Radford University

With the increasing adoption of Artificial Intelligence (AI) in the workplace, employees' career paths have become more diverse and less predictable in the era of Industry 4.0. As technological transformations accelerate, employee turnover patterns are also changing, as reflected in the growing prevalence of occupational transitions and large-scale layoffs. These shifts highlight the need for more developmental approaches to understanding and managing retention. To address this issue, the present paper examines how AI implementation influences employee turnover by focusing on both the motives and psychological states underlying the withdrawal process. Drawing on proximal withdrawal states theory, the paper provides a deeper understanding of the dynamic nature of employee withdrawal patterns. This perspective elucidates the withdrawal process shaped by AI adoption, emphasizing that employees' responses to technological disruption are diverse in both psychological and behavioral terms rather than uniform. Furthermore, the paper proposes Human Resource Development (HRD)-based interventions aimed at preventing undesirable turnover through employee education and career development initiatives. By integrating these elements, we introduce an HRD-focused framework for addressing turnover issues associated with AI adoption in a more developmental and sustainable manner. Finally, the paper outlines future research directions for empirically testing the proposed theoretical mechanisms and intervention strategies within the rapidly evolving technological landscape of work.

Many cemeteries include large amounts of greenspace and so have substantial potential to support urban plant and wildlife communities. However, the physical structure and design of these human-focused greenspaces may ultimately determine which species successfully inhabit these areas. Here, I studied the relationship between grave markers, a unique and ubiquitous feature of cemeteries that vary widely in shape and structure within and between burial areas, and the behavior of cemetery avian communities. I hypothesized that areas with greater structural heterogeneity of markers would be used by a larger diversity of species and that species would alter their behavior and interactions with markers based on marker structure. I assessed avian abundance and species richness in areas with varied upright and homogenously flat grave markers and observed behaviors exhibited by four common species in relation to grave markers and other structural features. While I found no relationship between grave marker heterogeneity and avian species richness or abundance, there is evidence for species-specific behavior and interactions with grave markers, suggesting that marker design is an important and relevant landscape feature for birds. These results have practical applications for cemetery design at a time when there is both increased public interest in environmentally friendly burials and growing competition for land in increasingly heavily developed urban areas.

This study aimed to explore the effects of eCoaching with online Bug In Ear (BIE) technology as preservice teachers implemented evidence-based practices (EBPs) during their student teaching placements in inclusive early childhood classrooms. We used a single-case multiple-probe research design, replicated across three participants, to evaluate the effects of the intervention on the delivery of two target behaviors: modeling and providing choices. A functional relation was observed, as preservice teachers increased practical application with fidelity of the two target behaviors after receiving the intervention. In addition, data from social validity surveys suggest eCoaching with online BIE technology is a socially valid method for receiving instructional support. Thus, findings show eCoaching with BIE technology to be a promising tool for improving preservice teachers' use of EBPs.

Using novel comprehensive administrative micro data on business applications in the United States over the period 2004-2023, we examine the characteristics of business applications and resulting startups that aim to develop Artificial Intelligence (AI) technologies or use AI in providing goods and services. AI-related applications begin rising around 2012, accelerate after 2016, and surge in 2023, consistent with major advances in AI technologies around these years. This growth is highly uneven across states and sectors. AI applications are more likely to come from corporations, transition to startups at higher rates, and anticipate greater initial employment than other applications. Startups originating from these applications achieve higher employment and revenue, but have a lower survival rate, reflecting an 'up-or-out' dynamic. Despite higher revenue, they exhibit a higher labor share and do not have higher labor productivity. The patterns suggest an accelerating AI diffusion through new business formation and a growing contribution from AI-related startups to business dynamism.

People in helping professions, including frontline urban ministries, often experience burnout and compassion fatigue. Despite feeling called into ministry, the work is demanding and requires the individual to demonstrate care, empathy, and support for and with individuals and groups. One congregation employs various interventions to mitigate burnout and address the vicarious trauma they experience in the ministry. This collective desires to provide intentional support for people who make space for those in their circles of care. The exploratory nature of this research study provides rich data as it was conducted using focus groups comprising staff from a church located in an urban setting. Results highlight how the staff acknowledges and addresses individual and collective vicarious trauma by incorporating intentional restorative practices to promote wellness, healing and sustainability.