Search Results (8)

This paper introduces a novel approach to job recommendation systems by incorporating personality traits evaluated through the Gallup CliftonStrengths assessment, aiming to enhance the traditional matching process beyond skills and qualifications. Unlike broad models like the Big Five, Gallup’s CliftonStrengths assesses 34 specific talents (e.g., ‘Analytical’, ‘Empathy’), enabling finer-grained, actionable job matches. While existing systems focus primarily on hard skills, this paper argues that personality traits—such as those measured by the Gallup test—play a crucial role in determining career satisfaction and long-term job retention. The proposed approach offers a more granular and actionable method for matching candidates with job opportunities that align with their natural strengths. Leveraging Gallup tests, we develop a job-matching approach that identifies personality traits and integrates them with recommendation algorithms to generate a list of the most suitable specializations for the user. By utilizing a GPT-4 model to process job descriptions and rank relevant personality traits, the system generates more personalized recommendations that account for both hard and soft skills. The empirical experiments demonstrate that this integration can improve the accuracy and relevance of job recommendations, leading to better career outcomes. The paper contributes to the field by offering a comprehensive framework for personality-based job matching and validating its effectiveness, paving the way for a more holistic approach to recruitment and talent management. Full article

Improving well-being at work is crucial for increasing employment among construction workers and ensuring the healthy and sustainable development of China’s construction industry. Construction workers generally experience insufficient sleep, heavy workloads, work–family conflict, etc. At present, the new generation of construction workers (NGCWs) born after 1980 is gradually becoming the main force at construction sites in China. The value concepts, life attitudes, and personality traits of this group are significantly different from those of the older generations. Given the generational differences among construction workers, this study focuses on the formation mechanism and explores the evolutionary laws of well-being at work among NGCWs. In-depth interviews with 23 new-generation construction workers were conducted, and data analysis followed a three-step coding process based on grounded theory. Then, a three-stage formation mechanism model was constructed through continuous analysis. Finally, the casual and stock–flow diagrams were drawn and simulated on the basis of the system dynamics. The results indicated that well-being at work was directly influenced by internal work motivation. Both individual characteristics and the external environment played a role in shaping work motivation; however, the key difference lay in the fact that the external environment impacted internal work motivation through the mediation of individual-environment matching. Moreover, enhanced well-being at work led to a higher level of workers’ internal needs, which, in turn, further increased the complexity of individual-environment matching. Meanwhile, individual characteristics affected the process by which motivation was transformed into well-being at work. The level of well-being showed an upward tendency under the synergistic influence of different factors; the increasing rate was high and subsequently low. Furthermore, salary, job competence, and belonging needs can significantly affect well-being at work. These findings provide theoretical support and practical references to China’s construction companies and government departments for the purpose of improving NGCWs’ well-being at work. Full article

This study compared the level of workplace violence experienced by personal healthcare workers in a district in Seoul, Republic of Korea, with those experienced by workers in office or service jobs. We matched 150 personal care workers with 150 office workers and 150 service workers using a propensity score. Workplace violence was categorized into psychological violence and physical violence. Of the surveyed personal care workers, 53.3% reported experiencing psychological violence, and 42.0% reported experiencing physical violence. After adjusting for self-reported work-related symptoms, personal care workers had significantly higher odds of experiencing psychological violence than office workers (OR = 5.01; 95% CI: 2.80–8.97) or service workers (OR = 7.54; 95% CI: 3.93–14.47). The adjusted odds for physical violence were also significantly higher for personal care workers compared with those for office workers (OR = 5.83; 95% CI: 2.96–11.50) and service workers (OR = 6.00; 95% CI: 2.88–12.49). In terms of specific types of workplace violence, personal care workers were 7–10 times more likely to experience unwanted sexual attention, sexual harassment, and physical violence than office or service workers. We found that personal care workers were more prone to workplace violence than office or service workers, with gender-based or physical violence being the most common types. Considering the negative impact of workplace violence on workers’ well-being and health services, policy updates and interventions focusing on personal care workers are needed to reduce workplace violence, safeguard workers’ rights, and establish a secure working environment. Full article

Youth not in education, employment, or training (NEET) refers to the most vulnerable group in the transition from school to work. While much research focuses on institutional factors behind the NEET incidence, the current study approaches the problem of the NEET youth from the perspective of non-cognitive skills. For measuring non-cognitive skills, the Big Five personality characteristics (openness, conscientiousness, extraversion, agreeableness, neuroticism) as well as grit were analyzed. The analysis was carried out using propensity score matching based on the data of the Russian Longitudinal Monitoring Survey (RLMS HSE) for 2016. This study shows that the majority of young people in the NEET group come from the poorest families. Nearly half of the NEET youth are not only not working, but they are also not looking for a job either. The analysis revealed that NEET youth fall behind in different non-cognitive abilities, with statistically significant differences in conscientiousness, extraversion, and grit, as well as a greater severity of neuroticism. Full article

Organizations in and associated with the real estate sector rely on a competent workforce capable of effectively managing sustainability practices. This study examined the alignment of sustainability-related qualifications between employers and individuals in the Swiss real estate-related job market. A comprehensive analysis was conducted on 600 job advertisements and 1520 personal profiles, employing a keyword-based search approach derived from sustainability definitions and contexts. The findings revealed that companies emphasized the importance of “sustainability” in their job advertisements, whereas employees rarely mentioned it in their profiles. Nevertheless, both employers and workers demonstrate a demand for expertise, competencies, and skills that contribute to fostering sustainability in the real estate domain. Noteworthy keywords encompassed digitalization, green buildings, economic thinking, creativity, and collaboration. To facilitate improved job matching between organizations and applicants and to ensure sustainable practices in the real estate sector, it is recommended that organizations integrate these suggested keywords in their job advertisements and that employees incorporate the corresponding keywords into their profiles. Furthermore, educational institutions can enhance their programs by incorporating these keywords and the proposed dimensions of sustainability into their educational frameworks. Full article

Purchasing a property entails making rankings, comparisons, and trade-offs among various housing characteristics. When trying to sell a house, real estate brokers take on an important role as a middle-person between the seller and buyer. Thus, this research sets up a dynamic price recommendation method for housing purchases and applies the fuzzy multiple criteria decision making (FMCDM) technique, so as to realize housing quality and evaluation. We utilize this method based on the prospect theory of the loss aversion effect, in order to aid real estate brokers’ job of coordinating between the seller and buyer. The method helps us to provide an objective view of the evaluation matrix. From the pricing strategy, the results are able to match price versus quality and improve brokers’ intermediation effects. The brokers can subsequently make recommendations regarding a suitable price, decisions on negotiation strategies to reach an agreement, and settle upon an acceptable price. Full article

Under the background of intelligent manufacturing, this paper aims to develop a model for person–job safe matching that optimizes safety with consideration of major equipment operator competency and task complexity. Safe matching cost is minimized in the developed model and is measured by the equipment downtime, production defect rate, and operator labor costs oriented by human factors. Human reliability is calculated with the goal of best value individual competency and best admit task complexity with a hierarchical structure. The 0-1 integer programming person–job matching model minimizes the human factor safety and wage costs and satisfies the requirements of the production order, budget and operator quantity requirement. An improved genetic algorithm is designed to solve the model. The computational results of the proposed model based on a case study for a large iron and steel company evidently demonstrated its effectiveness. A new integrated model provides more realistic matches for person–job assignment. Full article

The Korea Simulation Exposure Model for fine particulate matter (PM_2.5) (KoSEM-PM) was developed to estimate population PM_2.5 exposure in Korea. The data were acquired based on 59,945 min of the actual microenvironmental PM_2.5 measurements and on the time–activity patterns of 8072 residents of Seoul. The aims of the study were to estimate daily PM_2.5 exposure of Seoul population, and to determine the characteristics of a high exposure group. KoSEM-PM estimated population exposures by applying the PM_2.5 distribution to the matching time–activity patterns at 10-min intervals. The mean personal PM_2.5 exposure level of the surveyed subjects in Seoul was 26.0 ± 2.7 µg/m³ (range: 21.0–40.2 µg/m³) in summer. Factors significantly associated with high exposure included day of the week, age, industry sector, job type, and working hours. Individuals surveyed on Saturdays were more likely to be in the high exposure group than those surveyed on weekdays and Sundays. Younger, non-office-working individuals with longer working hours were more likely to be in the high exposure group. KoSEM-PM could be a useful tool to estimate population exposure levels to other region in Korea; to expand its use, microenvironmental measurements are required for other region in Korea. Full article