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Spoken service language is critical for service experiences and human welfare in many service settings. However, little is known about how spoken service language can enhance customer well-being in transformative service contexts. This paper explores spoken service language and well-being for customers experiencing vulnerability in a transformative service context, informed by an empirical account of the human welfare service of residential aged care.

Situated within transformative service research (TSR), this study was guided by a theoretical framework of service language and adopts a strengths-based approach to customer experiences of vulnerability. A qualitative multiple case study methodology was applied to explore carers’ perspectives on spoken service language and well-being from three residential aged care homes in Australia.

The findings demonstrate five spoken service language practices and four principles of spoken service language for well-being that co-create customer well-being and support the alleviation of customer experiences of vulnerability. Conceptualised as transformative spoken service language, the spoken service language practices and principles collectively recognise, support and leverage residents’ capabilities and uplift customer well-being, by enacting a process of mattering highly salient to transformative service contexts.

This study is the first to conceptualise how employee spoken service language can be used to support customer well-being and enhance transformative value for customers experiencing vulnerability to align with the goals of TSR. Practically, the study advocates for a greater awareness and more considered use of transformative spoken service language in human welfare and other transformative service contexts.

This study aims to improve the Unified Theory of Acceptance and Use of Technology (UTAUT) model by examining technological anxiety and other influential factors on international students' adoption of mobile learning (m-learning) during COVID-19 emergency remote teaching (ERT).

This study utilized the modified UTAUT framework to test hypotheses through a cross-sectional survey method. Participants were university students studying Chinese as a foreign language who were selected using a convenience sampling approach. An online questionnaire was then administered. The data collected from the surveys were analyzed using the partial least squares method with SmartPLS 4 software.

The study examined 16 hypotheses and found support for six of them. The results confirmed that performance expectancy (PE) is a significant predictor of behavioral intention (BI), and anxiety influences both PE and effort expectancy. The negative effect of social influence on anxiety was found to be significant, while facilitating conditions had a negative impact on learners' self-efficacy. The model fit indices indicated a good overall fit for the model.

This study presents a valuable contribution to the literature on m-learning in emergency education by incorporating technological anxiety into the enhanced UTAUT model. Examining the relationships between the key factors of the model provides a better understanding of learners' intentions and can inspire researchers to establish new theoretical foundations to evaluate the roles of these factors in diverse educational settings.

The study found that performance expectations are linked to learners' intentions, and anxiety indirectly affects BIs to use mobile learning platforms. Thus, these platforms should be designed to meet learners' expectations with minimum effort and eliminate anxiety triggers to facilitate ease of use. Language curriculum developers and policymakers should incorporate mobile learning applications to support diverse language skills, address students' needs and encourage their use through professional development opportunities for instructors.

Social factors have been found to significantly influence anxiety levels among learners. Therefore, it is crucial for teachers and family members to play an essential role in mitigating anxiety's adverse effects. Discussing related issues can enhance the quality of mobile learning and stimulate social initiative by providers, ultimately improving the learning experience for all learners, regardless of their location or circumstances. This can also contribute to the growth and development of society.

This study contributes to the originality of m-learning development by proposing an enhanced UTAUT model that considers anxiety and emphasizes the critical role of foreign learners' BIs. It provides fundamental guidelines for designing and evaluating m-learning in ERT contexts.

The context of a long-standing research tradition, discrimination has emerged as a critical factor contributing to inequalities within the labor market. While existing studies have primarily focused on overt discrimination during the recruitment and selection process, influenced by biases, attitudes, or stereotypes, there remains a significant knowledge gap regarding discrimination within the workplace and its underlying structural dimensions. This article aims to address this gap by examining the impact of organizational culture, structure and policies on workplace discrimination, with a particular emphasis on women and ethnic minorities.

Utilizing a case study strategy centered around a Belgian branch of a multinational professional service agency, data was gathered through ten semi-structured in-depth interviews conducted with employees representing various organizational levels.

The findings reveal that organizational culture, structure and policies may pose inherent risks in perpetuating discrimination throughout individuals' professional trajectories. Furthermore, it becomes apparent that, albeit often unconscious, these elements exhibit biases against women and ethnic minorities.

Given the unintentional nature of structural discrimination, it is crucial to foster increased awareness and understanding of these dynamics.

The originality of this research article lies in its focus on addressing a critical knowledge gap in the existing research tradition on discrimination in the labor market. While previous studies have primarily concentrated on overt discrimination during recruitment and selection, this article delves into the often overlooked area of discrimination within the workplace itself. It explores the intricate interplay of organizational culture, structure and policies in perpetuating discrimination, particularly against women and ethnic minorities. By utilizing a case study approach within a multinational professional service agency in Belgium, the research uncovers hidden biases and unconscious elements contributing to structural discrimination. This emphasis on understanding unintentional discrimination adds a novel dimension to the discourse on workplace inequalities.

Current and predicted continued dramatic increases in international migration and ethnocultural diversity of older adult cohorts pose challenges for health care services. Review studies on ethnoculturally diverse older adults and health care show a lack of focus on their service use experiences. This study aims to report a meta-ethnography that addresses this knowledge gap through answering the review question: How do ethnoculturally diverse older adults who are immigrants experience health careservices?

The authors applied a seven-phase method of meta-ethnography to guide the review. The authors conducted two literature searches (April 2018 and June 2020) in MEDLINE, CINAHL, Embase, Sociological Abstracts and Abstracts in Social Gerontology that yielded 17 papers eligible for review.

“There’s always something positive and something negative” is the overarching metaphor for answering the review question. Findings highlight positive and negative tensions within ethnoculturally diverse older adults’ health care use experiences of understanding and being understood, having trust in providers and the health care system, having needs, preferences and resources met and desire for self-care over dependency. The majority of experiences were negative. Tipping points towards negative experiences included language, fear, provider attitudes and behaviours, service flexibility, attitudes towards Western and traditional health care and having knowledge and resources.

The authors propose concrete actions to mitigate the tipping points. The authors discuss policy recommendations for health care system changes at the micro, meso and macro service levels to promote positive experiences and address mainstream service policy inequities.

How closely does the translation match the meaning of the reference has always been a key aspect of any machine translation (MT) service. Therefore, the primary goal of this research is to assess and compare translation adequacy in machine vs human translation (HT) from Arabic to English. The study looks into whether the MT product is adequate and more reliable than the HT. It also seeks to determine whether MT poses a real threat to professional Arabic–English translators.

Six different texts were chosen and translated from Arabic to English by two nonexpert undergraduate translation students as well as MT services, including Google Translate and Babylon Translation. The first system is free, whereas the second system is a fee-based service. Additionally, two expert translators developed a reference translation (RT) against which human and machine translations were compared and analyzed. Furthermore, the Sketch Engine software was utilized to examine the translations to determine if there is a significant difference between human and machine translations against the RT.

The findings indicated that when compared to the RT, there was no statistically significant difference between human and machine translations and that MTs were adequate translations. The human–machine relationship is mutually beneficial. However, MT will never be able to completely automated; rather, it will benefit rather than endanger humans. A translator who knows how to use MT will have an opportunity over those who are unfamiliar with the most up-to-date translation technology. As MTs improve, human translators may no longer be accurate translators, but rather editors and editing materials previously translated by machines.

The findings of this study provide valuable and practical implications for research in the field of MTs and for anyone interested in conducting MT research.

In general, this study is significant as it is a serious attempt at getting a better understanding of the efficiency of MT vs HT in translating the Arabic–English texts, and it will be beneficial for translators, students, educators as well as scholars in the field of translation.

This study aims to investigate the quality level of the leading three Public Administration Institutes’ (PAIs) websites in the Arab world.

A convenient sample of 203 Jordanian Government employees answered the questionnaire that assessed five quality dimensions (content, navigation, interface design, accessibility and educational purpose) for each website.

The website of PAI of Kingdom of Saudi Arabia recorded a high level in all quality dimensions, whereas the website of PAI of Jordan recorded moderate quality in all dimensions except for accessibility; the website of PAI of Egypt recorded a high level in all quality dimensions except for the educational purpose. Based on the qualitative analysis, participants agreed that the PAI website has the best quality, accessibility, navigation and design compared with the Egyptian and the Jordanian PAIs websites.

Designers of PAI websites should consider end users’ needs and regularly assess the website’s usability. PAIs developers should also establish more interactive portals to provide transparent and effective electronic services to users. The findings are significant in helping policymakers better understand the importance of distance training and learning using websites and platforms.

Developing a high-quality website enhances the relationship between the government and its employees, consequently establishing the credibility and trust of citizens in public services.

To the best of the authors’ knowledge, this is the first study that measures the quality of PAI websites in the Arab world. The findings provide more cross-culture evidence for the e-government and digital literature in helping policymakers develop more technology interactive platforms.

This study aims to examine the interaction effects of chatbots’ language style and customers’ decision-making journey stage on customer’s service encounter satisfaction and the mediating role of customer perception of emotional support and informational support using the construal level theory and social support theory as conceptual frameworks.

This study used a scenario-based experiment with a 2 (chatbot’s language style: abstract language vs concrete language) × 2 (decision-making journey stage: informational stage vs transactional stage) between-subjects design.

Findings show that during the informational stage, chatbots that use abstract language style exert a strong influence on service encounter satisfaction through emotional support. During the transactional stage, chatbots that use concrete language style exert a strong impact on service encounter satisfaction through informational support.

Findings provide some suggestions for improving customer–chatbot interaction quality during online service encounters.

This study offers a novel perspective on customer interaction experience with chatbots by investigating the chatbot’s language styles at different decision-making journey stages.

This study examines the dualities of digital services – that is, how customers’ favorite everyday digital services can positively and negatively contribute to their well-being. Thus, the study describes the meanings of favorite digital services as part of customers’ everyday lives and the types of well-being to which such services can contribute.

We used a qualitative research approach through semi-structured interviews conducted in 2021 to collect data from 14 young adults (22–31 years old) who actively used digital services in their daily lives.

Our findings revealed that customers’ favorite everyday digital services can contribute to their mental well-being, social well-being, and intellectual well-being. Within these three dimensions of well-being, we identified nine dualities of digital services that describe their positive and negative contributions: (1) digital escapism versus digital disruption, (2) digital relaxation versus digital stress, (3) digital empowerment versus digital subjugation, (4) digital augmentation versus digital emptiness, (5) digital socialization versus digital isolation, (6) digital togetherness versus digital exclusion, (7) digital self-expression versus digital pressure, (8) digital learning versus digital dependence, and (9) digital inspiration versus digital stagnation.

These findings suggest that everyday digital services have the potential to contribute to customer well-being in various aspects – both positively and negatively – accentuating the need for service providers to decipher the impacts of their offerings on well-being. Indeed, understanding the relationship between digital services and customer well-being can help companies tailor their services to customers’ needs. Companies that prioritize customer well-being not only benefit their customers but also create sustainable growth opportunities in the long run. Further, companies can use the derived information in service design to develop marketing strategies that emphasize the positive impacts of their digital services on customer well-being.

Although prior transformative service studies have investigated the well-being of multiple stakeholders, such studies have focused on services related to the physical and healthcare domains. Consequently, the role of everyday digital services as contributors to customer well-being is an under-researched topic. In addition, the concept of well-being and its various dimensions has received limited attention in previous service research. By investigating everyday digital services and their multidimensional contribution to customer well-being, this study broadens the perspective on well-being within TSR and aids in refining a more precise conceptualization.

This study aims to investigate a unique approach to learning languages through self-directed online learning. Specifically, it explores the self-management abilities and skills learners need while learning a language outside traditional classroom settings when using mobile-assisted learning technology.

A mixed-methods approach was used in this study, including an online survey of 84 people and 10 semi-structured interviews.

Findings reveal the significant role of specific and well-defined learning goals in enhancing learners’ performance. These goals can be either self-initiated by the learners themselves or defined by the technological features of the learning platform. However, the presence of distractions in learners’ daily lives presents challenges to effective time management, affecting learners both physically and psychologically. A key aspect of self-directed language learning lies in the learners’ ability to seek out relevant human and material resources beyond the confines of a single mobile-assisted language learning (MALL) tool. The authenticity of these resources is crucial in ensuring meaningful and effective learning experiences.

Understanding how learners navigate and discover valuable resources is a central focus of this study. This research offers valuable insights into the field of self-directed language learning, revealing the pivotal role of self-management skills with mobile-assisted learning technology. The findings contribute to the broader field of language education and offer practical implications for educators and developers seeking to optimize self-directed language learning experiences through innovative and technologically driven approaches.

MALL is often ideal for individualized informal learning, but the existing literature focuses heavily on formal learning situations, underestimating the importance of MALL practices in various informal settings. Most research reports on MALL-based self-directed learning primarily sample traditional English-learning university students. Therefore, there is a need for research on how nontraditional older adult learners self-direct their language learning with mobile technology outside the classroom.

The proliferation of ChatGPT, as in many other digital technologies and social media, has increasingly impacted many aspects of modern life, including second and foreign language education. This study, building on a common theoretical position of all these advances in Artificial intelligence (AI), seeks to establish a model for ChatGPT research on English language learning. It specifically explores the dimensions in which ChatGPT aids students in their English language learning.

The study adopts grounded theory in collecting and analyzing data from 20 ResearchGater (RG) through a two-week RG discussion about ChatGPT uses in their language learning contexts. Data collected via the discussion was analyzed thematically.

Preliminary findings show that ChatGPT can be used in developing learners' language skills; scaffolding the learning process by providing feedback to students on their language use and acting as partners in practicing language with recommended activities for more language practice.

The study contributes a five-dimension model for artificial intelligence assisted language learning (AIALL). The model involves flexible teacher's role to consolidate learner autonomy and provide enjoyable learning, urges future innovation, and celebrates various applications. Examining the AIALL model of ChatGPT for language learning, teachers should provide some directions for properly using this new application.