Search

Working hours have been discussed for over 150 years from a variety of perspectives such as worker health, corporate productivity, and job market stability. Despite extensive research in working hour reduction, there is limited evidence on the effect of hours worked by industry characteristics. This study examined the relationship between technical efficiency and working hours. For this, 514 Korean companies were divided into labour-intensive and knowledge-intensive industries, and changes in technical efficiency in each industry were investigated after implementing a working hour reduction policy. The efficiency of the labour-intensive industry improved after a reduction of working hours, whereas that of the knowledge-intensive industry decreased. These results imply that working hours should vary by industry. This study empirically illustrates the effect of reducing working hours and suggests practical guidelines for each country and company to increase technical efficiency by industry. [ABSTRACT FROM AUTHOR]

AbstractThe global population is experiencing a significant rise in cases of depressive disorders, which have been exacerbated by the COVID-19 pandemic. However, having limited resources and fear of social stigma have discouraged individuals from seeking professional psychological counseling or visiting hospitals. In response to this issue, psychiatrists have attempted the use of chatbots as a therapeutic aid. Therefore, in this study, users’ choice data about the mental healthcare AI chatbot are collected through conjoint analysis, and the collected data is analyzed using the mixed logit method to derive users’ preferences for the mental healthcare AI chatbot. Findings highlight a consistent preference among users for certain factors in both psychological counseling chatbots and traditional psychological counseling. At first, the findings indicate that users place the highest priority on pricing and the ability to connect with a professional counselor. Furthermore, users prefer chatbots that have a more human-like appearance and characteristics. By incorporating these preferences, chatbot developers can create a more user-centric mental healthcare AI chatbot. [ABSTRACT FROM AUTHOR]