Professional Barriers in Energy Efficiency Retrofits—A Solution Based on Information Flow Modeling - Xilong Liao; Chun Wang; Baiyi Li; Baizhan Li; Chenqiu Du (Buildings)
The challenge of high energy consumption and carbon emissions within China’s construction industry has become increasingly urgent, as over 40% of buildings are still non-energy efficient. The multifaceted nature of systems involved in building retrofits results in a complex project, with barriers in both retrofit design and construction becoming increasingly evident. This research comprehensively assesses the common barriers in building retrofits and investigates the potential for integrating energy-efficient retrofits with information flow modeling from an interdisciplinary perspective. In order to pinpoint the main barriers hindering building retrofits, this study employs the bibliometric software VOSviewer. The analysis uncovers that the primary obstacles to energy-saving renovations are categorized into technical, economic, environmental, and other barriers. These barriers are characterized by a high degree of specialization, the inadequate integration of information, and limited collaboration among stakeholders. Subsequently, a qualitative literature review was conducted following the PRISMA methodology, which screened 40 key sources. The following conclusions were drawn: (1) The design of energy-saving renovation processes is impeded by the limited professional perspectives within the construction industry, which restricts the practical applicability; (2) Decision making for energy-saving renovations encounters notable professional barriers and suffers from inadequate information integration; (3) There is a lack of clarity regarding information needs during the implementation phase, and no effective platform exists for information coordination; (4) Risk analyses in complex energy-saving renovations largely depend on expert interviews, lacking robust scientific tools. These findings highlight that knowledge gaps and information asymmetry are the central challenges. To tackle these issues, this paper suggests the implementation of an information flow model that integrates the IDEF0 and DSM for building energy-saving retrofit projects. The IDEF0 model can clearly describe the interaction relationship of all expert information through functional decomposition, while the DSM can show the dependency relationship and information flow path among specialties through the matrix structure. This model is anticipated to enhance professional information integration and collaboration. It is proposed that improved information integration and collaboration under this framework will significantly promote the advancement of professional generative AI.