framework of stimulus–organism–response and the IDC theory.

Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been explored from the stressor-strain-outcome (SSO) or stimulus-organism-response (SOR) perspectives. To further investigate SMF, the authors split it into the two constructs of exhaustion and disinterest. Furthermore, the authors introduced the concept of emotional labor and identified rules that may affect surface and deep acting strategies.

The authors designed and conducted a survey to collect data from social networking platform users.

Results from 364 users of social networking platforms supported most of the authors' hypotheses. First, most of the display rules affect the choice of deep or surface acting. Second, both types of acting lead to exhaustion, but only surface acting leads to disinterest. Third, discontinuance intention is affected by both types of fatigue.

This study contributes to SMF research by adding more antecedents (deep and surface acting) based on the emotional labor perspective and showing the impacts of communication rules on emotional labor. In addition, this study also distinguishes disinterest-style fatigue from exhaustion.

Studies have explored the determinants of customer advocacy because of customer advocacy's vital role in improving the efficiency and effectiveness of marketing. The current research complements the existing literature in the hospitality field by examining the association between restaurant innovativeness and customer advocacy while also investigating the mediating roles of self-image congruity and customer engagement.

The statistical software AMOS version 25 and bootstrapping were employed to test the hypotheses. Purposive sampling was employed for participant recruitment, and a self-administered questionnaire was used to collect data. Data were collected from Taiwanese customers who had dined at selected restaurants.

The results from 385 restaurant customers reported that self-image congruity had an indirect impact on customer advocacy through customer engagement. Customer advocacy was influenced by restaurant innovativeness through the mediation of customer engagement. The influence of restaurant innovativeness on customer advocacy was positively and sequentially mediated by self-image congruity and customer engagement.

Restaurant innovativeness is linked to customer advocacy through self-image congruity and customer engagement. Thus, restaurant managers should implement strategies focusing on innovativeness to improve self-image congruity and engagement among customers.

The current research may be the first to provide a research model that explores restaurant innovativeness, self-image congruity, customer engagement and customer advocacy in the hospitality context. This study also has practical implications for enhancing customer advocacy.

The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources.

Taguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms.

Research indicates that integral control parameters (K_i) affect outputs substantially more than proportional control parameters (K_p). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676.

This paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve.

The research aims to discuss technical and vocational students' long-term and complete evaluation of learning effectiveness under school-wide thematic teaching design.

This study adopted a mixed qualitative and quantitative approach to measure the learning effectiveness of thematic teaching in technical vocational schools using the Kirkpatrick model. Qualitative research conducted in-depth interviews with 32 interviewees, including students, parents, teachers, graduate alumni and the supervisors of off-campus internship units. Quantitative research conducted a questionnaire survey on vocational students. A total of 221 valid questionnaires were collected. In addition, this research conducts another quantitative survey on cooperative enterprises to compare the actual effect of the implementation of the school-wide thematic teaching students with the others, and a total of 35 valid questionnaires were collected.

The results of the research found that the effectiveness of thematic teaching method can achieve the expected goals of each level of Kirkpatrick model. The students taking thematic teaching are significantly better and fitting in the industry expects. Therefore, this research suggests the comprehensive introduction of school-wide thematic teaching to other school operators.

This research is the first study used the Kirkpatrick model to evaluate the effectiveness of school-wide thematic teaching design in hospitality education and providing a practical case for schools. This research combined qualitative and quantitative research methods to investigate the effectiveness of the teaching method through multiple perspectives. Through the feedback from supervisors of the hospitality industry, the school-wide thematic teaching design provides a good foundation for technical and vocational graduates.

The purpose of this paper is to identify the root cause of low yield problems in the semiconductor manufacturing process using sensor data continuously collected from manufacturing equipment and describe the process environment in the equipment.

This paper proposes a sensor data mining process based on the sequential modeling of random forests for low yield diagnosis. The process consists of sequential steps: problem definition, data preparation, excursion time and critical sensor identification, data visualization and root cause identification.

A case study is conducted using real-world data collected from a semiconductor manufacturer in South Korea to demonstrate the effectiveness of the diagnosis process. The proposed model successfully identified the excursion time and critical sensors previously identified by domain engineers using costly manual examination.

The proposed procedure helps domain engineers narrow down the excursion time and critical sensors from the massive sensor data. The procedure's outcome is highly interpretable, informative and easy to visualize.

This study aims to contribute to social identity theory in tourism by exploring the reflections of Chinese tourists visiting North Korea and how they negotiate their intergroup identity in this similar-others destination.

Data were collected via online platforms and in-depth interviews. A qualitative approach, i.e. thematic analysis, was used to analyse the two sets of data.

Results showed that when encountering North Koreans perceived as similar others amid the social, economic and political environments in which they were embedded, Chinese tourists often categorised themselves as ordinary tourists, preferentially treated tourists and vicarious tourists based on intergroup similarities to North Koreans. They also performed intergroup comparison to boost their self-esteem at group and collective levels and developed corresponding strategies to generate distinct emotional group commitments.

It is recommended that destinations reinforce the friendly and unique relationship with their similar-others source markets to improve their attractiveness. Destinations should also strive to enhance the experience of tourists from their similar-others markets by arousing their positive collective-level affection, emotional resonance and nostalgic memories and avoiding negative emotions.

This study offers a theoretical framework analysing the features of tourists’ social identities while visiting a similar-others destination, contributing to our understanding of the interactive and contingency nature of social identity in tourism, and responding to the call for addressing the broader social contexts in which tourists’ group identity is embedded.

本文致力于探索赴朝中国游客的反思以及他们在这个“类似他者”目的地如何协商群际身份, 以对旅游领域的身份认同理论做出贡献。

本文运用主题分析方法; 资料来源于网络文本和深度访谈。

当中国游客面对被视为“类似他者”的朝鲜人时（具有相似的社会、经济和政治环境）, 他们会根据与朝鲜人的群际相似性, 将自我分类为“普通游客”、“受优待者”和“过来人”三类。此外, 他们还会通过群际比较来提高群体层面和集体层面的自尊, 并且采取对应策略以产生不同的群体承诺。

本文提出了一个分析游客访问“类似他者”目的地时的社会认同的理论框架, 对理解旅游中的社会认同的互动性和偶然性做出了贡献, 并响应了在考察游客群体认同时关注其所处的更广泛的社会背景的呼吁。

目的地应该强化它们与“类似他者”客源市场之间友好且独特的关系, 以提升自身吸引力。目的地还应该唤醒游客积极的集体情感和怀旧, 产生主客情感共鸣, 并避免负面情绪, 以尽力提升来自“类似他者”客源地的游客的体验。

Este estudio pretende contribuir a la teoría de la identidad social en turismo mediante la exploración de las reflexiones de los turistas chinos que visitan Corea del Norte y cómo negocian su identidad intergrupal en este destino similar a otros.

Los datos se recogieron mediante plataformas en línea y entrevistas en profundidad. Se utilizó un enfoque cualitativo a través de análisis temático para analizar los dos conjuntos de datos.

Los resultados mostraron que, al encontrarse con norcoreanos percibidos como otros similares en el entorno social, económico y político en el que estaban integrados, los turistas chinos a menudo se categorizaban a sí mismos como turistas ordinarios, turistas con trato preferente y turistas vicarios basándose en las similitudes intergrupales con los norcoreanos. También, realizaban comparaciones intergrupales para aumentar su autoestima a nivel grupal y colectivo, y desarrollaban las estrategias correspondientes para generar distintos compromisos emocionales grupales.

Se presenta un marco teórico en el que se analizan las características de las identidades sociales de los turistas que visitan un destino similar a otro, lo que contribuye a nuestra comprensión de la naturaleza interactiva y contingente de la identidad social en turismo y responde a la necesidad de abordar los contextos sociales más amplios en los que se inserta la identidad de grupo de los turistas.

Se recomienda que los destinos refuercen las relaciones amistosas y únicas con sus mercados emisores similares para mejorar su atractividad. Los destinos deberían esforzarse por mejorar la experiencia de los turistas de sus mercados emisores similares, estimulando su afecto positivo a nivel colectivo, su resonancia emocional y sus recuerdos nostálgicos, y evitando las emociones negativas.

Computer vision and deep learning (DL) methods have been investigated for personal protective equipment (PPE) monitoring and detection for construction workers’ safety. However, it is still challenging to implement automated safety monitoring methods in near real time or in a time-efficient manner in real construction practices. Therefore, this study developed a novel solution to enhance the time efficiency to achieve near-real-time safety glove detection and meanwhile preserve data privacy.

The developed method comprises two primary components: (1) transfer learning methods to detect safety gloves and (2) edge computing to improve time efficiency and data privacy. To compare the developed edge computing-based method with the currently widely used cloud computing-based methods, a comprehensive comparative analysis was conducted from both the implementation and theory perspectives, providing insights into the developed approach’s performance.

Three DL models achieved mean average precision (mAP) scores ranging from 74.92% to 84.31% for safety glove detection. The other two methods by combining object detection and classification achieved mAP as 89.91% for hand detection and 100% for glove classification. From both implementation and theory perspectives, the edge computing-based method detected gloves faster than the cloud computing-based method. The edge computing-based method achieved a detection latency of 36%–68% shorter than the cloud computing-based method in the implementation perspective. The findings highlight edge computing’s potential for near-real-time detection with improved data privacy.

This study implemented and evaluated DL-based safety monitoring methods on different computing infrastructures to investigate their time efficiency. This study contributes to existing knowledge by demonstrating how edge computing can be used with DL models (without sacrificing their performance) to improve PPE-glove monitoring in a time-efficient manner as well as maintain data privacy.

The transformation towards the Green Economy (GE) in Poland is a relatively new topic for researchers, policymakers and business practitioners. A comprehensive picture of the shift towards the GE can help mentioned groups translate theoretical assumptions into practice.

This chapter presents the assessment of Poland's shift towards the GE, measured by the proposed Green Transformation Index (GTI).

The set of GE indicators was elaborated in Structured Literature Review (SLR) variation method. Then, this set of indicators was compared with the Statistics Poland (GUS) secondary data and employed in the taxonometric calculation methods.

In the result, the GTI for the Polish economy was proposed and calculated between 2007 and 2020. The GTI allowed us to present a dynamic analysis of the transformation towards GE in Poland.