This bibliographic analysis explores the evolving landscape of additive manufacturing (AM) in the context of Industry 4.0 and the emerging paradigms of Industry 5.0. This research critically examines the key literature and scholarly works to clarify the evolution, challenges, and opportunities presented by integrating AM technologies with digital transformation and advanced industrial practices. The exploration begins by tracing the foundational concepts of Industry 4.0, emphasizing the role of cyber–physical systems, data analytics, and automation in reshaping manufacturing ecosystems. It then moves to the developments of Industry 5.0, focusing on human-centric approaches, collaborative robotics, and sustainable manufacturing strategies that extend beyond automation. The impact of AM technologies across various sectors, from aerospace and automotive industries to healthcare and consumer goods, is central to this analysis. This article synthesizes empirical studies, case analyses, and theoretical frameworks to discern the synergies, challenges, and prospects of integrating AM into Industry 4.0 and the evolving Industry 5.0. Through this bibliographic journey, readers gain insights into the transformative potential of AM as a catalyst for innovation, agility, and sustainability in the digital age. The findings underscore the need for interdisciplinary collaborations, policy frameworks, and technological advancements to harness AM’s full potential within Industry 4.0 and 5.0.

The aim of this study is to draw on a cognitive-affective personality system to test if the personality–emotional exhaustion–turnover intentions/perceived service quality relationships are valid among agents working in offshoring call centers. This is achieved by comparing these relationships between two groups' agents: (a) agents interacting with customers having the same national culture in a developed country (ACSC); and (b) agents in a developing country interacting with customers having a different national culture (ACDC). Data were collected from three call centers in Morocco, representing the ACDC group, and a call center in Canada which represented the ACSC group. Data was analyzed using two steps: (a) a paired-samples t-test; and (b) a path analysis using a bootstrap based on the Monte Carlo method. The findings reveal invariant measure of all our concepts, and significant differences between the two groups (ACDC and ACSC) with respect to some personality–emotional exhaustion–turnover intentions/perceived service quality relationships.