Prioritizing Asset Information Requirements for Data-Driven Decision Making: A Fuzzy AHP Approach of Ethiopian Public University Buildings Cases

Abstract

Abstract Digitization of a building infrastructure requires the creation of big data that needs to be modelled and integrated into digital platforms from initial/design phase to operation & maintenance phases to serve as a single source of reliable information. This insufficient integration and/or transition of building information modelling (BIM) into asset management has posed challenges in the operation & maintenance performance. Thus, it is compulsory for owners and end-users to invest in creating digital data for built assets in taking advantage of incorporating building information modelling (BIM) into operational functions. Nevertheless, creating a BIM-enabled asset management and development of a big data repository is costly, time-consuming and requires expertise that may not be achievable without specific targets to make data-driven decisions. The aim of this study is to prioritize the information requirements using building improvement/adaptation, maintenance/ preservation and deconstruction/disassembling as strategic decisions in built asset management. The data for the pairwise comparisons among criteria, strategic decisions, and information requirements was collected from 11 expert’s using AHP pairwise questionnaire. The collected data was transformed into triangular fuzzy logic to overcome the lack of precision and uncertainties of human thought process. A fuzzy-AHP approach is utilized to analyze the collected data. The degree of importance of all forms of information requirement is determined in relation to the strategic decisions. The results showed that all forms of information requirements varies with the type of strategic decision. The results of the present study can help built asset owners and their representatives to define information need based on the decision type using criteria for efficient built asset management.