Stop focusing on Q1 journals, impact factor and H-index (they’re the WRONG metrics)

Academic careers don’t need to be built around journal rank metrics like impact factor or H-index. The more durable path, Sebastian’s experience suggests, is to slow down enough to make bigger contributions—often through applied research that matures over time into higher-quality journal work. His own publication record includes more than 30 papers and hundreds of citations, but the lesson he emphasizes is about process: avoid rushed output cycles that turn deadlines into a reason to publish quickly rather than to build something that lasts.

Sebastian’s first publication came in 2016, when he was still working in IT consulting. A larger research project with the University of Twente involved master’s students and deliverables that led to a technical paper on interoperability in logistics—centered on data modeling for data exchange, plus a prototype. That early bridge between industry work and academic publishing helped shape his long-term view: publishing is a way to document outcomes, not a scoreboard to chase. Over time, his work leaned heavily toward applied research formats—conference papers, workshop papers, and applied journal articles—because they support cumulative knowledge development and faster feedback loops with practitioners.

When deadlines and pressure hit during a PhD, the tendency is to “do something quick” to meet timelines. Sebastian credits his ability to avoid that trap to habits formed outside academia as well as deliberate planning. In IT consulting, he learned to handle multiple projects under short time windows, but in academia he added structure: maintain a clear research line on a whiteboard or one-page overview, reserve recurring focus blocks, and treat those blocks as protected time. He recommends 3–4 hours per week dedicated to major topics—no internet, locked room, and strict calendar commitment—because focus time is the only way to keep big contributions from being swallowed by meetings, teaching, supervision, funding work, and administrative duties.

He also argues that “no” must be managed professionally, not emotionally. Saying yes to everything creates workload and distorts what gets published. Instead, he advises negotiating priorities, offering help without taking on everything personally, and keeping a buffer for rest and ongoing demands. The goal is to prevent enthusiasm from becoming another form of overcommitment.

On research strategy, Sebastian describes building contributions in sequences rather than one-off papers: start with position or doctoral work, then add experiments or systematic literature reviews, and eventually develop design-oriented methods, prototypes, and—when ready—a more formal design theory with testable hypotheses. He illustrates this with a community-of-practice model used with transportation, logistics, and manufacturing companies. Over roughly four months and five workshops, teams use a human-centered AI design method to build prototypes; more than 40 companies participated, about 80% produced working prototypes, and examples included reducing empty mileage by coordinating loads across platforms and saving fuel costs through decision agents trained on Markov decision processes.

Finally, he ties his technical approach to ethics and governance. Human-centered design keeps people in the loop, supports early risk assessment, and addresses issues like hallucinations in large language models, black-box opacity, and accountability. He points to the need for auditability and explainability, plus organizational responsibility and AI literacy for end users. His “why” is impact: applied work that helps industry remain competitive and addresses sustainability challenges like logistics efficiency and climate-related disruptions—without turning publishing into a rat race.