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Concerning trends in graduate education, such as high attrition and underdeveloped skills, drive toward a new doctoral education approach. This paper aims to describe and propose a transformative doctoral education model (TDEM), incorporating elements that potentially address these challenges and expand the current practice. The model envisions discipline-specific knowledge coupled with a broader interdisciplinary perspective and addresses the transferable skills necessary to successfully navigate an ever-changing workforce and global landscape. The overarching goal of TDEM is to transform the doctoral student into a multi-dimensional and adaptive scholar, so the students of today can effectively and meaningfully solve the problems of tomorrow.

The foundation of TDEM is transformative learning theory, supporting the notion learner transformation occurs throughout the doctoral educational experience.

Current global doctoral education models and literature were reviewed. These findings informed the new TDEM.

Designed as a customizable framework for learner-centered doctoral education, TDEM promotes a mentor network on and off-campus, interdisciplinarity and agile career scope preparedness.

Within the TDEM framework, doctoral students develop valuable knowledge and transferable skills. These developments increase doctoral student career adaptability and preparedness, as well as enables graduates to appropriately respond to global and societal complex problems.

This proposed doctoral education framework was formulated through a review of the literature and experiences with curricular design and pedagogical practices at a research-intensive university’s teaching and learning center. TDEM answers the call to develop frameworks that address issues in doctoral education and present a flexible and more personalized training. TDEM encourages doctoral student transformation into adaptive, forward-thinking scholars and thriving in an ever-changing workforce.

This paper aims to investigate how emotional intelligence and voice climate interact with flow in work teams.

The authors used multilevel structural equation modeling to analyze the nested data (individuals within teams). A total of 42 work teams (166 full-time employees) from the service industry participated in this research.

The results showed that emotional intelligence and voice behavior are positively associated with flow experience at the individual level. It was also demonstrated that emotional intelligence exerts partial influence on flow via individual voice behavior. At the team level, the authors only found a positive relationship between emotional intelligence and flow.

This research fills the knowledge gap of flow’s antecedents in teams. Members who are emotional intelligent and active in making suggestions to teams are more likely to experience flow in teams. Practitioners should be able to facilitate flow in the workplace through implementing training modules related to emotion appraisal/regulation and effective voice behavior.