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The main goal of this study is to determine the role of employee commitment in the relations between the compensation system and turnover intentions of employees in the Republic of Serbia, as well as to investigate whether there is a mediating effect of employee commitment in this relation.

The primary methodology implemented in the research was data gathering, obtaining theoretical research works on the proposed relations and empirical studies based on the PLS-SEM, analysed by IBM SPSS Statistics and SmartPLS data processing software. The data for the analysis was obtained from a total sample of 764 employees, collected in the Republic of Serbia via an online questionnaire.

The results indicated a positive statistically significant relationship between the formative construct (compensation system) and reflective construct (commitment), as well as a negative statistically significant relationship between the compensation system and reflective construct (turnover intentions). Employee commitment partially mediates the relationship between the compensation system and turnover intentions of employees.

The study was conducted in Serbia and is thus rooted in the specific national context which is characterized by high power distance and high uncertainty avoidance and more collectivistic society with feminine values more expressed. Most of the previous investigations related to the mentioned constructs were performed in companies from more developed countries, including Western Europe and the United States of America, whereas there has been no such research conducted in Serbia to date. The results portrayed a mismatch between the expected relations regarding the attitudes of employees to the rewards and the proposed national context. Modern companies in Serbia need to follow a modern reward mechanism to build stronger commitment and decrease turnover intentions. Moreover, in most earlier research works, compensation was examined in terms of satisfaction with rewards, while this study was based on questions related to perceptions of employees toward HR compensation practices (“The organization offers me”-type questions), not related to their satisfaction. Further, in the majority of previous research works, the compensation system was examined as a variable in combination with other HR processes (staffing, training and development, career development, employee relations, HR planning, communication, etc.), as a HPWP, while in this case the authors used only the practice of compensation (reward elements and employee performance evaluation) to investigate relations with commitment and turnover intentions.

The emergence of artificial intelligence technologies, like ChatGPT, has taken the world by storm, particularly in the education sector. This study aims to adopt the unified theory of acceptance and use of technology to explore how effort expectancy (EEC) and performance expectancy (PEE) individually, jointly, congruently and incongruently affect higher education students’ intentions and actual uses of ChatGPT for their learning.

An advanced methodology – polynomial regression with response surface analysis – and a sample of 1,461 higher education students recruited in Vietnam through three-phase stratified random sampling approach were adopted to test developed hypotheses.

Both EEC and PEE were found to have a direct positive impact on the likelihood of higher education students’ intention to use ChatGPT, which in turn promotes them actually use this tool for learning purposes. Conversely, a large incongruence between EEC and PEE will lower the level of intentions and actual uses of ChatGPT for learning. However, when there is a growing incongruence between EEC and PEE, either in a positive or negative direction, the likelihood of students’ intentions to use ChatGPT for learning decreases.

Some practical implications are subsequently recommended to obtain advantages and address potential threats arising from the implementation of this novel technology in the education context.

This study shed the new light on the educational setting by testing how higher education students’ intentions to use ChatGPT and subsequent actual uses of ChatGPT are synthesized from the balance between high EEC and PEE.

The main objective of this study is to investigate the factors that influence the adoption intention of cloud computing services among individual users using the extended theory of planned behavior.

A purposive sampling technique was used to collect a total of 339 data points, which were analyzed using SmartPLS to derive variance-based structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA).

The results obtained from PLS-SEM indicate that attitude towards cloud computing, subjective norms, perceived behavioral control, perceived security, cost-effectiveness, and performance expectancy all have a positive and significant impact on the adoption intention of cloud computing services among individual users. On the other hand, the findings from fsQCA provide a clear interpretation and deeper insights into the adoption intention of individual users of cloud computing services by revealing the complex relationships between multiple combinations of antecedents. This helps to understand the reasons for individual users' adoption intention in emerging countries.

This study offers valuable insights to cloud service providers and cyber entrepreneurs on how to promote cloud computing services to individual users in developing countries. It helps these organizations understand their priorities for encouraging cloud computing adoption among individual users from emerging countries. Additionally, policymakers can also understand their role in creating a comfortable and flexible cloud computing access environment for individual users.

This study has contributed to the increasingly growing empirical literature on cloud computing adoption and demonstrates the effectiveness of the proposed theoretical framework in identifying the potential reasons for the slow growth of cloud computing services adoption in the developing world.

There is a growing awareness in today's organizations of the gap between existing digital technologies and those arising from digital innovation that contribute to reducing work exhaustion. However, no comprehensive framework has been proposed for the importance of adopting digital innovation in reducing work exhaustion. The purpose of this paper is to provide a holistic view by proposing a model for the importance of adopting digital innovation technologies and their role in reducing work exhaustion in Iraq as a developing country, and the model was proposed based on the theory of technology-organization-environment and diffusion of innovation.

To collect data, an electronic questionnaire was designed for a survey conducted on 183 Iraqi firms in the industrial sector. For data analysis, the structured equation model was used through the (AMOS. 26) program.

The results revealed the importance and significance of the study model in adopting the cloud of things (CoT) as one of the techniques of digital innovation in reducing work exhaustion.

The authors can conclude that the adoption of the CoT in small and medium enterprises (SMEs) can have a positive impact on the performance of the employees. The adoption of the CoT may provide SME managers with an opportunity to effectively manage various roles and responsibilities. While there were many limitations that this study faced, the authors focused on one type of digital innovation dynamics, which is the CoT, as they must focus on other technologies.

To the best of the authors’ knowledge, this study is one of the first studies in Iraq as a developing country that explains how emerging digital innovation can be leveraged to create innovative digital products and services as a CoT technology and subsequently lead to the reduction of work exhaustion. It also fills the literature gaps related to adoption factors of digital innovation and their role in reducing work exhaustion.

Career adaptability is emerging as an important research area in today's uncertain, volatile world of work created by the COVID-19 pandemic. The present study focuses on career adaptability research post-COVID-19 by scientifically capturing the literature evolution, hotspots and future trends using bibliometric analysis.

The Scopus database, due to its vast and quality literature, was used to search the papers from the period 2020 to 2023. Bibliometric data were extracted and analyzed from the relevant literature. For further scientific mapping, VOSviewer and Biblioshiny software tools were used.

Findings of the analysis suggest a positive research trend related to career adaptability research post-Covid. Keyword analysis revealed noteworthy clusters and important themes. Bibliometric visual networks regarding authors, sources, citations, future themes, etc. are also presented from the 441 analyzed publications with comprehensive interpretation.

The literature for carrying out the bibliometric analysis was confined to the Scopus database. Other databases in combination with different software can be used for future niche research. From the analysis, future research avenues and practical interventions are presented which have significant implications for future researchers, career counselors and managers.

The study summarizes the recent literature on career adaptability in the aftermath of the pandemic and makes a novel contribution to the existing literature. A reliable study has been provided by the authors using the scientific bibliometric technique. The study highlights emerging research trends post the pandemic. The results are concluded with further suggestions which can guide future research related to the topic.