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This study aims to identify and assess the factors challenging the integration of artificial intelligence (AI) technologies in healthcare workplaces.

The study utilized a mixed approach, that starts with a literature review, then developing and testing a questionnaire survey of the factors challenging the integration of AI technologies in healthcare workplaces. In total, 46 factors were identified and classified under 6 groups. These factors were assessed by four different stakeholder categories: facilities managers, medical staff, operational staff and patients/visitors. The evaluations gathered were examined to determine the relative importance index (RII), importance rating (IR) and ranking of each factor.

All 46 factors were assessed as “Very Important” through the overall assessment by the four stakeholder categories. The results indicated that the most important factors, across all groups, are “AI ability to learn from patient data”, “insufficient data privacy measures for patients”, “availability of technical support and maintenance services”, “physicians’ acceptance of AI in healthcare”, “reliability and uptime of AI systems” and “ability to reduce medical errors”.

Determining the importance ratings of the factors can lead to better resource allocation and the development of strategies to facilitate the adoption and implementation of these technologies, thus promoting the development of innovative solutions to improve healthcare practices.

This study contributes to the body of knowledge in the domain of technology adoption and implementation in the medical workplace, through improving stakeholders’ comprehension of the factors challenging the integration of AI technologies.

This study aims to explore network typology and the role of networks in immigrant entrepreneurs’ (IEs) business operations in South Africa (SA).

In-depth interviews were carried out with 25 IEs operating their business ventures in SA, selected via the purposive sampling method.

The findings indicated that IEs in SA use social networks most often, with minimal use of international business networks. In addition, the findings showed that IE networks’ key roles include providing them with access to referrals and resource provision. However, whilst resource provision emerged as a significant role, finance appeared as the main resource provided by networks.

To the best of the authors’ knowledge, this original paper provided theoretical and empirical contributions to research on network typology and its role for IEs. Thus, the study extended the current literature on the intersection of IEs and their networking behaviours.

Chat Generative Pre-trained Transformer (ChatGPT) has become everyone’s talk. It frightens many professionals, who worry about losing their jobs. ChatGPT may reconstruct some professions; some occupations may vanish while new ones may appear.

This mixed-methods study explores whether and how the use of ChatGPT impacts English is taught as a foreign language (EFL) students' social and emotional learning (SEL). The study used a questionnaire and collected perception data from 57 EFL students. A discussion with seven EFL professors was also formulated to triangulate the findings.

Results indicate that EFL students have high positive perceptions of using ChatGPT in their learning (M = 3.87). Results also showed that using ChatGPT has a moderate impact on EFL students' SEL (R = 514). This moderate effect was confirmed by the qualitative findings, which indicated that ChatGPT positively impacts EFL students' SEL by allowing them to practice conversation skills, aiding them in managing their emotional intelligence, providing them with feedback and reducing their anxiety. However, findings also indicated that ChatGPT reduces students' creativity and limits their emotional growth. Finally, the findings reported that for better use of ChatGPT, supervision is key.

This study recommends the use of ChatGPT in a way that helps students' creativity and emotional growth.

Mental health problems during the initial years of life are precursors of mental disorders in later life, as well as poor quality of life. However, understanding and assessing the quality of life among children is very challenging and requires appropriate assessment measures. Against this backdrop, this study aims to establish the evidence for the construct and convergent validity of Urdu version of Pediatric Quality of Life Inventory (PedsQL) in Pakistani children.

This study has a cross-sectional study design in which a sample of 291 primary school children (53.3% male children and 44.7% female children) were enrolled from 6 primary schools located in Rawalpindi District in 2021 through random sampling. Children’s ages ranged between 9 and 13 years (M = 10.51 years; SD = 0.73). Urdu translated version PedsQL, Rosenburg self-esteem scale (RSES), strengths and difficulties questionnaire (SDQ), difficulty subscale and socio-demographic form were administered in a group setting.

Confirmatory factor analysis showed model provided a better fit similar to three factors: social/school functioning; psychological functioning; and physical functioning with good alpha reliability for full scale as well for subscales (r = 0.87, r = 0.75, r = 0.77 and r = 0.73), respectively. Pearson’s correlation of the translated version with SDQ_difficulties (r = −0.33; p < 0.01) and RSES (r = −016; p < 0.01) depicted solid discriminant validity (r = −0.33; p < 0.01) and RSES showed good convergent validity (r = −0.16; p < 0.01). Hence; PedsQL, Urdu proved to be a reliable, valid and efficient tool for the assessment of quality of life among Pakistani children, and its three-factor structure model suggested previously for Pakistani children was confirmed.

This study is original work by the researcher as part of their PhD project.

With the great changes brought by information technology, there is also a challenge for the elderly's acceptance. This study aimed to determine the antecedents of elderly people's usage intention of financial artificial intelligent customer service (FAICS) and to examine the relationships between various factors and thus to help them better adapt to the digital age.

A mixed method, including the qualitative and quantitative study, was utilized to explore answers of the research questions. As the qualitative study, the authors used semi-structured interviews and data coding to uncover the influencing factors. As the quantitative study, the authors collected data through questionnaires and tested hypotheses using structural equation modeling.

The results of data analysis from interviews and questionnaires suggested that perceived anthropomorphism and virtual identity of elderly users have a positive impact on their perceived ease of use, and the perceived intelligence of elderly users positively influences their perceived ease of use, satisfaction and perceived usefulness. Additionally, the elderly's cognition age can moderate the effects of perceived usefulness and satisfaction on their usage intention of FAICS.

This study contributes to the literature by taking the elderly group as the research participants and combining those influencing factors with technology acceptance model and information systems success model. The findings provide a basis for accelerating the promotion of FAICS and help address the problem that the elderly have difficulty adapting to a new technology.

Using different trade indices spanning 2018–2021, this chapter investigates Afghanistan's current patterns, prospects and barriers for intra- and inter-regional trade perspectives, emphasising the different pathways by which Afghanistan trades with Central Asian economies. The empirical findings demonstrate that the anticipated significance of trade between Afghanistan and Central Asia is double compared to the existing levels of trade. Furthermore, the analysis encompasses the categorisation of sectors based on the intensity of usage of production factors like resource, labour and technology. The analysis further elaborates on Afghanistan's trade potential with Central Asia and vice versa by highlighting the comparative advantage, diversification, complementarity and similarity in trade. The findings suggest that larger economies are rated higher than smaller ones as size and development level are essential factors in regional trade development. The most effective channels of regional trade development are price competitiveness measures, intra-industry trade and trade complementarities. These findings have a substantial influence on the development of different trade policy efforts to stimulate investment and trade within and among the two regions.

Dietary supplements are important in improving maternal health and birth outcomes during pregnancy. This study aims to assess women’s knowledge about the benefits, sources and proper intake of dietary supplements during pregnancy.

This cross-sectional study was conducted among women at Jordan University Hospital in Amman, Jordan from July to October 2023.

A total of 448 women completed the questionnaire. Analysis of the results showed that among all questions, participants perceived sufficient knowledge about dietary supplements' beneficial effects. Around 50% of the participants did not recognize the importance of vitamin B12 and vitamin A. Most participants identified that iron supplements should not be taken with dairy products, coffee, tea, calcium and antacids. Most participants did not know the source of vitamin A (82.1%), and only 44% knew the correct source of vitamin B12. Less than half of the participants recognized the appropriate administration time for each dietary supplement.

The knowledge level of the interaction between iron and food, natural sources of vitamins and their benefits was high, less than half of the participants showed poor knowledge about the proper time to take the dietary supplement. Patient education and counseling is important to improve health outcomes.

Drawing on the leader–member exchange (LMX) theory, we examine the role of empowering leadership in employee organizational commitment and the organizational citizenship behavior. Furthermore, we examine if these relationships are explained by factors such as follower trust in the leader and leader authenticity.

We draw on survey data from 153 individuals serving the hospitality industry sector. The data are analyzed using structural equation modeling.

Results show that trust in a leader positively mediates the relationship between empowering leadership and organizational citizenship behavior as well as organizational commitment. We also find a direct association between empowering leadership and the two organizational outcomes. However, we do not find evidence of the moderating role of leader authenticity in empowering leadership and trust in leader–leader relationship.

This paper brings to light the significance of empowering leadership, especially for hospitality workers who often operate in stressful and deeply hierarchical organizational environments. Our study findings provide a pathway for how supervisors should follow an empowering form of leadership annculcate trust in employees for better organizational outcomes. The findings indicate significant theoretical and practical implications and offer recommendations for future research.

This chapter uses data from the Scopus database to present a comprehensive bibliometric analysis of fintech research, focusing on publication trends, citation patterns, and thematic clusters within the field. The analysis reveals notable trends, including influential publications, prolific authors, and their affiliations. It identifies and explores publications categorized into 23 distinct themes, representing key areas of inquiry in fintech, such as technological advancements, financial inclusion, innovation, data analytics, sustainability, and regulatory compliance. The study also identifies research gaps, indicating areas within fintech that have received limited scholarly attention. These findings provide valuable insights for researchers, policymakers, and industry practitioners. Researchers can better understand the fintech landscape, identify research gaps, and guide future inquiries. Policymakers can develop effective regulations and policies based on identified trends and challenges. Industry practitioners can leverage fintech developments to enhance their strategies and operations.

The competitiveness of destinations is crucial for tourism. In this context, the study aims to uncover customer satisfaction, experiences, feelings, and thoughts by conducting a comparative analysis of social media comments from various competitive tourism destinations.

Big data research was conducted to answer the research questions. The data was collected on a social media platform focusing on three destinations in the Mediterranean region. Three methods were employed to analyse the data: sentiment analysis, topic modelling, and named-entity recognition.

This study addressed traveller satisfaction levels. It identified the topics concerning each destination, examined the emotions expressed by travellers about these topics, explored the potential impact on future behaviour, and investigated the features of the destinations and satisfaction levels about these features. It also identified the prominent food and beverage names in destinations and explored tourists’ preferences regarding these foods and beverages.

The limitations of this study relate to the sample. The data used in this study was solely obtained from a single social media platform and focused on English-only comments. Further research that includes different social media platforms for hotel categories and considers reviews in local languages could capture a broader range of customer opinions and experiences.

Policymakers can gain insight into a destination’s position in the competitive landscape. This study has numerous implications for policymakers in the relevant destinations and managers in the design and implementation of services.

The findings of this study can have broader societal implications if considered and implemented by decision-makers and tourism businesses in the context of competitiveness.

The study’s originality lies in integrating multiple disciplines and comparing tourism destinations using big data. This study improves the understanding of competitiveness in three specific Mediterranean destinations. Previous research has focused on different contexts in these Mediterranean destinations. Therefore, the study fills this gap by focusing simultaneously on all three destinations in the context of competitiveness.