A Portfolio-Theoretic Algorithm for Institutional Research Planning Under Scientometric Objectives

Academic departments allocate scarce research resources under deep uncertainty as today’s choices about laboratories, early-career scholars, infrastructure, and emerging topics shape future publications, citations, grants, and scientific capacity. Unfortunately, the connection between the two is delayed, noisy, and interdependent. Economic portfolio optimization offers an established framework for such decisions, as it evaluates investments not only by expected return but also by risk, diversification, and dependence among assets. Nevertheless, research opportunities are not financial assets: their returns are multidimensional, scientometric, cumulative, and shaped by spillovers, strategic priorities, and institutional inertia. In this study, we formulate departmental research planning as a Departmental Scientometric Portfolio Optimization problem, and propose Departmental Epistemic Portfolio Optimization, an integrative decision-support heuristic that allocates resources using expected scientometric return, uncertainty, covariance, spillovers, diversity, concentration, strategic alignment, and adjustment costs. Using in silico experiments covering stable, emerging-field, monoculture, and budget-shock environments, we show that DEPO is competitive with classical portfolio and heuristic baselines while preserving high portfolio diversity, low topic concentration, and relatively smooth allocation dynamics in several settings. In the emerging-field environment, DEPO allocated sustained resources to uncertain and under-observed opportunities, demonstrating the operation of its exploration mechanism; however, this behavior did not produce a clear cumulative-return or oracle-regret advantage over the strongest feasible baselines for all tested conditions. Overall, the results suggest that departments may benefit from portfolio-based decision support when they seek to make explicit trade-offs among performance, exploration, diversity, concentration control, and institutional stability.