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The purpose of this quantitative, causal-comparative and predictive correlational design study is to examine how workload, surface acting, work group inclusion, and emotional exhaustion impact African-American and Caucasian American managers in domestic, white-collar roles. A critical variable is emotional exhaustion which has been identified as a key characteristic and predictor of burnout in the workplace. While many current burnout studies have excluded underrepresented minorities and focused on job performance and job demands in human service industries, this study addresses relevant psychological workplace factors that have been associated with detrimental mental and physical conditions of underrepresented minorities - emotional dissonance and lack of inclusion. Such conditions impact organization commitment, engagement, and job satisfaction. This has been a gap in literature as well as a call for future studies. Four instruments were used to measure the variables workload, surface acting, work group inclusion and emotional exhaustion via an online survey - workload subscale of the Areas of Worklife Survey, surface acting subscale of the Emotional Labour Scale, Work Group Inclusion Scale, and the emotional exhaustion subscale of the Maslach Burnout Inventory, respectively. The following paper provides an introduction, literature overview, method detail, and findings of the study. Using quota sampling and snowball sampling techniques, 146 participants were included in the study. Keywords: burnout, job demand, emotional dissonance, surface acting, emotional labor

The focus of this paper is on the topics of artificial intelligence and supply chain management and how artificial intelligence-enabled supply chains provide organizations with competitive advantages. The supply chain’s adoption of data collection technologies as part of digital transformation and movements of industry 4.0 creates a strong foundation for artificial intelligence analytics. Artificial intelligence has three branches sensing and interacting, decision-making, and learning. Each branch uses its algorithms and serves a different purpose for the business. Artificial intelligence-enabled supply chains create unique, inimitable competitive advantages that fit Michael Porter’s five forces.