The past decade has seen increased interest in entrepreneurship education outside business schools, driven both by changes in market demand and governmental policies. This has led to an expansion of embedded entrepreneurship education, where entrepreneurship is included as part of existing, non-business courses. Using the context-intervention-outcome-mechanism framework, we systematically review 33 cases of embedded entrepreneurship education programs to understand where, how, and with what outcomes such initiatives were implemented. Our analysis identifies four mechanisms, which explain how embedded entrepreneurship education functions: individual, team-based, organizational, and multi-organizational. Our analysis points to three key recommendations for embedded entrepreneurship education practice and three related avenues for future research: considering program scalability, intended outcomes and misaligned pedagogical models, and contextual diversity.

Purpose: Before the onset of the COVID-19 pandemic, most employees worked from their employers' offices, and new team members were integrated into their roles through standard onboarding procedures. However, in response to the pandemic, organizations quickly reestablished new remote onboarding strategies. As hybrid employment gains popularity, the onboarding process has been affected by the digital transformation (DT) phenomenon, and organizations must now implement remote strategies to onboard new employees. Design/methodology/approach: In this context, by considering the major changes that happen in the field, the purpose of this article is to provide a literature review of the onboarding process (OP), using the context-interventions-mechanisms-outcomes framework. Findings: The review identifies four mechanisms describing the complexity of the OP and the impact of DT: basic onboarding, advanced onboarding, integration of newcomers and remote onboarding. Originality/value: The findings have implications for both HR professionals concerned with onboarding strategy, and researchers studying the OP.

Scholars have become interested in understanding what drives academics to pursue an entrepreneurial path, but less attention is paid to the individual-level factors that are considered the best predictors of entrepreneurial intentions among academics (AEI). Using a configurational approach, this study investigates the individual factors that influence AEI by confirming whether and under what conditions the antecedents can explain the outcomes. Fuzzy-set comparative qualitative analysis (fsQCA) was performed to identify the causal paths that influence AEI. The results reveal multiple configurations of conditions that influence AEI. The findings show that the attitude toward entrepreneurship is a core condition that explains high AEI. This effect is obtained when a positive attitude among academics is supported by having higher self-efficacy and a mastery goal orientation. In addition, academic status (i.e., job position, job experience) can play an important role in this equation. Also, motivational factors (i.e., performance goal orientation, performance avoidance goal orientation) can lead to low AEI. This is one of the first studies to apply a configurational approach in examining different causal paths to AEI in a developing-country context. This paper uses academic status, self-efficacy, goal orientation, attitude toward entrepreneurship, and academic output as conditions to identify multiple unique pathways that influence AEI.

Throughout the article we reviewed the present literature on successful onboarding to identify determinants, measurement models, and outcomes associated with its success, ultimately offering pragmatic implementation techniques for companies to attain successful onboarding outcomes. We have applied a systematic approach to analyze relevant articles, categorizing determinants, measurement models, and outcomes into various classifications founded on their presence throughout the literature. Key findings include the identification of eleven determinants, four measurement mechanisms, and nine outcomes associated with successful onboarding. Integration of these factors provides organizations with practical strategies to enhance successful employee onboarding. This research enhances the current body of literature by synthesizing key determinants, measurement models, and outcomes associated with successful onboarding, offering a comprehensive framework for organizations to improve their onboarding processes.