F.-Javier Heredia - Academic web site

Publication Type	Journal Article
Year of Publication	2026
Authors	Grace Kelly Maureira; F.-Javier Heredia
Journal Title	Journal of European Real Estate Research
Publisher	Emerald
ISSN Number	1753-9269
Key Words	research; real state; CBRE; tenant mix; shopping centers
Abstract	This study examines the factors influencing retail rents in shopping centers across Spain utilizing datasets from 27 shopping centers across Spain, utilizing real-world data from a real estate company operating in the country. A regression model is constructed to estimate the impact of various factors on retail rent, including physical attributes, economic conditions, tenant mix and the type of shopping centers. The empirical analysis has identified several factors that significantly determine the rental rates of stores within shopping centers. These factors include the size and location of the store, the anchor status and retail category of the tenant, and the type of shopping center. Notably, stores located on lower floors tend to command higher rental rates compared to those on higher floors. On the contrary, the distance to the nearest anchor tenant does not appear to impact rental values. This is the first study to evaluate retail rents in Spanish shopping centers using real-world data from a leading real estate company. The findings present valuable insights for shopping center managers and landlords regarding tenant placement and lease structuring and contribute to the broader literature on retail real estate and shopping center management.
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DOI	https://doi.org/10.1108/JERER-03-2025-0039
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Publication Type	Conference Paper
Year of Publication	2024
Authors	Grace Kelly Maureira; F.-Javier Heredia
Conference Name	EURO24, 33rd European Conference on Operational Research
Conference Date	30/06-3/07/2024
Conference Location	Technical University of Denmark (DTU), Copenhagen, Denmark.
Type of Work	Contributed presentation
Key Words	research; real state; shopping centers; tenant mix; modeling; multi-objective optimization.
Abstract	The strategic allocation of tenants within shopping centers, known as "tenant mix," is crucial for enhancing profitability in the retail sector. This research delves into creating an ideal combination of retail categories and their placement to boost rental income, a primary financial source for mall operators. Utilizing integer linear programming, we propose a model that integrates the concept of tenant synergy at its core—a critical yet underexplored aspect in the literature. This model includes constraints based on the total leasable space available and the strategic distribution of store units. Drawing upon a dataset from 27 shopping centers in Spain, we construct a regression model to estimate base rent, positioning it as the critical component of our objective function to maximize rental income. Additionally, this objective function features a synergy-based scoring system as an extra component, designed to enhance sales revenues and create a balanced retail environment through strategic tenant placement. The eectiveness of our model is demonstrated through several case studies, highlighting its potential to increase rental income and sales. Our findings oer mall operators a practical tool to optimize vacant spaces, facilitating strategic decision-making in the retail industry.
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Publication Type	Conference Paper
Year of Publication	2023
Authors	Grace Kelly Maureira; F.-Javier Heredia
Conference Name	IFORS 2023 - 23rd Conference of the International Federation of Operational Research Societies
Conference Date	10-14/07/2023
Conference Location	Santiago, Chile
Type of Work	Contributed presentation
ISBN Number	978-956-416-407-6
Key Words	research; real state; shopping centers; tenant mix; modeling.
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DOI	https://doi.org/10.1287/ifors.2023
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Publication Type	Funded research projects
Year of Publication	2020
Authors	Grace Kelly Maureira; Jaume Masip; F.-Javier Heredia
Type of participation	Leader
Duration	09/2020-09/2023
Call	Industrial Doctorates Plan
Funding organization	Government of Catalonia (Generalitat de Catalunya).
Partners	AGAUR
Budget	33.960,00 €
Project code	2019 DI 098
Key Words	research; industrial doctorate; real state; service science; project; public; competitive
Abstract	El objetivo del proyecto es la realización de una tesis doctoral industrial para el desarrollo de una herramienta que determine y mejore la eficiencia operacional de las centros comerciales en Espana y Portugal. Des del punto de vista metodol6gico, esta tesis doctoral se enmarca en el ambito de la lnvestigaci6n Operativa (Operational Research). En particular, se deberan abordar los problemas planteados mas adelante (A) mediante el desarrollo de modelos estadfsticos que permitan formalizar la relaci6n existente entre diferentes inputs (parametros) y outputs (variables) del modelo y (B) mediante el uso de modelos y algoritmos de optimizaci6n matematica de diversa fndole, muy probablemente problemas de programaci6n estocastica mixta multiobjetivo.
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On April 2020 an agreement was settled between the UPC and CBRE Group Inc., the largest commercial real estate services company in the world, for the development of the project Modelos de optimización matematica en la gestión de centros comerciales (MOMGeCC) (Mathematical optimization Models for the Management of Shopping Malls). This project is going to be developped in the framework of the Industrial Doctorates Plan of the Government of Catalonia, through a Ph.D thesis of Ms. Grace Kelly Maureira under supervision of prof. F.-Javier Heredia (UPC) and Jaume Masip (CBRE). The purpose of this project is to develop stochastic mathematical optimization models to provide CBRE with a computational tool to optimize the strategical planning of the configuration and operation of shopping centers under uncertainty.