Work

Integrating psychological factors into AI-supported decision-making for reverse brain drain policies: A human-centered computing approach

Year: 2025

Type: article

Abstract: Policies targeting reverse brain drain are often limited to economic and institutional dimensions, and psychological factors are insufficiently considered. However, psychological factors such as belonging, identity, future expectations, perception of social status, and trust play a decisive role in individuals' decisions to return. Ignoring this dimension leads to policies failing to reflect individuals' true motivations and failing to ensure long-term commitment. The primary objective of this study is to develop an innovative decision-making model for determining the most appropriate public policies by analyzing the psychological factors affecting reverse brain drain. The study gathers the opinions of ten different experts, and machine learning techniques are used to calculate the importance of these opinions based on demographic characteristics. The criteria importance assessment (CIMAS) technique is used to determine the criteria weights, and the weighted integrated sum product (WISP) technique is used to prioritize strategies. To manage uncertainties more effectively, the model integrates fuzzy sets based on the Sierpiński triangle. This study contributes to the literature by presenting a comprehensive approach that focuses on the psychological factors affecting reverse brain drain. The proposed model offers a superior framework to existing studies in the literature by representing uncertainty in a multi-layered manner using Sierpiński triangle fuzzy sets, integrating psychological factors into decision-making processes, and calculating expert weights more objectively using machine learning. The study's findings indicate that "belonging and identity" and "hope and future expectations" are the most critical criteria. In terms of strategies, "predictable economic policies and political stability" and "competitive salary policies for highly qualified professionals" are the top priorities.

Source: Acta Psychologica

DOI: 10.1016/j.actpsy.2025.105728

Authors: Serkan Eti, Serhat Yüksel, Hasan Dinçer, Harun Çetinkaya, Furkan Baki Zaralioğlu

Institutions: Istanbul Medipol University, Khazar University

Language: English

Topic: Migration and Labor Dynamics

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

SDG: Reduced inequalities

Open Access status: gold

Estimated APC paid: $2,670