The search of the IBNET database resulted in a number of countries giving a considerable amount of utilities for the WWC indicator; the present analysis aims at making the most out of these data. The availability of the indicators per country as well as the reference year, which is the most recent year with available data, are presented in Table A1
. The utilities used in this analysis are not necessarily a representative sample of the respective countries’ water sector. In this study, when referring to a country, the utilities that report to the IBNET database are implied. The data employed for this study are the most readily available, while findings are restricted to the number of observations, i.e., the number of water utilities reporting this indicator.
3.1. Who Reports?
As far as the complaints for the water and sanitation services are concerned, they are related to changes in water quality or quantity [45
] or network damages. Therefore, time series monitoring and analysis would be the most effective approach to address this issue. In the absence of time series data, statistical evidence from many utilities in one year can provide key messages on customer complaints.
Some countries (Bangladesh, Russia, and Tanzania) provided a very small amount of utilities that report the examined indicator in the IBNET database. Other countries report a small amount of utilities without WWC values (e.g., only one for Peru). These countries are, however, examined, although statistical test comparisons may not allow for high significance. Table 1
presents the descriptive statistics of the WWC indicator per country. A country is included here if it reported for four or more utilities. The remaining countries are only included in Table A2
As can be observed, mean values vary considerably by country, with the lowest and highest average among the countries examined being achieved by Australia, with zero reported complaints, and Brazil with 0.2304, respectively. On the other hand, if Australia is excluded, the median values show a lower variation, i.e., 0.0001 and 0.1288, for utilities from Lithuania and Brazil, respectively, which, considering the upper percentile and maximum values, indicate the existence of extreme values. The descriptive statistics of the utilities’ OCC, for countries included in Table 1
, are analyzed in Table 2
, while the remaining countries are only included in Table A3
. Out of the 77 countries reporting this indicator in IBNET, the median country average is 0.03, and the upper quartile average is 0.11 [47
Note that, although considerable variations can be observed for the OCC with mean values ranging from, e.g., 0.849 for Brazil to 1.956 for Australia, these data are provided by the countries’ utilities’ and, as mentioned above, are not necessarily a representative sample. Furthermore, there are utilities in the database that do not report their OCC or utilities not registered at IBNET. Out of the 128 countries reporting this indicator in IBNET, the median country average is 1.15, and the upper quartile average is 1.42 [48
To provide statistical evidence for the discussed hypotheses, a large number of utilities and variability is necessary. Furthermore, it is essential that comparisons remain within the same legal political and economic system; otherwise, data compatibility issues may arise [18
]. In this analysis, cross-national comparisons could only be safe at the exploratory descriptive statistics phase. For this reason, all hypotheses are examined at a national level individually.
reports group comparisons for the parametric and equivalent non-parametric tests for the OCC of water utilities separated by whether or not they report their customers’ complaints in the IBNET database. It is evident for the utilities in Brazil that those reporting the selected quality indicator for the complaints by their customers perform financially better compared to those that do not report it by about 15.68% (t
= 4.332, p
Valid comparisons require an adequate number of water utilities per group compared. This is not the case here for most of the countries, since one of the groups has a low number of observations (reporting the WWC for Tanzania and not reporting WWC for Australia, Lithuania, Poland, and Zimbabwe). In order for the differences among the financial performance of utilities based on whether or not they report this quality indicator to be more evident the mean values of each group considered per country are calculated, as depicted in Figure 1
. It is evident that in all examined countries, apart from Peru where only one utility does not report complaints, the mean OCC of the utilities reporting the complaints of their customers is higher than those not reporting them.
It should be made clear that financial performance is not the only parameter related to the data openness of the utility. This finding is implicit information elicited by statistical comparisons of the OCC. Indeed, it is expected that there are other parameters that will affect the degree of openness in data for the water utilities apart from their financial performance. It has been demonstrated that the financial performance is also related to the size of the utility [14
]. Larger utilities are often obliged, due to their legal status, to be more open in their data compared to the smaller ones, which may have fewer staff members and less access to resources that would allow for the public posting of data. In Brazil, for example, comparing the size of utilities that provide their data for the WWC with those that do not, the former have an average value of 83,014 connections, while the latter have an average of 6714 connections (t
= 3.877, p
< 0.001). Note, however, that only 1082 out of the 1430 of the water utilities in Brazil have entered their number of connections in IBNET.
3.2. Who Complains?
The next step is to further examine the financial performance of the utilities based on the complaints reported. Is the number of complaints higher in the well performing utilities or those that are not performing so well? To address this, the correlations between the two examined indicators are examined, where this is possible, subject to data availability. Positive significant correlation is only found for Brazil (r
= 0.282, p
< 0.001) and negative for Zambia (r
= −0.751, p
= 0.008); all correlations can be found in Table A4
. Though the opposite signs of the Pearson coefficient could be suggested to lead to contradictory findings, it is important to note that for Brazil, the correlation was calculated based on 569 cases, while for Zambia from just 11. The results for the other countries give insignificant correlations (p
≥ 0.409), which could be attributed to the low number of reporting utilities. However, for water utilities in Peru (N = 44) and Serbia (N = 78), it is evident that there is no significant correlation (p
= 0.524 and p
= 0.886, respectively).
Further investigation is performed per group in Brazil enabled from the large number of utilities, as presented in Table 4
. It is observed that every possible group comparison (A, B, and C for groups defined by OCC values of lower and higher than: 1.7, 1.4, and 1.0, respectively) results to the same finding, i.e., the better the financial performance, the more the reported complaints. Note that the OCC is not claimed to be the only variable affecting the number of complaints. Although reporting complaints may be affected by some cultural, geographical, or organizational variables, in Brazil the size of the utilities, i.e., the number of connections, is positively related to both the number of complaints (r
= 0.096, p
= 0.019) and the OCC (r
= 0.092, p
The major statistical finding supported only by the utilities in Brazil is that those utilities that perform financially well also report more complaints compared to those performing not so well. Considering that there are several socio-cultural factors that may result in higher rates of complaints for goods and services [49
], it is risky to assume any generalization, considering that there are also countries with much fewer data but result in no or opposite sign correlation. It should be emphasized that complaints are negatively related to service quality and efficiency, and whenever possible it is important to study relations among both people’s perceptions of quality and actual chemical/technical quality [7