Establishment of Performance Indicators for Malaysian Water Utilities With the Presence of Undesirable Output

Abstract

In maintaining the efficiency of water supply services, it is crucial to monitor the performance of water utilities in a country. One of widely used tools to evaluate the performance of water supply services is Data Envelopment Analysis (DEA). However, prior DEA-related approaches for water sector performance have ignored the internal structure of water supply service operations; i.e. the water treatment process and water distribution process. Another neglected aspect is the presence of Non-Revenue Water (NRW) to be considered as an undesirable output in the water distribution process. This is in line with the goal to reduce the NRW level in water supply systems. Hence, this paper proposed a two-stage Network DEA with the presence of undesirable output to evaluate the performance of Malaysian water utilities. This proposed method advances the existing DEA-based approach on water utility performance measurement, where not only the potential reduced level of NRW can be determined, but, a new performance benchmarking indicator regarding the concept of efficiency and effectiveness of the water supply industry in Malaysia can be established from the same model.

Assessing China’s Use Efficiency of Water Resources from the Resampling Super Data Envelopment Analysis Approach

“…The use and management of water resources are complicated issues because it is important and necessary natural resources and economic resources that affects structural changes in the ecology and environment Conflicts may also arise between environmental sustainability and economic development. Therefore, previous research on water resources' use efficiency focused on improving equipment and technology such as: 1) wastewater treatment's technical advancement [6][7][8]; and utilizing economic and statistical methods to assess water resources' use efficiency through; 2) traditional statistical methods [9][10][11]; 3) data envelopment analysis (DEA) [12][13][14][15][16][17][18][19][20]; and 4) undesirable outputs [21,22]. A brief description runs as follows.…”

“…Gungor-Demirci et al [18] applied two-stage DEA to assess the performances of individual districts of a California water utility for the year 2014, and proposed that DEA offers a useful way to identify the strengths and weaknesses of individual districts and to guide subsequent managerial improvement initiatives. Kamarudin and Ismail [19] evaluated the performance of water supply services in Malaysia with the DEA approach. Liao et al [20] used DEA and the Malmquist index to evaluate the utilization efficiency of water resources in 12 western provinces of China in 1999-2008, taking GDP, fixed assets, annual water supply and the population's water usage as inputs and outputs.…”

Measuring the Operational Efficiency and the Water Resources Management Efficiency for Industrial Parks: Empirical Study of Industrial Parks in Taiwan

“…In the DEA-BCC model (Banker, Charnes and Cooper, the three scholars who proposed this model, named it after the first letter of their surnames) [89], the overall efficiency value of technical efficiency (TE) is calculated as the product of scale efficiency (SE) and pure technical efficiency (PTE) [89]. DEA has been applied in many studies to assess the efficiency of water use [83][84][85][90][91][92][93][94][95]. However, these studies are limited to the operational efficiency values, and few studies have integrated the analysis of non-operational efficiency values.…”

Non-revenue water reduction strategies: a systematic review

“…4.4 Water losses 4.4.1 Develop management processes. Appropriate WDN management can also prove an effective means of tackling NRW issues (Bhagat et al, 2019;Hussein et al, 2017;Kamarudin and Ismail, 2016;Yi et al, 2017), with NRW an indicator of WDN performance (Kamarudin and Ismail, 2016). There are many aspects to WDN management: (1) asset management (Mugisha, 2013); (2) dynamic modeling, which is based on a method that selects the best management actions (Karimlou et al, 2020); (3) operation and maintenance, which is applied to boreholes and hand pumps within a WDN (Silombela et al, 2018); (4) record keeping (Silombela et al, 2018); (5) programs such as GIS and management information system tools, which help in decision making and WDN management (Ndirangu et al, 2013); ( 6) budget management and the prioritization of NRW activities (Gambe, 2015); ( 7) the shift from traditional top-down approaches toward bottom-up approaches in certain WDNs, which emphasizes the involvement of multiple-stakeholders (Lai et al, 2017); (8) organizations that control the activity of utilities (Gonz alez-G omez et al, 2011).…”