Abstract

The aim of this paper is to develop a methodological tool for comprehensive evaluation of sustainability of water supply and sanitation services (WSSs) considering all quantitative and qualitative effective factors using the analytic hierarchy process. The proposed method has a significant advantage that determines which aspects have more priority and which ones are less important; hence, it gives a very good guideline for planning and implementation of a country's projects for sustainable development in WSSs. Additionally, the application of the proposed method is shown for Algeria as a case study. six dimensions, 12 criteria and 50 indicators were defined as three different levels of hierarchy for this purpose. Moreover, the matrices of pairwise comparisons were obtained by judgments of 12 experts in different involved fields including policy makers, managers and scientists. According to the results, the most important dimensions were economic (38.3%) and technical (26.1%) aspects. Furthermore, the financial autonomy (18.7%) and technical performance (18.4%) had the highest and transparency (2%) and organization (2.8%) had the lowest weights among all criteria. In addition, indicators with a high overall weight are: operation and maintenance cost, grand balanced budget, reliability, small budget balance, opportunity cost and state subsidy rates for investments.

INTRODUCTION

Water supply and sanitation services (WSSs) provide safe drinking water and also proper access to the sewage system for humans. WSSs not only have strong impacts on the people's life and health as well as the environment, but also have an important role in regional planning and participate in promoting social cohesion within a nation. Over time, these services have been increasingly faced with many challenges such as the increasing number of customers and their expectations, increasing demand for water resources, regulatory requirements for the quality of water and security of public health, environmental and financial issues, and so on. Additionally, there have been serious challenges to achieve the objectives of sustainability, because of institutional, financial and technical aspects on one hand (Haider et al. 2016) and their social and environmental impacts on the other hand.

The concept of sustainability is always associated with the concept of sustainable development (SD). According to the literature, there are several definitions for the SD concept, but the most usual ones are:

  • The Brundtland Report of the United Nations World Commission on Environment and Development (WCED) defined SD as ‘development that meets the needs of the present without compromising the ability of future generations to meet their needs and aspirations’ (Brundtland 1987).

  • The International Union for Conservation of Nature (IUCN) defines SD as ‘development that improves the quality of human life by respecting the carrying capacity of supporting ecosystems’ (The World Conservation Union/UNEP/WWF 2013).

The objective of this article is to develop a methodological tool for evaluation and measurement of sustainability considering all affecting quantitative and qualitative indicators for WSSs using the analytic hierarchy process (AHP). In comparison to the previous, presented methods for evaluation of SD in WSSs, the proposed approach is very easy to understand and use and also includes more criteria and indicators. Moreover, this study was conducted by the collaboration of different decision makers, involving scientists, policy makers, managers of resources and local units and so forth, and as such gives a comprehensive point of view. Additionally, the application of the method in Algeria as a case study was investigated.

Since 2001, the water supply service in Algeria has been managed by the Algerian Water Company (ADE) and the sanitation service has been managed by the National Office for Sanitation (ONA). The managers of these two services are faced with several challenges to put the government's policy for sustainable management into practice because of the mentioned multidimensional nature of SD (Hamchaoui et al. 2015). The proposed method has the significant advantage that it determines which aspects have more priority and which ones are less important; hence, it gives a very good guideline to planning and implementation of a country's projects for SD in WSSs.

The article is organized as follows. Following this brief introduction, the next section presents the multi-criteria analysis (MCA) and AHP approaches. The subsequent section describes the proposed method, while the final two sections are devoted to the presentation of ‘Results and discussion’ and a ‘Conclusion’, respectively.

LITERATURE REVIEW

According to the scientific literature, there are many methods, approaches and tools that have been developed to assess the sustainability of water resources management. The most widely applied approaches to water resources management are: cost-benefit analysis (CBA), life cycle assessment (LCA), integrated assessment (AI), triple bottom line (TBL), and MCA. Each of these approaches can be applied in different areas. CBA is a purely economic method that deals with monetary elements; it is a process of evaluating a system by comparing its costs to benefits (Pearce et al. 2006). LCA is a specific approach used to assess the environmental impact associated with a service or product throughout its life cycle; it does not include economic factors and social problems (Ness et al. 2007). TBL is a sustainability assessment approach based on a combination of three dimensions: economic viability, environmental sustainability, and social equity (Christen et al. 2006). AI is an approach applied to integrated river basin management and water resource allocation problems (Croke et al. 2007). The MCA is generally used as a decision-support tool, and may consider multiple criteria (Hajkowicz & Collins 2007). It is able to solve decision-making problems in water and sanitation that are generally complex in nature with multiple objectives (Hamouda et al. 2009). The MCA considers the various quantitative and qualitative dimensions that are possibly contradictory (Garfì et al. 2011), unlike the CBA and LCA methods, which take into account a single dimension, and the TBL and IA methods, which use only three dimensions.

Many researchers have found that the three dimensions of TBL are not enough to assess the sustainability of water resource management. So, they have added other dimensions, such as technical, governance, etc., (Hellström et al. 2000; Ashley et al. 2003; van Leeuwen et al. 2012; Marques et al. 2015). The dimensions considered are listed in Table 1.

Table 1

Various dimensions of sustainability considered in the literature

DimensionsReferences
Economic, environmental and social da Cruz & Marques (2013)  
Economic, environmental, social and technical Ashley et al. (2003)  
Economic, environmental, social, technical, and cultural Balkema et al. (2002)  
Economic, environmental, social, health and hygiene, cultural, functional and technical Hellström et al. (2000)  
Economic, environmental, social and institutional DiSano (2002)  
Economic, environmental, social, technical and governance Marques et al. (2015)  
DimensionsReferences
Economic, environmental and social da Cruz & Marques (2013)  
Economic, environmental, social and technical Ashley et al. (2003)  
Economic, environmental, social, technical, and cultural Balkema et al. (2002)  
Economic, environmental, social, health and hygiene, cultural, functional and technical Hellström et al. (2000)  
Economic, environmental, social and institutional DiSano (2002)  
Economic, environmental, social, technical and governance Marques et al. (2015)  

Multi-criteria analysis

MCA, which is able to consider various criteria simultaneously, has been used in diverse scientific fields for different purposes such as optimization and decision making (Sohani et al. 2017). There were some such studies that used MCA in order to evaluate SD in the water sector (Ruiz-Villaverde et al. 2013; Han et al. 2015; Marques et al. 2015; Borrego-Marín & Riesgo 2016). In the field of water resources management, the MCA method has a strong capacity to find well-structured, coherent and objective solutions to complex decision problems (Lai et al. 2008). According to Hajkowicz & Collins (2007), the most widely used methods of MCA in this area are: (i) AHP, (ii) Elimination and Choice Translating Reality (ELECTRE), (iii) Preference Ranking and Organization Method for Enrichment Evaluation (PROMETHEE), (iv) Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), (v) Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) and (vi) Fuzzy Set Analysis.

In this study, the applied approach is AHP, developed by Saaty (Saaty 1980), and is widely applied in problems involving multiple criteria, often contradictory (Georgiou et al. 2015).

Analytic hierarchy process

The AHP method was created to help to solve complex decision problems (Anagnostopoulos & Vavatsikos 2006). It helps to decompose a complex decision making problem with associated different criteria and indicators in a hierarchical system in which complex decisions are reduced to a series of pairwise comparisons between elements of the decision hierarchy (Balyani et al. 2015). The criteria considered are theme-based, on which one judges on the object of the evaluation. It is a representation derived from one or more indicators. An indicator is information that qualifies or quantifies the satisfaction of the criteria.

AHP is one of the methods of MCA. The AHP approach is applied in several areas and has been widely used in water management, for example, water resource management, water loss, irrigation, pollution; however, research is limited to addressing the sustainability of WSSs by applying AHP (Hamchaoui et al. 2015; Marques et al. 2015).

METHODOLOGY

AHP is one of the multi-criteria decision making methods in which the weights of the evaluation elements are determined by pairwise comparisons, which are made by an expert's judgments. This method is very simple and easy to use. In order to obtain a realistic result, experts from all involved related fields including scientists, managers and policy makers should participate in the process of judgments.

According to the scientific literature, the methodology that integrates the techniques of the MCA method to define and choose the best options will be initiated by defining the overall objective and then by developing the hierarchical structure by identifying a set of elements (dimensions, criteria and indicators). Then, pairwise comparisons will be made between the decision elements, checking and improving the consistency of preferences, drawing the relative weights of the elements for each level and obtaining the overall assessment of the options by aggregating the weighted decision elements (Zyoud et al. 2016). The proposed methodology is illustrated in Figure 1. More details will be explained in the following sections.

Figure 1

The process flowchart of the proposed method.

Figure 1

The process flowchart of the proposed method.

From Figure 1, the first phase involves structuring the decision problem in a hierarchical structure by identifying the elements (dimensions, criteria and indicators) appropriate to our goal, which is the sustainability of WSSs.

In the second phase, for all the levels, we will put in place a matrix of comparison in pairs to evaluate the importance of each of them. Then, the global weights are calculated.

Pairwise comparisons were performed for each level of the hierarchy (level 1 = dimensions, level 2 criteria = ‘Ci’ and level 3 = indicators ‘Ii’). For each comparison, the experts determined the relative importance using pairwise comparisons by the values suggested by Saaty (Saaty 1980), whose meanings are indicated in Table 2. The comparison leads to obtaining the decision matrix (Equation (1)).  
formula
(1)
Table 2

Saaty numerical scale for pairwise comparisons in AHP

Intensity of importanceDefinition
Equal importance of two elements 
Weak preference (element i over element j
Strong preference (i over j
Very strong preference (i over j
Absolute preference (i over j
2, 4, 6, 8 Intermediate values between two judgments (i over j
1/3 Weak preference (j over i
1/5 Strong preference (j over i
1/7 Very strong preference (j over i
1/9 Absolute preference (j over i
1/2, 1/4, 1/6, 1/8 Intermediate values between two judgments (j over i
Intensity of importanceDefinition
Equal importance of two elements 
Weak preference (element i over element j
Strong preference (i over j
Very strong preference (i over j
Absolute preference (i over j
2, 4, 6, 8 Intermediate values between two judgments (i over j
1/3 Weak preference (j over i
1/5 Strong preference (j over i
1/7 Very strong preference (j over i
1/9 Absolute preference (j over i
1/2, 1/4, 1/6, 1/8 Intermediate values between two judgments (j over i

Source:Saaty (1980).

A: is the decision matrix, aij (individual priority) are comparisons between elements i and j for all i, j ∈ {1, 2,…, n}.

In the previous step, we constructed a decision matrix for each element. The weight of each of the dimensions, criteria and indicators is calculated by applying the following steps:

  • Calculate the sum per column.

  • Divide each of the values in the column by the sum of the values.

  • The weight is given by calculating the average of each of the rows.

Then, we must check the consistency of the result. At this stage, we have the ‘weight’ of each of the elements. The AHP method then proposes validating the reliability of the result by calculating the consistency ratio (CR), which will enable us to detect defects in our calculation and evaluation. The CR is calculated by Equation (2).  
formula
(2)
  • RI: the Random Consistency Index, (RI) can be determined by Table 3 (Saaty 1980).

  • CI: the Consistency Index, which is calculated by Equation (3).  
    formula
    (3)
  • n: the number of rows or columns of the square matrix of judgment and RI.

  • λmax: the principal eigenvalue.

Table 3

Random index (RI)

n123456789101112131415
RI 0.52 0.89 1.11 1.25 1.35 1.40 1.45 1.49 1.52 1.54 1.56 1.58 1.59 
n123456789101112131415
RI 0.52 0.89 1.11 1.25 1.35 1.40 1.45 1.49 1.52 1.54 1.56 1.58 1.59 

Source: adapted from Saaty (2008).

If CR ≤ 0.1, the matrix is considered sufficiently coherent; otherwise, the assessments may require some revision to reduce inconsistencies (Saaty 1980). In the case of comparison matrices for Algeria, at first some CR values were greater than 0.1; therefore, experts were asked to revise their judgments in order to achieve consistent results. The CR of each pairwise comparison matrix is indicated at the footnote for it. As can be seen, the values of CR for all elements of them are less than 0.1. Once the weights of the elements per level are calculated, the final weight is computed by simply multiplying the weights of the lowest level (the indicators) by the weights of the higher levels (the corresponding criteria and dimensions).

Finally, phase 3 aims to evaluate and analyze the results. All that remains is to evaluate our different results by choosing the best indicators for the evaluation of the sustainability of the WSSs, where the results with the greatest final weights are identified.

RESULTS AND DISCUSSION

The selection of dimensions, criteria and indicators

The dimensions, criteria and indicators for assessing the sustainability of WSSs in Algeria are presented in Table 4. A questionnaire was given to each expert and they determined the dimensions, criteria and indicators on the basis of their knowledge, experience and background in the management of WSSs.

Table 4

Dimensions, criteria and indicators which were considered for Algeria

DimensionsCriteriaIndicators
Economic (D1) Total cost recovery (C 1.1Cost of operation and maintenance (O&M) (i 1.1.1
Cost of capital (i 1.1.2
Opportunity cost (i 1.1.3
Transaction costs (i 1.1.4
Environmental cost (i 1.1.5
Financial autonomy (C 1.2Grand balanced budget (i 1.2.1
Small budget balance (i 1.2.2
State subsidy rates for investments (i 1.2.3
Subsidy rate for the operating account (i 1.2.4
Environmental (D2) Environmental impact (C 2.1Protection against pollution (i 2.1.1
Pollution control (i 2.1.2
Minimize overexploitation of groundwater (i 2.1.3
Protection of water bodies (i 2.1.4
Use of resources (C 2.2Efficient use of water (i 2.2.1
Fight against waste (i 2.2.2
Energy consumption (i 2.2.3
Use of materials (i 2.2.4
Social (D3) Accessibility to services (C 3.1Rate of access to drinking water services (i 3.1.1
Rate of access to sanitation services (i 3.1.2
Service quality of WSS (i 3.1.3
Distributed water quality (i 3.1.4
Claim rates (i 3.1.5
Affordability (C 3.2Affordable tariff of drinking water (i 3.2.1
Affordable tariff of sanitation (i 3.2.2
Social pricing (i 3.2.3
Willingness to pay (i 3.2.4
Technical (D4) Technical performance (C 4.1Detection and repair of leaks (i 4.1.1
Reliability (i 4.1.2
Failures (i 4.1.3
Network yields (i 4.1.4
Modernization (C 4.2Use of new technologies (i 4.2.1
Employee training (i 4.2.2
Remote monitoring and remote management (i 4.2.3
Rehabilitation of WSS systems (i 4.2.4
Governance (D5) Transparency (C 5.1Information to users (i 5.1.1
Public participation and consultation (i 5.1.2
Existence of information and documentation (i 5.1.3
Access to information and data (i 5.1.4
Policy and planning WSS services (C 5.2Stability of the WSS services policy (i 5.2.1
Strategy and alignment with urban planning (i 5.2.2
The business planning (i 5.2.3
Water resources planning (i 5.2.4
Institutional (D6) Regulations (C 6.1Update of the water code (i 6.1.1
Updating the National Water Plan (PNE) (i 6.1.2
Reform of tariff policy (i 6.1.3
Application of international standards for the quality of drinking water and purified water (i 6.1.4
Organization (C 6.2Application of a new organization for water services (ADE) (i 6.2.1
Application of a new organization for sanitation services (ONA) (i 6.2.2
The union of the two institutions, ADE and ONA, in one public company (i 6.2.3
The use of delegated management in major cities (i 6.2.4
DimensionsCriteriaIndicators
Economic (D1) Total cost recovery (C 1.1Cost of operation and maintenance (O&M) (i 1.1.1
Cost of capital (i 1.1.2
Opportunity cost (i 1.1.3
Transaction costs (i 1.1.4
Environmental cost (i 1.1.5
Financial autonomy (C 1.2Grand balanced budget (i 1.2.1
Small budget balance (i 1.2.2
State subsidy rates for investments (i 1.2.3
Subsidy rate for the operating account (i 1.2.4
Environmental (D2) Environmental impact (C 2.1Protection against pollution (i 2.1.1
Pollution control (i 2.1.2
Minimize overexploitation of groundwater (i 2.1.3
Protection of water bodies (i 2.1.4
Use of resources (C 2.2Efficient use of water (i 2.2.1
Fight against waste (i 2.2.2
Energy consumption (i 2.2.3
Use of materials (i 2.2.4
Social (D3) Accessibility to services (C 3.1Rate of access to drinking water services (i 3.1.1
Rate of access to sanitation services (i 3.1.2
Service quality of WSS (i 3.1.3
Distributed water quality (i 3.1.4
Claim rates (i 3.1.5
Affordability (C 3.2Affordable tariff of drinking water (i 3.2.1
Affordable tariff of sanitation (i 3.2.2
Social pricing (i 3.2.3
Willingness to pay (i 3.2.4
Technical (D4) Technical performance (C 4.1Detection and repair of leaks (i 4.1.1
Reliability (i 4.1.2
Failures (i 4.1.3
Network yields (i 4.1.4
Modernization (C 4.2Use of new technologies (i 4.2.1
Employee training (i 4.2.2
Remote monitoring and remote management (i 4.2.3
Rehabilitation of WSS systems (i 4.2.4
Governance (D5) Transparency (C 5.1Information to users (i 5.1.1
Public participation and consultation (i 5.1.2
Existence of information and documentation (i 5.1.3
Access to information and data (i 5.1.4
Policy and planning WSS services (C 5.2Stability of the WSS services policy (i 5.2.1
Strategy and alignment with urban planning (i 5.2.2
The business planning (i 5.2.3
Water resources planning (i 5.2.4
Institutional (D6) Regulations (C 6.1Update of the water code (i 6.1.1
Updating the National Water Plan (PNE) (i 6.1.2
Reform of tariff policy (i 6.1.3
Application of international standards for the quality of drinking water and purified water (i 6.1.4
Organization (C 6.2Application of a new organization for water services (ADE) (i 6.2.1
Application of a new organization for sanitation services (ONA) (i 6.2.2
The union of the two institutions, ADE and ONA, in one public company (i 6.2.3
The use of delegated management in major cities (i 6.2.4

The pairwise comparisons

For a pairwise comparison of each dimension, criterion and indicator, a panel of 12 experts in the field of water management in Algeria was consulted. These experts were chosen on the basis of their experience and scientific contribution. In addition, the 12 experts were selected to cover different profiles:

  • Four Decision-makers (one senior official of the Ministry of Water Resources + one Director of Water Resources + two Heads of the Water Resources Department).

  • Four Managers of WSSs (one Director ADE + one Director ONA + two Heads of services).

  • Four Scientists (two professors + two teacher researchers).

Each expert makes his judgment using the Saaty scale (Table 2) and delivers his own matrix of comparison in pairs. The decision matrices for dimensions, criteria and indicators are then calculated by calculating the average of each individual priority (aij) for the three decision matrices (Tables 57).

Table 5

The matrix of pairwise comparison of six dimensions

 EconomicEnvironmentalSocialTechnicalGovernanceInstitutional
Economic 
Environmental 1/5 1/4 1/3 
Social 1/4 1/5 
Technical 1/2 
Governance 1/7 1/3 1/3 1/5 1/3 
Institutional 1/5 1/2 1/4 1/3 
Sum 2.29 13.83 10.83 4.07 22.00 15.33 
 EconomicEnvironmentalSocialTechnicalGovernanceInstitutional
Economic 
Environmental 1/5 1/4 1/3 
Social 1/4 1/5 
Technical 1/2 
Governance 1/7 1/3 1/3 1/5 1/3 
Institutional 1/5 1/2 1/4 1/3 
Sum 2.29 13.83 10.83 4.07 22.00 15.33 
Table 6

The matrix of pairwise comparison of 12 criteria

 C 1.1C 1.2C 2.1C 2.2C 3.1C 3.2C 4.1C 4.2C 5.1C 5.2C 6.1C 6.2
C 1.1 
C 1.2 
C 2.1 1/5 1/5 1/3 1/4 1/3 
C 2.2 1/5 1/5 1/3 1/5 1/7 
C 3.1 1/4 1/4 1/3 
C 3.2 1/2 1/3 1/3 1/5 
C 4.1 
C 4.2 1/5 1/4 1/3 1/2 1/4 1/3 
C 5.1 1/7 1/7 1/3 1/3 1/5 1/5 1/9 1/3 1/5 1/3 
C 5.2 1/5 1/7 1/2 1/3 1/2 1/5 
C 6.1 1/3 1/5 1/3 1/4 1/3 1/2 1/3 1/2 
C 6.2 1/7 1/5 1/3 1/2 1/3 1/5 1/7 1/2 
 C 1.1C 1.2C 2.1C 2.2C 3.1C 3.2C 4.1C 4.2C 5.1C 5.2C 6.1C 6.2
C 1.1 
C 1.2 
C 2.1 1/5 1/5 1/3 1/4 1/3 
C 2.2 1/5 1/5 1/3 1/5 1/7 
C 3.1 1/4 1/4 1/3 
C 3.2 1/2 1/3 1/3 1/5 
C 4.1 
C 4.2 1/5 1/4 1/3 1/2 1/4 1/3 
C 5.1 1/7 1/7 1/3 1/3 1/5 1/5 1/9 1/3 1/5 1/3 
C 5.2 1/5 1/7 1/2 1/3 1/2 1/5 
C 6.1 1/3 1/5 1/3 1/4 1/3 1/2 1/3 1/2 
C 6.2 1/7 1/5 1/3 1/2 1/3 1/5 1/7 1/2 

λmax = 13.61 and CR = 0.0952 < 0.1.

Table 7

The pairwise comparison of indicators

 
 

  • After calculating the sum of the columns.

  • Then, each of the values in the column is divided by the sum of the values.

    0.436 0.361 0.369 0.492 0.318 0.326 
    0.087 0.072 0.023 0.082 0.136 0.130 
    0.109 0.289 0.092 0.049 0.136 0.261 
    0.218 0.217 0.462 0.246 0.227 0.196 
    0.062 0.024 0.031 0.049 0.045 0.022 
    0.087 0.036 0.023 0.082 0.136 0.065 
    0.436 0.361 0.369 0.492 0.318 0.326 
    0.087 0.072 0.023 0.082 0.136 0.130 
    0.109 0.289 0.092 0.049 0.136 0.261 
    0.218 0.217 0.462 0.246 0.227 0.196 
    0.062 0.024 0.031 0.049 0.045 0.022 
    0.087 0.036 0.023 0.082 0.136 0.065 

  • The weight is given by calculating the average of each of the rows.

DimensionsWeight
Economic 0.383 
Environmental 0.089 
Social 0.156 
Technical 0.261 
Governance 0.039 
Institutional 0.072 
DimensionsWeight
Economic 0.383 
Environmental 0.089 
Social 0.156 
Technical 0.261 
Governance 0.039 
Institutional 0.072 

Calculate λmax

1.00 5.00 4.00 2.00 7.00 5.00   0.383   2.604 
0.20 1.00 0.25 0.33 3.00 2.00   0.089   0.551 
0.25 4.00 1.00 0.20 3.00 4.00   0.156   1.062 
0.50 3.00 5.00 1.00 5.00 3.00 × 0.261 1.909 
0.14 0.33 0.33 0.20 1.00 0.33   0.039   0.251 
0.20 0.50 0.25 0.33 3.00 1.00   0.072   0.435 
1.00 5.00 4.00 2.00 7.00 5.00   0.383   2.604 
0.20 1.00 0.25 0.33 3.00 2.00   0.089   0.551 
0.25 4.00 1.00 0.20 3.00 4.00   0.156   1.062 
0.50 3.00 5.00 1.00 5.00 3.00 × 0.261 1.909 
0.14 0.33 0.33 0.20 1.00 0.33   0.039   0.251 
0.20 0.50 0.25 0.33 3.00 1.00   0.072   0.435 
2.604  0.384  6.784 
0.551  0.089  6.227 
1.062 0.156 6.801 
1.909  0.261  7.317 
0.251  0.039  6.458 
0.435  0.072  6.077 
  6.611 
2.604  0.384  6.784 
0.551  0.089  6.227 
1.062 0.156 6.801 
1.909  0.261  7.317 
0.251  0.039  6.458 
0.435  0.072  6.077 
  6.611 

λmax = 6.611

With: n = 6 and λmax and CI are equal to 6.611 and 0.122108 respectively. And RI = 1.25

CR = (0.122108/1.25) = 0.0977 < 0.1

It is evident that since CR = 0.0977 is less than 0.1, the degree of consistency of comparison is acceptable.

Following the steps in the methodology presented in Figure 1, the experts have attributed a great importance to the two dimensions: economic and technical, whose weights are 38.3% and 26.1%. The other results are shown in Figure 2.

Figure 2

The obtained results of implementation of the proposed model for Algeria.

Figure 2

The obtained results of implementation of the proposed model for Algeria.

The financial autonomy and technical performance with the weights of 18.7% and 18.4% are the most important criteria of economic and technical dimensions respectively. In the social dimension, the highest weight was given to the criteria of affordability (9.2%). The criterion of the use of resources had the highest weight to the environmental dimension (5.1%). The transparency and organization criteria, which belong to the governance and institutional dimensions respectively with the weights of 2% and 2.8%, have the lowest weight and importance.

The results show that the scientists, policy makers and managers who answered the interview consider that the three criteria, financial autonomy, recovery of full costs and technical performance, are the most important aspects of WSSs sustainability in Algeria. This can be interpreted by saying that respondents recognized that WSSs in Algeria have financial difficulties and also manage poorly in the way that maintenance is done, with large water loss rates in the network.

According to the results, the most important indicators in the eyes of the experts are the indicators ‘i.1.1.1 and i.1.2.1’ (cost operation and maintenance and grand balanced budget) and then the indicators ‘i.4.1.2, i.1.2 .2, i.1.1.3 and i.1.2.3’ (reliability, small budget balance, opportunity cost and state subsidy rates for investments). So, based on the opinions of 12 experts, the indicators associated with criteria (C 1.1 (Total cost recovery), C 1.2 (Financial autonomy) and C 4.1 (Technical performance)) are the most important criteria to move WSSS services in Algeria towards sustainability. The indicators of the four criteria ‘C 5.1 (Transparency), C 5.2 (Policy and Planning WSSs), C 6.1 (Regulations) and C 6.2 (Organization) have the weakest impact, which emphasize that according to experts' judgment the two dimensions (governance and institutional) do not have a big role in the sustainable management of the WSSs in Algeria. This can be explained by these three facts: (i) decision makers and managers do not undertake consultation of the public in decision making and users do not have access to information and WSSs data, (ii) there is no long-term planning in services and use of water resources, and (iii) although there are a lot of rules that are related to WSSs, they are not followed well. The obtained results of implementation of the proposed model for Algeria are depicted in Figure 2.

The overall weights of all 50 indicators that were obtained by AHP are depicted in Figure 3.

Figure 3

The weights of all 50 indicators which were obtained by AHP.

Figure 3

The weights of all 50 indicators which were obtained by AHP.

The two main problems faced by WSSs managers are budget deficits and poor technical performance. This is why most experts felt that the challenges must be met by finding solutions: (i) to improve the economic and financial situation of the ADE and the ONA; and (ii) to increase the technical performance of the drinking water supply or sanitation system. And among the solutions proposed by the 12 experts (pairwise comparison for indicators) were: (i) balancing the small and large budget balances of the water companies by state subsidies or by cross-subsidies between the tranches and the water pricing, or by applying the principle of sustainable cost recovery with current pricing reform; (ii) improving the performance of existing grids by repairing leaks, decreasing water wastage, illicit branches, and rehabilitating networks.

As was seen, this method, in which sustainability of WSSs can be measured and evaluated comprehensively, helps with knowledge of which dimensions, criteria and indicators are the most important ones and have a significant role in improvement of the quality of the services, so it provides a very clear and comprehensive perspective for the managers and policy makers who are going to plan for SD in WSSs in the country.

CONCLUSION

An easy to use methodological tool for evaluation and measurement of the sustainability of WSSS using AHP was presented. The application of the proposed method was shown for Algeria as a case study considering a comprehensive three-level hierarchy that included six dimensions, 12 criteria and 50 indicators respectively. The process was undertaken using the judgments of 12 experts from different related fields including policy makers, managers of WSSs and scientist. The results showed that the economic (38.3%) and technical (26.1%) dimensions had more priority than others (environmental, social, governance and institutional). Moreover the financial autonomy (18.7%) and technical performance (18.4%) were the most important criteria, while transparency (2%) and organization (2.8%) had the least importance. In addition, from the point of view of the experts, significant indicators were cost of operation and maintenance as well as grand balance budget. By means of this method, the amount of priority for each effective factor can be easily and precisely determined, so it helps policy makers and managers to better plan for current and future WSSs development projects.

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