Search results

The paper draws extensively from Aristotle’s Poetics, a classical work on the aesthetics of drama. Drawing from symbolic and thematic elements from folklore and mythology, this paper aims to illustrate how the Poetics can be referenced as an allegorical device in the design of culture-building strategies and interventions.

This exploratory paper examines Aristotle’s “Poetics” and the range of creative expression this literature provides as a conceptual design framework for the development of a culture map in creating a distinctive organisational mythology. The Poetics articulates an Aristotelian perspective on theatre which infuses itself as a new language in offering structural and archetypical plot devices in the development of an organisational narrative.

Findings from this explorative study can provide a creative roadmap to culture practitioners and leaders, to be used as a determining reference point in developing culture maps and change management interventions.

Poetics has its detractors, notably Bertolt Brecht and Augusto Boal. Boal examines how Poetics promotes a narrative that suppresses free thinking and encourages a cult of feudal personality, therefore encouraging industrial and cultural oppression, which he rebelled against through the development of his “Theatre of the Oppressed”. This new kind of theatre discarded the Aristotelian model of thinking. Ideas proposed in the Poetics may also lend verisimilitude to the propagation of obsessive consumerism through the definitive symbolism it offers in the development of institutionalised personality cults.

The Poetics as a creatively driven reflexive study provides a forward movement in the study of culture design templates. Its definitive allegorical devices and metaphors act as action principles through which an enterprise culture and its value system can be examined and developed.

This study aims to determine how the attitudes toward artificial intelligence (AI) of religious tourists affect their AI self-efficacy and their engagement in AI. This study specifically intends to investigate the mediating role of AI self-efficacy in the relationship between attitudes toward AI and the engagement in AI of religious tourists. This study also seeks to identify the role of AI assistant use as a moderator in the relationship between attitudes toward AI and AI self-efficacy.

The data used in this study was gathered from a sample of 282 religious tourists who had just visited Karbala, central Iraq. Purposive sampling, which comprises a focused and systematic approach to data collection, was used after carefully assessing the distinctive characteristics and properties of the research population.

The results showed that attitudes to AI had a noticeable impact on AI self-efficacy, which, in turn, exerted a positive impact on engagement with AI. In addition, the use of AI assistants acted to positively moderate AI self-efficacy in terms of mediating the link between attitudes to AI and AI engagement.

The distinctive focus on religious tourists adds an original perspective to the existing literature, shedding light on how their attitudes towards AI impact not only their self-efficacy but also their engagement in dealing with AI. In addition, this study delves into the moderating role of AI assistant use, introducing a unique factor in understanding the complex interplay between attitudes, self-efficacy, and engagement in the context of religious tourism. The selection of Karbala, central Iraq, as this study site further adds originality, providing insights into a specific religious and cultural context.

This study aims to construct a sentiment series generation method for danmu comments based on deep learning, and explore the features of sentiment series after clustering.

This study consisted of two main parts: danmu comment sentiment series generation and clustering. In the first part, the authors proposed a sentiment classification model based on BERT fine-tuning to quantify danmu comment sentiment polarity. To smooth the sentiment series, they used methods, such as comprehensive weights. In the second part, the shaped-based distance (SBD)-K-shape method was used to cluster the actual collected data.

The filtered sentiment series or curves of the microfilms on the Bilibili website could be divided into four major categories. There is an apparently stable time interval for the first three types of sentiment curves, while the fourth type of sentiment curve shows a clear trend of fluctuation in general. In addition, it was found that “disputed points” or “highlights” are likely to appear at the beginning and the climax of films, resulting in significant changes in the sentiment curves. The clustering results show a significant difference in user participation, with the second type prevailing over others.

Their sentiment classification model based on BERT fine-tuning outperformed the traditional sentiment lexicon method, which provides a reference for using deep learning as well as transfer learning for danmu comment sentiment analysis. The BERT fine-tuning–SBD-K-shape algorithm can weaken the effect of non-regular noise and temporal phase shift of danmu text.

This paper aims to investigate research activity on barriers for minority and underserved groups to access and use mental health services.

Using Scopus, relevant articles published from 1993 to 2022 were collected. The final list included 122 articles.

Research hotspots included cultural and ethnic barriers, obstacles encountered by LGBTQ+ individuals, challenges faced by refugees and immigrants, limited access in rural areas and barriers affecting special populations. The top 10 cited articles focused on language barriers, cultural stigma, gender-specific challenges and systemic obstacles. New research avenues included the role of technology in overcoming barriers to access mental health services.

Policymakers and practitioners can use this knowledge to develop targeted interventions, enhance cultural competence, reduce stigma, improve rural access and provide LGBTQ+-affirming care, ultimately promoting equitable mental health care.

This research underscores the importance of addressing mental health service barriers for equity and social justice. Neglecting these disparities can worsen mental health, increase health-care costs, reduce productivity and lead to higher social welfare expenses, perpetuating disadvantages.

This paper's uniqueness lies in its comprehensive analysis of barriers and facilitators to mental health service utilization among minority and underserved groups. It serves as a basis for developing evidence-based strategies to improve service accessibility and enhance the well-being of marginalized communities.

This study aims to address a significant gap in the literature by exploring the individual nature and microfoundation perspective of cultural friction during the integration phase following cross-border mergers and acquisitions (CBMAs). It focuses on the role of face, a pivotal facet of interactions within Asian organizations, elucidating its importance in post-M&A integration outcomes.

Using a conceptual approach, this study draws on three bodies of literature, namely, cultural friction, microfoundations and face concerns. It reconsiders cultural friction as a microfounded construct and introduces face concerns as a pivotal element to understanding the challenges faced by managers at the forefront of CBMAs involving Asian companies. The conceptual approach is illustrated with examples for the world of practice.

This research makes two significant contributions to the fields of CBMAs and cultural friction. First, it demonstrates the relevance of the concept of cultural friction at the individual level, shedding light on the complex post-CBMA integration process. Second, this study demonstrates the critical role of face concerns in the sociocultural integration following CBMAs. This is underexplored in extant literature.

The crucial role of face is well known to those working in Asia. Yet academic inquiry remains underdeveloped on this issue for CBMAs. The friction derived from face concerns provides additional insights into the nature of the cultural challenges confronting managers during sociocultural integration and elucidates the micro-mechanisms influencing individuals’ responses to cultural friction. This research responds to calls to examine the human side of M&As uncovering previously neglected issues within intercultural managerial encounters.

In recent decades, the student population in dormitories has increased notably, primarily attributed to the growing number of international students. Dormitories serve as pivotal environments for student development. The coordination and compatibility among students can significantly influence their overall success. This study aims to introduce an innovative method for roommate selection and room allocation within dormitory settings.

In this study, initially, using multi-attribute decision-making methods including the Bayesian best-worst method and weighted aggregated sum product assessment, the incompatibility rate among pairs of students is calculated. Subsequently, using a linear mathematical model, roommates are selected and allocated to dormitory rooms pursuing the twin objectives of minimizing the total incompatibility rate and costs. Finally, the grasshopper optimization algorithm is applied to solve large-sized instances.

The results demonstrate the effectiveness of the proposed method in comparison to two common alternatives, i.e. random allocation and preference-based allocation. Moreover, the proposed method’s applicability extends beyond its current context, making it suitable for addressing various matching problems, including crew pairing and classmate pairing.

This novel method for roommate selection and room allocation enhances decision-making for optimal dormitory arrangements. Inspired by a real-world problem faced by the authors, this study strives to offer a robust solution to this problem.

This study investigated two key aspects: (1) how a hospital bundles limited resources for preventive care performance and (2) how to develop IS capabilities to enhance preventive care performance.

A case study method was adopted to examine how a hospital integrates its limited resources which leads to the need for resource bundles and an understanding of IS capabilities development to understand how they contribute to the delivery of preventive care in a Malaysian hospital.

This research proposes a comprehensive framework outlining resource-bundling and IS capabilities development to improve preventive care.

We acknowledge that the problem of transferring and generalizing results has been a common criticism of a single case study. However, our objective was to enhance the reader’s understanding by including compelling, detailed narratives demonstrating how our research results offer practical examples that can be generalized theoretically. The findings also apply to similar-sized public hospitals in Malaysia and other developing countries, facing challenges like resource constraints, HIS adoption levels, healthcare workforce shortages, cultural and linguistic diversity, bureaucratic hurdles, and specific patient demographics and health issues. Further, lessons from this context can be usefully applied to non-healthcare service sector domains.

This study provides a succinct strategy for enhancing preventive care in Malaysian public hospitals, focusing on system integration and alignment with hospital strategy, workforce diversity through recruitment and mentorship, and continuous training for health equity and inclusivity. This approach aims to improve resource efficiency, communication, cultural competence, and healthcare outcomes.

Efficiently using limited resources through HIS investment is essential to improve preventive care and reduce chronic diseases, which cause approximately nine million deaths annually in Southeast Asia, according to WHO. This issue has significantly impacted the socioeconomic development of developing countries.

This research refines resource orchestration theory with new mechanisms for resource mobilization, extends IS literature by identifying how strategic bundling forms specialized healthcare IS capabilities, enriches preventive care literature through actionable resource-bundling activities, and adds to HIS literature by advocating for an integrated, preventive care focus from the alignment of HIS design, people and institutional policies to address concerns raised by other research regarding the utilization of HIS in improving the quality of preventive care.

This study aims to demonstrate what myths of and about science are reproduced in this popular cultural work (movie – “Oppenheimer”). This is done by examining the unconscious hegemonic positions supported by the reproduction of stereotypical and mythical images of science.

Content/Text Analysis: The conceptual analysis of a cultural text – a film (“Oppenheimer”) – through a theoretical apparatus (B. Latour’s theory).

The film demonstrates its reproduction of three distinct elements. Firstly, it exhibits classic scientistic clichés pertaining to technoscience. Secondly, it highlights the replication of the individualized monomyth about the (super) hero, leading to the exclusion of the intricate conditions of technoscience’s existence. Lastly, the film aligns with the Californian ideology, as proposed by Barbrook.

The value of the text is twofold: (1) To show that the classical approaches of Bruno Latour are still relevant. (2) To show what hidden premises and myths about technoscience are being propagated through a work of pop culture (the film “Oppenheimer”) and, in effect, to show what kind of influence of cultural hegemony is at work here.

Tourists with different cultural backgrounds think and behave differently. Accurately capturing and correctly understanding cultural differences will help tourist destinations in product/service planning, marketing communication and attracting and retaining tourists. This research employs Hofstede's cultural dimensions theory to analyse the variations in destination image perceptions of Chinese-speaking and English-speaking tourists to Xiamen, a prominent tourist attraction in China.

The evaluation utilizes a two-stage approach, incorporating LDA and BERT-BILSTM models. By leveraging text mining, sentiment analysis and t-tests, this research investigates the variations in tourists' perceptions of Xiamen across different cultures.

The results reveal that cultural disparities significantly impact tourists' perceived image of Xiamen, particularly regarding their preferences for renowned tourist destinations and the factors influencing their travel experience.

This research pioneers applying natural language processing methods and machine learning techniques to affirm the substantial differences in the perceptions of tourist destinations among Chinese-speaking and English-speaking tourists based on Hofstede's cultural theory. The findings furnish theoretical insights for destination marketing organizations to target diverse cultural tourists through precise marketing strategies and illuminate the practical application of Hofstede's cultural theory in tourism and hospitality.

An increasing number of images are generated daily, and images are gradually becoming a search target. Content-based image retrieval (CBIR) is helpful for users to express their requirements using an image query. Nevertheless, determining whether the retrieval system can provide convenient operation and relevant retrieval results is challenging. A CBIR system based on deep learning features was proposed in this study to effectively search and navigate images in digital articles.

Convolutional neural networks (CNNs) were used as the feature extractors in the author's experiments. Using pretrained parameters, the training time and retrieval time were reduced. Different CNN features were extracted from the constructed image databases consisting of images taken from the National Palace Museum Journals Archive and were compared in the CBIR system.

DenseNet201 achieved the best performance, with a top-10 mAP of 89% and a query time of 0.14 s.

The CBIR homepage displayed image categories showing the content of the database and provided the default query images. After retrieval, the result showed the metadata of the retrieved images and links back to the original pages.

With the interface and retrieval demonstration, a novel image-based reading mode can be established via the CBIR and links to the original images and contextual descriptions.