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Effective translation has become essential for seamless cross-cultural communication in an era of global interconnectedness. Translation management systems (TMS) have redefined the translation landscape, revolutionizing project management and execution. This study examines the attitudes of translation agencies and professional translators towards integrating and utilizing TMS, with a specific focus on Saudi Arabia.

The study's design was based on a thorough mixed-methods strategy that purposefully combined quantitative and qualitative procedures to create an array of findings. Through a survey involving 35 participants (both project managers and professional translators) and a series of interviews, this research explores the adoption of TMS, perceived benefits, influencing factors and future considerations. This integrated approach sought to investigate the nuanced perceptions of Saudi translation companies and expert translators about TMS. By combining the strengths of quantitative data's broad scopes and qualitative insights' depth, this mixed-methods approach sought to overcome the limitations of each method, ultimately resulting in a holistic understanding of the multifaceted factors shaping attitudes within Saudi Arabia's unique translation landscape.

Based on questionnaires and interviews, the study shows that 80% of participants were familiar with TMS, and 57% had adopted it in their work. Benefits included enhanced project efficiency, collaboration and quality assurance. Factors influencing adoption encompassed cost, compatibility and resistance to change. The study further delved into participants' demographic profiles and years of experience, with a notable concentration in the 6–10 years range. TMS adoption was linked to improved translation processes, and participants expressed interest in AI integration and mobile compatibility. Deployment models favored cloud-based solutions, and compliance with industry standards was deemed vital. The findings underscore the evolving nature of TMS adoption in Saudi Arabia, with diverse attitudes shaped by cultural influences, technological compatibility and awareness.

This research provides a holistic and profound perspective on the integration of TMS, fostering a more comprehensive understanding of the opportunities, obstacles and potential pathways to success. As the translation landscape continues to evolve, the findings from this study will serve as a valuable compass guiding practitioners and researchers towards effectively harnessing the power of technology for enhanced translation outcomes.

The integration of the Internet in translation creates several opportunities for translators. This study aims at examining the impact of using web-based translation (WBT) on translating religious texts.

The study followed a quasi-experimental study design. Sixty students enrolled in English Department, University of Bisha, participated in this study. The participants were divided randomly into three groups (i.e. words group, sentences group and passages group). The data was collected through a translation test and a questionnaire.

The results indicated that WBT is more beneficial in translating words than translating sentences or passages. In addition, WBT is more beneficial when words are translated from English into Arabic as well as from Arabic into English. The results from the questionnaire revealed positive attitudes toward using WBT in the process of translation.

This use of technology in translation has been examined in many studies (e.g. Bundgaard et al., 2016). WBT can be used to translate any field of knowledge. One of these fields is religious translation. According to O'Connor (2021), the study of religious translation has expanded greatly in recent years from its strong textual tradition and a constant focus on equivalence and translatability. However, very little has been done to examine the impact of WBT on translating religious texts. Therefore, this study aims at exploring the impact of WBT on translating religious texts with special reference to Islamic texts.

The spread of Covid-19 has led to the closure of educational institutions worldwide, forcing academic institutions to find online platforms. The purpose of this paper is to accelerate the development of the online learning (OL) environments within those institutions. The Covid-19 pandemic has unfolded the extent of the academic institutions' readiness to deal with such a crisis.

In this vein, the study aimed to identify the perception of translation instructors in teaching translation courses online during Covid-19, using a questionnaire to explore the strategies and challenges of teaching and assessing students' performance. The analysis revealed instructors' reliance on Zoom and Microsoft Teams in offering virtual classes and WhatsApp in communication with students outside the class.

The findings revealed the relative effectiveness of online education, but its efficacy is less than face-to-face learning according to the respondents' views. It was also found that students faced difficulties in OL, which lie in adapting to the online environment, lack of interaction and motivation and the deficiency of data connections. Even though online education could work as an aid during Covid-19, but it could not replace face-to-face instruction. Based on the findings, the study recommended blended learning. Combining online education with face-to-face instruction, i.e. face-to-face plus synchronous and asynchronous, would result in a rigorous OL environment.

The research is genuine and there is no conflict of interest.

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.

While digital transformation holds immense promise, organizations often fail to realize its benefits. This study aims to address how policies for digital transformation benefits realization are translated into practice.

The authors apply a qualitative, comparative case study of two large, public-sector health care organizations in Sweden. Through document and interview data, the authors analyze the process of translation.

The study finds that practice variation is primarily caused by two types of decoupling: policy-practice and means-ends. Contrary to previous studies, coercion in policy compliance is not found to decrease practice variation.

The limitations primarily stem from the empirical selection of two large public health-care organizations in Sweden, affecting the study’s generalizability. Reducing practice variation is more effectively achieved through goal alignment than coercion, leading to implications for the design of governance and control.

Policymakers should, instead of focusing on control-related compliance, work to align organizational objectives and policies to decrease practice variation for successful benefits realization.

The study contributes to better benefits realization of digital transformation initiatives in health care. As such, the authors contribute to a better functioning and more transformative health care in times of increased demand and decreased supply of health-care services.

The study challenges conventional wisdom by identifying that coercion is less effective than goal alignment in reducing practice variation, thereby enhancing the understanding of policy implementation dynamics in health-care settings.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

The authors argue that the mainstream scholarly discourse on hybridity and accounting is thus far primarily interested in the use and effects of accounting “in” hybrid organizations. Consequently, the literature has to a lesser extent explored how accounting mediates hybrid settings (while also being mediated), and the role of disentanglements in such processes. In hybrid settings, objects are difficult to define, and measures and tools difficult to agree upon. However, the literature on hybrid accounting is inconclusive and indicates that accounting can potentially both stabilize and de-stabilize relations in a hybrid setting. The authors address the research question of how accounting emerges and manifests itself in a process of entangling and disentangling in a heterogeneous emerging hybrid setting.

The paper is based on a longitudinal qualitative case study of the implementation of social investments, a public sector calculative framework based on the logic of measuring long term and social and economic impact of prevention. Methodologically, the study was guided by actor-network theory. In total, 18 observations and 48 interviews were conducted.

The observation the authors make in their case study is that much effort was spent on both keeping things apart and tying elements together. What the authors add to the literature is an illumination of how the interplay between entanglements and disentanglements facilitated the design idea of social investments to be enacted as multiple semi-integrated and purified hybridizations. The authors describe different translation points, each representing a specific hybridization where elements were added, recombined and disentangled. Still, the translation points were not completely compartmentalized, but rather semi-integrated where associations were facilitated through active mediation, likeness and productiveness for each other.

One limitation is the single case approach. A second limitation arises from the ANT approach to hybridity.

A practical implication of this paper is that in hybrid settings, the semi-integrated character may be interpreted as a strength because it allows the mobilization of heterogenous actors. However, this may also come at the cost of governability and raises further questions of managerial practices in hybrid settings.

The paper suggests the potentially productive role of disentanglements in allowing multiple hybridizations to evolve in hybrid accounting settings.

The paper suggests the potentially productive role of disentanglements in allowing multiple stabilized hybridizations to evolve in hybrid accounting settings.

In this paper, we depart from extant conceptualisations of knowledge translation mechanisms to examine projects as a way to achieve effective knowledge transfer. Our empirical analysis focused on a university–industry research project in the automotive industry.

The empirical analysis was based on a qualitative investigation. We analysed material collected within a research project involving a partnership between two universities and Fiat-Chrysler Automotive (FCA), a multi-brand auto manufacturer with a product range covering several different market segments. We used three data collection techniques: internal document analysis, participant observation and semi-structured interviews.

Our findings show that, in a U-I research project, goals represent a key dimension to support knowledge translation. Defining the goal implies an ongoing negotiation process, where researchers and company employees work together, in order to converge towards a shared meaning of the goal. In this sense, goal orientation and goal-based interaction have significant implications for knowledge translation processes.

Studies to date have focussed on the concept of knowledge translation as a way to contextualise the transfer from the source of knowledge to the receiver and to interpret the knowledge to be exchanged. This study expands the understanding of knowledge translation mechanisms in university–industry research settings. It investigates the concept of projects as powerful knowledge translation mechanism in a dynamic and longitudinal perspective. Our contribution provides insight, reflecting on how the use of projects may represent a way to facilitate knowledge transfer and build up new ideas and solutions.

The purpose of the current study was to examine the role of distance learning in enhancing introverted students’ lack of communication and social interaction to improve their performance in translation class. Cain (2013) and Kuzeljevich (2017) agreed that identifying “introverted” and “extroverted” students is important for meeting their learning needs. While extroverted students have strong social skills that allow them to interact comfortably in different learning environments, introverted students tend to be more shy, quiet, and silent, thus, requiring more careful planning in classroom settings. Therefore, educators need to support introverted students in reaching their full academic and social potential.

The present case study adopted a qualitative research method to explore the role of online/distance learning during the COVID-19 pandemic in enhancing introverted students’ performance and communication abilities in translation classes. The researcher of the current study spent a considerable time observing and set herself as part of the group (i.e. translation students of level 6 class) to understand the phenomenon, events and the new situation of having translation students interact in online settings. Data collection was based on this observation, interviews with the participants and archival documents. To enhance the validity and credibility of this research, the researcher employed the method of triangulation.

The results (see Appendixes A, B and C) revealed the level of students interactions in translation classes and their attitudes toward online learning. Based on the observations made by the instructor, the researcher found that the involvement of the introverted students during online translation learning was remarkable, as they provided their translation outputs in the chat window of Microsoft Teams with no hesitation. Consequently, 65% of the students were providing their translation output through the chat window, which indicates that they are more introverted and preferred not to speak. Comparing this result to face-to-face translation class, the researcher found that 25% of the students provided their translation outputs through oral participation.

This study contributes to the field of translation and education. Previous studies have not sufficiently examined the role of distance learning in enhancing the performance and communication of introverted students in translation classes. The current study is also expected to provide insight into the field of technical translation in remote teaching and learning settings.