Influence of Artificial Intelligence and Robotics Awareness on Employee Creativity in the Hotel Industry

How does leadership AI awareness shape employee voice behavior? based on the framework of hindrance and challenge stressors

BackgroundThe rapid advancement of Artificial Intelligence (AI) is driving transformative changes across various sectors, reshaping organizational management models and altering work dynamics for employees.ObjectiveThis study employs the framework of hindrance and challenge stressors to examine the impact of leadership AI awareness on employees' voice behavior (VB).MethodsWe analyzed survey data from 487 employees in knowledge-intensive industries across China.ResultsLeadership AI awareness, under hindering stressors, positively correlates with employees' job insecurity (JI), which inversely affects their VB; JI acts as a mediator. Conversely, under challenging stressors, leadership AI awareness enhances employees' intrinsic motivation, which positively correlates with VB. Intrinsic motivation also mediates this relationship. Additionally, AI self-efficacy moderates the influence of leadership AI awareness on employees' VB.ConclusionsThis study elucidates a dual-path mechanism through which leadership AI awareness affects employees' VB and delineates the boundary conditions for this influence. The findings offer managerial insights for stimulating employees' VB amidst AI integration in the workplace.

AI enhancing prefabricated aesthetics and low carbon coupled with 3D printing in chain hotel buildings from multidimensional neural networks

There are approximately 70,000 economy chain hotels worldwide, generating about 300 million tons of carbon dioxide annually. While reducing carbon emissions can lower energy consumption, these hotels must also continually attract guests to ensure revenue growth and achieve sustainable development. This study focuses on the application of Artificial Intelligence (AI) in the prefabricated renovation of hotels, investigating how AI plays a crucial role in coupling low-carbon construction and aesthetic design. Using multidimensional algorithms within machine learning (ML), neural networks (NN), and statistical modeling (SM), this paper analyzes the impact of AI-driven prefabricated room renovations on tourist satisfaction and carbon emissions. The results indicate that AI can not only optimize energy consumption and structural efficiency in the renovation process but also achieve low-carbon goals while maintaining high-quality aesthetic designs. This study offers new theoretical insights into the integration of low-carbon and aesthetic design, filling gaps in the current literature, providing a pathway for achieving sustainable development goals (SDG 7, 8, and 12), and offering valuable implications for robotic intelligent construction and 3D printing in prefabricated buildings industry.

"Remaining Vigilant" While "Enjoying Prosperity": How Artificial Intelligence Usage Impacts Employees' Innovative Behavior and Proactive Skill Development

As Artificial Intelligence (AI) has become a crucial element in the competitive advantage of enterprises, it is important to understand how to stimulate employees' creativity and initiative to cope with AI-driven changes. Drawing from the traditional Chinese wisdom of "remaining vigilant while enjoying prosperity" and based on the Conservation of Resources Theory, this study explored the impact of AI usage on employees' innovative behavior and proactive skill development. The results of a three-stage survey of 350 questionnaires showed that (1) AI usage positively influences employees' innovative behavior and proactive skill development; (2) job absorption partially mediates the relationship between AI usage and employees' innovative behavior; (3) AI job replacement anxiety partially mediates the relationship between AI usage and proactive skill development; and (4) employees' learning goal orientation positively moderates the impact of AI usage on innovative behavior through job absorption and on proactive skill development through AI job replacement anxiety. This study provides insights into how individuals respond to AI-driven changes and offers a novel perspective for developing research on AI usage at the individual level.

Navigating AI transitions: how coaching leadership buffers against job stress and protects employee physical health

The dynamic interplay between Artificial Intelligence (AI) adoption in modern organizations and its implications for employee well-being presents a paramount area of academic exploration. Within the context of rapid technological advancements, AI's promise to revolutionize operational efficiency juxtaposes challenges relating to job stress and employee health. This study explores the nuanced effects of Artificial Intelligence (AI) adoption on employee physical health within organizational settings, investigating the potential mediating role of job stress and the moderating influence of coaching leadership. Drawing from the conservation of resource theory, the research hypothesized that AI adoption would negatively impact employee physical health both directly and indirectly through increased job stress. Critically, our conceptual model underscores the mediating role of job stress between AI adoption and physical health. Further, introducing a novel dimension to this discourse, we postulate the moderating influence of coaching leadership. To empirically test the hypotheses, we gathered survey data from 375 South Korean workers with a three-wave time-lagged research design. Our results demonstrated that all the hypotheses were supported. The results have significant implications for organizational strategies concerning AI implementation and leadership development.

The Association between Artificial Intelligence Awareness and Employee Depression: The Mediating Role of Emotional Exhaustion and the Moderating Role of Perceived Organizational Support

The combination of artificial intelligence (AI) technology with the real economy has dramatically improved the efficiency of enterprises. However, the replacement of AI for employment also significantly impacts employees' cognition and psychological state. Based on the Conservation of Resources Theory, the relationship between AI awareness and employee depression is explored in this article while examining the mediating role of emotional exhaustion, as well as the moderating role of perceived organizational support. Based on a sample of 321 respondents, the empirical results show that (1) AI awareness is significantly positively correlated with depression; (2) emotional exhaustion plays a mediating role between AI awareness and depression; (3) perceived organizational support negatively moderates the relationship between emotional exhaustion and depression; (4) perceived organizational support negatively moderates the mediating role of emotional exhaustion between AI awareness and depression. The research conclusions provide a theoretical basis for organizations to take measures to intervene in the negative impact of changes in AI technology on employees' mental health.

Factors influencing consumers' willingness to accept service robots: Based on online reviews of Chinese hotels

The application of robots in service industry is increasing. Compared with related studies in other countries, the research on users' acceptance of mid-range and high-range hotel service robots in China is preliminary. Based on the interaction between Chinese consumers and hotel service robots, this study explored the factors that influence consumers' willingness to accept robots in human-robot interaction. According to the service robot integration willingness scale (performance efficacy, intrinsic motivation, anthropomorphism, social influence, facilitating conditions, and emotion), this study conducted content analysis and sentiment analysis on 4,107 online reviews from 68 mid-range and high-range hotels in Qunar. The results showed that users' overall evaluation of robot service in mid-range and high-range hotels is positive. The most frequently mentioned dimension by users is performance efficacy, followed by intrinsic motivation, anthropomorphism, and emotion, finally, the facilitating conditions, the five dimensions have positive impact on users' evaluation of service robots; the influence of social influence on human-robot interaction evaluation has not been found. This study supplements the research on service robot and provides a reference for hotel managers to make decisions.