Humanizing or mechanizing the self? How mindset moderates AI usage on employee self-perception and job crafting.

This study constructs a moderating mediation model to link public sector employees’ Artificial Intelligence (AI) usage with employees’ moral norms and ethical decision-making behaviors. Based on the theory of public service motivation, this study hypothesizes that the impact of AI usage on employees’ ethical decision-making behaviors acts through the mediating effects of employees’ service motivation, employees’ moral norms, and employees’ ethical perceptions and that the relationship between AI usage and employees’ service motivation, employees’ ethical norms, and employees’ ethical perceptions is moderated by the culture of the public organization. The selected data from 417 public sector employees in China supported most of the research hypotheses. The findings show that employee service motivation, employee moral norms, and employee moral cognition mediate the relationship between AI usage and employee ethical decision-making behavior. Public organization culture moderated the relationship between AI usage and employee service motivation, as well as AI usage and employee ethics. This study reveals the complex mediating and moderating relationships between AI usage and employees’ ethical decision-making behaviors in the public sector. It provides important theoretical and practical insights for further understanding and promoting public sector employees’ ethical behaviors in the era of AI.

This study aims to analyse the influence of artificial intelligence (AI) usage on the design thinking skills of accounting students and the role of academic integrity as a moderator in this relationship. This study uses a quantitative approach with a survey method involving 323 accounting students from various universities in Indonesia. Data analysis was conducted using Partial Least Squares Structural Equation Modelling (PLS-SEM) to test the direct influence of AI usage on design-thinking skills and the role of academic integrity moderation. The results show that AI usage has a positive and significant effect on the design thinking skills of accounting students, which shows that the higher the utilisation of AI in learning, the more developed the design thinking skills of students. Additionally, academic integrity has been shown to strengthen the relationship between AI usage and design thinking skills, suggesting that students with high academic integrity are more likely to use AI responsibly to explore ideas and develop innovative solutions rather than simply seeking instant answers. This research contributes to the literature by describing the role of academic ethics in AI usage in accounting education, which has rarely been discussed in previous research. By integrating Social Cognitive Theory (SCT), this study shows how the interaction between behavioural factors (AI usage) and personal factors (academic integrity) can affect students' design-thinking skills. These findings have implications for educational institutions, lecturers, and students in ensuring that AI is used ethically and responsibly to support the development of high-level thinking skills in accounting.

This study explores the extent of Artificial Intelligence (AI) usage among students and its implications for academic ethics, with a specific focus on STKIP DDI Pinrang. Employing a mixed-methods approach, quantitative data were collected through Likert-scale questionnaires distributed to 40 students, while qualitative insights were gathered via interviews with selected respondents. The findings indicate that students’ AI usage is very high (mean score: 4.45), particularly through tools such as ChatGPT, Grammarly, and Quillbot. However, their ethical awareness remains moderate, both in terms of understanding academic ethics (3.1562) and awareness of the ethical implications of AI use (3.04). Correlation analysis reveals a negative relationship between the intensity of AI usage and students' ethical perceptions. Thematic analysis of interviews confirms that students tend to use AI as a substitute rather than a support, and lack institutional guidance on its ethical boundaries. These findings highlight a critical gap between technological proficiency and ethical literacy. The study recommends integrating digital ethics education across curricula and establishing clear institutional policies to ensure responsible AI use in academic settings.

Job crafting is an important self-focused proactive behavior. While previous research has highlighted the role of leadership in shaping employee job crafting, two key limitations exist. First, it has predominantly focused on leadership styles, neglecting leaders’ reactions to various forms of employee proactivity and their consequent impacts on employee job crafting. Second, it has not distinguished between different orientations of job crafting, leading to an incomplete understanding of how leaders influence distinct job crafting behaviors. To obtain an in-depth and nuanced understanding of how leaders affect employees’ job crafting, this paper examines the impact of managerial voice endorsement, as a positive managerial response to employees’ proactivity, on employees’ engagement in promotion- and prevention-oriented job crafting and elucidates the associated mechanisms. Through two multi-wave field studies, we found that managerial voice endorsement is positively related to promotion-oriented job crafting via status and negatively related to prevention-oriented job crafting via cynicism. In addition, a lower rather than a higher leader-member exchange relationship strengthens the positive indirect effect of managerial voice endorsement on promotion-oriented job crafting via status. This paper expands on existing knowledge by investigating how, why, and when employees craft jobs as a reaction to managerial voice endorsement.

As Artificial intelligence (AI) becomes increasingly prevalent in modern society, understanding its adoption among older adults is crucial. Therefore, this study examines the relationship between AI usage, Big 5 personality traits, and positive solitude, among adults aged 60 and over in Israel. Grounded in the Technology Acceptance Model (TAM), the study explore how personality traits and positive solitude influences perceived AI usability and adoption. A sample of 260 older adults participated in the study. Data were collected through online validated questionnaires and open-ended questions, using Qualtrics. Results revealed that AI users (mean age 69.91, SD=6.7) were younger than non-users (M=74.91, SD=7.6). Of the AI users, 68% were women, 94% were home-dwelling, 65% married, and 98% independent. Additionally, 76% reported using AI for 30-120 minutes daily. Non-users felt subjectively older both physically (M=62.82, SD=11.7) and mentally (M=62.82, SD=10.7) compared to users (physical: M=54.84, SD=13.5; mental: M=58.65, SD=12.7). Significant correlations were found between attitude to life and perceived ability to use AI (r=0.315, p< 0.01), as well as between attitude to life and aging perception (r=0.495, p< 0.01). The qualitative analysis revealed varied responses to AI use. Participants noted significant benefits, including new opportunities and skill enhancement. However, they also encountered technical challenges, concerns about data reliability, and difficulties in formulating effective queries. These findings offer valuable insights into promoting AI adoption among older adults, potentially enhancing their quality of life and independence in the digital age. Future research should explore interventions to increase AI acceptance and usage among this population.

Rapid advancements in the field of Artificial Intelligence (AI) and adaptive learning have revolutionized the way educational processes occur, especially in ESL settings. This paper seeks to evaluate the impact of implementation of AI and adaptive learning on the engagement and learning of university-level ESL learners. For this purpose, quantitative approach was adopted; and 250 ESL learners were targeted through a survey based on the 5-point Likert scale. Four primary constructs were incorporated in the proposed conceptual framework namely AI Usage (AIU), Adaptive Learning (AL), Student Engagement (SE) and Learning Outcomes (LO). Data analysis was conducted by utilizing Partial Least Square Structural Equation Model (PLS-SEM). Results demonstrate that both AI usage and AL have significant positive influences on SE. In addition, AL has a comparatively greater influence as compared to AI due to the reason that AL is personalized learning. Besides, SE is found to have the greatest influence on LO, which confirms the role of student engagement as a mediator between technology usage and learning outcome. Also, AI usage has a positive influence on LO with a smaller magnitude as compared to SE. Overall findings of this study highlight the significance of using AI-based technology and personalized learning systems to increase student engagement and improve their learning in the field of ESL. This study makes an important contribution to literature through employing PLS-SEM in ESL setting, which has been used quite rarely before. Practical implications have been discussed for educators, institutions and policymakers to enhance the process of ESL learning through use of technology. Future research could further investigate other factors like learner satisfaction, digital literacy etc.

PurposeDespite receiving much attention in recent job design literature, job crafting research has neglected motivational and multilevel perspectives, limiting the understanding of how to foster employee job crafting. Drawing on job crafting and self-determination theory, the purpose of this paper is to explore individual- and team-level predictors and the mechanisms involved in employees’ job change behaviors. The authors propose that employees’ intrinsic motivation and two team-level properties – team knowledge sharing and trust – have important roles to play.Design/methodology/approachThe multilevel data were collected from 311 employees from 62 work teams in Korean companies. Hierarchical linear modeling analysis was used. A supplementary data collected from 162 individuals working in the USA were used for analysis.FindingsThe results showed that intrinsic motivation and team knowledge sharing are positively related to job crafting. In addition, intrinsic motivation mediated the relationship between team knowledge and individual job crafting. Finally, team trust was shown to play a cross-level moderating role, strengthening the positive relationship between employees’ intrinsic motivation and job crafting.Originality/valueApplying motivational and multilevel perspectives, this paper uncovers the roles of individual motivation and team context in fostering employee job crafting. This study helps to extend the theoretical domains of job crafting and provides practical insights into how to promote employees’ job crafting.

As the application of artificial intelligence (AI) in the workplace increases, investigating its impact on work engagement is crucial for optimizing human resource management and enhancing organizational productivity and competitiveness. Based on the Conservation of Resources theory, this study investigated whether AI usage exhibits a double-edged sword effect on work engagement and examined the moderating role of core task characteristics substitution in this relationship. A two-wave study was conducted among 279 employees from China, and Hayes's PROCESS macro was used to test the moderated mediation model. The findings indicated that (1) AI usage enhances work engagement by increasing psychological availability and indirectly increases work engagement by suppressing work alienation; (2) core task characteristics substitution diminishes the enhancing effect of AI usage on psychological availability and the inhibiting effect of AI usage on work alienation; and (3) overall, AI usage tends to suppress work alienation, demonstrating an empowering effect. However, under conditions of high core task characteristics substitution, AI usage can increase work alienation, revealing potential negative effects. The findings enrich our understanding of the complex impact of AI usage on work engagement and offer valuable insights for managers to improve employee experiences in the AI era.

At this modernity, various applications have been innovated to entertain people and foster romantic connections, with one of the most notable being the increasing integration of artificial intelligence (AI) in romantic relationships. This study, conducted in the Philippines, aims to explore the relationship between relationship satisfaction from using AI in romantic relationships and the level of AI usage, while evaluating its significance in today’s generation. A total of 338 students ranging from Grade 11 to fourth-year college students, participated in this research, which employs a quantitative approach with a descriptive research design. The results revealed that participants were "satisfied" with their relationship satisfaction from using AI (M = 3.71, SD = 0.79), with 67% to 98% agreeing that AI positively influences their romantic relationship satisfaction. The overall AI usage in romantic relationships had a high mean score (M = 3.66, SD = 0.66), suggesting significant engagement with AI in this context. A moderately positive correlation (r = 0.585, p < 0.000, N = 338) was found between AI usage and relationship satisfaction, indicating that as AI usage increases, so does relationship satisfaction, underscoring the role of AI in enhancing emotional aspects of romantic relationships.

BackgroundIn recent years, the integration of artificial intelligence (AI) into the contemporary workplace has transformed the landscape of numerous industries. Despite its benefits, AI usage has also brought about significant controversies, particularly concerns over job displacement and job insecurity. These changes may drive employees to consider alternative work arrangements, including moonlighting.ObjectiveDrawing on Conservation of Resources Theory and Career Construction Theory, this study investigates the relationship between AI usage and employee moonlighting intention. Specifically, it explores the mediating role of job insecurity and the moderating effect of career adaptability.MethodA two-wave questionnaire survey was conducted among 376 employees. Structural equation modeling and PROCESS macro in SPSS were used to test the hypothesized relationships, including mediation and moderation effects.ResultsThe findings indicate that AI usage is positively associated with employee moonlighting intention. Job insecurity mediates this relationship, while career adaptability moderates the effect of AI usage on job insecurity. At high levels of career adaptability, the impact of AI usage on job insecurity is significantly reduced or even reversed.ConclusionThis study bridges the topics of AI usage and employee moonlighting, unveiling the psychological mechanism linking technological change to career behavior. By identifying job insecurity and career adaptability as key factors, the study provides both theoretical insights and practical implications for organizations navigating workforce transformation in the era of AI.

The study aimed to investigate the main effect of leader humility on job crafting and the potential three-way interaction effect between leader humility, trust in leaders, and gender on job crafting. Data were collected from 158 employees in two organizations in South Korea. In order to analyze the proposed hypotheses, we used hierarchical regression analysis and PROCESS macro (Model 3) in SPSS with 5,000 bootstrap samples. The results revealed that leader humility influences job crafting, and the impact of leader humility on task crafting depends on the level of trust. In particular, higher trust between a leader and employee indicates a more positive relationship between leader humility and the employee’s task crafting behaviors. Furthermore, a moderated moderation effect was discovered of gender on the two-way interaction effect. The results of this study highlight that leader humility plays an important role for employees’ job crafting behavior particularly when they have highly trusting relationships with their leaders. In addition, this study provides a comprehensive understanding of leader humility’s effect on job crafting by investigating the role of gender.

Objective: The objective of this study was to review existing research on job crafting and work engagement in hotel industry. The aim is to provide a reference for hotels to enhance job crafting and work engagement among their employees. Theoretical Framework: The current study examines job crafting and work engagement in hotel industry. Method: This study adopts a systematic literature review by selecting and analysing seven relevant studies published between 2013 and 2023 from Scopus database. This study applies PRISMA to systematically synthesize and integrate existing research on job crafting and work engagement in hotel industry through identification, screening, and feasibility. Findings: The results of previous research have proven that there is a positive relationship between job crafting and work engagement in the hotel industry, and vice versa. The variables of job crafting and work engagement also play a role as mediating variables. Practical implications: This study provides practical implications by fostering organizational context and formal organizational systems that can encourage job crafting, both in terms of policies and procedures. To enhance job crafting and work engagement, hotel management should pay attention to emotional support. Originality/value: The existing literature concerning job crafting and work engagement within the hotel industry is constrained. This research offers a thorough and critical analysis in response to the existing limited literature.

Human interaction with generative artificial intelligence (AI) is characterized by user’s agency. This paper proposes two approaches for employees in using generative AI and explores how these approaches influence the creative outcomes of AI usage. Through a scale development study, we proposed and validated measurements for the inspiration and shortcut approaches, as well as their theoretical nomological network. In a field study, the results reveal that the usage approaches moderate the indirect effect of AI usage on creative performance through idea generation: when the inspiration approach is higher, the indirect effect of idea generation between AI usage and creative performance is stronger; conversely, when the shortcut approach is lower, the indirect effect is also stronger. The study reveals the moderating role of different approaches in how AI usage fosters creativity, thereby enriching the literature on human-AI interaction.

In recent years, job crafting has been an important topic in human resource management and has become an important issue to address with the rapid development in social economy. We utilised hierarchical linear regression analysis to test the moderating role of openness to experience and conscientiousness on the relationship between supervisor developmental feedback and job crafting. Participants (n = 337) were recruited from a large manufacturing enterprise in Hunan, China. They completed validated measures of supervisor developmental feedback, job crafting, openness to experience, and conscientiousness. Following hierarchical regression analyses, results showed that supervisor developmental feedback enhanced employee job crafting. Openness to experience and conscientiousness moderated this relationship. To increasing employee job crafting, human resource managers should utilise which would benefit organisation productivity.

Job crafting (i.e. employees proactively altering their own work design) has garnered scholarly attention as job design researchers have shown benefits to performance, job attitudes, and well-being from bottom-up work redesign. Interestingly, research has neglected to differentiate between engagement in job crafting and effectiveness in job crafting, and therefore few studies examine the outcomes of crafting efforts that lead to real changes in work experience relative to those that do not. Resultant from this gap is a paucity of study on outcomes of failed job crafting efforts, theoretical confusion as to why job crafting has certain effects, and little guidance for practitioners on how to craft jobs effectively or manage subordinate job crafting. To address this issue, we introduce a construct, job crafting effectiveness, defined as the extent to which crafting improves person-job fit, and propose relationships between effective and ineffective crafting, individual work outcomes (performance, job attitudes, well-being) and others’ work outcomes. Implications for theory and practice are discussed, including potential for the development of interventions that train workers on how to be effective and ethical job crafters, and a research agenda to inform these interventions.