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作者

Jihye Shin;Abbas Rajabifard;Mohsen Kalantari;Behnam Atazadeh

来源

HABITAT INTERNATIONAL,Vol.112,P.102371

语言

英文

关键字

Dispute;Strata title;Condominium;Property ownership;Architectural design;Machine learning technique

作者单位

The Centre for Spatial Data Infrastructures and Land Administration, Department of Infrastructure Engineering, The University of Melbourne, Victoria, 3010, Australia;The Centre for Spatial Data Infrastructures and Land Administration, Department of Infrastructure Engineering, The University of Melbourne, Victoria, 3010, Australia

摘要

With the trend towards increased property disputes in multi-owned buildings (MOBs), a greater focus is needed on dispute management to prevent huge litigation costs, high-stress levels, and disharmony in urban communities. Existing studies have recognized that pinpointing sources of disputes allows proactively minimizing dispute occurrence and influence. Ownership structure and architectural design of MOBs are viewed as the critical sources, but the effects of their detailed aspects on disputes remain unclear. This study aims to identify ownership and architectural factors of MOBs impacting on the incidence and intensity of disputes within communities in the property. It first defines crucial MOB factors causing disputes and a measurement model of the dispute intensity in the context of Victoria, Australia. It then investigates relationships between the factors and the intensity by employing Boosted Classification Tree, a machine learning technique, for 101 tribunal cases. This research confirms six factors highly associated with the dispute intensity: design of common areas, ownership space boundaries, ownership space arrangement, allocation of co-ownership share, design of individual units, and accessory spaces for each unit. The results shed light on MOB factors to be controlled at planning stages for mitigating disputes and their influence.