In the rapidly evolving landscape of human resources and talent acquisition, the impact of the usage of artificial intelligence (hereafter, AI) on recruitment biases has emerged as a pivotal and transformative subject of study. Therefore, this study aims to critically evaluate the impact of AI usage on recruitment biases, particularly in the context of China. The data was gathered through a survey of 423 respondents working in the manufacturing sector. We use a cross-sectional dataset and various diagnostics (i.e., reliability and collinearity tests). The empirical findings using multivariate regression techniques suggested that Al usage is reshaping the recruitment process by offering innovative solutions to tackle biases that have pervaded the hiring process for years. However, human involvement is indispensable in the recruitment process, alongside the use of AI. Although the use of AI can efficiently handle tasks such as resume screening and data analysis, human judgment brings essential qualities to the hiring process. Human recruiters possess the ability to assess a candidate's soft skills, cultural fit, and emotional intelligence, as these qualities are challenging for AI to comprehend. The policy implications of the study recommend that by combining the strengths of AI efficiency with human insight, organizations can create a recruitment process that is not only objective and efficient but also considerate, ethical, and aligned with the values and goals of the company

This study aims to investigate the phenomenon of over-ordering behavior in social dining as a significant contributor to food waste, utilizing an integrated conceptual model that combines the theory of planned behavior (TPB) and the norm activation model (NAM) with the moderating role of Mianzi. A total of 583 responses collected through an online survey are analyzed using partial least squares–structural equation modeling (PLS-SEM). The findings reveal that awareness of consequences and ascription of responsibility positively influence personal norm, while personal norm negatively affects consumers’ attitude towards over-ordering. Furthermore, attitude, subjective norm, and perceived behavioral control (PBC) are positively and significantly associated with over-ordering behavior. Notably, Mianzi moderates the relationship between personal norms and attitude. These findings contribute to a deeper understanding of the factors influencing consumers’ over-ordering behavior and provide valuable insights for addressing food waste in social dining contexts. The study’s limitations are discussed, and future research directions are suggested to advance the field of food waste reduction.