ISBN: 978-981-18-5852-9 DOI: 10.18178/wcse.2022.04.157
Impact of Commercial Risk on Real Estate Projects: An Application of Machine Learning to Real Estate
Abstract— The health crisis has marked a milestone in the digital transformation worldwide, influencing all
processes in the various productive sectors of an economy. One example is the real estate industry, which had
to digitize its legal, commercial, supervision, and analysis processes, etc., since it was affected by productive
and social restrictions that had an impact on the increase in the rate of unemployment and interruption in the
payment chain. As a result, it was assumed that the acquisition of a property in this context was a delayed
need, understood as a commercial risk for real estate companies. However, there have been increases in
several real estate markets around the world, showing that the impact of commercial risk in the real estate
sector was on a smaller scale. In this sense, the use of big data and machine learning techniques have made it
possible to identify and analyze such risks and the industrial engineer as a process professional is in charge of
adapting these innovative tools in risk measurement. Due to these facts, this study has been motivated with
the objective of measuring the impact of commercial risk in a developing economy, applying K-means
technique, an unsupervised learning algorithm. The results showed that residential real estate projects did not
demonstrate a significant impact of commercial risk, with an average increase of 8 months in the payback
period, while massive projects did not have a statistically significant impact, increasing the payback period
by an average of 13 months.
Index Terms— Risk; Real Estate; Machine Learning; Clustering; Payback; Sales velocity.
Felix Alberto Pacheco-Fuster
Faculty of Economic Engineering, Statistics and Social Sciences, Universidad Nacional de Ingenieria, Peru
Juan Alejandro Ortega-Saco
Faculty of Industrial Engineering, Universidad Privada del Norte, Peru
Faculty of Business Sciences, Continental University, Peru
Cite: Felix Alberto Pacheco-Fuster, Juan Alejandro Ortega-Saco, Franklin Cordova-Buiza, " Impact of Commercial Risk on Real Estate Projects: An Application of Machine Learning to Real Estate, " WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications, pp. 1366-1374, Sanya, China, April 15-18, 2022.