This study aimed to examine the impact of working conditions and sociopsychological factors on job satisfaction among office workers. Using data from the 2017–2018 Working Conditions Survey, exploring how workplace conditions and sociopsychological elements could impact job satisfaction. This study examined data from 9801 workers to explore the effects of working conditions and psychosocial environments on job enthusiasm, which subsequently impacts job satisfaction. Analyzing 1416 office workers, it found that fewer working hours, better work-life balance, improved work conditions, and lower depression levels enhance job enthusiasm, significantly affecting job satisfaction. The work environment had the most substantial impact, encompassing relationships with colleagues, task completion time, and confidence. Work-life imbalance and depression were also significant, with work-life balance being crucial for modern society, especially the younger generation. Poor working conditions and unstable psychosocial environments negatively affect job enthusiasm and satisfaction, with findings supporting previous research on job stress and turnover intentions in various industries. This study highlights the need for organizational policies that support these aspects to improve overall employee well-being and productivity.

Researchers need to seek the opinions of individuals about what they think related to neuromarketing and its applications. This study is intended to reveal the conceptual perception of neuromarketing. In this context, a comparative analysis was designed for university students studying in social sciences and health sciences due to the interdisciplinary nature of neuromarketing. Thus, it was investigated in which areas the conceptual perception of neuromarketing was higher and how it was perceived at the same time. Survey method was used to collect data. The relevant literature was scanned to determine the questions in the survey, and previous studies in this field were taken into account. Accordingly, the survey consists of two parts. In the first part, there are 6 questions to determine the demographic characteristics of the participants. In the second part, 14 questions were included to determine the conceptual perception of neuromarketing. The questions to the participants were evaluated with a 5-point Likert scale (from 1 = disagree strongly to 5 = agree strongly). It was concluded that there were 499 valid surveys (n = 499). As a result, it was seen that participants in social sciences and health sciences differed significantly in the conceptual perception of neuromarketing (p = 0.000). It was found that the perception level of social sciences is higher than health sciences.

This study examined the labor regulations regarding the hours of work and rest for representative fishing countries (Norway) by the International Labor Organization (ILO) Convention C188—Work in Fishing, 2007. A dual comparative analysis with Norway is used to explore policy implications for the representation and protection of fishers’ labor standards in Korea. This study examined the possibility of synchronisation between national and international legislation on the hours of work and rest for fishers, with a particular focus on the Norwegian case. The objective is to identify policy enhancements related to the Korean Seafarers Act. This study looked in depth at the fatigue and well-being problems faced by Korean fishers working long times on various vessels. It is based on the results of a qualitative comparative study. To achieve the objectives, We proposed to ‘the name of the fishing vessel’, which are excluded from the protections afforded by the Seafarers Act and to clarify the regulations regarding the labor standards for them. This proposal will provide compensation and protection for Korean fishers’ labor rights. It aims to enhance labor conditions in line with ILO standards, harmonize national and international agreements to protect small-scale fisheries and contribute to the development of environmentally friendly propulsion technologies, such as hydrogen-fueled electric hybrids and LPG (Liquefied Petroleum Gas).

Ecuador acknowledges the need to improve infrastructure and resources for educational inclusion, but it faces challenges in effective implementation compared to developed countries that have made advancements in this area. The objective of this research was to map the regulations and practices related to the implementation of inclusive infrastructure and educational resources at the international level, identifying knowledge gaps and opportunities for adaptation in Ecuador. An exploratory theoretical review was conducted following PRISMA-ScR guidelines, using searches in academic databases and official documents. Qualitative and regulatory studies from the United States, Finland, Canada, and Japan were selected, analyzing 16 scientific articles and 11 official documents. The results reveal that Ecuador faces challenges in the implementation of inclusive regulations, particularly in infrastructure and resources, highlighting the need to establish national accessibility standards, invest in assistive technologies, and offer continuous teacher training to enhance educational inclusion. The research uncovered a negative cycle where the lack of effective implementation of inclusive regulations perpetuates inequality and reinforces institutional inertia. For successful reform, the regulatory structure, resource management, and educational culture in Ecuador must be addressed simultaneously.

Accurate demand forecasting is key for companies to optimize inventory management and satisfy customer demand efficiently. This paper aims to Investigate on the application of generative AI models in demand forecasting. Two models were used: Long Short-Term Memory (LSTM) networks and Variational Autoencoder (VAE), and results were compared to select the optimal model in terms of performance and forecasting accuracy. The difference of actual and predicted demand values also ascertain LSTM’s ability to identify latent features and basic trends in the data. Further, some of the research works were focused on computational efficiency and scalability of the proposed methods for providing the guidelines to the companies for the implementation of the complicated techniques in demand forecasting. Based on these results, LSTM networks have a promising application in enhancing the demand forecasting and consequently helpful for the decision-making process regarding inventory control and other resource allocation.