Iskanje po katalogu digitalne knjižnice

Opis: Purpose – In the hotel industry, as in all services, the goal is to have satisfied employees who are engaged in their job. From a marketing perspective, one of the possible ways companies can achieve that is by adopting internal marketing practices. Hence, the purpose of this paper is to research the relationship between internal marketing and different dimensions of employee engagement (emotional, cognitive and physical) in the hotel industry. Design/Methodology/Approach – The data was collected through a paper-and-pencil questionnaire on a sample of 573 hotel employees in Croatia. Adapted scales from previous research were used for measuring research constructs using the back-translation technique. Conceptual model and hypotheses were tested with covariance based structural equation modelling. Findings and implications – The results show that internal marketing had a positive and statistically significant impact on emotional and cognitive engagement. Cognitive engagement, in turn, had a positive impact on emotional and physical engagement, while emotional engagement had a positive impact on physical engagement. Limitations – The use of self-evaluations could potentially cause social desirability bias. The study is limited only to Croatian hotels, which might vary from hotel industries in other parts of the world. Originality – This paper contributes to the development of internal marketing, as it identifies the relationship between internal marketing and different forms of employee engagement. Employee engagement is approached multidimensionally as consisting of emotional, cognitive and physical engagement. By distinguishing different engagement dimensions, the paper contributes to the theory of personal engagement with testing employee engagement concept in the hotel industry.
Ključne besede: internal marketing, employee engagement, hotel industry, hotels, Croatia
Objavljeno v DKUM: 16.01.2025; Ogledov: 0; Prenosov: 12
Celotno besedilo (945,22 KB)
Gradivo ima več datotek! Več...

Opis: The paper’s main aim is to analyze five constructs of organizational culture, AI-supported leadership, AI-supported appropriate training of employees, teams’ effective performance, and employee engagement, and their relationship through the prism of artificial intelligence on a sample of large and medium-sized Slovenian companies. The second aim of the paper is to test the proposed model with two different statistical techniques in the scope of structural equation modeling (SEM) that enable us to assess linear (PLS-SEM) and non-linear relationships (CB-SEM) among the constructs. The empirical research included 437 medium-sized and large Slovenian companies. From each company, a CEO or owner participated in our research. The findings of the research with both techniques show that organizational culture had no impact on AI-supported appropriate training of employees and was not significant as well as that organizational culture had an impact on AI-supported leadership. The impact of AI-supported leadership on AI-supported appropriate training of employees were supported only for the PLS-SEM model. The impact of AI-supported leadership for employees on teams was positive. Contrary to that, the impact of AI-supported leadership for business solutions on teams was non-significant. In both cases, AI-supported appropriate training of employees’ impact on teams was strong and positive. Also, employee engagement impact on teams was positive and statistically significant with PLS-SEM and CB-SEM methods. The research yields important implications for companies seeking to integrate artificial intelligence effectively in their operations. It emphasizes the critical role of AI-supported leadership in driving positive outcomes, such as improved employee training and enhanced team effectiveness. Companies should focus on developing leaders who can leverage AI tools to foster a skilled and engaged workforce. By adopting data-driven decision-making processes and incorporating insights from structural equation modeling, organizations can develop effective AI integration strategies. These provide valuable guidance for enhancing human resource management practices and achieving successful AI adoption across companies. The findings contribute to the formation of new views in the field of artificial intelligence implementation in the companies and show companies a broader picture of which aspects of human resource management need to be improved.
Ključne besede: leadership, organizational culture, employee engagement, artificial intelligent
Objavljeno v DKUM: 22.04.2024; Ogledov: 185; Prenosov: 56
Celotno besedilo (3,09 MB)
Gradivo ima več datotek! Več...

Opis: In the hospitality industry, employee turnover is extremely high. It is often caused by minimal growth opportunities, intensive work, lack of flexibility, limited opportunities for promotion, lack of recognition, etc. Investment in human resources, strategies that maintain an adequate workforce and improve employee engagement is quite justified cost with multiple returns. The specific issue is that hospitality leaders often do not know the relationships between employee satisfaction, employee motivation and employee engagement, which may be the basis for understanding their intention to leave the job. The purpose of this study was to examine the relationship between the three job-related constructs: motivation, job satisfaction, and work engagement, as well as to examine their impact on employee turnover. The results confirmed a positive relationship between job satisfaction and motivation, satisfaction and work engagement, as well as the relationship between motivation and engagement. On the other side, the results showed that job satisfaction, dedication, and vigor negatively predict employee turnover. The findings may provide hotel managers with a foundation to understand this issue and assume where to direct their research and how to improve job conditions.
Ključne besede: job satisfaction, motivation, work engagement, employee turnover, hotel employees, Serbia
Objavljeno v DKUM: 26.01.2024; Ogledov: 365; Prenosov: 5
Celotno besedilo (335,82 KB)
Gradivo ima več datotek! Več...