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Doctoral degrees are generally the highest level of education provided by educational institutions in Western countries. Nevertheless, doctoral degree holders – i.e. Philosophiae Doctors (PhDs) – struggle to find a job that matches their knowledge and expertise. This article investigates the effects that PhDs' satisfaction with different attributes of educational services has on their ability to obtain employment either in academia or outside it.

Secondary data were accessed from a nationwide survey performed in Italy between February and July 2014. More than 16,000 people who achieved a doctoral degree between January 2008 and December 2010 were involved in the analysis. The four-years' time-span was justified by the need to avoid potential biases produced by a short time lapse between data collection and the awarding of the respondents' doctoral degree. A logistic regression model was designed to shed light on the relationship between doctoral degree holders' satisfaction and their ability to find employment.

This study results suggested that the attributes of educational services had varying effects on the doctoral degree holders' ability to obtain work. More specifically, the perceived quality of research and methodological courses delivered by educational institutions and the quality of the technologies and digital resources available at the host university were found to positively affect the ability of doctoral degree holders to get a job in academia. Conversely, the satisfaction with the quality of the teaching activities was positively related to the doctoral degree holders' employability outside academia.

The quality of educational services provided to students attending a doctoral degree course affects their ability to find work. Enhancing the quality of educational services may reduce the risk of unemployment amongst doctoral degree holders.

To the best of the authors' knowledge, few attempts have been made to investigate the interplay between the quality of educational services and doctoral degree holders' employability.

The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots.

This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering.

Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education.

The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective.

This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.

This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.

Within the labor-intensive construction industry characterized by distinctly structural shortages in the labor force worldwide, efficient and effective migration of construction workers across regions is critical for the smooth operation of construction activities. This study aims to investigate how the interregional migration patterns of construction workers are impacted by the disparities in both employment opportunities and environment amenities between the origin and destination provinces.

Drawing on the push and pull theory and the archival data on 13,728 migrant construction workers in China, descriptive analyses are first performed to characterize the interregional migration patterns of the investigated construction workers. Combining regional data in the National Bureau of Statistics of China, this study uses hierarchical regression modeling techniques to empirically test the relative importance of the employment-related and environment-related factors in driving the interregional migration of construction workers after controlling for the effects of related economic and geographic factors.

The results provide evidence that the interregional migration of construction workers is principally driven by the disparities in employment opportunities while disparities in environment amenities (including climate comfort disparity, medical service disparity and educational service disparity) generally play much fewer substantive roles. With regard to the impacts of employment opportunities, the results provide evidence that compared with the disparity in job market size, the disparities in job income and industry development level are more significantly relevant factors, which positively pull and adversely push the interregional migration flows, respectively.

This study contributes to a deepened understanding of how workers specifically balance their employment and amenity needs to make temporary migration decisions in the “laggard” labor-intensive construction industry. This study also adds to the literature on population migration by characterizing the specific characteristics of construction workers and the temporary nature of the workers' migration activities. The findings hold important practical implications for construction organizations and policymakers for effectively managing the mobility of migrant construction workers.

The extant literature on migrant construction workers has primarily focused on the consequences of international migration and the generalization of empirical findings on population migration mechanisms in other domains to the construction industry is substantially limited by the specific characteristics of construction workers and the temporary nature of their migration activities. In addressing this gap, this study represents an exploratory effort to quantitatively characterize the interregional migration patterns of construction workers in the labor-intensive construction industry and examines the roles of employment opportunity and environmental amenity in driving interregional migration.

This study evaluated the impact of a faculty training program on student assessment using the Kirkpatrick model.

A self-reported survey assessed 111 Saudi and non-Saudi participants' satisfaction. Subjective and objective measures (self-reported measures, assessment literacy inventory and performance-based assessment tasks) gauged participants' learning level. Pre- and post-training data were collected from 2020 to 2022.

A highly significant effect on satisfaction (>80%) and learning levels was observed, as manifested by workplace practices of student assessment (>70%, the cut-off score). Pre- and post-training comparisons of participants' satisfaction and assessment literacy scores showed significant improvements following training. Multiple regression analyses showed no significant effects for gender and educational attainment but a substantial impact of academic cluster on participants' student assessment skills.

Long-term effects of training faculty on assessment practices and student achievement will be studied at the institutional level in future research.

The current study contributes to human capital investment via faculty training on student assessment, helping them comply with assessment best practices. This assures the quality, fairness and consistency of assessment processes across disciplines in higher education institutions, enhances assessment validity and trust in educational services and may support institutional accreditation.

This study provides opportunities for sharing best practices and helps establish a community of practice. It enhances learning outcomes achievement and empowers higher education graduates with attributes necessary to succeed in the labor market. The human capital investment may have a long-term impact on overall higher education quality.

This study contributes to the scarce literature investigating the impact of training faculty from different clusters on student assessment using subjective and objective measures. It provides developing and evaluating a long-term student assessment program following the Kirkpatrick model.

Augmented reality is one of the technologies that developed and became widespread, especially after the 2000s. It is seen that innovations such as 3D virtual reality glasses, artificial intelligence-supported smart chatbots that communicate with customers in a virtual environment, keyless hotel systems, the Internet of Things, augmented reality applications, smart personal assistants, digital infrastructure concepts and face recognition systems are used in tourism businesses. The place and use of augmented reality technologies in tourism enterprises are discussed in this study. This study was evaluated from the perspective of UTAUT2. The purpose of this study is to examine the usability of augmented reality technologies in tourism businesses.

Within the scope of the study, interviews were held with augmented reality application developers, digital marketing agencies and accommodation business managers. The obtained data were processed with the MAXQDA analysis program.

It has been determined that augmented reality is a useful and informative technological tool for tourists, it can help sales, promotion and marketing activities, and its usability potency in accommodation businesses is high.

When the literature is reviewed, it is understood that the studies that apply to the opinions of the application developers and the managers of the accommodation establishments are limited. Therefore, this study has been prepared to contribute to the literature in this respect. This study examines and discusses the use of augmented reality technologies in tourism enterprises, the benefits and difficulties they will create from the perspective of application developers and accommodation business managers and their place in tourism enterprises. This study was evaluated from the perspective of UTAUT2. There is a need for research developed using UTAUT models in technology acceptance studies. In this respect, it will contribute to the literature.

This study sheds light on the impact of coronavirus disease 2019 (COVID-19) on self-employed women in Mauritius and delves into their coping strategies amid unprecedented circumstances.

The study employs a comprehensive methodology encompassing both qualitative and quantitative approaches. Qualitative analysis is conducted via interviews with self-employed women in Mauritius, capturing their experience with COVID-19. Quantitative analysis uses survey data from 732 firms to investigate factors affecting online sales, a major survival strategy adopted by businesses.

The study finds a notable trend wherein many interviewed women have transitioned their businesses online – a pivot that stands out as a common response within the sample. The quantitative analysis indicates the significance of a strong online presence, particularly on social media and web-based platforms designed for the sale of goods and services. These factors correlate with higher online sales, potentially enhancing resilience during pandemic-induced lockdown periods.

This study stands out for its originality, representing the first study investigating how women entrepreneurs in Mauritius have navigated the challenges posed by the COVID-19 crisis.

This study aims to investigate the usability of a public university website for measuring its efficiency, users’ satisfaction or anxiety while searching for and retrieving information through different devices.

A task-based approach was adopted for the study. Twenty-eight participants were asked to complete 11 information-searching tasks on the website. The participants were divided into two groups. The tasks were carried out by members of each group, using desktop and mobile devices in a rotating fashion. Volunteers observed the participants' actions and recorded information regarding their productivity, time usage (using a timer), satisfaction or annoyance while performing each task. Finally, based on the use of the devices, a comparison was established between the participants' performance accuracy, efficiency and anxiety.

The study provides an overview of a task-based user experience carried out on the university website using a combination of qualitative and quantitative research methods. According to the results, participants' satisfaction levels were generally high, and their anxiety levels were low while completing the tasks on a mobile device. In comparison to the desktop, it took less time overall to complete all tasks. On the other hand, using a desktop computer (97.1%) resulted in better task completion success rates for participants than using a mobile device (85.7%).

No previous task-based evaluation study of this kind has been conducted to assess the usability of any university website in Bangladesh.

This study aims to investigate how organizations from different sectors interpret the meaning of business continuity management (BCM) in the light of the COVID-19 pandemic.

A survey was conducted to capture the views of organizations across five different sectors. The sample consisted of ten senior managers; two from the banking sector; two from the supply chain sector (agricultural and food supply chains); two from the tourism sector; two from the services sector; and two from the higher education sector. An interviewer-administered questionnaire was used to collect the data. One manager from each sector represented a local business/enterprise and the other represented an international business/enterprise.

It was found that different organizations/businesses understood BCM differently. Therefore, a variety of interpretations have been obtained.

This study sheds light on how different organizations understand BCM in times of crisis, such as the COVID-19 pandemic. By understanding the different interpretations, it becomes clearer whether or not these organizations have applicable business continuity plans in place.

This is the first study to investigate the different interpretations of the meaning of BCM across different business sectors. The majority of the existing studies on BCM discuss the process from the perspective of a single business or sector. The study was conducted during the COVID-19 pandemic, a period that witnessed prolonged and critical disruptions facing almost all businesses and organizations and which threatened the survival of some of them.

The current research inspects the moderation role of ownership concentration on chief executive officer (CEO) characteristics and real earnings management (REM) relationship in Jordan.

Driscoll–Kraay regressions were run using data from 348 firm-year observations for companies listed on the Amman Stock Exchange between 2013 and 2018.

Driscoll–Kraay regressions demonstrate that CEO experience, tenure and political connections improve REM practices. Ownership concentration diminishes and limits REM practices when combined with CEO experience, tenure and political connections, since all three have a negative and significant link with REM.

Initial constraints include the study’s lack of generalisability due to a small number of CEO-related parameters. Second, critics of the ideal model for judging EM have a foreseeable flaw. No generally accepted model is perfect.

This study’s conclusions are crucial for industry participants, including companies, policymakers, investors and the general public. These findings will help investors, practitioners and regulators understand that businesses with significant ownership concentrations and experienced CEOs have superior earnings and low REM practises.

The findings of this study have an optimistic impact on the existing body of knowledge. The current literature has yet to properly inspect the moderation role that ownership concentration has on the connotation between CEO characteristics and EM.

Despite several research studies in both developed and developing nations, ownership concentration has been almost virtually neglected. The current study could fill a hole in earlier research, rendering it a novel study.