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There is a history of overwork in China, and regulations to protect workers are insufficient. This study explores the relationship between working long hours and self-rated health among rural-urban migrant workers in China. Survey data from the 2018 China Family Panel Studies (CFPS) is used to construct a simultaneous equation model, and the 3SLS method is applied. The results showed that: (1) Migrant workers had good health. However, overtime work is very common among migrant workers in China, and male migrants work more overtime. (2) Migrant laborers' health and income are causally related, with better health leading to higher income. In contrast, the compensatory effect of income by extending working hours on health is smaller than the damage caused by overtime work for the male migrants who have more severe overtime work, resulting in a negative income effect on health. (3) The incentive effect of income on labor supply and the positive interaction effect of increasing labor hours to increase income are only reflected in the standard labor time sample. Therefore, for the heavy overwork group whose working hours have already reached the limit, income increases can no longer motivate them to extend their labor hours. Therefore, provincial and national policy transformations are needed to regularize working hours and remuneration while maintaining individual health. [ABSTRACT FROM AUTHOR]

Work–life balance (WLB), which has become a central issue in workers' everyday lives, is a global issue with a growing body of investigation into its meaning and the construction of suitable measurement scales, but varying meanings for WLB have been observed in studies. Due to these discrepancies, review or summary work is needed to identify the trends and development of WLB among workers, including (a) the commonly used WLB scales, (b) the antecedents and outcomes related to WLB and (c) the frequency of the emergence of these antecedents and outcomes. This review aims to provide an overview of empirical studies investigating the antecedents and outcomes of WLB. A total of 99 published articles from 77 journals over the period of 2006–2020 were extracted. The research methods, analysis methods, countries investigated, pivot of WLB scales used, and thematic topics and research gaps were identified. The trends of WLB, including the establishment of standard working hours, the availability of working from home, the effects of technologies on achieving WLB and the benefits of WLB for subjective wellbeing, are discussed. The research insights will provide the research directions for constructing WLB scales and investigating issues that significantly affect the WLB of employees. [ABSTRACT FROM AUTHOR]

Several factors over the years have contributed to stigma in public transport. Many studies have highlighted the need to make the transport system more equitable both from economic and gender perspectives. This study attempts to demonstrate how the perceptions of public transport users and non-users are stigmatized from social and cultural standpoints. Thus, it identifies the social and cultural stigma-induced barriers embedded with the use and people's general perception about the public bus service, taking SAPTCO (Saudi Public Transport Company) as a case study. The study results suggest that privacy concern is the primary cause of stigma. Most of the users are unwilling to ride with their families as SAPTCO does not account for gender needs (e.g., privacy, travel convenience, safety, comfort, etc.). Moreover, people from the high-income classes are more stigmatized against this ridership. A fuzzy inference system (FIS) model is used to analyze the survey questionnaire responses and understand what stigma means for the public bus service. Expert opinions are employed to generate "if–then" rules of the FIS models. Sensitivity of the defined fuzzy model is conducted to different aspects of the ridership. The study results further suggest that "inconvenience" poses the highest impact while "feeling safe", "privacy", "fare", "timing", and "comfort" are found to be the medium impact-making variables for stigma. The stigma-defining variables would be critical for the public bus service to improve its service quality and help (re-)design the policies that would attract a high amount of ridership. Some solutions are suggested in the end that would complement, strengthen, and promote the current SAPTCO service. The demonstrated methodology of this study would be relevant and adaptive to any relevant context to improve public transportation service and pertaining policies. [ABSTRACT FROM AUTHOR]

This research is a pioneering study into the adoption of mobile-based money services for financial inclusion and sustainability in developing countries like Togo. Owing to their differences from more usual mobile-based banking and payment services, such technology is being aggressively promoted by providers of network telecommunication companies. However, the factors influencing its sustainable acceptance remain largely unknown. This paper extends the original Technology Acceptance Model (TAM), by integrating self-efficacy (SEMM), technology anxiety (TAMM), and personal innovativeness (PIMM). The research model is assessed with survey data of 539 actual and prospective mobile money users employing structural equation modeling–artificial neural networks (SEM–ANN) approach. A feed-forward-back-propagation (FFBP) multi-layer perceptron (MLP) ANN with significant predictors obtained from SEM as the input units and the root mean square of errors (RMSE) indicated that the ANN method achieves high prediction accuracy. The results present conclusive evidence that perceived ease-of-use (PEMM) is the most significant factor affecting consumers' attitudes to mobile-based money. While perceived usefulness (PUMM) and PIMM affect adoption decisions, their impact is much lower. Consumer attitudes and intentions were found to have a significant relationship with TAM. SEMM and TAMM; however, they showed mixed results. These findings will be useful to retain prevailing users and attract new ones. [ABSTRACT FROM AUTHOR]

For enterprise, how to quickly realize the selection of green innovative design projects has become a key issue for improving innovation performance. Based on an analysis of enterprise product innovation and customer green preferences, an indicator set for innovation performance in enterprise was established. Considering the fuzziness of the correlation between indicators for innovation performance in enterprise and consumer's green preferences, a fuzzy clustering method was used to identify the internal relations among the indicators for innovation performance with green preferences of customers. Then a wavelet neural network was used to select the innovation design project for various green preferences of customers. Finally, a case study was proposed to verify the feasibility and effectiveness of the method. This work can help the enterprise to develop green design, products, and serve uniformly, which can effectively shorten green product development cycles, reduce cost, and improve enterprise innovation performance greatly. [ABSTRACT FROM AUTHOR]