A The meaning of life is the purpose that defines a person’s existence based on a set of fundamental objectives that give meaning to life or not. Furthermore, not all individuals have a meaning in life, and it may be absent at some point or stage of life. Objective: To analyze Peruvian older adults’ socioeconomic factors and the meaning of life. Method: A descriptive, comparative, quantitative cross-sectional study was conducted. One thousand older adults were intentionally selected through quotas of 100 older adults in 10 localities in Arequipa, Peru. They were administered a survey validated with high levels of reliability on the meaning of life and socioeconomic factors. Results: A moderate level of meaning in life was found. Most older adults believe that increasing age decreases the purpose of living, and existential emptiness grows. Conclusions: Statistically significant differences (p < 0.05) were found between the meaning of life and the following socioeconomic factors: retirement, religion, educational level, cohabitation, marital status, income, and occupation. It is understood that older adults who scored higher on these factors indicate having meaning in life because they still fulfill the role of providers for the family economy, being util to their families compared to the majority who scored low, which indicates an absence of meaning of life leading to an increase existential void.

Managing the spread of “disinformation” is becoming an increasingly difficult task of our time, with an emphasis on digital marketing and its influence on organizational reputation. This paper aims to analyze the phenomenon of disinformation, with emphasis on the role of digital marketing and the consequent effect on organizational image. Thus, using the systematic literature review methodology, the study defines and categorizes different types of disinformation, namely fake news, misinformation, and propaganda, and how they are spread across different channels. Using the research, it is possible to conclude that digital marketing is more effective in spreading disinformation than traditional media and word-of-mouth; social media management and content marketing are the most effective. The work also evaluates the catastrophic impact of disinformation on an organization’s image, fiscal health, and the trust of its stakeholders. Using the Chi-Square Test for Independence and Logistic Regression, the study determines the factors likely to lead to severe consequences of disinformation campaigns. Last but not least, the paper also suggests ways of preventing the spread of disinformation, which include improved education on the use of digital platforms, better fact-checking systems, and an improved code of ethics in digital marketing.

Despite having a strategic position in supporting the Indonesian economy, the productivity of SME’s is still suboptimal. The increase in the number of SME’s has not been followed by increased competitiveness due to various limitations experienced by this sector. In an effort to provide a comprehensive picture in improving the performance of food processing SME’s in developing countries such as Indonesia, the purpose of this study was to examine the function of product innovation, internet marketing, and brand identity in shaping competitive advantage having an impact on business performance. This research is focused on food processing SME’s in the city of Bogor. The number of samples used was 100 SME’s. The sampling method used the non-probability sampling method with a snowball sampling technique. The data obtained were analyzed using the Structural Equation Model (SEM). Based on the age characteristic of business actors, the majority of business actors were 40–50 years old, of which 52% had their final formal education at high school level. As many as 61% of respondents had attended business training. Based on the results of the Partially Least Square (PLS) SEM analysis, it was found that product innovation, internet marketing and brand identity all had a significant positive effect on competitive advantage and business performance. The influence of brand identity on competitive advantage had the greatest effect, with a value of 0.451. This study contributes to existing research by examining the determinants of the business performance of processed food SME’s through the holistic model offered. This research is innovative because the business raises new issues related to internet marketing by SME’s and investigates them empirically.

In recent years, awareness of sustainability has increased significantly in the hospitality industry, particularly within the hotel sector, which is recognized as a major contributor to environmental degradation. In response to this challenge, hotel managers are increasingly implementing green human resource management (GHRM) practices to increase Organizational Citizenship Behavior. Considering job satisfaction, and organizational commitment as mediator. A survey was conducted with 383 employees from three- and four-star Egyptian hotels and the obtained data were analyzed using SPSS version 22 and Amos version 24. Structural equation modelling was used to analyze the data. The study revealed that GHRM practices positively impacts Organizational Citizenship Behaviors (OCB), job satisfaction and organizational commitment in addition, the study found that job satisfaction and organizational mediates the relationship between Green Human Resource Management and Organizational Citizenship Behavior. The study found a positive link between GHRM and OCB, partially mediated by job satisfaction and organizational commitment. The recommend that implementation of GHRM practices in the hotel industry can have significant positive implications.

The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R² from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R² is compared to the experiments. No changes in Test R²’s were observed on GBM and XGBoost, which retained same Test R² across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R² of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R²; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.

This study analyzes the social and individual stigmatization toward Venezuelan immigrants in Peru within the context of the largest migratory movement in Latin America, driven by the political, economic, and humanitarian crisis in Venezuela. The study employs a qualitative approach, using semi-structured in-depth interviews with a diverse sample of 24 participants from major Peruvian cities, including Lima, Arequipa, Cusco, and Trujillo. These in-depth interviews provide insights into the complexity of perceptions toward Venezuelan migrants, ranging from stigmatizing views driven by associations with economic threats and criminality to more positive perceptions that acknowledge the migrants’ adaptability and economic contributions. The findings reveal that while negative stereotypes perpetuate social exclusion and pressures for cultural assimilation threaten the preservation of migrant identities, there are also narratives highlighting resilience and successful integration. The study emphasizes the importance of implementing intercultural education programs, promoting labor integration policies, and collaborating with the media to combat stigma. It concludes that addressing these challenges through a multidimensional, human-rights-based approach can foster greater social cohesion and better integration of migrants, benefiting both the migrant population and Peruvian society.

This study investigates the utilization of artificial intelligence (AI) technology to enhance practical content development within the media specialization program at Palestine Technical University, Kadoorie. The primary objective is to examine the extent to which media specialty lecturers employ AI technology in developing practical content. A mixed-methods approach is employed, qualitative data are gathered through in-depth interviews with faculty members to elucidate their perceptions and experiences regarding the integration of AI technology in practical content development. The study aims to provide valuable insights into the benefits and challenges of AI integration in practical content development for media specialization programs The study reveals diverse views on AI integration in media education at Palestine Technical University, Kadoorie. Faculty recognize AI’s benefits like personalized learning and productivity but also express concerns about over-reliance and ethics. Consensus exists on cautious AI implementation to maximize benefits and address drawbacks. Obstacles to AI adoption include cost, skills gaps, and ethical considerations, highlighting the complexity of integration. The study emphasizes a balanced approach, offering insights for enhancing practical content development in media specialization programs at Palestine Technical University, Kadoorie.

Introduction: The heterogeneity of occupational morbidity by gender in those suffering from carpal tunnel syndrome (CTS) has been little studied in the Latin American context. The objective of this study was to estimate the incidence and prevalence of CTS of occupational origin in the Ecuadorian salaried population according to gender, In addition, the differences in risk between women and men are compared. Methods: We use the only administrative registers of CTS qualified as occupational diseases in the country between the years 2017 and 2019. Period incidence rates were estimated to compare the risk in women versus men (RR, CI 95%) by age group and economic activity. Results: CTS is the second most common occupational disease in Ecuador. Women workers are more likely tosuffer from CTS and showed twice the risk compared to men [RR = 2.10 (95%CI: 1.94–2.11); p = 0.000]. This risk increases with age and for the vast majority of economic activities. The occupations of agriculture and warehousing stand out for their importance. Conclusions: The results shown in this study raise the fundamental need to improve epidemiological surveillance systems and occupational health policies by considering gender differences in order to adequately address risks and promote safe and healthy working environments for all.