An Integrated Methodology Using Extended Swara and Dea for the Performance Analysis of Wastewater Treatment Plants: Turkey Case - Ayyildiz, Ertugrul; Yildiz, Aslihan; Taskin Gumus, Alev; Ozkan, Coskun (SPRINGER, 2021)
Public and private companies make significant water infrastructure investments to meet increasing water demand. In this context, investments in wastewater treatment plants (WWTPs), which play an important role in recycling of used water, are also increasing. This study investigates determination of the efficiency scores of WWTPs considering each metropolitan municipality as a decision-making unit (DMU). In this study, a two-step methodology is established to determine efficiency scores of WWTPs. In the first step, the input and output parameters are searched by a literature review for the performance evaluation, and candidate parameters are determined. Then, to determine the most appropriate and related parameters, the importance weights of all candidate inputs and outputs are computed using the extended stepwise weight assessment ratio analysis (SWARA) method. Next, the inputs and outputs are chosen according to their importance weights. In the second step, efficiency scores of WWTPs are calculated using output-oriented data envelopment analysis (DEA) models. Based on the expert opinions, the parameters used as input variables are as follows: Daily Wastewater Amount per Person Discharged in Municipalities, WWTP Capacity, and Number of WWTPs; and the parameters used as output variables are as follows; Amount of Wastewater Treated in WWTPs and Municipal Population Served by WWTPs. The results are presented and discussed by sensitivity analysis. Results show that 14 metropolitan municipalities have total efficiency, 19 metropolitan municipalities have technical efficiency, and 21 metropolitan municipalities have scale efficiency.
Keywords: Wastewater treatment plant; Extended SWARA; Data envelopment analysis; Performance evaluation; DECISION-MAKING MODEL; NEURO-FUZZY SYSTEM; ECO-EFFICIENCY; SUPPLIER SELECTION; ENERGY EFFICIENCY; CRITERIA; SUSTAINABILITY; ALGORITHMS; FRAMEWORK; Environmental Sciences & Ecology