潜在Dirichlet分配
建筑信息建模
范围(计算机科学)
独创性
数据科学
新颖性
水准点(测量)
分类
计算机科学
主题模型
比例(比率)
知识管理
工程类
地理
定性研究
社会学
情报检索
运营管理
地图学
人工智能
社会科学
哲学
神学
调度(生产过程)
程序设计语言
作者
Jacopo Cassandro,Claudio Mirarchi,Maryam Gholamzadehmir,Alberto Pavan
出处
期刊:Engineering, Construction and Architectural Management
[Emerald (MCB UP)]
日期:2024-07-12
标识
DOI:10.1108/ecam-04-2024-0435
摘要
Purpose The paper clarifies research gaps and future directions in building information modeling (BIM) research by analyzing research trends and publication patterns. It aims to (1) systematically categorize the vast array of BIM literature into coherent main topics, (2) identify the most and least explored areas and (3) propose directions for future research based on identified research gaps. Design/methodology/approach This study uses the Latent Dirichlet Allocation (LDA) method to manage large datasets and uncover hidden patterns in academic journals and conference articles. To clarify the scholarly focus, the main topics in BIM research are categorized into three groups: (1) primary areas of focus, (2) moderately explored topics and (3) least investigated topics. Findings The findings revealed 10 main topics (MTs) and 57 subtopics (STs), identifying key areas such as project design and management (20%), innovative construction technology (14%) and sustainable construction/life cycle management (14%). Conversely, it also highlighted underexplored areas like Facility/safety management and urban data development, suitable for future research. Research limitations/implications While this work provides a structured overview of the BIM domain, it reveals opportunities for further exploring the complexity of the interrelation among interdisciplinary topics. Originality/value The novelty of this study is its extensive scope, analyzing over fifteen thousand BIM articles from 2013 to 2023, which significantly expands the literature scale previously reviewed. This comprehensive approach maps BIM research trends and gaps and also shows the hierarchical trend line of publications in each main topic, setting a benchmark for future studies.
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