An empirical evaluation of tech interventions to improve financial decision-making

Abstract

Purpose

This paper aims to empirically compare the degree to which two technological interventions, based on the computer-supported collaborative learning (CSCL) and the technology acceptance model (TAM), were associated with a different incidence of financial biases.

Design/methodology/approach

The study adopted a quasi-experimental research design. The authors randomly assigned the participants (N = 507) to one of two training conditions or a control group, and in turn, we assessed the incidence of financial biases after the training interventions.

Findings

Participants who took part in the TAM-based group reported lower financial biases than those in the CSCL-based training group and the control group.

Research limitations/implications

Literature suggests that two educational approaches, i.e. the CSCL and the TAM, can implement individuals’ financial decision-making. These educational approaches involve technology to support individuals in reducing the incidence of cognitive biases. This study contributes by advancing empirical evidence on technological supports for interventions to improve financial decision-making.

Practical implications

Suboptimal decision-making may lead to adverse consequences both at the individual and social levels. This paper contributes to the literature on debiasing interventions by offering initial evidence on technological-based interventions in the domain of financial decision-making. The authors discuss the application of this evidence in lifelong training.

Originality/value

This study provides evidence on how different technological interventions are associate with a lower incidence of financial biases.

Citation

Tommasi, F., Ceschi, A., Weller, J., Costantini, A., Passaia, G., Gostimir , M. and Sartori, R. (2021), "An empirical evaluation of tech interventions to improve financial decision-making", European Journal of Training and Development, Vol. 45 No. 6/7, pp. 633-649. https://doi.org/10.1108/EJTD-11-2020-0169