Interpretive Structural Modeling based factor analysis on the implementation of Emission Trading System in the Chinese building sector

Abstract

The Emission Trading System has been promoted as a tool for providing financial and cost-effective incentives to carbon emitters to apply emission reduction measures. The mechanism of Emission Trading System has been applied in many energy-intensive industries such as electric power industry. However, it appears that Emission Trading System finds limited application in building sector due to the unique characteristics of buildings. This study presents an identification and analysis on the factors affecting the implementation of Emission Trading System in the building sector within the context of China. Research data are collected from semi-structured interviews with a group of carefully selected experts. As a result, fifteen representative factors have been identified, and discussions on their representativeness have been conducted. The intricate interrelationships between the identified factors have been examined based on a hierarchy structure established by using the Interpretive Structural Modeling method. Furthermore, these factors have been classified into four categories: autonomous factors, dependent factors, linkage factors, and driving factors, which is based on the calculation of the factors' driving/dependence power by applying the Matrice d'Impacts croises-multipication appliqué a classement (MICMAC) technique. This classification provides a different profile between individual factors from that by traditional study where the relative importance is generally given between factors. The findings on these factors provide valuable references for helping policy designers and practitioners adopt effective policies and measures to promote the development of ETS in the Chinese building sector.