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Generation Z (Gen Z) is entering the hotel workforce and will soon become the dominant group. This has called for a better understanding of this workforce’s attitudes and perceptions towards working in the hotel industry. This study aims to examine the effect of organizational socialization on the retention of Chinese Gen Z employees, the mediating role of person–environment fit (P-E fit) and the moderating effect of career commitment.

Time-lagged data were collected from 426 Gen Z new employees from 20 upscale hotels at two different times (2 weeks and 12 weeks after the employees entered the hotel). Confirmatory factor analysis, structural equation modeling, bootstrapping analysis and moderated hierarchical regression analyses were used for data analysis.

Organizational socialization positively affects employee retention via person–environment fit. Moreover, career commitment positively moderates the relationship between person–environment fit and employee retention.

Hotels must view organizational socialization as a long-term investment in Gen Z talent management by offering effective training through diverse methods, creating a collaborative environment and helping them develop career plans to enhance their career commitment.

This study unpacks the four dimensions of organizational socialization and investigates their differential effects on Gen Z employees’ retention through P-E fit. The moderating role of career commitment is also examined. This study contributes to the growing body of hospitality human resources management research on this new generation of workforce in China.

This research delves into the dynamic realm of app design by examining the impact of app icon familiarity and authority on image fit, influencing users' app usage intention. Focusing on the distinctive circumstances of Chinese and Korean customers, the study aims to provide insightful information about how application user behavior changes.

Utilizing structural equation modeling, the study employs data from 293 Korean and Chinese consumers. The research design incorporates a thoughtful approach, including parallel translation methods, focus group interviews, and pre-experimental testing to ensure survey accuracy and validity. The study strategically selects stimuli from the Apple App Store rankings, emphasizing icon features and type considerations.

The results provide important new information about the connections between usage intention, image fit, authority, and familiarity with app icons. Notably, app icon familiarity and authority positively influence image fit. Furthermore, app icon image fit emerges as a positive predictor of usage intention, mediating the complex interplay between familiarity, authority, and intention. The study also identifies moderating effects, shedding light on the nuanced role of app icon features and types.

Originating from a comprehensive exploration of icons, this study significantly contributes to the field by exploring icon differences and uncovering the intricate mechanisms guiding users' decisions. The findings offer valuable insights for app designers, marketers, and researchers seeking a deeper understanding of user behavior in diverse cultural contexts, thereby enhancing the theoretical and practical foundations in app usability and consumer behavior.

The research evaluated the feasibility of 3D dynamic fit utilizing female compression tops by comparatively analyzing the virtual and actual dynamic fit.

Six female participants were 3D body-scanned and photographed in compression tops in four types of athletic movements (pull-up, kettlebell swing, circle-crunch and sit-up). Fit measurements, waist cross-sectional areas, waist width, waist depth, numerical simulation of clothing pressure (kPa) and objective pressure measurements (kPa) were collected from 3D virtual animation, 3D fit scan data and actual photos with the four types of athletic motions. The data were comparatively investigated between virtual and actual dynamic fit.

The 3D-animated body was not reflected with human body deformation because only bone structure was changed while maintaining the constant forms of muscle and body surface in athletic movements. Due to this consistency of virtual dynamic fit, there were significant differences with the actual dynamic fit at the top length, shoulder width and waist cross-sectional areas. Also, the virtual dynamic pressure indicated significantly higher levels than the objective dynamic pressure while presenting no significant correlations at the front neckline, breast, lateral waist, upper back, back armhole and back waist.

This study is the first to verify multiple aspects of virtual dynamic fit using 3D digital technology. This study provided useful information about which aspects of the current virtual animation need to be improved to apply in the dynamic fit evaluation.

Our proposed machine learning model contributes to improving the quality of Hire by providing a more nuanced and comprehensive analysis of candidate attributes. Instead of focusing solely on obvious factors, such as qualifications and experience, our model also considers various dimensions of fit, including person-job fit and person-organization fit. By integrating these dimensions of fit into the model, we can better predict a candidate’s potential contribution to the organization, hence enhancing the Quality of Hire.

Within the scope of the investigation, the competencies of the personnel working in the IT department of one in the largest state banks of the country were used. The entire data collection includes information on 1,850 individual employees as well as 13 different characteristics. For analysis, Python’s “keras” and “seaborn” modules were used. The Gower coefficient was used to determine the distance between different records.

The K-NN method resulted in the formation of five clusters, represented as a scatter plot. The axis illustrates the cohesion that exists between things (employees) that are similar to one another and the separateness that exists between things that have their own individual identities. This shows that the clustering process is effective in improving both the degree of similarity within each cluster and the degree of dissimilarity between clusters.

Employee competencies were evaluated within the scope of the investigation. Additionally, other criteria requested from the employee were not included in the application.

This study will be beneficial for academics, professionals, and researchers in their attempts to overcome the ongoing obstacles and challenges related to the securing the proper talent for an organization. In addition to creating a mechanism to use big data in the form of structured and unstructured data from multiple sources and deriving insights using ML algorithms, it contributes to the debates on the quality of hire in an entire organization. This is done in addition to developing a mechanism for using big data in the form of structured and unstructured data from multiple sources.

Central to the fit concept is that congruence between individual and environmental attributes leads to improved outcomes. However, when discussing fit, researchers often describe congruence as alignment between distinctive or unique individual and environmental attributes. We suggest that current approaches to examining fit do not adequately account for this assumption of distinctiveness because they fail to consider normative expectations and preferences. As such, we propose an alternative theoretical and methodological approach to conceptualizing and measuring fit.

We introduce the normative theory of fit, outline how researchers can decompose fit into distinctive and normative components and identify areas for future research.

Management researchers have largely ignored the importance of decomposing fit into distinctive and normative components. This shortcoming necessitates additional research to ensure a more accurate understanding of fit and its relationship with outcomes.

We provide a clarification and critical examination of a pervasive construct in the field of management by introducing the normative theory of fit, identifying areas where researchers can employ this theoretical lens and suggesting a reevaluation of the importance placed on differentiation that is traditionally employed in practice.

This study establishes the principles and process steps of a new basic trousers pattern using measurements obtained according to the rules of the anthropometric measurement system. The newly developed pattern-making system in this study will be called the “Anthropometric Measurements Based Pattern Making System” (AnMePa). It is aimed at producing trousers that are more fitting to the body, thanks to this pattern-making system.

In this research, four pattern-making systems used in many parts of the world were compared with the “Anthropometric Measurements Based Pattern Making System” (AnMePa) with regard to the overall appearance and body fit of trousers prepared according to these systems. 10 virtual mannequins (VM) with different adult female body measurements were created, and trousers patterns were prepared for these mannequins. The trousers’ patterns were made and dressed on the mannequins in a 3D virtual dressing system. The body fit of the virtual garments was evaluated by five experts. The scores given by the experts were evaluated using the fuzzy logic method.

According to the results, it is seen that the new basic trousers pattern developed by utilizing the anthropometric measurement system, AnMePa, provides the best body fit among the basic trousers patterns created according to the other examined pattern-making systems. The combination of 3D virtual dressing and fuzzy logic in the evaluation of garment body fit is considered an innovative method for the future of fashion design and production.

In the developed AnMePa, unlike the existing pattern-making systems, values that can be associated with the body measurements of individuals in a way that could be suitable for each community were used instead of constant values in the pattern-making process. Furthermore, the integration of 3D virtual fitting and fuzzy logic in assessing garment fit is considered a pioneering approach with significant implications for the future landscape of fashion design and production.

Snap fits are crucial in automotive applications for rapid assembly and disassembly of mating components, eliminating the need for fasteners. This study aims to focus on designing and analyzing serviceable cantilever fit snap connections used in automobile plastic components. Snap fits are classified into permanent and semi-permanent fittings, with permanent fittings having a snap clipping angle between 0° and 5° and semi-permanent fittings having a clipping angle between 15° and 45°. Polypropylene random copolymer is chosen for its exceptional fatigue resistance and elasticity.

The design process includes determining dimensions, computing assembly, disassembly pressures and creating three-dimensional computer-aided design models. Finite element analysis (FEA) is used to evaluate the snap-fit mechanism’s stress, deformation and general functionality in operational scenarios.

The study develops a modified snap-fit mechanism with decreased bending stress and enhanced mating force optimization. The maximum bending stress during assembly is 16.80 MPa, requiring a mating force of 7.58 N, while during disassembly, it is 37.3 MPa, requiring a mating force of 16.85 N. The optimized parameters significantly improve the performance and dependability of the snap-fit mechanism. The results emphasize the need of taking into account both the assembly and disassembly processes in snap-fit design, because the research demonstrates greater forces during disassembly. The approach developed integrates FEA and design for assembly (DFA) concepts to provide a solution for improving the efficiency and reliability of snap-fit connectors in automotive applications.

The research paper’s distinctiveness comes from the fact that it presents a thorough and realistic viewpoint on snap-fit design, emphasizes material selection, incorporates DFA principles and emphasizes the specific requirements of both assembly and disassembly operations. These discoveries may enhance the efficiency, reliability and sustainability of snap-fit connections in plastic automobile parts and beyond. In conclusion, the idea that disassembly needs to be done with a lot more force than installation in a snap-fit design can have a good effect on buzz, squeak and rattle and noise, vibration and harshness characteristics in automobiles.

The entrepreneurial intention of employees refers to the motive of those who work in a company to resign and start their businesses instead of continuing to be wage earners. It is one of the under-studied aspects of entrepreneurship research. Accordingly, this research paper aimed to find out whether perceived person–organization fit was related to the entrepreneurial intentions of employees and whether perceived workplace ostracism and loneliness mediated this process.

A cross-sectional study was conducted to achieve the purpose. The data were collected through a questionnaire technique from a total of 572 employees. Participants were from 20 different provinces of Turkey and 27 different sectors. Hypotheses were tested through the structural equation modeling technique.

Findings indicated that a lack of perceived person–organization fit resulted in entrepreneurial intention. Workplace ostracism resulted in workplace loneliness. Workplace ostracism and loneliness significantly mediated the relationship between perceived person–organization fit and entrepreneurial intention.

To the best of authors’ knowledge, this study was the first to establish and test the relationships between person–organization fit, entrepreneurial intention, workplace ostracism and loneliness. In this regard, findings can benefit researchers and practitioners in better figuring out why some employees leave their companies to start their businesses while others do not.

The study emphasizes the role of an individual's mindfulness and temperance in making employees fit their organizations by comparing the direct effect of mindfulness and its indirect effect through temperance on the employees' person–organization fit (P-O fit). Data were collected from 185 Indian employees working at managerial positions in manufacturing and service industries through an online questionnaire in a cross-sectional research design. Structure equation modelling (SEM) was used to test the associations, and it was observed that mindfulness among employees is positively related to their P-O fit. Similarly, employees' temperance is also positively associated with their P-O fit. Furthermore, it is observed that temperance acts as a partial mediator between mindfulness and P-O fit. Mindful employees would be more aware of their surroundings, making them aware of the values that the workplace demands. The same awareness would compel the employees to have temperance (self-control) to keep their values in line with organizational values. The study contributes to the virtue theory and the value congruence theory in the organizational context. This study recommends that the management promotes mindfulness and temperance among the employees through various interventions and new technological aids to promote the P-O fit of the employees. To the best of our knowledge, this original work has novelty to investigate the relationship of mindfulness with P-O fit, taking into account the role of temperance of the employee.

Low-fit brand extensions offer several potential benefits, yet their success is challenging. Building on construal level theory, this study aims to investigate how different advertising appeals can improve the evaluations of low-fit brand extensions through two different processes (cognitive and affective).

Two experiments were conducted with US consumers. Study 1 used a 2 (extension fit: high, low) × 2 (ad appeal: abstract, concrete) between-subjects design. Study 2 applied a 2 (brand associations: promotion, prevention) × 2 (ad appeal: promotion, prevention) between-subjects design. Multivariate analyses and follow-up means comparisons were used to analyse data.

Study 1 found that an abstract ad appeal is more effective for promoting low-fit brand extension because it improves the perception of fit. Study 2 showed promotion vs prevention ad appeals lead to better evaluation of low-fit brand extensions when matched with parent brand associations (promotion vs prevention) in terms of construal level. This matching effect is underpinned by processing fluency.

Ad appeals can influence low-fit brand extension evaluation by influencing the perception of fit (cognitive process) or processing fluency (affective process). Future research could consider different ad appeals and other construal related factors to generalise these findings.

Marketers can design different ad appeals to effectively advertise low-fit brand extensions. These findings can guide managers in the development of effective advertising strategies.

This research offers a new perspective on how ad appeals can enhance low-fit brand extension evaluation.