efficiency evaluation of the municipal management of ... · integrality, efficiency, economic...

International Journal of Engineering & Technology IJET-IJENS Vol:14 No:01 43

142001-9393-IJET-IJENS © February 2014 IJENS I J E N S

Efficiency Evaluation of the Municipal Management

of Public Services of Water Supply, Sanitary

Sewerage and Solid Waste

1Dirceu Scaratti,

2Alexandre Ströeher,

3Gidiane Scaratti

1Doctor in Production Engineering – Federal University of Santa Catarina (UFSC). Florianópolis (SC), Brazil.

1Researcher and professor at University of West of Santa Catarina (UNOESC)

Videira (SC), Brazil 2Sanitary and Environmental Engineering Student – University of West of Santa Catarina (UNOESC)

Videira (SC), Brazil 3Master Student in Chemical Engineering – Federal University of Santa Catarina (UFSC)

Florianópolis (SC), Brazil

Corresponding Author: Dirceu Scaratti

e-mail: [email protected]

Abstract-- This study aimed to evaluate the municipal

management of the three basic sanitation services (water supply,

sanitary sewerage and solid waste) using Data Envelopment

Analysis (DEA). The study was applied in municipalities with a

population between 20,000 and 50,000 inhabitants using DEA

measures non-radial (additive) interval [0, 1]. Were evaluated 39

municipalities that provide all three services from 50

performance indicators used in the management of economic-

financial processes, customer, market and conformity of

products. In the study, the municipalities that achieved

efficiencies in providing services (index = 1) are: 12.8% in water

supply, 5.1% in sanitary sewerage, 20.5% in solid waste, when

evaluated individually. However, when all three services (water

supply, sanitation and solid waste) were evaluated concomitantly,

the efficiency was only 7.7% of the municipalities. The other

municipalities in the sample had lower assessment, in other

words, indices <1 and classification inefficient. It was found that

in Brazil, municipalities provide better service in the

management of solid waste, when evaluated in comparison with

the other two types of services. The use of DEA in evaluating the

efficiency of municipal sanitation demonstrated success when

applied jointly in water supply, sanitary sewerage and solid

waste. Results of this research enabled the Brazillian

governments evaluated to know the efficiency of sanitation

services provided and will provide strategies and actions aimed

at improving them along the population.

Index Term-- Municipal management, efficiency, water supply,

sanitary sewerage, solid waste.

1. INTRODUCTION

The Brazilian population growth increased the consumption of

treated water, generation of effluents and solid waste.

Numerous researches associated with the services of water

supply and/or sanitary sewerage or solid waste are published

in many countries of the world, given the concern for the

health conditions of people and environmental sustainability.

Sanitation actions can be considered preventive for health,

when ensuring the quality of the water supply as well as the

collection, treatment and appropriate final disposal of human

waste and garbage produced on a daily.

Brazil has a large geographical region, which have different

economic development levels, social and cultural and the

performance of basic sanitation services, whose diversity of

management models can be municipal, state, public and/or

private, each with specific characteristics, which directly

influenced the development indices of population attendance.

The Public Policy of basic sanitation in Brazil contemplates

how citizens' rights, access to services of water supply,

sanitary sewerage and solid waste with universalization,

integrality, efficiency, economic sustainability, safety, quality,

regularity and integration of infrastructure and their services

with management of water resources.

This article aims to evaluate the efficiency of water supply

services, sanitary sewerage and solid waste in Brazilian

municipalities using Data Envelopment Analysis (DEA). The

DEA model adopted uses the measure does not radial additive

[1] from 50 performance indicators to evaluate the processes

of economic-financial management, conformity of products,

market and customers.

Associating evaluation models aiming its concomitant

application to the services of water supply, sanitary sewerage

and solid waste, constitutes a paradigm that aims to contribute

to improving the deficiencies of basic sanitation in Brazilian

municipalities, considering, studies have prioritized

assessments of efficient allocation of resources (productivity

and technical efficiency) and/or processes and management,

separately, for water supply. [2, 3, 4, 5, 6, 7, 8, 9 and 10],

sanitary sewerage [11], solid waste [12, 13 and 14]. Some

studies noted for jointly evaluate water supply and sanitary

sewerage [15, 16, 17, 18, 19, 20, 21, 22 and 23]. However, no

published studies were found by applying the DEA,

concomitantly for water supply, sanitary sewerage and solid

waste.

2. MATERIAL AND METHODS

Researches initiated [24] gave rise to the DEA, and in the

1970s were already consolidated the research lines of building

efficient frontiers technique developed by [25 and 26] that

mailto:[email protected]



used measures not radial, which allow changing the

production process because they enable changing the

proportions of the products and raw materials. In this research

we adopt the measure DEA additive [1].

For the evaluation of efficiency of basic municipal sanitation

services rendered in Brazilian municipalities will be built

curves of optimal performance. Such curves are called

efficiency frontiers for index = 1.0 and inefficiency for indices

< 1.0; considered efficient the Brazilian municipality (Mun)

represented by point(s) = 1.00 and, inefficient when

represented by point(s) < 1.0. Moreover, the further away the

efficiency frontier for the classification of a Mun, is the most

inefficient service sanitation rendered by him. In this context,

the algorithm used to evaluate a Mun° contemplated several

performance indicators (PI) simultaneously (PIj, j = 1, 2, ..., J)

and respective measurements (Mj, j = 1, 2, .. ., J) transformed

into monotone increasing functions on an interval [0, 1].

Considered observed values 0 ≤ mj ≤ 1 of the measures Mj, j =

1, 2, ..., J resulting from the performance function properly

and that do not exist or are not known optimal standards mj*

for the measures Mj, j = 1, 2, ..., J, the efficiency of a Mun° is

evaluated to other Mun similar Munn, n = 1, 2, ..., N, in the

same measurements Mj, j = 1, 2, ..., J.

The mathematical model used to verify the efficiency of

services of water supply, sanitary sewerage and solid waste

will indicate if a particular Mun of the sample is efficient or

not. The DEA used resulted in measurements M1, ..., Mk from

assumed values m1, ..., mK, as shown in Equation 1, such

that:

K...,,2,1k,. mzmn

kn

N

0nk

always that

N...,,2,1,0n,n,0e1 zz nn

N

0n

(1)

The existence of any Munn better than a Mun° can be

resolved by checking if there are any numbers Zn ≥ 0, n =

0, 1, 2, .., N, Equation 2, such that:

1zn

N

0n

k

,. mmzm0

k

n

kn

N

0nk

there is

some k such that,

mmzm0

1

n

kn

N

0nk

.

(2)

While, to see if there are such Zn, was adopted

Equations 3 and 4, linear programming:

Find: sk ≥ 0, k = 1, 2, ...K e zn ≥ 0, n = 0, 1, 2, ..., N; which

maximizes S = k

K

1n

s

(3)

Such that 1zn

N

0n

msmz0

kk

n

kn

N

0n

.

k = 1, 2, ..., K (4)

Thus, when some index present result (S*> 0), the

Muno evaluated is inefficient because there are any indicators

to measure positive for some s*k> 0,indicating the possibility

of valued service decrease the measure of inefficiency of this

Mun at least one of the performance indicators without

harming the other(s) indicator(s).Therefore, when the index is

S* = 0, the Muno is assessed as efficient, as the product s*k for

all k = 0, indicates that it will not be possible to improve the

efficiency measure for a particular Mun either indicators,

without sacrificing performance by at least another indicator.

The proposed model assessed the effectiveness of

basic sanitation using the DEA approach. From it verified the

efficiency of the services of water supply, sanitary sewerage

and solid waste related to economic-financial situation,

products compliance, market and customers, consolidated into

a synthetic indicator interval of efficiency [0,1].

The mathematical algorithm produced relatives measures that

may vary from one municipal service to another. The DEA

model designed to aggregations of measures was implemented

in software © Lingo.

Table I shows the performance indicators adopted in the

evaluation model and the Table II illustrates the schematic

model adopted for aggregate measures of efficiency of the

municipal water supply, sanitary sewerage and solid waste.

The data used were obtained from the Brazilian

Institute of Geography and Statistics (IBGE) and the National

Information System on Sanitation (SNSA) of the Brazilian

government, and the elements of the study were 39 Brazilian

municipalities (Mun) with a resident population between

20,000 and 50,000 inhabitants [27 and 28].

The measures of the indicators were transformed into no

dimensional measures and are presented in Appendix A.



Table I

Performance indicators applied to the model

Indicators: Economic-financial efficiency Unit Water

supply

Sanitary

sewerage

Solid

waste

Total expenses on services per m3 billed R$/m3 X

Operating expense per m3 billed R$/m3 X

Indicator of financial performance Percentage X

Index billing losses Percentage X

Margin of expenses of employees Percentage X

Expense with employees in operating expenses Percentage X

Electricity expense in operating expenses Percentage X

Participation in operating revenue in total revenue water Percentage X

Participation in operating revenue in total revenue sewage Percentage X

Billing days committed with accounts receivable Days/years X X

Per capita expense on the services of solid waste R$/inhab/year X

Index of financial costs in the municipality solid waste Percentage X

Unit cost of solid waste collection R$/ton X

Indicators: Conformity of products efficiency Unit Water

supply

Sanitary

sewerage

Solid

waste

Index of macromeasurement Percentage X

Index of hydrometration Percentage X

Average water consumption by economy m3/month/econ X

Water consumption billed by economy m3/month/econ X

Average per capita consumption of water L/inhab/day X

Index of losses in distribution Percentage X

Index of treated sewage compared to water consumed Percentage X

Collection and treatment of SWH Yes or no X

Billing and collection for the services of CCW and CDW Yes or no X

Street sweeping, weeding and mowing Yes or no X

Recyclables Waste Collection with Collectors Yes or no X

Processing Waste (Sanitary Landfill or Dump) Yes or no X

Environmental Licensing (EOL, PEL or ELO) Yes or no X

Water proofing Processing Unit Yes or no X

Draining Gas and Leachate Treatment Yes or no X

Indicators: Market efficiency Unit Water

supply

Sanitary

sewerage

Solid

waste

Index of total water service Percentage X

Index of urban water service Percentage X

Productivity index: active savings per employee Econ/func X X

Index of total sewage service Percentage X

Index of urban sewage service Percentage X

Index sewage collection produced Percentage X

Rate of full coverage of collection RW Percentage X

Mass of RW+PW collected per capita Kg/inhab/day X

Rate of sweeper per urban inhabitant Func/1000inhab X

Rate of weeding per urban inhabitant Func/1000inhab X

Indicators: Customers efficiency Unit Water

supply

Sanitary

sewerage

Solid

waste

Index of water fluoridation Percentage X

Loss index per connection Percentage X

Incidence of analysis of residual chlorine nonstandard Percentage X

Incidence of analyzes of turbidity nonstandard Percentage X

Incidence of analyzes of total coliforms nonstandard Percentage X

Index of sewage collected treatment Percentage X

Recovery rate of recyclable regarding HW and PU Percentage X

Mass recovered per capita HW and PW Percentage X

Mass per capita collected via selective collection Kg/inhab/year X

Mass of SWH per capita collected Kg/inhab/year X

SWH: Solid Waste from health; CCW: Civil Construction Waste; CDW: Construction and demolition waste; EOL:

Environmental operating license; PEL: Preliminary environmental license; ELO: Environmental license of operation; RW:

residential waste; PW: public Waste; HW: Household waste; SWH: Solid waste health



Table II

Schematic model for assessing the efficiency of sanitation services in Brazilian municipalities

Water supply Sanitary sewerage Solid waste

Performance indicators (PIj, j = 1, 2, ..., J) efficiency: economic and financial,

conformity of products, market and customers

PIj1 PIj1 PIj1 PIj1 PIj1 PIj1 PIj1 PIj1 PIj1 PIj1 PIj1 PIj1


...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ......

PIJ PIJ PIJ PIJ PIJ PIJ PIJ PIJ PIJ PIJ PIJ PIJ

Measures monotonous and growing (Mj, j = 1, 2, ..., J of the interval [0, 1]) efficiency:

Economic-financial, conformity of products, market and customers

Efficiency of water

supply services

Efficiency of

sanitary sewerage services

Efficiency of

solid waste services

Efficiency of sanitation services in Brazilian municipalities

3. RESULTS

In applying the DEA model, measures were generated

aggregating economic-financial, conformity of products,

market and customers indicators to define the efficiency of

services of water supply, sanitary sewerage and solid waste.

The mathematical algorithm applied to the DEA approach

to aggregate measures of market efficiency (with three

performance indicators), municipality n°. 1 (M1) for the

services of water supply was as follows:

max=0*z1+0*z2+0*z3+, ... , +0*z39+1*s1+1*s2+1*s3;

for=z1>=0; z2>=0; z3>=0 , ... , z39>=0; s1>=0; s2>=0;

s3>=0;

PIj1=0.79*z1+1.00*z2+0.00*z3+, ... , +0.84*z39-1*s1+

0*s2+0*s3=0.79;

PIj2=0.41*z1+0.83*z2+0.24*z3+, ... , +1.00*z39+0*s1-

1*s2+0*s3=0.41;

PIj3=0.98*z1+1.00*z2+0.43*z3+, ... , +0.34*z39+0*s1+

0*s2-1*s3=0.98;

Such that=1*z1+1*z2+1*z3+, ... , +1*z39=1;

END

Similarly, the DEA algorithm was applied according to the

equations (3 and 4) to evaluate the efficiency of customers

(EC), market (EM), the conformity of products (ECP) and

economic-financial (EEF) well as the efficiency of water

supply services (EWS), sanitary sewerage services(ESS), solid

waste services(ESW) and basic sanitation (EBS). The results

of the application to a municipality of the sample are shown in

Table III.

Table III

Efficiency measures of sanitation services in the municipality M10

Water supply Aggregate

measures Sanitary sewerage

Aggregat

measures

Solid

waste

Aggregate

measures

Customers (EC) 0.76 Customers (EC) 1.00 Customers (EC) 051

Market (EM) 0.11 Market (EM) 0.53 Market (EM) 0.51

Conformityofproducts

(ECP) 0.71


(ECP) 1.00


(ECP) 0.91

Economic-Financial

(EEF) 1.00

Economic-Financail

(EEF) 0.56

Economic-Financial

(EEF) 0.35

Water supply (EWS) 0.66 Sanitary sewerage (ESS) 0.78 Solid waste (ESW) 0.73

Basic Sanitation (EBS)

0.75

It is observed in the results presented in Table III that this

municipality of the sample had an efficient management

(1.00) for EEF and inefficient for EC (0.76), EM (0.11) and

ECP (0.71) in the water supply service. For sanitary sewerage

service, management efficiency for EC and ECP, inefficient

for EM (0.53) and EPS (0.56). In turn, all the factors evaluated

in solid residues were ineffective: EC (0.51), EM (0.75) ECP

(0.91) and EEF (0.35).

Consequently, the performance resulting from the

aggregation of the EWS (0.66), ESS (0.78) and ESW (0.73),

Ind 1 Ind 1 Ind 1 Ind 1 Ind 1 Ind 1 Ind 1 Ind 1 Ind 1 Ind 1 Ind 1 Ind 1


..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... .....

Ind n Ind n Ind n Ind n Ind n Ind n Ind n Ind n Ind n Ind n Ind n Ind n

GESTÃO DO SANEAMENTO BÁSICO

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resulting in the ineffectiveness of sanitation services (0.75) of

M10, in other words, this municipality can improve 0.25,

compared to the other 38 municipalities in the sample.

The synthetic indicators for the service water supply,

sanitary sewerage and solid waste are presented in Table IV.

Here, it can be seen that five municipalities obtained efficient

management (1.00) to the service of water supply (EWS), two

in sanitation sewerage (ESS), and eight solid waste (ESW).

The basic sanitation service (EBS) which aggregates the

results of EWS, ESS and ESW concomitantly, was effective

for only three municipalities, although nine other

municipalities have obtained inefficiency ≤ 0.10.

The municipalities of greater inefficiency were: M10 in

EWS (0.66); M23 in ESS (0.32), M10 and M35 in ESW (0.73)

and M16 in EBS (0.68). The lowest average of synthetic

indicators (aggregate values) was observed for the EC (SS)

(0.47) and the highest average was observed for the EEF (WS)

(0.94).

4. DISCUSSION

The data envelopment analysis is adopted in various

forms with the aim of assess the relative efficiency as a

function of performance applied to organizations, Decision

Maker Units (DMU), inputs and outputs, returns to scale or

non-radial measures.

Applying DEA additive measure of this study allowed,

through mathematical algorithm, construct a synthetic

indicator identifying measures S* ≥ 0 to performance

indicators adopted in the evaluation of efficiency of services

of water supply, sanitary sewerage and solid waste, separately

and jointly as aggregate efficiency.

The visualization of the final results of the evaluation of the

efficiency can be seen below being possible to view their

efficiency frontiers. Figure 1 illustrates the synthetic indicators

aggregated to customers, market, conformity of product and

economic-financial for water supply services in the 39

municipalities of the study.

Fig. 1. Synthetic indicators of efficiency of water supply service

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1 2 3 4 5 6 7 8 91

01

11

21

31

41

51

61

71

81

92

02

12

22

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42

52

62

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82

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13

23

33

43

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83

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Evaluated municipalities

SYTHETIC INDICATOR OF EFFICIENCY OF WATER SUPPLY SERVICE



Table IV

Results aggregated into synthetic indicators

M

Efficiency of water supply service

(EWS)

Efficiency of sanitary sewerage

service (ESS)

Efficiency of solid waste service

(ESW) SINT*

EBS EEF

(WS)

ECP

(WS)

EM

(WS)

EC

(WS) SINT*

EWS EEF

(SS)

ECP

(SS)

EM

(SS)

EC

(SS) SINT*

ESS

EEF

(SW)

ECP

(SW)

EM

(SW)

EC

(SW) SINT*

ESW

1 1.00 1.00 0.62 0.93 0.90 0.73 1.00 0.65 1.00 0.86 0.73 0.67 0.64 0.57 0.74 0.86

2 1.00 0.68 0.52 1.00 0.81 0.85 0.25 0.60 0.00 0.44 0.60 0.82 1.00 0.44 0.84 0.73

3 1.00 1.00 0.98 0.83 1.00 1.00 1.00 0.96 1.00 1.00 0.84 1.00 0.81 0.42 0.87 1.00

4 0.99 0.71 0.71 0.83 0.82 0.81 1.00 0.76 1.00 0.90 0.79 0.67 0.72 0.52 0.77 0.86

5 0.76 0.88 0.93 1.00 0.90 0.66 0.09 0.74 0.00 0.38 0.80 1.00 0.71 0.42 0.83 0.73

6 0.87 0.83 0.77 0.99 0.88 0.67 0.12 0.81 0.00 0.41 0.68 0.91 0.71 1.00 0.92 0.77

7 1.00 0.89 0.66 0.71 0.83 0.89 0.95 0.73 0.93 0.89 0.86 0.94 0.79 1.00 1.00 0.94

8 1.00 0.56 0.73 1.00 0.83 1.00 0.30 0.57 0.00 0.48 0.89 0.51 0.57 0.82 0.79 0.73

9 0.84 0.73 0.78 1.00 0.85 0.64 0.21 0.78 0.00 0.42 0.88 0.72 0.83 0.42 0.82 0.73

10 1.00 0.71 0.11 0.76 0.66 0.56 1.00 0.53 1.00 0.78 0.35 0.91 0.75 0.51 0.73 0.75

11 1.00 0.89 0.53 0.87 0.83 0.59 1.00 0.66 1.00 0.82 0.89 1.00 0.54 0.42 0.80 0.85

12 0.86 0.74 0.68 1.00 0.83 0.56 1.00 0.41 1.00 0.75 1.00 0.54 0.54 0.53 0.92 0.86

13 1.00 0.75 0.75 1.00 0.89 0.76 1.00 0.85 1.00 0.91 0.91 0.83 0.59 0.75 0.86 0.92

14 1.00 0.82 0.64 1.00 0.88 1.00 0.95 0.08 0.00 0.52 0.87 1.00 0.64 0.94 0.95 0.81

15 1.00 1.00 0.58 0.83 0.86 0.77 1.00 0.70 1.00 0.88 0.98 1.00 0.73 0.48 0.90 0.91

16 0.74 0.67 0.76 1.00 0.80 0.48 0.19 0.78 0.00 0.37 0.97 0.65 0.70 0.44 0.78 0.68

17 1.00 1.00 0.66 1.00 0.93 0.62 1.00 0.72 1.00 0.85 0.95 0.53 0.76 0.68 0.83 0.90

18 0.94 0.81 0.79 1.00 0.90 0.89 0.06 0.81 0.00 0.45 0.04 0.80 0.78 0.97 0.75 0.73

19 0.94 0.83 0.98 1.00 0.95 0.86 0.04 0.57 0.05 0.39 0.96 0.70 0.76 0.42 0.81 0.75

20 0.74 0.93 1.00 1.00 1.00 0.46 0.17 0.77 0.00 0.36 0.64 1.00 0.78 0.48 0.83 0.77

21 1.00 0.81 0.63 1.00 0.87 1.00 0.39 0.57 0.00 0.50 0.98 0.77 0.79 0.44 0.87 0.78

22 1.00 0.75 1.00 0.84 1.00 0.74 1.00 1.00 1.00 0.99 0.66 0.40 1.00 0.43 0.75 0.96

23 1.00 0.55 0.66 1.00 0.81 0.71 0.06 0.45 0.00 0.32 1.00 0.71 0.55 0.42 0.84 0.69

24 1.00 0.87 0.95 0.96 0.96 0.72 0.99 0.04 0.00 0.45 0.88 0.76 0.60 1.00 0.90 0.80

25 0.91 0.80 0.79 0.93 0.87 0.78 0.07 0.84 0.00 0.43 0.99 1.00 0.66 1.00 1.00 0.80

26 1.00 0.63 0.76 0.82 0.81 0.79 0.98 0.79 0.97 0.89 1.00 0.49 0.75 0.56 1.00 0.93

27 1.00 1.00 0.76 1.00 0.95 1.00 0.19 0.75 0.00 0.50 0.61 0.86 0.92 0.77 0.91 0.82

28 1.00 1.00 0.66 1.00 0.93 0.84 0.42 0.72 0.31 0.58 0.96 1.00 0.80 0.79 1.00 0.87

29 1.00 0.88 0.91 1.00 0.96 1.00 1.00 0.76 1.00 0.95 0.74 1.00 1.00 0.75 1.00 1.00

30 1.00 0.66 0.80 0.84 0.84 0.42 0.57 0.71 0.00 0.44 0.66 0.83 0.62 0.54 0.75 0.71

31 1.00 1.00 0.71 0.91 0.92 1.00 0.45 0.76 0.32 0.64 0.26 0.72 1.00 0.48 0.74 0.80

32 1.00 1.00 0.53 0.66 0.81 0.37 1.00 0.29 1.00 0.68 0.73 0.53 0.99 1.00 1.00 0.86

33 1.00 0.96 0.98 1.00 1.00 0.76 0.00 0.82 0.00 0.41 0.60 0.52 1.00 0.42 0.76 0.77

34 1.00 1.00 0.96 1.00 1.00 0.75 0.91 0.10 0.00 0.45 0.89 1.00 0.79 0.43 0.88 1.00

35 0.86 0.75 1.00 0.83 0.95 0.77 1.00 1.00 1.00 1.00 0.63 0.58 0.78 0.54 0.73 0.94

36 0.79 1.00 0.91 0.73 0.87 0.69 1.00 0.98 1.00 0.95 0.95 0.86 0.81 0.74 0.95 0.95

37 0.85 0.70 0.55 1.00 0.79 0.58 0.65 0.17 0.00 0.36 1.00 0.54 1.00 0.46 1.00 0.75

38 0.83 0.53 0.69 0.61 0.68 0.73 1.00 0.68 1.00 0.86 1.00 1.00 0.91 0.42 1.00 0.88

39 1.00 1.00 0.75 1.00 0.95 1.00 1.00 0.79 1.00 0.96 0.98 0.82 0.74 0.73 0.92 0.98

X 0.94 0.82 0.74 0.92 0.88 0.75 0.64 0.65 0.47 0.64 0.79 0.78 0.77 0.62 0.86 0.83

M: municipalities in the sample; EWS: efficiency of the water supply service; EEF (WS): economic and financial efficiency; ECP (WS):

efficiency of conformity of products, EM (WS): market efficiency, EC (WS): efficiency of customers; ESS: efficiency of sanitary

sewerage service; EEF (SS): economic and financial efficiency; ECP (SS): efficiency of product compliance, EM (SS): market efficiency,

EC (SS): efficiency customer; ESW: efficiency of solid waste service; EEF (SW): economic and financial efficiency; ECP (SW):

efficiency of product compliance, EM (SW): market efficiency, EC (SW): efficiency customer. X: average values.* The "SINT" values are

derived by aggregating the indicators SINT*EWS: EEF (WS), ECP (WS),EM (WS) and EC (WS); SINT*ESS: EEF (SS), ECP (SS), EM

(SS) and EC (SS); SINT*ESW: EEF (SW), ECP (SW), EM (SW) and EC (SW). Turn, SINT*EBS is the results from the aggregation of

measures SINT*EWS, SINT*ESS and SINT*ESW and corresponds of the efficiency of basic sanitation service.



Each synthetic municipal indicator corresponds to

the aggregate evaluation of 23 performance indicators, whose

numerical results are shown in Table 4. In Figure 1 - the

Municipality 25 has owned S > 0, whose measure is the

relative inefficiency of the other 38 municipalities assessed,

similar interpretation to the other points of the graph, except

the municipalities 3, 20, 22, 33 and 34 which have S = 0,

indicating efficiency. Among the studies that adopted the

DEA to evaluate the water supply, stands out: [8 and 9], to

evaluate public companies in the sector of water supply

against the regulatory frame and its potential economic and

the costs of price review performed by regulatory agencies in

England and Wales (England and Wales).

Romano and Guerrini [7] evaluated the cost efficiency

of 43 Italian public companies of water supply services

grouped into clusters. The results indicated that the ownership

structure, size and geographical location had an impact on the

performance of water utilities.

Kulshrestha and Vishwakarma [6] to evaluate the

efficiency of water supply services in 20 urban centers in the

state Madhya Pradesh in India, aiming to measure the

inefficiencies of management and financial losses. The results

indicated that there are significant deficiencies among several

municipalities evaluated, and the larger cities have better

efficiency than smaller cities. However, even the larger

municipalities need restructuring and downsizing of its

operations and significant savings in operating expenses,

people and unbilled water can be obtained if adopted best

practices.

In turn [4] evaluated the efficiency of urban water

supply in 27 Indian cities applying the DEA as an analytical

tool to measure technical efficiency. Cities are classified into

different groups according to the structure of their services for

water supply and management of municipal or parastatal. The

results indicate that the functional autonomy management

shows better performance and, in addition, the results also

have implications for the cost of water supplied. It was found

that most water utilities are operating with decreasing returns

to scale, which implies that water must have a minimum bid

price.

Alsharifet al., [3] demonstrated that DEA can be

a useful tool to evaluate the relative efficiency of water supply

systems and establish benchmarks to measure progress in the

management of water resources. The study was conducted

with the water supply systems of the Palestinian territories of

the West Bank and Gaza Strip. The efficiency scores of Gaza

were considerably lower than those of the West Bank. Water

losses were the main source of inefficiency, while the size of

the municipalities evaluated affected a little bit the efficiency

of water supply services.

Figure 2 similarly illustrates the synthetic indicators

aggregated into the sanitary sewerage service in the 39

municipalities of the study.

Fig. 2. Synthetic indicators of efficiency of sanitary sewerage service

Each synthetic municipal indicator corresponds to the

aggregate evaluation of 08 performance indicators, whose

numerical results are shown in Table IV and the interpretation

similar to Graph 1. It is observed that there is a wide variation

in the results, the municipality 23 has the greater inefficiency

and only municipalities 3 and 35 are efficient.

Some recent studies have been developed jointly

assessing water supply and sanitary sewerage, all adopting the

DEA.

Cruz, Carvalho and Marques [18] used a data set of 253 to

evaluate 45 Portuguese companies of water supply and

sewage. The results showed that a single measurement may

not provide enough information for monitoring multi-utilities,

so when adopted along with other indicators, the proposed

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1 2 3 4 5 6 7 8 91

01

11

21

31

41

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61

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81

92

02

12

22

32

42

52

62

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82

93

03

13

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83

9

Mea

sure

th

e Sy

nth

eti

c In

dic

ato

r o

f sa

nit

ary

Sew

era

ge


SYNTHETIC INDICATOR OF EFFICIENCY OF SANITARY SEWERAGE SERVICE



model contributes to decision making prioritizing efforts to

improve the overall efficiency.

In turn, [15] evaluated the performance of services for

water supply and urban sewage in Australia, with the objective

of determining if there was an improvement in productivity

and efficiency after the entry of the private sector in business.

Were adopted the Malmquist model to determine the different

levels of improvement in productivity and efficiency from the

1990s. The results point to a modest productivity gains in

larger urban centers, regardless of the company structure.

Furthermore, the study highlights the need to consider

exogenous factors can influence the results of productivity in

companies with monopoly characteristics and dependent on

raw materials such as water.

Al-Assa'd and Sauer [16] evaluated the sectors of water

supply and sewage in Jordan in two stages: first the DEA was

used to evaluate the efficiency and the second, adopted the

Tobit model to determine the impact of uncontrollable factors

about the inefficiencies of the concessionaires of water supply

services and sewage. The results of the application show that

there is a potential to reduce inputs and operating expenses 15-

20% in the sector of water and 23-27% in the sector sewage.

In turn, the results of the application of Tobit model indicate

that commercial activities have a direct impact on improving

efficiency for both sectors.

Moreover [21] adopted the DEA to measure technical

efficiency of supply water and sewage companies from 17

municipalities of the Province Markazi (Iran). The results

indicated less than 30% of municipalities were technically

efficient. The low financial income and water losses were the

main sources of inefficiency.

Figure 3 similarly illustrates the synthetic indicators

aggregated to the solid waste service of 39 municipalities in

the study.

Fig. 3. Synthetic indicators of efficiency of solid waste service

Each synthetic municipal indicator corresponds to the

aggregate evaluation of 19 performance indicators, whose

numerical results are shown in Table 4 and the interpretation

similar to Figure 2. It is observed that the variation in results is

lower when compared to the results of water supply and

sanitary sewerage, showing smaller inefficiency in the

provision of related services, also demonstrating the most

efficient municipalities, 08 among the 39 evaluated.

The issue of solid waste also has some recent studies

adopting DEA [13] researched the local infrastructure

installation of solid waste management based on the use of

analytic network process and quantitative focus from applying

DEA. The research objective was to evaluate the performance

of alternative locations and facilities for solid waste

management defining the best location to install the

infrastructure.

While [14] evaluated the efficiency of the 293

municipalities in Belgium in collecting and processing solid

waste using the DEA model. The application allowed the

overall efficiency and cost estimate of cost efficiency in the

treatment of various fractions of municipal solid waste with

the following line: (bulkywaste, residual waste, greenwaste,

packagingwaste, other municipal waste, other EPR-waste).

In turn, [12] adopted the DEA in evaluating the efficiency

of production and logistics in solid waste management in

Provinces of Japan according to the authors, when the market

fails to regulate the sector, benchmarking and efficiency

behaviors by units of decision-making in the sector come into

play, and the collection of waste is the main cost of the

activity of the productive chain of municipal solid waste. That

is, the collection of waste in metropolitan Tokyo represents

74.7% of the total cost of the activity. The list of

underperforming municipalities assessed indicates that the

geographical features and the number of small communities

inhabited is a determining factor for its inefficiency, for that,

not achieve minimum efficient scale in collecting their waste.

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1 2 3 4 5 6 7 8 91

01

11

21

31

41

51

61

71

81

92

02

12

22

32

42

52

62

72

82

93

03

13

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33

43

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63

73

83

9

Me

asu

re t

he

Syn

the

tic

Ind

icat

or

of

solid

was

te


SYNTHETIC INDICATOR OF EFFICIENCY OF SOLID WASTE SERVICE



Applying DEA indicated that the production technology in the

municipal level assessed is constant return to scale.

In Brazil, there are no reports in the literature evaluating

the effectiveness of management services for water supply,

sanitary sewerage and solid waste using DEA. However, we

can highlight three sector researches. One, produced by [17],

were used the DEA approach (constant return) to evaluate the

technical efficiency of state-owned of water supply and

sanitary sewerage, in which it was found that 15 of them

(57.69%) were efficient. When observed under the focus

DEA-V (variable returns to scale), 21 (80.77%) were

considered efficient.

In turn, [23] evaluated the effectiveness of 20 public state

companies water and sewage during the period 1996-2000.

The study used DEA to measure the relative efficiency from

three inputs (staff expenses, operating costs and other

operating costs) and four products (produced water, treated

sewage, population served with water and population served

with treated sewage). The results indicated efficiency at 55%

of companies (1997) and 65% of companies in the other years

of the study (1996, 1998, 1999 and 2000). However the whole

period 1996-2000, only 45% of companies remained efficient.

Recently [22] adopted the DEA additive measure to

evaluate the efficiency of the management of municipal water

supply and sanitary sewerage. Were comparatively evaluated,

53 Brazilian municipalities with populations between 50,000

and 100,000 inhabitants, using 33 performance indicators

whose results were transformed into dimensionless measures

of the interval [0,1] before applying DEA. The results

indicated that nine water supply services (9.43%) and three

sanitary sewerage (5.67%) were efficient evaluation. In

assessing aggregate management of basic sanitation (water

supply and sanitary sewerage), only one municipality (1.89%)

achieved efficient evaluation.

When assessing the efficiency of services water supply,

sanitary sewerage and solid waste so as set for representing

basic sanitation in Brazil, applying DEA additive measure

indicates that 7.70% (municipalities: M3, M29 and M34) are

efficient . However, other 23.08% had inefficiency ≤ 0.10.

Figure 4 illustrates the aggregate results of the efficiency of

basic sanitation in Brazil.

Fig. 4. Synthetic efficiency indicators of basic sanitation in Brazil

5. CONCLUSIONS

The present application DEA additive measure,

pointed potential to measure the effectiveness of services for

water supply, sanitary sewerage and solid waste in

municipalities, so as together through a series of indicators of

economic-financial performance, compliance of products,

market and customers. The use DEA from a mathematical

algorithm to construct a synthetic indicator identified several

possibilities of improving the inefficiencies.

Furthermore, the study was of fundamental

importance to demonstrate the inefficiency of management

services for water supply, sanitary sewerage and solid waste,

mainly because they, in Brazil, have no direct competition,

which credits the inefficiency of the main threats to

performance of the sector organizations.

Considering that this research included in their

assessment a sample of municipalities with a population

between 20,000 and 50,000 inhabitants, the proposed model

may have extended its application to other municipalities with

public or private services in other countries of the world.

Other searches that may include indicators of

population health and Human Development Index (HDI) of

the United Nations Development Programme (UNDP) of

United Nations (UN).

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1 2 3 4 5 6 7 8 91

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11

21

31

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bas

ic s

anit

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SYNTHETIC INDICATOR OF EFFICIENCY OF BASIC SANITATION IN BRAZIL



ACKNOWLEDGEMENTS

This study was supported by National Council for Scientific

and Technological Development (CNPq) and The Scholarship

Program of Initiation of Technological Development and

Innovation (PIBITI) of Brazilian government.

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Measuring the efficiency of decision making units. European journal of operational research. 2(4): 429 - 444.

[26] FÄRE, R.; LOVELL, C.A.K. (1978). Measuring the technical

efficiency of production. The Journal of Economic Theory. 19: 150-162.

[27] BRASIL. Instituto Brasileiro de Geografia e Estatística (2010).

Estimativas populacionais para municípios brasileiros. Rio de Janeiro: IBGE, 2010.

[28] BRASIL. Ministério das Cidades (2011). SNIS - Sistema Nacional

de Informações sobre Saneamento: diagnóstico dos serviços de

água e esgotos - 2009. Brasília: MCIDADES, 616p.

http://www.sciencedirect.com/science/article/pii/S0956053X12002309





APPENDICES

Appendix A: This appendix lists the performance indicators adopted and their dimensionless measures on the interval [0, 1]

for each type of service reported: water supply, sanitary sewerage and solid waste, corresponding to a Brazilian municipality (M).

Appendix A.1

Indicators and measures of water supply

M

Economic-financial indicator Market indicator


1 1.00 1.00 0.12 0.91 0.97 0.97 0.11 0.81 0.00 0.79 1.00 0.00

2 0.26 0.25 0.67 0.88 0.55 0.55 0.79 0.92 0.70 0.41 0.83 0.24

3 0.73 0.73 0.50 0.49 0.74 0.74 0.00 0.85 0.77 0.98 1.00 0.43

4 0.50 0.49 0.76 0.68 0.14 0.14 0.75 0.85 0.98 0.87 1.00 0.19

5 0.58 0.57 0.54 0.00 0.61 0.61 0.52 0.90 0.00 1.00 1.00 0.05

6 0.71 0.72 0.66 0.68 0.25 0.25 0.65 0.81 0.36 0.82 1.00 0.43

7 0.64 0.64 0.87 0.57 0.42 0.42 0.53 0.98 0.81 0.66 1.00 0.24

8 0.24 0.23 1.00 0.58 0.63 0.63 0.60 0.97 0.93 0.70 0.96 0.45

9 0.54 0.54 0.35 0.55 0.50 0.50 0.62 0.80 0.46 0.86 0.99 0.42

10 0.64 0.63 0.61 0.85 0.25 0.25 1.00 0.78 0.46 0.00 0.00 0.25

11 0.04 0.11 0.45 0.78 0.32 0.32 0.79 0.95 0.45 0.68 0.68 0.15

12 0.22 0.22 0.68 0.73 0.26 0.26 0.67 0.64 0.48 0.78 1.00 0.20

13 0.73 0.72 0.58 0.82 0.53 0.53 0.74 0.81 0.75 0.58 1.00 0.60

14 0.00 0.00 0.86 0.65 0.34 0.34 0.53 0.62 1.00 0.73 1.00 0.13

15 0.66 0.66 0.77 0.97 0.35 0.35 0.75 0.89 0.68 0.56 0.88 0.24

16 0.81 0.81 0.40 0.35 0.41 0.41 0.54 0.74 0.00 0.84 1.00 0.38

17 0.65 0.65 0.85 1.00 0.19 0.19 0.72 0.94 0.08 0.67 1.00 0.24

18 0.42 0.42 0.83 0.51 0.45 0.45 0.65 0.92 0.79 0.92 1.00 0.38

19 0.80 0.80 0.43 0.86 0.55 0.55 0.55 0.95 0.87 0.99 1.00 0.30

20 0.56 0.55 0.00 0.40 0.20 0.20 0.66 0.86 0.23 1.00 1.00 0.27

21 0.59 0.59 0.93 0.67 1.00 1.00 0.52 0.90 0.00 0.54 1.00 0.28

22 0.36 0.35 0.76 0.63 0.72 0.72 0.74 0.60 0.74 1.00 1.00 0.27

23 0.27 0.26 0.50 0.67 0.52 0.52 0.87 0.74 0.93 0.73 1.00 0.17

24 0.07 0.07 0.66 0.65 0.56 0.56 0.57 0.64 1.00 1.00 1.00 0.11

25 0.72 0.72 0.64 0.55 0.90 0.90 0.33 0.76 0.00 0.69 1.00 0.62

26 0.16 0.15 0.21 0.33 0.71 0.71 0.93 0.63 0.83 0.77 1.00 0.45

27 0.63 0.63 0.54 0.08 0.72 0.72 0.15 0.95 0.00 0.94 1.00 0.19

28 0.24 0.33 0.77 0.97 0.32 0.32 0.78 0.83 0.98 0.64 1.00 0.28

29 0.68 0.69 0.99 0.55 0.45 0.45 0.66 0.94 0.57 0.98 1.00 0.22

30 0.79 0.78 0.41 0.50 0.00 0.00 0.93 0.86 0.07 0.85 1.00 0.47

31 0.15 0.18 0.87 0.51 0.66 0.66 0.82 0.80 0.95 0.68 1.00 0.37

32 0.67 0.66 0.62 0.89 0.23 0.23 0.94 0.60 0.00 0.51 1.00 0.00

33 0.26 0.25 0.91 0.72 0.52 0.52 0.75 0.60 0.95 0.99 1.00 0.32

34 0.08 0.07 0.97 0.59 0.42 0.42 0.69 0.65 0.93 1.00 1.00 0.16

35 0.79 0.79 0.40 0.42 0.83 0.83 0.17 0.90 0.08 0.93 1.00 1.00

36 0.77 0.77 0.16 0.31 0.39 0.39 0.49 0.92 0.67 0.98 1.00 0.20

37 0.23 0.40 0.41 0.46 0.33 0.33 0.73 0.69 0.74 0.56 1.00 0.03

38 0.19 0.32 0.39 0.34 0.38 0.38 0.54 0.89 0.68 0.76 1.00 0.23

39 0.90 0.90 0.83 0.92 0.57 0.57 0.51 0.96 1.00 0.84 1.00 0.34

Economic-financial indicators: PIj1 - Total expenses on the services per m³ billed; PIJ2 – Operating expense per m³

billed; PIJ3 - indicator of financial performance; PIj4 – Index billing losses; PIj5 - Margin of expenses of employees;

PIj6 - Expense with employees in operating expenses; PIj7 - Electricity expense in operating expenses; PIj8 -

Participation in operating revenue in total revenue water; PIj9 - Billing days committed with accounts receivable.

Market Indicators: PIj1 - Index of total water service; PIJ2 – Index of urban water service; PIJ3 – Productivity index:

active savings per employee.

M – Municipality of sample.



M

Conformity of products indicators Customers indicators

PIj1 PIj2 PIj3 PIj4 PIj5 PIj6 PIj1 PIj2 PIj3 PIj4 PIj5

1 0.00 0.00 0.29 1.00 0.29 0.00 1.00 0.95 0.99 0.99 0.99

2 0.96 0.98 0.68 0.11 0.68 0.00 0.84 0.99 0.96 0.99 0.00

3 1.00 1.00 0.94 0.13 0.94 0.52 1.00 0.82 0.82 1.00 0.95

4 0.00 0.98 0.89 0.10 0.89 0.52 1.00 0.85 0.00 0.00 0.00

5 0.00 0.90 0.88 0.32 0.88 0.04 1.00 0.00 0.97 0.00 0.86

6 1.00 1.00 0.82 0.14 0.82 0.71 0.95 0.91 0.73 0.99 0.97

7 0.00 1.00 0.97 0.14 0.97 0.45 0.16 0.83 0.00 0.00 0.00

8 0.00 1.00 0.64 0.04 0.64 0.37 1.00 0.84 0.00 0.00 0.00

9 0.00 1.00 0.88 0.12 0.88 0.61 1.00 0.88 0.97 0.00 0.95

10 0.00 1.00 0.86 0.15 0.86 0.62 0.95 0.90 0.90 0.61 1.00

11 0.00 1.00 0.96 0.11 0.96 0.64 1.00 0.91 0.00 0.00 0.00

12 0.92 0.94 0.36 0.00 0.36 0.84 0.92 0.98 0.89 0.00 0.00

13 0.00 0.97 0.74 0.24 0.74 0.96 1.00 0.96 0.00 0.00 0.00

14 1.00 1.00 0.76 0.05 0.76 0.78 0.67 0.94 0.99 1.00 1.00

15 0.00 1.00 0.99 0.19 0.99 0.70 1.00 0.91 0.85 0.99 0.96

16 0.00 0.74 0.65 0.27 0.65 0.35 0.94 0.64 0.00 0.00 0.00

17 0.94 1.00 0.92 0.20 0.92 0.00 1.00 1.00 0.85 0.83 0.99

18 0.97 1.00 0.85 0.06 0.85 0.40 1.00 0.84 0.00 0.00 0.00

19 0.00 0.76 0.50 0.47 0.50 1.00 1.00 0.95 0.92 0.00 1.00

20 0.98 1.00 0.59 0.29 0.59 0.42 1.00 0.69 0.99 0.00 0.97

21 1.00 1.00 0.71 0.07 0.71 0.76 1.00 0.94 0.00 0.98 0.98

22 1.00 0.81 0.59 0.06 0.59 0.49 1.00 0.89 0.00 0.94 0.00

23 0.00 0.82 0.61 0.02 0.61 0.35 1.00 0.87 0.00 0.00 0.00

24 0.40 1.00 0.91 0.18 0.91 0.58 0.93 0.84 0.98 0.83 0.99

25 0.00 0.99 0.93 0.19 0.93 0.34 0.54 0.77 1.00 0.00 0.00

26 0.00 1.00 0.85 0.05 0.85 0.32 0.90 0.78 0.95 0.00 1.00

27 1.00 1.00 0.71 0.25 0.71 0.00 0.00 0.24 0.00 0.00 0.00

28 0.98 1.00 0.93 0.17 0.93 0.78 1.00 0.93 0.00 0.00 0.00

29 0.00 1.00 0.96 0.19 0.96 0.33 0.98 0.74 0.00 0.00 0.00

30 0.00 0.81 0.60 0.26 0.60 0.54 0.00 0.78 0.00 0.00 0.00

31 0.21 1.00 0.98 0.07 0.98 0.55 0.79 0.86 1.00 1.00 0.00

32 0.00 0.98 0.61 0.78 0.61 0.96 0.00 0.90 0.90 0.00 0.93

33 0.81 0.98 0.90 0.18 0.90 0.82 0.81 0.93 0.99 1.00 0.00

34 1.00 1.00 0.69 0.08 0.69 0.40 1.00 0.84 0.00 0.00 0.00

35 1.00 0.96 1.00 0.05 1.00 0.65 1.00 0.89 0.96 0.97 0.98

36 0.00 0.98 0.87 0.17 0.87 0.36 0.60 0.71 0.00 0.76 0.99

37 0.00 0.97 0.49 0.00 0.49 0.36 1.00 0.86 0.00 1.00 0.00

38 0.00 0.98 0.86 0.07 0.86 0.34 0.69 0.78 0.93 0.95 0.00

39 0.94 1.00 0.46 0.52 0.46 0.00 1.00 0.99 0.00 0.90 0.99

Conformity of products indicators: PIj1 - Index of macromeasurement; PIJ2 – Index of hydrometration; PIJ3 - Average

water consumption by economy; PIj4 – Water consumption billed by economy; PIj5 - Average per capita consumption

of water; PIj6 - Index of losses in distribution;

Customers Indicators: PIj1 - Index of water fluoridation; PIJ2 – Loss index per connection; PIJ3 – Incidence of analysis

of residual chlorine nonstandard.




Appendix A.2

Indicators and measures of sanitary sewerage

M

Economic-financial

indicator

Conformity

of products

indicator

Market indicators Customers

indicators

PIj1 PIj2 PIj1 PIj1 PIj2 PIj3 PIj4 PIj1

1 0.00 0.65 0.00 0.00 0.90 1.00 0.68 0.00

2 0.70 0.82 0.75 0.24 0.61 0.78 0.75 1.00

3 0.77 0.74 0.00 0.43 0.99 1.00 0.80 0.00

4 0.98 0.69 0.00 0.19 0.90 1.00 0.91 0.00

5 0.00 0.83 0.91 0.05 0.95 1.00 0.91 1.00

6 0.36 0.77 0.88 0.43 0.91 1.00 0.88 1.00

7 0.81 0.80 0.05 0.24 0.84 1.00 0.80 0.07

8 0.93 0.76 0.70 0.45 0.49 0.60 0.69 1.00

9 0.46 0.59 0.79 0.42 0.92 0.98 0.78 1.00

10 0.46 0.27 0.00 0.25 0.51 0.51 0.80 0.00

11 0.45 0.51 0.00 0.15 0.82 0.82 0.80 0.00

12 0.48 0.17 0.00 0.20 0.41 1.00 0.00 0.00

13 0.75 0.54 0.00 0.60 0.80 1.00 0.97 0.00

14 1.00 0.02 0.05 0.13 0.05 0.06 0.04 1.00

15 0.68 0.64 0.00 0.24 0.79 0.95 0.80 0.00

16 0.00 0.48 0.81 0.38 0.92 1.00 0.80 1.00

17 0.08 0.72 0.00 0.24 0.83 0.98 0.80 0.00

18 0.79 0.84 0.94 0.38 0.93 0.98 0.93 1.00

19 0.87 0.92 0.96 0.30 0.99 1.00 1.00 0.95

20 0.23 0.76 0.83 0.27 0.94 1.00 0.82 1.00

21 0.00 0.83 0.61 0.28 0.60 0.75 0.60 1.00

22 0.74 0.00 0.00 0.27 1.00 1.00 0.80 0.00

23 0.93 0.26 0.94 0.17 0.30 0.36 0.93 1.00

24 1.00 0.00 0.01 0.11 0.00 0.00 0.00 1.00

25 0.00 0.52 0.93 0.62 0.81 0.97 0.92 1.00

26 0.83 0.45 0.02 0.45 0.89 1.00 0.80 0.03

27 0.00 0.93 0.81 0.19 0.97 1.00 0.80 1.00

28 0.98 0.63 0.58 0.28 0.75 0.98 0.84 0.69

29 0.57 0.94 0.00 0.22 0.98 0.99 0.80 0.00

30 0.07 0.57 0.43 0.47 0.93 1.00 0.42 1.00

31 0.95 0.88 0.55 0.37 0.85 1.00 0.80 0.68

32 0.00 0.00 0.00 0.00 0.27 0.59 0.25 0.00

33 0.95 0.00 1.00 0.32 0.93 1.00 0.99 1.00

34 0.93 0.00 0.09 0.16 0.07 0.07 0.08 1.00

35 0.08 0.83 0.00 1.00 0.97 1.00 1.00 0.00

36 0.67 0.89 0.00 0.20 0.99 1.00 1.00 0.00

37 0.74 0.20 0.35 0.03 0.10 0.19 0.34 1.00

38 0.68 0.82 0.00 0.23 0.84 1.00 0.60 0.00

39 1.00 0.94 0.00 0.34 0.92 1.00 0.85 0.00

Economic-financial indicators: PIj1 - Billing days committed to accounts receivable; PIJ2 – Participation in operating

revenue in total revenue sewage;

Conformity of products indicators: PIj1 - Index of treated sewage compared to water consumed;

Market indicators: PIj1 –Productivity index: active savings per employee; PIj2 - Index of total sewage service; PIj3 -

Index of urban sewage service; PIj4 - Index sewage collection produced;

Customers indicators: PIj1 - Index of sewage collected treatment.




Appendix A.3

Indicators and measures of solid waste

M

Economic-financial

indicators Market indicators Customers indicators

PIj1 PIj2 PIj3 PIj1 PIj2 PIj3 PIj4 PIj1 PIj2 PIj3 PIj4

1 0.85 0.95 0.27 0.61 0.24 0.07 0.15 0.21 0.08 0.18 0.07

2 0.73 0.00 0.95 0.14 0.51 1.00 1.00 0.05 0.04 0.00 0.00

3 0.84 0.93 0.64 1.00 0.32 0.10 0.13 0.00 0.00 0.00 0.00

4 0.67 0.90 0.68 0.92 0.39 0.00 0.00 0.08 0.06 0.00 0.13

5 0.85 0.94 0.50 0.79 0.35 0.00 0.18 0.00 0.00 0.00 0.01

6 0.94 0.99 0.00 1.00 0.00 0.09 0.10 0.00 1.00 0.78 0.04

7 0.83 0.92 0.71 0.79 0.56 0.18 0.06 1.00 0.97 0.00 0.17

8 0.89 0.98 0.69 0.28 0.30 0.10 0.23 0.97 0.46 0.00 0.00

9 0.87 0.95 0.71 1.00 0.34 0.38 0.00 0.00 0.00 0.00 0.00

10 0.00 0.77 0.18 1.00 0.39 0.00 0.00 0.00 0.00 0.00 0.17

11 0.96 0.76 0.84 0.41 0.33 0.00 0.00 0.00 0.00 0.00 0.00

12 0.88 0.99 0.99 0.09 0.61 0.00 0.00 0.17 0.29 0.00 0.00

13 0.89 0.95 0.77 0.30 0.39 0.14 0.13 0.57 0.36 0.37 0.03

14 0.89 0.84 0.76 0.50 0.44 0.08 0.07 0.00 0.00 0.00 1.00

15 0.90 0.95 0.97 1.00 0.22 0.07 0.02 0.00 0.00 0.00 0.12

16 0.93 0.97 0.90 0.70 0.47 0.08 0.05 0.00 0.00 0.00 0.05

17 0.89 0.97 0.87 0.77 0.40 0.29 0.04 0.00 0.00 1.00 0.04

18 0.00 0.00 0.00 0.93 0.39 0.19 0.02 0.88 0.54 0.63 0.00

19 0.95 0.98 0.84 0.98 0.22 0.09 0.11 0.00 0.00 0.00 0.01

20 0.83 0.97 0.00 1.00 0.00 0.16 0.22 0.00 0.00 0.00 0.12

21 0.96 1.00 0.86 1.00 0.23 0.19 0.10 0.00 0.00 0.00 0.06

22 0.91 0.00 0.96 1.00 0.54 0.87 0.00 0.00 0.00 0.00 0.04

23 0.97 1.00 0.92 0.43 0.33 0.00 0.00 0.00 0.00 0.00 0.00

24 0.85 0.94 0.73 0.35 0.33 0.25 0.08 0.94 0.49 0.63 0.03

25 0.91 0.98 0.96 0.35 0.42 0.33 0.15 0.94 0.61 0.56 0.00

26 1.00 0.00 0.00 0.92 0.00 0.19 0.22 0.42 0.01 0.14 0.00

27 0.79 0.94 0.00 1.00 0.00 0.34 0.45 0.00 0.47 0.33 0.23

28 0.94 0.99 0.85 1.00 0.29 0.07 0.16 0.66 0.40 0.33 0.06

29 0.70 0.89 0.53 1.00 0.46 0.30 0.23 0.56 0.40 0.28 0.06

30 0.90 0.98 0.00 0.72 0.23 0.00 0.00 0.22 0.08 0.07 0.07

31 0.66 0.00 0.00 1.00 0.41 0.36 0.31 0.00 0.00 0.00 0.13

32 0.25 0.93 0.91 0.37 0.59 0.93 0.57 0.00 0.00 0.00 0.75

33 0.79 0.91 0.00 1.00 0.09 0.04 0.77 0.00 0.00 0.00 0.00

34 0.88 0.92 0.77 1.00 0.32 0.04 0.13 0.00 0.00 0.01 0.02

35 0.64 0.81 0.34 0.88 0.43 0.17 0.09 0.14 0.10 0.10 0.08

36 0.86 0.97 0.91 0.96 0.34 0.23 0.10 0.61 0.32 0.23 0.07

37 0.73 0.92 1.00 0.00 1.00 0.78 0.35 0.00 0.00 0.00 0.09

38 0.94 0.98 0.97 0.95 0.50 0.25 0.17 0.00 0.00 0.00 0.00

39 0.95 0.99 0.89 0.73 0.37 0.11 0.22 0.51 0.31 0.22 0.11

Economic-financial indicators: PIj1 - Per capita expense on the services of solid waste; PIJ2 - Index of financial costs in

the municipality solid waste; PIj3 - Unit cost of solid waste collection;

Market indicators: PIj1 – Rate of full coverage of collection RW; PIj2 - Mass of RW+PW collected per capita; PIj3 -

Rate of sweeper per urban inhabitant; PIj4 - Rate of weeding per urban inhabitant;

Customers indicators: PIj1–Recovery rate of recyclable regarding HW and PW; PIj2 - Mass recovered per capita HW

and PW; PIj3 - Mass per capita collected via selective collection; PIj4 - Mass of SWH per capita collected.

RW: residential waste; PW: public Waste; HW: Household waste; SWH: Solid waste health




M

Conformity of products indicators

PIj1 PIj2 PIj3 PIj4 PIj5 PIj6 PIj7 PIj8

1 1.00 0.75 1.00 0.50 0.50 1.00 0.00 0.00

2 0.50 0.75 1.00 0.25 1.00 1.00 1.00 0.33

3 1.00 1.00 1.00 0.75 1.00 1.00 1.00 0.33

4 1.00 0.50 1.00 0.25 0.50 0.00 1.00 0.33

5 1.00 0.75 0.50 0.25 1.00 1.00 1.00 0.33

6 1.00 0.75 1.00 0.25 1.00 1.00 1.00 0.67

7 1.00 1.00 1.00 1.00 0.50 0.00 0.00 0.33

8 1.00 0.75 1.00 0.75 0.00 0.00 0.00 0.00

9 0.50 0.75 1.00 0.75 1.00 1.00 0.00 0.00

10 1.00 0.50 1.00 0.00 1.00 1.00 1.00 0.67

11 0.50 1.00 0.00 0.00 0.50 1.00 1.00 0.00

12 1.00 0.50 1.00 1.00 0.00 0.00 0.00 0.00

13 0.50 0.75 1.00 1.00 1.00 0.00 1.00 0.67

14 1.00 0.00 1.00 0.25 1.00 1.00 1.00 0.67

15 1.00 1.00 1.00 1.00 0.75 0.00 0.00 0.33

16 0.50 0.75 1.00 0.25 1.00 1.00 0.00 0.00

17 0.50 1.00 1.00 0.75 0.50 0.00 0.00 0.00

18 0.50 1.00 1.00 0.25 1.00 0.50 1.00 0.67

19 1.00 0.75 1.00 0.25 1.00 1.00 0.00 0.00

20 1.00 1.00 1.00 0.75 1.00 0.25 1.00 0.67

21 1.00 1.00 1.00 0.25 1.00 1.00 0.00 0.00

22 0.50 0.50 1.00 0.25 0.00 0.00 0.00 0.00

23 1.00 1.00 1.00 0.75 1.00 0.00 0.00 0.00

24 1.00 0.75 1.00 1.00 0.75 1.00 0.00 0.00

25 0.50 1.00 0.50 1.00 0.75 1.00 0.00 0.00

26 0.00 0.75 1.00 0.75 0.25 0.00 0.00 0.00

27 1.00 1.00 1.00 1.00 0.00 0.00 0.00 0.00

28 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00

29 1.00 0.75 1.00 1.00 1.00 1.00 1.00 0.67

30 1.00 0.75 1.00 1.00 1.00 1.00 0.00 0.33

31 0.50 1.00 1.00 0.75 1.00 1.00 0.00 0.00

32 0.50 1.00 1.00 0.25 0.00 0.00 1.00 0.00

33 1.00 1.00 1.00 0.25 0.00 0.00 0.00 0.00

34 1.00 0.00 1.00 0.25 1.00 1.00 1.00 0.67

35 1.00 1.00 1.00 0.75 0.00 0.00 0.00 0.00

36 1.00 1.00 1.00 1.00 0.00 0.00 0.00 0.00

37 1.00 0.50 1.00 0.00 0.00 1.00 0.00 0.00

38 1.00 1.00 1.00 0.25 1.00 1.00 1.00 0.67

39 1.00 0.75 1.00 0.75 0.50 1.00 1.00 0.00

Conformity of products indicators: PIj1 - Collection and treatment of SWH; PIj2 - Billing and collection for the services

of CCW and CDW; PIj3 - Street sweeping, weeding and mowing; PIj4 - Recyclables Waste Collection with Collectors;

PIj5 - Recyclables Waste Collection with Collectors; PIj6 - Environmental Licensing (EOL, PEL or ELO); PIj7 –Water

proofing Processing Unit; PIj8 - Draining Gas and Leachate Treatment.

SWH: Solid Waste from health; CCW: Civil Construction Waste; CDW: Construction and demolition waste; EOL:

Environmental operating license; PEL: Preliminary environmental license; ELO: Environmental license of operation.


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