In the medical field, while AI-driven systems promise enhanced efficiency, diagnostic accuracy, and operational effectiveness, they also raise critical concerns about responsibility, accountability, and ethical judgment. Despite the growing body of empirical research on medical AI, limited attention has been given to the theoretical implications of AI integration from a management and organizational perspective. Our study develops a conceptual framework to explain the dual nature of AI-supported medical decision-making by integrating insights from decision-making theory, algorithmic management, and healthcare management literature. We propose that AI simultaneously enhances decision efficiency while creating new forms of responsibility ambiguity and ethical tension. The framework conceptualizes how AI capability, human–AI interaction, and organizational governance jointly shape decision outcomes, professional accountability, and organizational trust. By offering a theoretically grounded model, this study contributes to literature in three ways. First, it extends traditional decision-making theory to AI-augmented healthcare contexts. Second, it introduces responsibility as a central construct in human–AI collaboration. Third, it provides a foundation for future empirical research and managerial practice in healthcare organizations navigating AI adoption.
The researchers explored enhanced recognition and reward systems within a healthcare organization to determine effect on employee morale and organizational success. Using a flexible research design, the researchers sought to understand the lived-experiences of healthcare professionals and how they perceived recognition within their organizations. Data were collected using in-depth interviews with 26 participants. By examining participants’ subjective responses, the researchers determined how recognition and reward systems affected workforce stability and organizational performance. Although participants were healthcare professionals, the outcomes are applicable to organizations across industries.
This study examines how tax system characteristics affect firm behavior in transition economies using panel data from the BEEPS survey. Generalized ordered probit models show that tax administration practices significantly influence firms’ perceptions of tax burdens. To address endogeneity, the analysis estimates unexplained tax obstacles using methods from happiness economics. Results reveal that firms previously reporting tax administration as an obstacle later spent more time on tax compliance, made slightly fewer payments, and experienced more frequent tax inspections. The findings offer insights into how evolving business conditions and tax practices shape firm operations over time.
Leaders in Global Software Development (GSD) organizations have experienced tremendous growth because of increased GSD awareness, greater benefits, and improved process effectiveness in distributed settings. GSD acceptance and adaptation in dynamic, complex environments may be attributed to an added advantage. The primary GSD challenges identified are team coordination, communication, collaboration, trust, culture, people, geographical distance, and time zones. This study reviewed the literature and identified appropriate GSD techniques that enable leaders to implement best management practices to improve software product quality. This paper provides a detailed critical literature review, summarized results, and a comparative study. This study identified emerging GSD challenges in the literature as potential success factors when properly addressed. In addition, the research confirmed GSD techniques that may help leaders manage software product quality effectively, avoid project failures, and meet customer expectations.
Frontline service workers and/or their supervisors delivering clearly inaccurate, bad, and/or unlawful service to customers or other “persons of interest” (POI) that causally precedes negative outcomes is one category of shitshow service-failure performance. The study presents both case studies and findings from national data showing that shitshow service enactments by performing professional public servants (PPSs) occur daily and more frequently in the U.S. than in other economically developed nations. Substantial case evidence supports the view that shitshow performances readily occur even when service protagonists have decades of job experience and/or have trained newly hired professional public servants. “Professional public servants” (PPS) includes employees working in various government agencies, departments, and branches (e.g., clerks in a branch of the U.S. Postal Service, a frontline service provider in a state department of motor vehicles, public libraries, and local/state/federal police officers). This study proposes “LARP” (i.e., live-action role-playing) by PPSs as actors with protagonists, POI (i.e., “person of interest”), and additional collaborative roles) in face-to-face enactments in recorded, actual shitshow performances (i.e., the psychological equivalent of a live virus immunization) provides the emotional heat needed to help prevent subsequent real-life shitshow reenactments.
