Auke Hunneman

The Journal of Finance and Data Science 11 Doi: https://doi.org/10.1016/j.jfds.2025.100166

This research delves into the predictive modeling of credit card delinquency by harnessing both credit and debit data, offering a nuanced perspective on consumer financial behavior. The study introduces a novel hierarchical Bayesian regression model that significantly surpasses traditional machine learning algorithms in predictive accuracy. By integrating behavioral aspects of financial decision-making, the model provides a profound understanding of the factors influencing delinquency, such as payment timing and repayment ability. We found that the combination of credit and debit data allows for a more comprehensive assessment of a cardholder's financial behavior and risk potential. The model effectively captures individual variations in financial behavior, making it possible to predict delinquency with higher precision. This approach not only enhances the predictive power but also aids in understanding the underlying patterns of financial behavior that lead to credit risk. The practical implications of this research are substantial for financial institutions, which can leverage these insights to refine risk assessment processes and develop targeted strategies for managing credit risk. The findings advocate for a more informed approach to credit scoring that considers broader behavioral factors, offering a strategic advantage in the competitive financial services market.

International Business Review 23(4) Doi: https://doi.org/10.1016/j.ibusrev.2023.102121

Speed of internationalization may refer to how early a new venture goes abroad as well as how fast it expands its activities post-entry. The present paper incorporates both aspects and analyzes to what extent several dimensions of speed influence the ability of new ventures to survive in export markets. Based upon extant theories, two perspectives are deduced – a Learning perspective and a Resource perspective – leading to partly contrasting hypotheses. The hypotheses are tested based upon a unique data set consisting of all new ventures established in Norway a specific year that started to export goods in the following nine years. Among the findings are that survival rates increase when ventures go international immediately after inception and when they expand rapidly into new countries rather than focusing on expanding their export share in a limited number of markets, thus lending support to the Resource perspective.

Journal of Retailing and Consumer Services 73 Doi: https://doi.org/10.1016/j.jretconser.2023.103355

In this paper, we extend a retail location evaluation model with the possibility to include the effect of department size adaptation at the store level. We relate department-level store sales to a store's competitive and demographic environment, thereby providing richer insights into the drivers of department sales than a model of just aggregate sales. Further, we accommodate heterogeneity in consumer characteristics over space by using zip code level data and unobserved spatial effects in department sales by including spatially autocorrelated error terms. Using spatial panel data for 30 clothing stores belonging to one Dutch retail chain, we demonstrate how to use the modeling approach to analyze and predict sales performance of new and existing stores. We show that the predictive performance of our model is superior to that of a benchmark model that does not include spatial autocorrelation.

International Journal of Gastronomy and Food Science 31 Doi: https://doi.org/10.1016/j.ijgfs.2022.100656

Packaging and label design are crucial in facilitating the perception of brand premiumness. However, we know relatively little about how common design characteristics used in a product’ packaging affect consumers' perception of premiumness. Related research suggests that consumers may associate some features, such as symmetry, with premiumness, given their quality connotations. In this article, we report an online study (n = 741) designed to evaluate the influence of curvature (round vs. angular), symmetry (symmetrical vs. asymmetrical), and mark (black vs. no fill) on consumers' premiumness perceptions, across four different food product categories (chocolate, coffee, jam, and ice-cream), and two price conditions. Overall, we find a significant positive effect of symmetry, and a significant effect of mark on all except one product category. The effect of mark and curvature on consumers’ premiumness perception appeared to be affected more by context and product-category. Consistent with evolutionary theory, the results provide evidence for the hypothesis that symmetry is a key indicator of brand premiumness. This contributes to our understanding of the aesthetics of premium brands and suggests specific implications for practitioners.

Spatial Economic Analysis 17(1) Doi: https://doi.org/10.1080/17421772.2021.1916574

This paper sets out a general framework for store sales evaluation and prediction. The sales of a retail chain with multiple stores are first decomposed into five components, and then each component is explained by store, competitor and consumer characteristics using random effects models for components observable at the store level and spatial error random effects models for components observable at the zip code level. We use spatial panel data over four years for estimation and a subsequent year for evaluating one-year-ahead predictions. Set against a benchmark model that explains total sales directly, the prediction error of our framework is reduced by 34% for existing stores during the sample period, by 5% for existing stores one year ahead and by 26% for new stores.