Synthetic Identity and the Dilution of Opportunity Cost: A longitudinal study on the erosion of financial agency under predictive algorithms).

This OSF repository contains the datasets, analysis scripts, and supplementary materials associated with the study examining the long-term effects of AI-driven recommendation systems on human decision-making and financial agency in digital commerce environments. The research investigates how repeated exposure to algorithmic recommendations influences user satisfaction, perceived autonomy, purchase behavior, and the emergence of what we conceptualize as a Synthetic Identity. The study is based on a longitudinal experimental design with repeated measurements, combining behavioral data and psychometric indicators collected across multiple weeks of interaction with AI-mediated recommendation systems. The analytical framework includes mixed-effects models, event-study estimations, piecewise linear mixed models for structural change detection, and robustness analyses using information-theoretic measures. This repository provides the anonymized datasets used in the analyses, data dictionaries, variable coding documentation, and replication materials necessary to reproduce the findings reported in the associated manuscript. All shared data have been de-identified to protect participant privacy and are made available exclusively for academic, educational, and scientific reproducibility purposes in accordance with open science principles.