基于ISM的公共建筑大数据质量影响因素研究  

Research on Influencing Factors of Big Data Quality of Public Buildings Based on Interpretive Structural Modeling

作　　者：宋朋波 刘伊生[1] 郑旺 SONG Pengbo;LIU Yisheng;ZHENG Wang(School of Economics and Management,Beijing Jiaotong University,Beijing 100044,China)

机构地区：[1]北京交通大学经济管理学院,北京100044

出　　处：《河南科学》2021年第6期1025-1032,共8页Henan Science

基　　金：国家自然科学基金面上项目(7187010712)。

摘　　要：基于文献分析以及专家咨询,从内部、环境、人员3个角度对影响公共建筑大数据质量的因素进行全面分析和梳理,挖掘出20个影响公共建筑大数据质量的系统要素,并运用解释结构模型的方法,建立了公共建筑大数据质量影响因素的整体框架模型.结果表明,影响公共建筑大数据质量的系统要素具有丰富的层次性,绝大多数要素都是通过多路径对公共建筑大数据质量产生影响的,其中管理和统计人员的综合素质对数据质量的干预性最强,是影响公共建筑大数据质量的根本因素,而数据搜集录入成本、统计渠道的多样性、数据库的维护和数据技术改进在提高数据质量过程中发挥着基础作用.Based on the literature analysis and expert consultation,the paper comprehensively analyzed and sorted out the influence factors from the perspectives of internal,environmental and personnel,and mined 20 systematic factors that affect the quality of big data of public buildings.By using interpretation structure model(ISM),an overall framework model about influence factors of big data quality of public buildings was established.Some conclusions have been arrived as follows.Firstly,the system factors that affect the quality of big data of public buildings have rich levels,and most of them affect the quality of big data of public buildings through multiple paths.Secondly,the comprehensive quality of managers and statistician have the strongest influence on data quality,which is the fundamental factor to improve the big data quality of public buildings.At last,the cost of data collection and input,diversity of statistical channels,database maintenance and data technology improvement play a fundamental role in the process of improving data quality.

关 键 词：公共建筑 碳交易 数据质量 解释结构模型 影响因素 

分 类 号：TU87[建筑科学]