Establishment of Key Performance Indicators for Green Building Operations Monitoring—An Application to China Case Study

Abstract

Released green building evaluation standards for operation stage include a huge number of indicators, which are very comprehensive and systematic. However, the indicators of these standards are very complicated and a large amount of time and manpower are consumed for their evaluation. To evaluate the operational performance of green buildings more practically and efficiently, some studies collect the operational data for part of the indicators (mainly focusing on building energy performance, indoor environmental quality or occupant satisfaction), which are too rough to evaluate the performance of green building. This paper proposed a total of 27 key performance indicators (KPIs) for green building operations monitoring. The number of proposed indicators is much fewer than the evaluation standards, as well as suitable for long-term monitoring, which can dramatically reduce evaluation time and cost. On the other hand, the indicators involving Outdoor environmental quality, Indoor environmental quality, HVAC system, P&D system, Renewable energy system, Total resource consumption and User behavior, which are more comprehensive and systematic than the conventional monitoring studies for operational performance of green building. Firstly, an indicators library for operations monitoring of green building was established based on relevant standards and literature review in this field. Secondly, “SMART” principle and Delphi method were adopted to select the key performance indicators for green building operations monitoring. Different background experts regarding green building industry were chosen to screen the most relevant, accessible and measurable indicators. Subsequently, two projects in China were selected for case study of key performance indicators proposed in this paper for green building operations monitoring to validate the feasibility and advancement.

Strategy of Maintainable Renewal of Assembled Residential Buildings Based on PSO-ELM

“…e authors of [5] used artificial neural network algorithms to establish a dynamic decision system to analyze the factors affecting the development of industrialized housing and found that high cost is the most important influencing factor limiting its development. e authors of [6] compared the costs of four different structural systems of industrialized housing in the UK and concluded that efficiency learning, technological innovation, the establishment of an efficient on-site construction organization mode, and strengthening the production management of prefabricated components can effectively reduce the costs [7]. e authors of [8] established a database of 179 prefabricated assembled houses, and through a detailed case study of five residential communities, the results showed that standardized design can improve the design efficiency and the production scale of prefabricated components.…”

“…With the expansion of the construction scale of assembled buildings, the construction activities of assembled buildings are distributed in parallel to their component production, logistics and transportation, on-site assembly, and other operation spaces, which are very prone to construction safety accidents at this stage with insu cient reserves of safety technology and management measures [5]. Facing the increasingly severe construction safety management situation, how to nd e ective technologies and strategies to deal with safety accidents in the construction of assembled buildings with limited investment in safety resources is a key issue that needs to be solved [6].…”

Investigating Smart City Development Based on Green Buildings, Electrical Vehicles and Feasible Indicators

“…The most important indicators regarding GB and EVs that affect energy sustainability in smart cities are presented in Table 4, which shows the indicators and sub-indicators for GBs and EVs [82][83][84][85][86][87][88][89][90][91][92][93][94]. The implementation of these indicators presented leads to the improvement of the residential life quality of the smart cities in the future.…”

Reducing data requirements when selecting key performance indicators for supply chain management: The case of a multinational automotive component manufacturer

“…in reducing cost. The papers that considered reducing the number of KPIs were predominantly focused on Multi-Criteria Decision-Making approaches, such as Analytic Hierarchy Process (and its variants) (Carlucci, 2010;Podgórski, 2015;Kumar and Garg, 2017), Delphi (Li et al, 2020) and ELECTRE (Gonçalves et al, 2015). Some contributions based on linear programming (Liebetruth and Otto, 2006) were found.…”