The project investigated in the current study was one of the major national community development projects implemented in Sudan. The project aimed to meet the urgent community driven recovery and development needs in the war affected and underdeveloped areas of North Sudan by providing social and economic services and infrastructure. The project covered five different states and more than 40 localities. Since 2006, the project has brought essential services to over two million people by financing over 1,000 community subprojects in education, health, water supply and village photovoltaic solar systems to power basic community infrastructure. Over 134 water supply subprojects were implemented, which are providing clean water sources to 525,810 people (261,190 males and 264,620 females) and their animals. Table 1 shows the water projects investigated in the current study.

The study aimed to assess the sustainability of nine different CBWS projects distributed over five localities in four different states in Sudan (Figure 1). These CBWS projects were co-funded by the National Ministry of Finance (NMF), and Multi-Donor Trust Fund (MDTF) and monitored by the World Bank (WB). The project aimed to meet the urgent community driven recovery and development needs in the war affected and underdeveloped areas of North Sudan by providing social and economic services and infrastructure. An Environmental and Social Impact Assessment (ESIA) study was carried out before the projects implementation according to World Bank requirements to assure minimal future environmental, water resources and social impacts of the projects. Types of water supply projects and population served are shown in Table 2.

Figure 1.

Sampling sites map showing the projects investigated and the population

In the current research, nine CBWS projects in Sudan were evaluated and analyzed. A sustainability index for monitoring and assessment was developed. Sustainability criteria and indicators were selected based on literature review and discussions with projects’ stakeholders. Furthermore, a model was constructed to quantify the relationships between different sustainability criteria and their overall effect on project sustainability. The sustainability theoretical model was constructed using PLS-PM analysis. Figure 2 gives an overview of the approach used in the current research.

Figure 2.

Research approach for PLS-PM

The second part of the current study aims to explore and evaluate the different variables that affect the overall performance of CBWS projects and to rank these variables based on their significance on the overall project sustainability. The approach used is presented in Figure 2.

Model hypothesis and development.

The current model is a qualitative data-driven model. It was built based on qualitative data and can be applied to predict the effect of the variables on the overall sustainability of the project. Data of 382 respondents were grouped into three. The first group is 322 respondents (from 5 different villages) that were used for developing the model. The second one is 40 respondents (from 3 villages) that are used for model validation. The third one is 20 respondents (from 1 village) that are used for the application of the model (prediction of sustainability). Model construction and analysis was carried out using XLSTAT-PLSPM [14]:

• Model hypothesis - The development of the model started with a theoretical model that has been tested by an indication test and a causality test. The model was developed based on latent variables (indicators) relationship hypothesis (Figure 3). The hypotheses were defined based on PCA which was carried out to pre-assess criteria relationships (data not shown);

• Model development and confirmation – Indicators data of CBWS projects were quantified in range 0 to 5. All quantitative data of the indicators were entered into the model as shown in Figure 1, and the model was analyzed and confirmed by PLS-PM. All data were first screened for outliers. Outliers data test was conducted using boxplots. PLS path model build-up began with assessing the unidimensionality of the measurement model in which the reflective indicators must be in a geometrical space of one dimension. The unidimensionality of variables was checked using Cronbach’s alpha, Dillon-Goldstein’s rho and latent variables eigenvalues. Model validity was assessed based on Goodness of Fit (GoF), R2 and the Average Variance Extracted (AVE) [15].

Figure 3.

Model structure and hypothesis

The scheme of a theoretical model that expresses the relationship among indicator variables is shown in Figure 3. This theoretical model was tested using a total of 382 respondents from the projects to observe the logical relationship between criteria (latent) variables and indicator (manifested) variables. Latent variables are the unobserved ones, while manifested variables are the observed ones.

XLSTAT software [14] was used to perform PLS path modeling analysis involving only reflective indicators and the centroid scheme for the inner estimation. A preliminary analysis for verifying the composite reliability of blocks is required because each reflective block represents only one latent construct (one dimension). In general, formative measurement model should be evaluated looking at the reliability and the validity of the constructs. In order to do that each indicator’s reliability was checked by looking at standardized loadings, Cronbach’s alpha, Dillon-Goldstein’s rho values [16].

The fit of the outer, inner and global models improved substantially when manifest variables with standardized loading < 0.7 were excluded [17]. The following manifest variables were removed: Usage Behavior (UB), Community Participation in O&M (CPOM), Book Recording System (BRS), Continuity of the System (CS) and Water Quality (WQ). Cronbach’s alpha and Dillon-Goldstein’s rho > 0.7 for all criteria, which indicates a correct outer model specification, measuring the internal consistency (Table 4).

The coefficients presented in Tables 5a and 5b showed that manifest (indicators) and latent (criteria) variables were well predicted by the PLS–PM framework. The prediction performance of the PLS–PM was high for both the outer, inner and global models. As concerns the goodness of fit, there is no overall fit index in PLS–SEM. Nevertheless, a global criterion of goodness of fit has been proposed by Tenenhaus et al. [15]. Both GoF and relative GoF in the current model reflected the high quality of the construct for both outer and inner model (Table 5a).

The R2 coefficient showed that endogenous latent variables were acceptable predicted by the explanatory latent variables (Table 5b). The R2 values provided an unbiased estimate of the proportion of variance explained; adjusted R2 provided very similar values to R2. The average commonality coefficient indicated that variance of the manifest variables was well reproduced by its respective latent variable (average commonality ≥ 0.50 (Table 5b). Another index used to evaluate the model is the commonality or AVE which is measuring to what extent the variability of the block is explained by the latent construct. The Average Variance Extracted (AVE) of 0.50 indicates a sufficient degree of construct validity.

According to Table 5b, the model explained 89% of the total variations in project sustainability. Social, organizational, technical and reliability/risk aspects had a direct significant effect on the project sustainability and no direct effect on the financial aspects of project sustainability (Table 6, Figure 5). However, the structural model showed both indirect and direct paths (effects) between technical, reliability/risk, organizational and social aspects (Figure 6).

Figure 5.

Path model structure (indicators in red were removed from the model due to their low correlation with their correspondent latent variables)

Figure 6.

Direct and indirect effects between different latent variable (sustainability criteria)

Based on these results, all proposed hypothesis were where all criteria have a direct positive effect on project sustainability, except for hypothesis 5 which supposed that there is a direct correlation between financial aspects of the projects and sustainability. According to PLS-PM analysis, financial aspects have an indirect effect on project sustainability, while it has a substantial direct influence on technical aspects (Figure 6). Both organizational and technical aspects have the highest influence on the projects’ sustainability as indicated by their path coefficients, while social aspects have the lowest effect on sustainability (Figure 5). These results would indicate that social participation alone is not enough to guarantee the sustainability of community-based projects.

Among the many interventions designed to address the rural domestic water supply and sustainability problem, CBM has gained considerable prominence since the late 1980s. Essentially CBM owes much of its origin from the neo-liberal traditions of a reduced role of the state, human rights and empowerment approaches aim development. CBM ought to achieve specific objectives including:

• Identifying development priorities by the target community itself;

• Strengthening the civic skills of the poor through community organizations;

• Enabling communities to work together for the common good (Mansuri and Rao, 2003).

However, the sustainability of CBM remains low and limited throughout Sub-Saharan Africa − including Sudan − due to limitations associated with the current perceptions in CBM and conceptual misunderstandings. Based on our study, sustainability of CBWS projects are influenced by different internal as well as external factors affecting its functional ability, which also have been indicated by many previous researchers [18]–[21]. This is was indicated by the PLS model which explained 89% of the variability in project sustainability reflecting that there are other factors influencing project sustainability by 12% and were not included in the model.

Although community participation and management seems to be a useful tool for sustainable rural water resources management [22]–[24]. In the current study, it was observed that most of the sustainability related problems were mainly due to poor community management as also was reflected by PLS model, indicating that organization issue has a great load on project sustainability (Figure 5). This deficiency in internal community management has also been reflected by [25], reflecting the need for external support to monitor and evaluate CBUs performance and to follow up the meetings conducted with the community. This is in accordance with Harvey and Reed [19], who also indicated that most of the projects related to the community management do not occur immediately after the commissioning of the improved water supply facility, but sometimes later within 1–3 year, which is similar to the projects’ age subjected to the assessment in the current study. Therefore, software activities to leverage communities’ ability in managing the implemented projects are one of the major governmental aspects that should be focused on. Also, building the capacity of rural communities served by water facilities to demand social accountability are key strategies that could potentially improve the impact of limited funding in service delivery. According to interviews with different projects’ stakeholders, the reason behind the lack of enough software activities is funding availability. However, giving the priorities to hardware activities rather than software is a major issue. Although ‘internal budget switching’ from software to hardware activities could be a positive step toward a much better impact on decentralized financing on CBM and functional sustainability of rural point water facilities, undermining the role of community training on implement projects management can jeopardize the whole sustainability issue of the project. It is worth mentioning that the local NGOs are excluded from this equation, and their role in community support is still negligible. Since the 1990s, there have been many rural water supply projects that incorporate demand-driven and community management model, although few of these projects planned for such a post-project back-up for the communities [sometimes it is called Post-Construction Support (PCS)]. However, many studies revealed the importance of such PCS mechanisms [26], [27].

Another determinant that affects the communities’ performance in managing implemented projects is their financial ability. According to the current study, financial issues do not have a direct influence on projects’ sustainability (based on the PLS model results), but they still have a great role in the communities’ ability to maintain the project. The success of CBM models in ensuring functional sustainability of point-water facilities largely depends on the ability and willingness of water users to participate in water-related community development initiatives, especially by making financial contributions to meet the initial cost of construction, major repairs and routine O&M [9]. Although all projects investigated in the current study have a financial contribution mechanism to sustain their project, their financial ability still limited especially if the project running costs are beyond their financial limits. Based on our study, sustainable CBWS project requires internal cooperation as well as external assistance [18]-[21]. Therefore, governmental and/or other stakeholders’ intervention is required to ensure the projects’ functionality and sustainability.