Prediction of Delay Occurrence in Disputed Real Estate Projects: An Artificial Neural Network Approach

Abstract

Real estate disputes are inevitable and regarded as being the most important factor influencing timely completion of projects. Indian real estate sector is largely affected due to different project characteristics and cultural practices adopted around the different regions of country resulting into disputes. Given various reasons for disputes in Indian real estate sector, the project’s completion may be delayed. To eliminate the discrepancy of an unorganized sector, Government of India (GOI) enforced the Real Estate (Regulation and Development) Act, 2016 by forming The Real Estate Regulatory Authority (RERA). The reform of regulatory framework leads to elimination of differential cultural practices but the real estate sector still encounters disputes due to varied project characteristics. Thus it becomes necessary to understand, analyze and forecast the pattern generating delay due to claims and disputes in Indian real estate sector. This study attempts to implement artificial neural network (ANN) to predict whether disputed project might be delayed or not based on the project characteristics. The soft computing model is developed utilizing around 180 past judgments from five Mahanagar Palika (municipal corporation) namely Ahmedabad, Surat, Vadodara, Gandhinagar and Rajkot under Gujarat RERA (GujRERA). The findings of the research will help the authority to take necessary steps at initial stage of project to eliminate the disputes and to avoid utilization of considerable amount of resources for resolving these disputes.