Scoring - Elimination

8/2/2019 Scoring - Elimination

http://slidepdf.com/reader/full/scoring-elimination 1/8

Kassab, M., Hegazy, T., and Hipel, K.W. 1

Multiple Criteria Decision Support for Infrastructure

Privatization

M. Kassab1, T. Hegazy

2, and K.W. Hipel

1

1. Systems Design Engineering Dept., University of Waterloo, Waterloo, ON, N2L

3G1, Canada; PH: (519) 888-4567 ext.: 33283; FAX: (519) 888-6197.

2. Civil Engineering Dept., University of Waterloo, Waterloo, ON, N2L 3G1, Canada;

PH (519) 888-4567 ext.: 32174; FAX (519) 888-4349; e-mail: [email protected]

Abstract

In this paper, a multi-criteria decision making (MCDM) framework is introduced for

evaluating and comparing a wide range of privatization schemes for infrastructurefacilities. The proposed framework helps the decision maker identify all stakeholders,

their options, and their preferences. Two MCDM techniques are applied

consecutively to arrive at the most suitable privatization decision: (1) the Eliminationmethod which uses user-defined thresholds to eliminate unfeasible alternatives; and

(2) the Scoring method that uses user-defined criteria to score the short-listedsolutions and arrive at the best one. Based on the framework, a computerized decisionsupport system has been developed and tested on a case study involving the

privatization of a water treatment plant.

Introduction

In recent years, there has been a growing trend towards involving the private

sector in the management and operation of infrastructure systems, particularly in

areas such as transportation, water and wastewater, and power. Among the factorsthat have triggered the privatization trend are: aging infrastructure, escalating

demands on infrastructure services due to population growth, the scarcity of governmental resources, the increase in globalization, and the realization bygovernments that they are unable to provide efficient services. All of these factors are

operating around the world and have opened the door for private investors in more

than one hundred countries (National Science Foundation 2004) to finance, manageand own infrastructure projects that were once considered the sole responsibility of

the government.




Despite its successes in many countries, privatization has resulted in some

disasters. For example, in the early 1970s, France awarded four road concessions,

three of which went bankrupt after the oil shock and were bailed out by the French

government (Guasch 2003). About the same time, many of the 12 highway franchisesin Spain had higher costs than anticipated, while traffic was much lower than

expected. Three highways went bankrupt and the remaining contracts requiredrenegotiation. In Canada, the privatization of Hamilton waste water sewage project in1995 failed due to the failure of the private partner to meet its contract obligations.

These examples illustrate a common experience: most private infrastructure

concession contracts are renegotiated. In the literature, Guasch (2003) examined morethan 1,000 different private concession contracts covering the sectors of transport,

power, water, and telecommunications awarded during the 1990s in Latin America

and found that, within three years, terms had been changed substantially in over 60 percent of the contracts. Many of the problems associated with infrastructure

privatization decisions resulted from the lack of a systematic methodology to choose

the proper privatization option.

Privatization: A challenge

In general, the commonly used selection process for selecting the privatization

proposals involves identifying the alternatives, stakeholders, criteria and preferencesrelated to a given privatization situation. With the main functions that can be

privatized being ownership, investment, operation, billing, and maintenance, various

combinations of these functions produce different Public-Private Partnership (PPP)alternatives. Each of these alternatives suits specific circumstances and stakeholders’

preferences to different degree. To compare among various privatization scenarios,

various categories of criteria have been used in the literature (Gleick 2002; Loxely

1999; Park 1999; UNIDO 1996). Common categories include public/social,technological, operational and administrative efficiency, economical, environmental,

and political criteria. The criteria also include both numeric and non-numeric aspects.

In the literature, many methods have been used in evaluating PPP options,

such as net present value (NPV), the Kepno-Trego technique (Tiong and Alum 1997),and the single-criterion evaluation technique (Smith 1999). In general, however,

existing methods lack a comprehensive decision support for all the steps involved,

including identifying PPP alternatives, short listing of feasible ones, and making afinal decision, considering the preferences of all stakeholders.

Decision support system for privatization

The proposed decision support system for infrastructure privatization isstructured as shown in Figure 1. It includes a literature compilation of the typical

options and evaluation criteria used by various stakeholders in various privatization

situations. Also, as shown at the right side of Figure 1, the core of the DSS is amultiple criteria decision analysis (MCDA) module. This module integrates several

methods as discussed in the following subsections.




The Elimination method

The elimination method (MacCrimmon 1973; Radford 1989) provides theability to eliminate some of the decision alternatives that do not meet certain

acceptance thresholds set by the stakeholders involved. The elimination method

involves: Listing the acceptance thresholds rules; eliminating infeasible solutions;

and finally ranking the short listed solutions. In the fist stage, acceptance rules areranked from most important at the top to least important at the bottom, based on

brain-storming, as shown in the left side of Figure 2. Then, each alternative is scored

with respect to each acceptance rule (numeric and non-numeric scores are possible).For example, the last rule specifies that for an alternative to be accepted, the

percentage of foreign shareholders should not exceed 50%. As shown in Figure 2,

alternatives 1 and n are unacceptable (shaded) because they were scored higher that50%. Following this process, all the failures to meet the acceptance rules were

highlighted. The leasing alternative, for example, fails with respect to Technology

Transfer (its score, 8%, is less than the 10% threshold). At the end of the process,short listed solution are identified as the ones that pass the upper rules (highest

priority) and also have less rules being violated. All others are then eliminated. As

shown in the example of Figure 2, the strength of this technique is its simplicity inidentifying and eliminating less desirable alternatives. In addition, this method allows

the user to use richer rules that have combined and/or conditional thresholds.

Group Decision Making: The Scoring Method

After prescreening using the elimination method, a short list of the more

preferred alternatives is ready for group decision analysis. In this process, the short

listed alternatives are evaluated against detailed criteria that reflect the preferences of various stockholder groups. In this process, first the important criteria and their

weights are defined, then, the expected consequences of each alternative are assigned

numerical values by each group. The overall preference score or value for eachalternative is simply the weighted summation of its scores for all the criteria.

- Stakeholders

- Options

- Preferences

- Solution Acceptance Rules

- Evaluation Criteria

User Interface

Figure 1: Component of the DSS for Infrastructure Privatization

MCDSS

Components

Scoring Method

- Screening alternatives

Elimination Method

- Arrive at best the solution

Optimum Decision




Giving a score i

jv for alternative i with respect to each criterion j with weight w j, then

the overall score, vi, for alternative i is given weighted sum represented as:

1 1 2 2 3 3

1

...........q

i i i i i i

q q j q

j

v w v w v w v w v w v=

= + + + + = ∑

Prototype Decision Support System

Using the macro language of Microsoft Excel, a prototype Decision SupportSystem (DSS) was developed. Basically, the decision support system was developed

as a workbook that contains several worksheets, including a main screen with a

simple interface and buttons to activate the step-by-step process, as shown in Figure

3. The interface automates all of the computations involved and allows the user or

decision maker to interact with the system to obtain decision support.

Score for Privatization Alternatives

1 2 3 4 n

Ranked Acceptance Rules Threshold Asset Sale Leasing O & M BOT Services

Public and Social Impact ≥ B+ B+ B- B+ B+ B-

Technology Transfer (%) > 10 % 15 8 13 7 12.5

Operational Efficiency ≥ 10% 40 15 20 30 12Economic Cost Reduction (millions) ≥ 1m 1.6 1.1 1.2 0..9 1.75

Degree of Risk Transfer to Government < 35% 10 29 25 25 25

Environmental Protection > B C B C+ A B-

Political (Foreign Shareholders) ≤ 50% 60% 15% 9% 20% 70

Failed on Rules 1, 2, 6

Failed on Rules 1, 6, 7

Failed on Rules 2, 4

Failed on Rules 6, 7

Failed on Rule 6

a) Scoring of Alternatives

b) Ranking of Alternatives

Figure 2: Elimination Method Example

Figure 3: Main Menu Screen

1

2

3

Basic Data:- Stakeholders

and options

Elimination Method- Short listing of

solutions

- Scoring and selectionof solution with top score




Privatization case study

In December 1994, a Regional Municipality in the province of Ontario,Canada signed a ten-year, $180 million contract with a private company. The contracttransferred the region’s water and sewage system operation, management and

maintenance responsibilities to the private sector. When the deal was signed, it wasthe largest private-public partnership (PPP) agreement of this type in North America.Details on the decision-making process that resulted in the selection of (Operation &Maintenance O&M) are not available. However, a detailed report (Loxely 1999)highlighted the flaws in this PPP agreement and its failure. Using the proposed DSS,a comparison is made between the system’s suggested solution and what historicallyhappened. The step-by-step analysis is described as follows:

Step 1: Identify stakeholders and their mutually exclusive options. Fivestakeholders were specified in this case study, as shown in Figure 4. The firststakeholder is the Private sector, which has four decision options: rebuild and operate

(R&O), renovate-operate-manage (R&O&M), operate and manage (O&M), andfinally Purchase the whole facility (purchase). The Second stakeholder is theEmployees, represented by their union. It is assumed that they have two decisionconditions for approving any proposal: a guarantee that no employee be fired, or aguarantee that the facility will remain unionized. The third stakeholder representsPublic users. This group is assumed to have two decision options for approving proposals: fee increases must be less than 2% annually or open bid competition must be allowed to prevent a monopoly. The fourth stakeholder is the Environmentalgroup, which has two decision conditions: installation of a filtration system to screenout any hazardous materials, or regular quality control and tests by an independent party. Finally, the fifth stakeholder group is the Government, having two decisionconditions: No share for non-Canadian private sector; or at least 51% of the privatesector should be Canadian owned. It is noted that the specified options represent thestakeholders’ mutually exclusive choices. Based on these options, their combinations(4x2x2x2x2=64) represent the number of privatization alternatives or decision states.

Figure 4: Stakeholders, Options, and Alternative Decisions

5Stakeholders

and their options

Total solutions: 64




Step 2: Short listing feasible solutions. Given 64 decision states, it is important toidentify and exclude any solutions with infeasible options. In the present case study,nine acceptance rules are used (left side of Figure 5). Once the acceptance rules werespecified, each of the possible solutions was evaluated with respect to the rules, asshown in the right side of Figure 5. Accordingly, the program highlighted the failures

of each solution. For example, solution 34 (soln 34) fails with respect to the 6

th

andthe 7th rules since its level of environmental protection is B, and its foreign ownershipexceeds the threshold limit of 50%.

Thus, based on the weights of the rules and the evaluation values, the system rankedthe solutions depending on how many rules were satisfied. For example, solution 36is ranked 57 since it violates 6 rules. After eliminating low ranked alternatives, ashort list of 10 feasible alternatives was generated.

Step 3: in this step, the short listed solutions were exposed to a more detailed analysisusing the simple scoring method, to determine the best solution. This processinvolved defining the important evaluation criteria and soliciting their relativeweights from the stakeholders, as shown in the left hand side of Figure 6. Theweights represent the relative importance and indicate the relative preference of all parties with respect to the final decision.

Figure 6: Simple Scoring Method

Evaluating the solutions with respect toacceptance rules (Scores made by user)

Figure 5: Applying the Elimination Method

rule 1rule 2rule 3

rule 4rule 5

rule 6

rule 7rule 8

rule 9

Acceptance rules

Stakeholders Solution 6Private sector R&O&M

Employees Unionize

Public users <2% Increase

Environmentals Regular tests

Government No shareWeights specified

by user




Once the criteria and their relative weights (sum to a total of 1.0) were determined,the evaluation process proceeded. In this process, the stakeholders’ scores wereaveraged for each short listed solution, with respect to each criterion. As shown inFigure 6, scores were assigned on a scale of 1 to 100. Next, the total score achieved by each solution is calculated by the system; and finally, as shown in Figure 6, the

system highlighted solution 6 with the highest score.

In solution 6, the most important issue for the Government is the “efficiency and costsaving” criterion which corresponds to the private sector being able to perform the job and save the Government money. Hence, the Government assigned it a score of 90. The second criterion is “Financial risk transfer”, because it represents other serious problems facing the government, which are budget cuts and emergencyfinancing. A score of 70 was assigned to reflect its importance. The third criterion is“Operational efficiency”, which scored 70 due to the importance of saving moneyand providing adequate service. Next, the “Environmental risk & quality of service”criterion scored a value of 50, and the “Issues of accountability and transparency”scored a low value of 20 because the union and the environmental groups will bemonitoring Private sector performance. Next, the “Impact on workers andcommunity” criterion also scored a low value of 20 due to the existing union, and theabsence of foreign ownership and the inclusions of environmental monitoring. Thelast criterion, “Economic development benefits” was assigned a high score of 90 asone of the main reasons for outsourcing these facilities is to help the local economy.

The DSS determined that solution 6 “Renovate-Operate-Manage (R&O&M)” is a better decision than the failed decision of “Operate and Manage (O&M)” actuallyused. The R&O&M solution is different from O&M, because of the addition of thetask of renovating the old facility. Part of the failure of this real-life project was dueto the high cost of renovation to the government, in addition to the unsatisfactory performance of the private sector. As such, the current condition of the privatizedinfrastructure must be an important aspect to consider in the decision making process.

Conclusions

In this paper, a Multi-Criteria Decision-support System framework isintroduced to evaluate and compare a wide range of privatization schemes for infrastructure facilities. The framework is designed to consider the variousviewpoints of stakeholders and accordingly determine the most appropriate privatization decision that satisfies all stakeholders’ preferences. Two MCDA

techniques were utilized in the MCDSS procedure: the Elimination method, and theSimple scoring method. An example application of waste water treatment plant wasthen presented to demonstrate the practicality and usefulness of the developed prototype. The developed framework makes the selection process clear andtransparent and helps decision makers in the public and private sectors select the proper Public Private Partnership alternatives, and thereby save time and money.




References

Gleick, P.H, G. Wolff, E.L. Chalecki,and R. Reyes. (2002). The Privatization of Water and Water Systems. The World Water 2002-2003. Island Press, Washington, DC.

Guasch, J. L. (2003). Granting and Renegotiating Infrastructure Concessions: Avoiding the

Pitfalls. The World Bank, Washington DC.

Kassab, M., Hipel, K.W., and Hegazy, T. (2004). Infrastructure Privatization. The Second

National Symposium on Roads and Bridges Technologies, Tripoli, Libya.

Loxely, S. (1999). The Hamilton-Wentworth-Philip Utilities Management Corporation PPP .Hamilton, Ontario, Canada, 1999.

MacCrimmon, K.R. (1973). An Overview of Multiple-Objective Decision-Making . InMultiple-Criteria Decision-Making, J. L.Cochrance and M. Zeleny (eds.), Universityof South Carolina Press, Columbia, 18-44.

National Science Foundation (NSF). (2004).

http://www.nsf.gov/od/lpa/news/press/pr982.htm>(Feb. 24, 2004).

Park, H., and D. Choi. (1999). A study on Water Privatization in Korea. Korea AdvanceInstitute of Science and Technology, Korea.

Radford, K.J. (1989). Individual and Small Group Decisions. Springer Verlag, New York.

Smith, A.J. (1999). Privatized Infrastructure: The Role of Government . Thomas TelfordPress, London, UK.

Tiong, R. L. K., and J. Alum. (1997). Evaluation of Proposals for BOT projects. International Journal of Project Management , 15(2), 67-72.

UNIDO. (1996). UNIDO BOT Guidelines. United Nations Industrial DevelopmentOrganization, Vienna. Austria.

Scoring - Elimination

Documents

Transcript of Scoring - Elimination