Table 2.

Advantages and disadvantages of the IDA and SDA methods.

Method	Application Condition	Advantages	Disadvantages
Index decomposition analysis (IDA)	Usually used to examine the driving factors of energy/energy-related emissions changes in a specific sector (e.g., the transport sector) [21,24,25].	(1) High flexibility in formulation and application [21]. (2) A large number of factors can be easily handled with the Logarithmic Mean Divisia Index (LMDI) method [21]. (3) Relatively low data requirement. Both data with high or low degree of sector disaggregation can be used [21].	(1) In SDA terminology, cannot deal with indirect effect [21]. (2) The application is limited in one-stage decomposition models [21].
Structural decomposition analysis (SDA)	Often employed by those comfortable with using input–output analysis [21,25].Primarily used to analyse the energy/emissions changes in the whole economy [21,24,25].	(1) Both direct and indirect effect is captured [21]. (2) Can include two-stage decomposition models [21].	(1) Relatively high data requirement [22]. (2) The application relies on the availability of input-output tables, limiting the flexibility [21].