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.

随着多方建筑 (MOB) 中财产纠纷的增加趋势，需要更加关注纠纷管理，以防止巨额诉讼成本、高压力水平和城市社区的不和谐。现有研究已经认识到，查明纠纷的来源可以主动减少纠纷的发生和影响。MOB 的所有权结构和架构设计被视为关键来源，但其细节方面对争议的影响尚不清楚。本研究旨在确定影响社区内财产纠纷发生率和强度的 MOB 的所有权和建筑因素。它首先定义了导致争议的关键 MOB 因素以及澳大利亚维多利亚背景下争议强度的测量模型。然后，它通过对 101 个法庭案件采用机器学习技术 Boosted Classification Tree 来调查因素与强度之间的关系。本研究确认了与争议强度高度相关的六个因素：公共区域的设计、所有权空间边界、所有权空间安排、共同所有权份额的分配、单个单元的设计以及每个单元的附属空间。研究结果阐明了在减轻争议的规划阶段需要控制的 MOB 因素及其影响。分配共同所有权份额，设计单个单元，以及每个单元的附属空间。研究结果阐明了在减轻争议的规划阶段需要控制的 MOB 因素及其影响。分配共同所有权份额，设计单个单元，以及每个单元的附属空间。研究结果阐明了在减少争议的规划阶段需要控制的 MOB 因素及其影响。