Additive decomposition in two-stage DEA: An alternative approach

Typically, a two-stage production process assumes that the first stage transforms external inputs to a number of intermediate measures, which then are used as inputs to the second stage that produces the final outputs. The three fundamental approaches to efficiency assessment in the context of DEA (two-stage DEA) are the simple (or independent), the multiplicative and the additive. The simple approach does not assume any relationship between the two stages and estimates the overall efficiency and the individual efficiencies for the two stages independently with typical DEA models. The other two approaches assume a series relationship between the two stages and differ in the way they conceptualize the decomposition of the overall efficiency to the efficiencies of the individual stages. This paper presents an alternative approach to additive efficiency decomposition in two-stage DEA. We show that when using the intermediate measures as pivot, it is possible to aggregate the efficiency assessment models of the two individual stages in a single linear program. We test our models with data sets taken from previous studies and we compare the results with those reported in the literature

Additive decomposition in two-stage DEA: An alternative approach

Typically, a two-stage production process assumes that the first stage transforms external inputs to a number of intermediate measures, which then are used as inputs to the second stage that produces the final outputs. The three fundamental approaches to efficiency assessment in the context of DEA (two-stage DEA) are the simple (or independent), the multiplicative and the additive. The simple approach does not assume any relationship between the two stages and estimates the overall efficiency and the individual efficiencies for the two stages independently with typical DEA models. The other two approaches assume a series relationship between the two stages and differ in the way they conceptualize the decomposition of the overall efficiency to the efficiencies of the individual stages. This paper presents an alternative approach to additive efficiency decomposition in two-stage DEA. We show that when using the intermediate measures as pivot, it is possible to aggregate the efficiency assessment models of the two individual stages in a single linear program. We test our models with data sets taken from previous studies and we compare the results with those reported in the literature

Additive decomposition in two-stage DEA: An alternative approach

Typically, a two-stage production process assumes that the first stage transforms external inputs to a number of intermediate measures, which then are used as inputs to the second stage that produces the final outputs. The three fundamental approaches to efficiency assessment in the context of DEA (two-stage DEA) are the simple (or independent), the multiplicative and the additive. The simple approach does not assume any relationship between the two stages and estimates the overall efficiency and the individual efficiencies for the two stages independently with typical DEA models. The other two approaches assume a series relationship between the two stages and differ in the way they conceptualize the decomposition of the overall efficiency to the efficiencies of the individual stages. This paper presents an alternative approach to additive efficiency decomposition in two-stage DEA. We show that when using the intermediate measures as pivot, it is possible to aggregate the efficiency assessment models of the two individual stages in a single linear program. We test our models with data sets taken from previous studies and we compare the results with those reported in the literature