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Social identity theory describes how an individual’s behaviors and choices are influenced by social group membership, including those related to financial planning. Social group behavior can also be influenced by structural barriers. The primary cause of poverty at retirement stems from the lack of financial planning for retirement. Underprivileged populations tend to have limited access to resources thus, they have difficulty saving for retirement. This study aims to identify barriers to financial planning among underprivileged populations through the framework of the social identity theory.

This qualitative study examines key aspects of retirement planning among underprivileged populations using the social identity theory. Findings were based on 32 in-depth interviews with individuals from the Arab population in Israel.

Four central themes emerged from the interviews, detailing the motivations for financial planning for retirement: social identity, pension literacy, reliance on the national social security network and (lack of) trust in the state and the pension system.

By utilizing the social identity theory, this study identifies potential barriers retirement planning among people from underprivileged populations. Understanding these barriers is vital for policymakers globally, due to the expected increase in the rate of older adults in coming years. Lack of proper retirement planning can lead to an increased rate of poverty among older adults.

The current study seeks to explore the links between principal self-efficacy, openness to change, well-being, and transformational leadership. Specifically, we tested a mediated-effects model where principal self-efficacy and openness to change were treated as independent variables, well-being as mediator, and transformational leadership as dependent variable.

Survey data were collected from 351 principals employed in Turkish schools and analysed using confirmatory factor analysis and structural equation modelling.

The results suggested the direct empirical relationship of principal self-efficacy and openness to change with transformational leadership, and indirect through professional well-being.

Our study enriched our understanding of school leadership by elucidating the potential mechanisms that underpin the implementation of transformational leadership practices.

The article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over time.

This paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) framework.

Using monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under examination.

It provides new evidence on changes over time in monetary policy rules.

This paper aims to examine the mediation effect of organizational learning on the link between human resource management (HRM) practices and organizational performance in some Big4 financial services companies.

The quantitative methodology was chosen for this research, using resource theory and knowledge-based approach to explain the relationship between latent variables. A sample of 403 HR employees and managers of the companies under study in France was selected in 2022. Structural equations modeling was used based on the Spss-Amos program to test the research hypotheses.

The results revealed that organizational learning played a mediating role between HRM practices (hiring, training, motivation and decision-making) and organizational performance and that learning enabled the performance of workers to improve and achieve competitive advantages in this field.

The sample was based on four international companies working in the field of financial services and consulting and providing their services within France, which may affect the generalisability of the results and limit them to the studied sector.

The contribution of the study is to improve the awareness of administrators, decision makers and company employees of the importance of organizational learning for companies, and to stimulate motivation to learn and exchange knowledge in a constructive way that enhances organizational performance. Working on organizational culture change through HRM-practices-based learning as an effective mechanism for organizational performance improvement is one implication. These practises influence cadres' attitudes toward their work, which improves their performance.

Working on organizational culture change through HRM-practices-based learning as an effective mechanism for organizational performance improvement is one implication. These practises influence cadres' attitudes toward their work, which improves their performance.

This study seeks to provide cadres and executives with an in-depth analysis of HRM and organizational learning, which, through its integration of these attributes, can contribute to the earning of knowledge-based competitive advantage and achieve superior and sustainable performance.

Grounded in coping model of user adaptation (CMUA), this research aims to provide insights into understanding the social mechanism influencing faculty’s adoption and adaptation of mobile technology (MT). An extensive review of the literature highlights a significant gap in empirical research regarding the adoption of MT and faculty adaptation when viewed through the lens of group dynamics.

This study is based on an exploratory study conducted at two engineering universities in France. A qualitative method enabled a comprehensive examination of faculty members using multiple field-based observations and semi-directive interviews at both University A and University B.

While extant research tends to prioritize individual-level approaches, the integration of MT within higher education inherently involves social dynamics. Our results reveal that faculty’s perceived control and their initial perception over adoption of MT play an important role in shaping their adaptation behavior. The findings suggest that the adoption of MT among faculty members is influenced by various organizational factors. Specifically, the organizational logic of adoption affects their primary appraisal of MT, while group norms and social influence shape their adaptation acts. Furthermore, the organization’s continuous commitment to supporting faculty members also impacts their coping activities, ultimately influencing their overall adoption and utilization of MT.

This study builds upon the limited yet growing body of literature on a theme highly relevant for practitioners, scholars as well as MT users in a higher education environment. The paper extends the CMUA by exploring the relationship between MT adoption and continuous user adaptation at both group and organizational levels. Our proposed framework assists universities in articulating their MT adoption and implementation strategy in harmony with a clear vision of their users’ adaptation activities before, during and after the implementation.

The study aims to investigate the relationship between E-government and corruption. It also examines the moderator role of national culture through Hofstede’s dimensions on the association between E-government and corruption.

In addition to panel regression techniques, the authors use the random forest method to assess the order of importance of all significant variables in determining corruption. The sample of this study consists of 55 countries during 2008–2020 period.

The results show that E-government is negatively correlated with corruption. The authors also find that both economic and cultural variables play an important role in determining corruption. However, religion has no impact on corruption. The results can potentially assist regulators and policy-makers when trying to control corruption as they should take into consideration the cultural background of citizens when making rules and procedures that aim at reducing corruption.

The current study uses random forests model, which allows the regression of variables based on the construction of a multitude of decision trees. The main contribution of using this model compared to the other regression models used in prior studies is to extract the relative importance of each significant variable. More precisely, it evaluates the rank of importance for each significant variable that drives corruption rather than merely identifying variables that drive corruption regardless of their relative importance.

This study addresses a gap in the literature by examining the marketing strategies adopted by wineries in the context of wine tourism. This study aims to identify marketing strategic orientations and highlight their significance in the context of wine tourism.

The research uses a comparative case study approach, focusing on two wine regions, Roussillon (France) and Empordà (Spain). It involves the analysis of 99 active winery websites to identify marketing orientations. Descriptive statistics, cluster analysis and ANOVA tests were used to achieve this.

The study reveals four distinct wine tourism strategic orientations adopted by wineries in these regions. It emphasizes the importance of external ties, varying levels of competitiveness, website performance and geographical differences as key findings. The results show that wineries with a clear diversification strategy benefit from a higher level of competitiveness.

This research contributes to the academic literature by identifying different marketing strategies within wine tourism, highlighting their importance and providing a comprehensive analysis of key areas, thus adding original insights to the existing body of literature.

This study aims to understand the progressive marketization of health data collection and use, through a study of its historical development in France, from the 1930s to the present day.

The authors collected a set of legal, institutional, political and media data. These came from the INA (National Audiovisual Institute), the French national newspaper websites and the websites legifrance.gouv.fr and vie-publique.fr. The authors then conducted a thematic content analysis.

The study results highlight the changes in the health-care system related to the increased use of data in France over three major periods. The first period – 1930s to 1980s – is marked by the creation of the French social security system to collect large sets of data to better manager people’s health care. The second period – 1980s to 2000s – is characterized by the adoption and assimilation of tools to manage patient data through several national and European regulations. The last period – 2000s to the present – saw the introduction of measures in favor of the digitalization of health care, and consequently of data, in parallel with the advancement of digital technologies in general. The institutional dynamics in healthcare have evolved with the nature of the actors and their practices, in connection with new perceptions about health data.

This research sheds light on the historical transformation of health data collection and use in France, revealing the involvement of diverse stakeholders, the discourses driving data development and the need for regulation. It exposes the dual nature of health data collection and use, initially sanctioned by the state and public entities but later exploited for private interests.

This study proposes an integrated Machine Learning and simulated framework for a personalized learning system. This framework aims to improve the integrity of the provided tasks, adapt to each student individually and ultimately enhance students' academic performance.

This methodology comprises two components. (1) A simulation-based system that utilizes reinforcement algorithms to assign additional questions to students who do not reach pass grade thresholds. (2) A Machine Learning system that uses the data from the system to identify the drivers of passing or failing and predict the likelihood of each student passing or failing based on their engagement with the simulated system.

The results of this study offer preliminary evidence of the effectiveness of the proposed simulation system and indicate that such a system has the potential to foster improvements in learning outcomes.

As with all empirical studies, this research has limitations. A simulation study is an abstraction of reality and may not be completely accurate. Student performance in real-world environments may be higher than estimated in this simulation, reducing the required teacher support.

The developed personalized learning (PL) system demonstrates a strong foundation for improving students' performance, particularly within a blended learning context. The findings indicate that simulated performance using the system exhibited improvement when individual students experienced higher learning benefits tailored to their needs.

The research offers evidence of the effectiveness of personalized learning systems and highlights their capacity to drive improvements in education. The proposed system holds the potential to enhance learning outcomes by tailoring tasks to meet the unique needs of each student.

This study contributes to the growing literature on personalized learning, emphasizing the importance of leveraging machine learning in educational technologies to enable precise predictions of student performance.

Gen Z, the largest and fastest-growing consumer generation, is transforming the hospitality industry as both customers and employees. By critically synthesizing empirical literature, this study aims to explore how this generation’s distinct behaviors are reshaping customer expectations and workforce trends within the sector.

A critical synthesis of empirical studies was used to examine current research on Gen Z as customers and employees in the hospitality industry.

Gen Z exhibits distinct preferences and expectations in their dual roles as customers and employees, prompting substantial shifts in hospitality industry standards and practices. They rely heavily on digital channels and peer recommendations when making travel decisions and expect highly personalized, tech-enabled experiences. This young cohort of travelers values unique, authentic and sustainable offerings. As employees, Gen Z prioritizes flexible work arrangements, career growth and workplaces aligned with sustainability, diversity and social responsibility. Hospitality providers must adapt their customer experience, marketing and HR strategies to meet these evolving demands.

To engage Gen Z customers and employees in the hospitality industry effectively, businesses must prioritize personalized experiences, leverage technology and adopt sustainable practices aligned with Gen Z’s social and environmental values. Moreover, offering adaptable work environments with remote opportunities and investing in professional development enhances appeal for Gen Z employees. Understanding Gen Z’s values and behaviors can help businesses improve customer satisfaction, attract top talent and remain competitive in a rapidly evolving market.

This study represents a preliminary endeavor to provide a critical assessment of Gen Z in the hospitality and tourism sector, offering novel insights into their travel behaviors, preferences and work values. It explores their expectations, attitudes toward work and career choices, offering guidance on how businesses can meet the evolving demands of this key demographic.