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CHAPTER 7
SELECTION OF A BOT PROMOTER
7.1 INTRODUCTION
In many developing countries, rapid economic growth is surpassing infrastructure development.
Governments in these countries are unable to fund vital infrastructure development and
rehabilitation, and are therefore, exploring new infrastructure procurement routes through public-
private partnerships (PPPs) by arrangements like BOT. A BOT (Build-Operate-Transfer) project
can be described as a project based on the granting of a concession by a client (usually a public
or governmental agency) to a consortium or concessionaire (usually in the private sector) who is
required to ‘Build’ (including financing, design, managing project implementation, carrying out
project procurement, as well as construction), ‘Operate’ (including managing and operating the
facility or the plant, carrying out maintenance etc., delivering product/service, and receiving
payments to repay the financing and investments costs, and to make a margin of profit) and to
‘Transfer’ the facility or plant in operational condition and at no cost to the client at the end of
the concession period.
The BOT projects are gaining importance as the private sector not only have a greater credit
standing and capacity to finance the large scale projects but also have better and efficient
managerial capabilities. If procured properly, the BOT option offers a win-win solution to the
government as well as the private sector. From the government’s perspective, private sector
funding put in less strain on the government whilst bringing an added advantage of cost and
resource efficiency to the project. From the private sector’s perspective, BOT projects present
great opportunities to expand investment and earn higher returns.
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A significant repositioning of risks between project participants is a striking aspect of the
procurement paradigm of BOT. The risks that are generally assumed by the governments are
transferred to the private sector in BOT projects leading the BOT concessionaire engulfing into
far more and deeper risks than a contractor for traditionally procured projects [76][8][132].
Moreover, the eccentricity of construction is that no two projects are identical in terms of site
conditions, design, use of materials, labor requisite, plants and equipment requirements,
construction methods, technical complexity, and degree of managerial skills required. Further,
under BOT arrangement, the project is also greatly influenced by the political, legal,
environmental, economical and commercial risks. In such a situation, one critical contributor to
the success of a BOT project is the selection of an appropriate concessionaire who has the
capacity to provide the best overall deal throughout the build-operate-transfer process. Further a
number of multi-national financial institutions such as the World Bank and Asian Development
Bank have strongly recommended the use of competitive selection procedure for PPP
infrastructure projects. However, the low-bid, while promoting competition and a transparent fair
playing procedure may not result in the best value for money expended.
The concessionaire selection should therefore involve a selection technique which should give
the best value to the owner. A workable selection technique should clearly indicate the stages
involved in the selection process and what measures to take at each stage [97]. It should enable
evaluators to derive both quantitatively and qualitatively the relative benefits, drawbacks, and
risks involved in each alternative tender. Internationally open competitive tendering is a trend in
the concessionaire selection practices. This open competitive tendering process consists of the
following stages :(1) request for prequalification (RFQ);(2) prequalification; (3) tender
invitation; (4) tender evaluation and short listing; (5) negotiations with short listed bidders; and
(6) selection of best tender and award of concession [73]. The non price factors such as the
financial, technical, managerial capabilities of the promoter are taken into consideration during
the prequalification stage. A major problem that has been encountered in BOT projects is the
time delay during the prequalification stage of the tendering process. The government generally
takes around six months to 1 year time for prequalification of the applicants in the PPP projects.
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Globally, the binary method of selection (selecting consortia) that meets all the pre-established
“must” criteria while rejecting any consortium that fails to satisfy any of these criteria has been
used extensively while short listing the applicants during the pre-qualification process. This
practice does not rank the applicants and as such all the qualified applicants satisfying the “must”
criteria are short listed for further selection process, which in most cases is a very large number,
and the further selection process becomes costlier as well as time consuming.
The industry therefore needs a method which can rank the various promoters so that the number
required for prequalification can be selected. In this chapter a transparent, multi-attribute
decision support system has been developed for addressing the pre-qualification issues such as
the decision criteria analysis, weights assessment and decision model development. Further, a
best value procurement model is developed to select the private sector partner which provides a
balance between the consideration of price and qualifications so as to provide the best value to
public procurer. Sensitivity analysis has been applied which will help the owners/governments to
ensure that the results would be sufficiently robust and due to a slight variation in one or more
weighting factors.
7.2 SELECTION PROCESS
A significant paradigm shift is noticed in project procurement by BOT concepts. In traditional
project the role of the contractor is reactive whereas in BOT project the concessionaire has to
play a proactive role. In traditional project the various function of finance, design, construction
and operation are fragmented and the relationships between various participants are often
confrontational.
Selection of the right concessionaire, which is critical to the success of such BOT-type PPPs,
depends on the quality of identifying and defining suitable project-specific criteria and the
quality of formulating an efficient tender evaluation methodology. The concessionaire of a BOT
project undertakes far more responsibilities and deeper risks than a contractor in a traditional
project. The selection of an appropriate concessionaire is absolutely crucial to the success of any
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BOT project. Therefore, it is necessary to formulate a workable and efficient selection
framework.
The concessionaire is often a consortium (special purpose company) formed for a particular
project and usually has no track record. What make things more complicated in concessionaire
selection is that the concessionaire has more commitments than a mere contractor. In addition to
construction, the concessionaire is also responsible for finance, design, long-term operation and
maintenance, and transfer of the project facilities to the client in operational conditions at the end
of the concession period. The competence of the concessionaire is dependent on the overall
resources and capabilities of the constituent companies, the concessionaire’s ability to formulate
competitive financial and technical packages, and the partnering skills of the proposed project
participants.
The characteristics of BOT type projects and the great commitments and broad risks assumed by
the concessionaire require a best value approach in the selection of an appropriate
concessionaire. In adopting the best value approach, owner/client should clearly define the
objectives it wishes to achieve, the relative importance of each value item, and the contributors
to each value item, and then develop both objective and subjective indicators to evaluate these
contributors. The owner’s objectives should be translated into an appropriate tender evaluation
package that contains a set of criteria and their corresponding value functions. The conflicts may
exist among various objectives in the best value selection scenario, and hence there should be a
trade off according to relative importance of these objectives.
This process is commonly used by governments or their agencies to serve three purposes:
• To obtain the best deal for the public;
• To be fair to all competing promoters; and
• To allow alternative proposals to be considered.
A typical evaluation and selection process in a competitive BOT tender is shown in Figure 7.1.
[73]
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Figure 7.1 : Selection Process in a Competitive Tender of BOT Project [73]
The various competitive tender evaluation methods are described in Table 7.1. [2]
Table 7.1. Competitive Tender Evaluation Methods
Tender Evaluation
Method Brief description
Simple scoring
method
Maximum achievable score points are assigned to each predetermined
selection criterion, against which alternative tenders are evaluated, and a score
is then awarded to each tender for each criterion. The awarded score for each
criterion may range from 0 to the predetermined maximum achievable score
points for that criterion. The total score for a tender is the sum of all awarded
score points for all evaluation criteria. The tender with the highest total score
is chosen as the winning tender.
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NPV method
This method is often used to assess the commercial and financial packages of a
BOT tender. For conforming or equivalent designs, the tender with the lowest
NPV of tolls/tariffs over the concession period is selected as the winning
tender. This method is suitable for projects where there are relatively correct
estimations of the quantities of products or services to be provided by the
project (such as a power or water treatment plant) based on the off-take
agreement. The client may also compare the NPV of the construction,
operation and maintenance costs, and financial charges over the concession
period (or even over the whole project life) for further evaluation.
Multi-attribute
analysis
Various criteria are classified into several criterion packages (e.g., financial,
technical, managerial, legal, and environmental). Each of these packages may
in turn include many sub-criterion packages. According to their relative
importance, varying weights are assigned to each main package and also to
each sub-package within that main package; and maximum available score
points are allocated to each criterion within a main or sub-package. Each
tender proposal is then evaluated against every criterion and awarded a score
for that criterion. The proposal with the highest total weighted score will be
chosen for the BOT concession.
Kepner – Tregoe
decision analysis
technique
This technique includes the following decision stages: formulating a ‘‘decision
statement,’’ identifying and weighting decision objectives (in terms of
‘‘MUST’’ and ‘‘WANT’’ criteria), generating alternatives, evaluating
alternatives against the MUST and WANT criteria, and selecting the most
suitable alternative. The decision statement provides the focus for the
following steps and sets limits in the selection. The MUST and WANT criteria
identify specific requirements of the decision. The MUST criteria function as a
screen to eliminate failure-prone alternatives by a ‘‘Yes-or-No’’ judgment.
Then, the remaining alternatives will be judged on their relative performance
against WANT criteria. The WANT criteria give the evaluator a comparative
picture of the remaining alternatives.
Two-envelope Price is submitted in a separate envelope. Tenders are assessed on non-price
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method criteria first. Then, the price envelope of the highest scoring proposal based on
non-price criteria is opened. If its price is within government’s budget (not
known to tenderers) then the contract is awarded to the highest scorer.
NPV method +
scoring method
Then NPV method is used for financial evaluation while the weighted point
scoring method is used for qualitative evaluation.
Binary method +
NPV method
Tenders are first evaluated against pre-established ‘‘MUST’’ criteria via the
binary method. Any tender failing to satisfy any ‘‘MUST’’ criteria is rejected.
Then, remaining tenders are evaluated against the NPV method.
In this research we have developed a two stage promoter selection process, it includes a
prequalification (short listing stage) as well as a bid evaluation stage. Since in the bid evaluation
stage the shortlisted bidders are required to specify only the amount of their bid and all other
parameters are fixed, the competence of the bidders has to be taken care of only during the
prequalification (short listing stage). If the shortlisted bidders are already available then the
prequalification is not needed and the BOT promoter can be selected only in one stage. A best
value model based on project specific characteristics has also been developed in which factors
other than price can also been considered to provide the best value for the money spent to the
facility procurer.
7.3 BEST-VALUE MODEL CONCEPTS
The majority of public sector construction contracts are awarded on a low bid basis. While the
low bid has promoted open competition and a fair playing field but it may not result in the best
value or the best performance during and after the construction. As noted by Scott the low bid
system encourages contractor to implement the cost cutting measures instead of quality
enhancing measures and therefore makes it less likely that contracts will be awarded to the best
performing contractors who will deliver the optimum quality projects.
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The best value procurement is viewed as a balanced between the consideration of price and
qualifications so as to provide the best value to the owner. The NCHRP 10-61 research study
recommends a few basic strategies to implement in the area of Best Value Procurement. The goal
for best value selection is to obtain the optimum combination of price and technical capabilities
of a contractor. However, owners should base best value selection criteria only on the project
elements that add measurable value to the project.
A definition of Best Value Procurement for construction is suggested as follows: “a procurement
process where price and other key factors are considered in the evaluation and selection process
to minimize impacts and enhance the long term performance and value of construction.”
7.4 DEVELOPMENT OF BEST VALUE PROCUREMENT METHODS
The best value model concept is shown in figure 7.2
Figure7.2 Best Value Model Concept
The following are the two best value procurement methods which can be implemented in the
following manner:-
i. One Step Best value Procurement: in these types of projects the owner determines that
there is no advantage to shortlist and prequalify the bidders through a competitive screening
system. The step by step procedure is as follows :
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a. Owner select the best value parameters for a given project and then selects best value
evaluation criteria associated with chosen best value parameter.
b. A best value rating (scoring system) is selected.
c. A best value award algorithm is then selected and a Request for Proposal (RFP) is published
detailing both award algorithm and the requirements to submit the information and
documentation to be a responsive best value bidder.
d. An evaluation panel can be form to conduct the best value proposals.
e. Proposals are then received and evaluated in accordance with the published evaluation plan
and the award is made using the selected best value award algorithm.
ii. Two Step Best Value Procurement: This method is for those projects where the bidders are
shortlisted through a competitive screening system. The two phase best value procurement
generally has the following steps:
f. From the qualifications and quality information a best qualified bidders are shortlisted. This
is done by publishing a Request for Qualification (RFQ) for each individual project using
evaluation criteria. For each evaluation criteria a measurable standard is developed to
measure the qualification.
g. List of prequalified bidders will be announced after evaluating the statements of
qualifications (SOQ).
h. A best value RFP will be published giving in detail both the award algorithm and the method
by which the step 1 qualifications will be carried over into the final evaluation.
i. The evaluation panel will evaluate all responsible proposals in accordance with the published
evaluation panel and the award will be made accordingly.
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he decision model is shown in figure 7.3 and the algorithm for the award is as follows.
Figure7.3. Decision Model of determining the successful offeror using qualitative cost technical
trade off.
Trade off analysis not only considers the rating and scores but the competing proposals are
analyzed by the selection officials and therefore it depends on the subjectivity and the judgment
of the selecting officials.
Weighted Criteria for both Price and Technical. In this algorithm the technical proposal and the
price proposal are evaluated simultaneously. A generic algorithm is as follows. The general
equation for the best value is shown as follows [101]
n
BVj = ∑ PSi Wi
i=1
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Where, BVj= best value for contractor j; n = number of parameters included in the best value
equations; PSi = parameter i scale; and Wi = weight of parameter i.
The offeror with the highest best value score is selected.
However, the best value score can be obtained by the analytical hierarchy process where the
various criteria are grouped into a progressively few groups to ultimately form a single criterion.
7.5 PREQUALIFICATION
As indicated in type I algorithm the final award decision is based on price and hence in most of
the countries including India prequalification process is adopted to shortlist capable bidders who
can provide best value to the owner/ public procurer. Like the traditional public sector
construction contracts, some form of pre-qualification is adopted for most BOT projects in
countries such as Australia, Canada, The Philippines, UK, USA, and India. The main aim of the
request of qualification (RFQ) is to shortlist a number of competitive proposals by consortia
which consist of reputable and experienced contractors, operators and bankers. In a competitive
tender for BOT concession, the number of promoters for the BOT contract may be limited due to
the technical, financial, and/or sometimes political constraints imposed upon the promoters.
As a general practice, detailed submissions are not sought in initial responses to an invitation to
develop a major infrastructure project. The preferred option is to identify the characteristics of
the companies or consortia submitting and from this develop a “shortlist” of perhaps 7 or 8
bidders. This procedure ensures that unsuccessful bidders are not required to incur unnecessary
costs. The pre-qualification process will therefore ascertain the financial, technical and
managerial ability of each consortium in undertaking the project.
For governments in some countries such as Malaysia, Hong Kong and Thailand, it is not the
practice to carry out pre-qualification of BOT promoters. In these countries, the invitation to
tender for a BOT project is announced in the newspapers and interested promoters are generally
given a period of 3-4 months to prepare detailed submissions. The reasons for these governments
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following this approach is that they believe that the scale of investments required for BOT
projects and the keen competition will deter small companies from submitting proposals. Instead,
it will attract only serious promoters who are financially strong. [95].
7.5.1 Request for Qualification in India.
In India, pre-qualification process is adopted to shortlist eligible bidders for the BOT projects.
The criteria of evaluation along with the schedule of bidding process are described in the RFQ
document. Most of the central government departments such as NHAI, Railways, Ministry of
Surface Transport and various state government departments such as Housing Boards, Municipal
Corporations, State Road Development Authorities etc. and various public sector undertakings
are using this route to develop their infrastructure facilities.
The document includes (i) Project brief, (ii) Instructions to applicant, (iii) Criteria for evaluation
and evaluating methodology, (iv) Schedule of bidding process, (v) Formats for application giving
eligibility details.
For developing an integrated township project under PPP concept the applicant’s competence
and capability has to be established based on the following parameters :
i. Technical experience
ii. Financial capability in terms of
a. Net worth
b. Net cash accruals
c. Annual income
The following is a list of documents normally asked to be submitted as part of the application :
i. Letter of Application, duly completed and signed by the applicant
ii. General information about the applicant with company profile, memorandum and articles
of association, etc.
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iii. Joint bidding agreement (applicable if a application is submitted by a consortium of
firms)
iv. Power of attorney for appointing lead member (applicable for a consortium)
v. Power of attorney in favour of the authorized signatory to application documents duly
attested by notary public.
vi. Information on litigation
vii. Information for technical qualification including supporting details.
viii. Information for financial qualification.
ix. Net worth certificate from the statutory auditors
x. Audited annual reports for the last 3 financial years.
xi. Undertakings from applicant firm/member of consortium; and holding/subsidiary
company (applicable for firms relying upon the experience of their holding or subsidiary
company)
xii. In case of a consortium, relevant information listed above shall be submitted for each
member.
xiii. The original RFQ document issued to the applicant, duly initialed on all pages by the
authorized signatory as a token of acceptance.
7.5.2 Prequalification Criteria
In general a two stage contractor selection process is adopted. In the first stage the non price
factors are considered to shortlist the promoters. This necessitates the establishment of a set of
appropriate selection criteria. Contractor prequalification is a typical multi attribute decision
making process involving a set of appropriate selection criteria. The issues involved include
weight assessment of various decision criteria where in relative importance of criteria and
evaluation of criteria assigned by decision makers are assigned both tangible and/or intangible
variables. These criteria are identified through a systematic research approach that includes
1. literature review of previous studies for PPPs and other type of contracts,
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2. Experience and lessons learnt from worldwide PPP practices and
3. Interviews/ correspondences/ postal surveys with international PPP experts and
experienced practitioners.
The binary method of selection (selecting consortia) that meets all the pre-established “must”
criteria while rejecting any consortium that fails to satisfy any of these criteria has been used
extensively while short listing the applicants during the pre-qualification process in India. This
practice does not rank the applicants and as such all the qualified applicants satisfying the “must”
criteria are shortlisted for further selection process, which in most cases is a very large number,
and the further selection process becomes costlier as well as time consuming.
Further mostly only two “must” criteria are used – (i) Financial capability and (ii) technical
experience of the consortia. This process does not provide any weightage to an entrepreneur who
may provide a leading role to manage the projects.
Lessons have been learned from some failed PPP projects, such as the two BOT transportation
projects in Thailand and the failure of Malaysia’s privatized national sewerage project. The
failure of this sewerage project was due to a number of reasons (Zhang 2005a) :
i. The lack of competition and transparency in the selection of the concessionaire.
ii. Low equity - debt ratio
iii. Over generous “safety nets” extended to the concessionaire by the government.
iv. Inefficiencies and management blunders of the concessionaire.
v. Frequent change of ownership of the concession company in a short period.
vi. Strong public opposition.
This shows clearly that the managerial capacity of the promoter/concessionaire is also an
important criterion which should be included at the pre-qualification stage. The short listing
evaluation process should use the multi attribute analysis method instead of the binary method
and should rank the applicants so that a predetermined number be included from the list in the
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order of their rank for further selection process. The procedure should be transparent and known
to all participants before submitting the proposal. In the subsequent section a multi attribute
method has been developed to select and rank the bidders/applicants.
7.5.3 Development of multi attribute method of ranking
The prequalification process is mainly aimed at reducing the number of interested consortia to a
shortlist (e.g., of seven or eight), each consisting of reputable and experienced contractors,
operators, and investors. Apart from additional commercial evaluations, compared with the DBB
approach, a much longer time horizon and more complicated contractual and financial
relationships need to be assessed in the tender for a BOT project.
7.5.4 Methodology of evaluation
The problem of evaluation of applicants reduces to that of a problem of multi attribute decision-
making where there could be conflicting objectives having different importance (weights) to the
owner. The methodology organizes the problem in the following sequential format:
• Step 1: Define basic criteria
• Step 2: Group basic criteria in to progressively fewer groups to ultimately
form a single criteria.
• Step 3: Rank the applicants.
• Step 4: Sensitivity Analysis. The sensitivity analysis is made to see the effect
of altering the weights of the criteria on the ranking of the alternatives.
7.5.5 Generation of a Four Package Criterion Set
The critical success factors identified in previous studies, evaluation criteria used in worldwide
PPP projects, and experience and lessons from international PPP practices enabled the
generalization of a four package criteria set for evaluation of the applicants. The four packages
considered are :
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Entrepreneural package Environmental package
FP1 net worth TP1 Experience of doing similar projects EP1 Leadership and entrepreneurshipEP1 Qualifications/ experience of safety, health and environmental personnel
FP2 Average Annual turnover TP2 Experience of other projects EP2 Project management skills EP2 Past health and safety performance
FP3 Annual Income TP3 Plants and equipments owned EP3 Risk management system EP3 ISO 14000 Certifications
FP4 Loan Agreement TP4 Strong and capable project teamEP4 Contractual relationships among participants
FP5 Equity - debt ratio TP5 Project organization structure
Technical packageFinancial PackageManagerial package
(i) Financial package consisting of five basic criteria
(ii) Technical package consisting of five basic criteria
(iii) Managerial Entrepreneur package consisting of four basic criteria
(iv) Managerial Environment package consisting of three basic criteria
The last two managerial packages are grouped into one package at the second level along with
the financial and technical packages. The details of these criteria are given in table 7.2. the
hierarchy is shown in figure7.4.
Table 7.2 : Evaluation Packages For Short Listing
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Figure7.4. Hierarchy of criteria for short listing/ prequalification
7.5.6 Development of the AHP model
The hierarchy developed consists of 5 levels as shown in figure7.4. The top level represents the
goal of ranking the project promoter. The last level is represented by the various alternatives that
is the promoters. The objectives of prioritizing the promoters is according to how they meet the
requirements as represented by the three major categories of financial, technical and managerial
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preferences. Thus, these objectives are assigned to the level just below the top level. The third
level constitutes the sub categories of only one major objective - managerial and at fourth level
constitutes the sub categories of these two major objectives and two sub objectives of the third
major objective. Fifth level constitutes all the alternatives that is all the promoters.
7.5.7 Procedure of the AHP Model
AHP model require determining the relative importance of each of the element in the hierarchy.
Each element in the level is compared with other elements at the same level pair wise based on
the scale of 1 to 9 as per the definitions of the weight given in table 3.1. Pair wise comparisons
are made to the three second level elements of the model hierarchy with respect to the overall
goal of the model of selecting the best promoter as shown in table7.3. The experts in this
particular case assigned a weight of 2 for financial package compared with technical package.
Thus, the experts considered the financial package to have equal to weak importance than the
technical package. From this matrix the normalized priority values of the three elements can be
computed as shown in table 7.3
Table7.3 Relative weights at level 2.
SYNTHESIZE MATRIX PRIORITY
VECTOR FP TP MP FP TP MP
FP 1.00 2.00 6.00 0.60 0.60 0.60 0.60
TP 0.50 1.00 3.00 0.30 0.30 0.30 0.30
MP 0.17 0.33 1.00 0.10 0.10 0.10 0.10
In similar manner the elements in the third level of the hierarchy are compared pair wise to their
associated factors of the second level. For example the entrepreneur (EP1) and environment
(EP2) are compared with respect to the managerial package. The comparison values are shown in
table 7.4 with the priorities listed in the last column.
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FP1 FP2 FP3 FP4 FP5PRIORITY VECTOR
RANKING VECTOR
FP1 1.00 2.00 2.00 1.00 1.00 0.25 0.25 0.25 0.25 0.25 0.250 1.00
FP2 0.50 1.00 1.00 0.50 0.50 0.13 0.13 0.13 0.13 0.13 0.125 0.50
FP3 0.50 1.00 1.00 0.50 0.50 0.13 0.13 0.13 0.13 0.13 0.125 0.50
FP4 1.00 2.00 2.00 1.00 1.00 0.25 0.25 0.25 0.25 0.25 0.250 1.00
FP5 1.00 2.00 2.00 1.00 1.00 0.25 0.25 0.25 0.25 0.25 0.250 1.00
SYNTHESIZED MATRIX
TP1 TP2 TP3 TP4 TP5 TP1 TP2 TP3 TP4 TP5
TP1 1.00 2.00 2.00 1.50 0.65 0.24 0.24 0.24 0.24 0.24 0.238 1.00
TP2 0.50 1.00 1.00 0.75 0.33 0.12 0.12 0.12 0.12 0.12 0.119 0.50
TP3 0.50 1.00 1.00 0.75 0.33 0.12 0.12 0.12 0.12 0.12 0.119 0.50
TP4 0.67 1.33 1.33 1.00 0.43 0.16 0.16 0.16 0.16 0.16 0.159 0.67
TP5 1.54 3.08 3.08 2.31 1.00 0.37 0.37 0.37 0.37 0.37 0.366 1.54
PRIORITY VECTOR
RANKING VECTOR
SYNTHESIZE MATRIX
Table 7.4 Relative importance at level 3 for managerial package consisting entrepreneur (EP1)
and environment (EP”2) criteria.
SYNTHESIZE
MATRIX PRIORITY
VECTOR
RANKING
VECTOR EP1 EP2 EP1 EP2
EP1 1.00 2.00 0.67 0.67 0.67 1.00
EP”2 0.50 1.00 0.33 0.33 0.33 0.50
The pair wise comparison matrix, synthesized matrix, priority vectors and ranking vectors at
level 4 for Financial, Technical and managerial sub-package are shown in Table 7.5 to 7.8 with
their priority vector in the second last column.
Table 7.5 Relative importance at level 4 for financial package
Table 7.6 Relative importance at level 4 for Technical sub package
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EP1 EP2 EP3 EP4PRIORITY VECTOR
RANKING VECTOR
EP1 1.00 2.00 3.00 2.25 0.44 0.44 0.44 0.44 0.439 1.00
EP2 0.50 1.00 1.50 1.13 0.22 0.22 0.22 0.22 0.220 0.50
EP3 0.33 0.67 1.00 0.75 0.15 0.15 0.15 0.15 0.146 0.33
EP4 0.44 0.89 1.33 1.00 0.20 0.20 0.20 0.20 0.195 0.89
SYNTHESIZED MATRIX
EP1 EP2 EP3PRIORITY VECTOR
RANKING VECTOR
EP1 1.00 2.00 3.00 0.55 0.55 0.55 0.545 1.00
EP2 0.50 1.00 1.50 0.27 0.27 0.27 0.273 0.50
EP3 0.33 0.67 1.00 0.18 0.18 0.18 0.182 0.33
SYNTHESIZED MATRIX
Table 7.7 Relative importance at level 4 for managerial – entrepreneur sub package
Table 7.8 Relative importance at level 4 for managerial - environment sub package
The relative importance of various promoters with respect to various basic criteria at level 5 are
compared by pair wise comparison matrix and their preferences with respect to promoters
(alternatives) are obtained and are shown in tables 7.9 to 7.12. The four promoters are
represented by P1, P2, P3 and P4.
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FP1 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 0.65 0.80 1.00 P1 0.21 0.21 0.21 0.21 0.209 0.65
P2 1.54 1.00 1.23 1.54 P2 0.32 0.32 0.32 0.32 0.321 1.00
P3 1.25 0.81 1.00 1.25 P3 0.26 0.26 0.26 0.26 0.261 0.81
P4 1.00 0.65 0.80 1.00 P4 0.21 0.21 0.21 0.21 0.209 0.65
SYNTHESIZED MATRIX
FP2 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 0.50 0.50 1.50 P1 0.18 0.18 0.18 0.18 0.176 0.50
P2 2.00 1.00 1.00 3.00 P2 0.35 0.35 0.35 0.35 0.353 1.00
P3 2.00 1.00 1.00 3.00 P3 0.35 0.35 0.35 0.35 0.353 1.00
P4 0.67 0.33 0.33 1.00 P4 0.12 0.12 0.12 0.12 0.118 0.33
SYNTHESIZED MATRIX
FP3 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 0.50 0.50 1.50 P1 0.18 0.18 0.18 0.18 0.176 0.50
P2 2.00 1.00 1.00 3.00 P2 0.35 0.35 0.35 0.35 0.353 1.00
P3 2.00 1.00 1.00 3.00 P3 0.35 0.35 0.35 0.35 0.353 1.00
P4 0.67 0.33 0.33 1.00 P4 0.12 0.12 0.12 0.12 0.118 0.33
SYNTHESIZED MATRIX
FP4 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 0.40 0.40 1.50 P1 0.15 0.15 0.15 0.15 0.150 0.40
P2 2.50 1.00 1.00 3.75 P2 0.38 0.38 0.38 0.38 0.375 1.00
P3 2.50 1.00 1.00 3.75 P3 0.38 0.38 0.38 0.38 0.375 1.00
P4 0.67 0.27 0.27 1.00 P4 0.10 0.10 0.10 0.10 0.100 0.27
SYNTHESIZED MATRIX
FP5 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 0.50 0.50 1.50 P1 0.18 0.18 0.18 0.18 0.176 0.50
P2 2.00 1.00 1.00 3.00 P2 0.35 0.35 0.35 0.35 0.353 1.00
P3 2.00 1.00 1.00 3.00 P3 0.35 0.35 0.35 0.35 0.353 1.00
P4 0.67 0.33 0.33 1.00 P4 0.12 0.12 0.12 0.12 0.118 0.33
SYNTHESIZED MATRIX
Tables7.9 Comparison matrix for promoters at level 5 for Financial package FP1 to FP5
177
TP1 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 2.00 2.00 1.50 P1 0.38 0.38 0.38 0.38 0.375 1.00
P2 0.50 1.00 1.00 0.75 P2 0.19 0.19 0.19 0.19 0.188 0.50
P3 0.50 1.00 1.00 0.75 P3 0.19 0.19 0.19 0.19 0.188 0.50
P4 0.67 1.33 1.33 1.00 P4 0.25 0.25 0.25 0.25 0.250 0.67
SYNTHESIZED MATRIX
TP2 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 3.00 3.00 1.50 P1 0.43 0.43 0.43 0.43 0.429 1.00
P2 0.33 1.00 1.00 0.50 P2 0.14 0.14 0.14 0.14 0.143 0.33
P3 0.33 1.00 1.00 0.50 P3 0.14 0.14 0.14 0.14 0.143 0.33
P4 0.67 2.00 2.00 1.00 P4 0.29 0.29 0.29 0.29 0.286 0.67
SYNTHESIZED MATRIX
TP3 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 0.50 1.00 2.00 P1 0.22 0.22 0.22 0.22 0.222 0.50
P2 2.00 1.00 2.00 4.00 P2 0.44 0.44 0.44 0.44 0.444 1.00
P3 1.00 0.50 1.00 2.00 P3 0.22 0.22 0.22 0.22 0.222 0.50
P4 0.50 0.25 0.50 1.00 P4 0.11 0.11 0.11 0.11 0.111 0.25
SYNTHESIZED MATRIX
TP4 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 4.00 4.00 2.00 P1 0.50 0.50 0.50 0.50 0.500 1.00
P2 0.25 1.00 1.00 0.50 P2 0.13 0.13 0.13 0.13 0.125 0.25
P3 0.25 1.00 1.00 0.50 P3 0.13 0.13 0.13 0.13 0.125 0.25
P4 0.50 2.00 2.00 1.00 P4 0.25 0.25 0.25 0.25 0.250 0.50
SYNTHESIZED MATRIX
TP5 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 4.00 4.00 2.00 P1 0.50 0.50 0.50 0.50 0.500 1.00
P2 0.25 1.00 1.00 0.50 P2 0.13 0.13 0.13 0.13 0.125 0.25
P3 0.25 1.00 1.00 0.50 P3 0.13 0.13 0.13 0.13 0.125 0.25
P4 0.50 2.00 2.00 1.00 P4 0.25 0.25 0.25 0.25 0.250 0.50
SYNTHESIZED MATRIX
Table 7.10 Comparison matrix for promoters at level 5 for Technical package TP1 to TP5
178
MP-EP1 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 1.00 1.00 1.50 P1 0.27 0.27 0.27 0.27 0.273 1.00
P2 1.00 1.00 1.00 1.50 P2 0.27 0.27 0.27 0.27 0.273 1.00
P3 1.00 1.00 1.00 1.50 P3 0.27 0.27 0.27 0.27 0.273 1.00
SYNTHESIZED MATRIX
MP-EP2 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 2.00 2.00 1.50 P1 0.38 0.38 0.38 0.38 0.375 1.00
P2 0.50 1.00 1.00 0.75 P2 0.19 0.19 0.19 0.19 0.188 0.50
P3 0.50 1.00 1.00 0.75 P3 0.19 0.19 0.19 0.19 0.188 0.50
P4 0.67 1.33 1.33 1.00 P4 0.25 0.25 0.25 0.25 0.250 0.67
SYNTHESIZED MATRIX
MP-EP3 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 0.50 1.00 1.50 P1 0.21 0.21 0.21 0.21 0.214 0.50
P2 2.00 1.00 2.00 3.00 P2 0.43 0.43 0.43 0.43 0.429 1.00
P3 1.00 0.50 1.00 1.50 P3 0.21 0.21 0.21 0.21 0.214 0.50
P4 0.67 0.33 0.67 1.00 P4 0.14 0.14 0.14 0.14 0.143 0.33
SYNTHESIZED MATRIX
MP-EP4 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 2.00 2.00 1.50 P1 0.38 0.38 0.38 0.38 0.375 1.00
P2 0.50 1.00 1.00 0.75 P2 0.19 0.19 0.19 0.19 0.188 0.50
P3 0.50 1.00 1.00 0.75 P3 0.19 0.19 0.19 0.19 0.188 0.50
P4 0.67 1.33 1.33 1.00 P4 0.25 0.25 0.25 0.25 0.250 0.67
SYNTHESIZED MATRIX
MP-EP1 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 0.50 0.50 1.50 P1 0.18 0.18 0.18 0.18 0.176 0.50
P2 2.00 1.00 1.00 3.00 P2 0.35 0.35 0.35 0.35 0.353 1.00
P3 2.00 1.00 1.00 3.00 P3 0.35 0.35 0.35 0.35 0.353 1.00
P4 0.67 0.33 0.33 1.00 P4 0.12 0.12 0.12 0.12 0.118 0.33
SYNTHESIZED MATRIX
Table 7.11 Comparison matrix for promoters at level 5 for Managerial - entrepreneur package
EP1 to EP4
Table 7.12 Comparison matrix for promoters at level 5 for Managerial - environment package
EP1 to EP3
179
MP-EP2 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 2.00 2.00 1.50 P1 0.38 0.38 0.38 0.38 0.375 1.00
P2 0.50 1.00 1.00 0.75 P2 0.19 0.19 0.19 0.19 0.188 0.50
P3 0.50 1.00 1.00 0.75 P3 0.19 0.19 0.19 0.19 0.188 0.50
P4 0.67 1.33 1.33 1.00 P4 0.25 0.25 0.25 0.25 0.250 0.67
SYNTHESIZED MATRIX
MP-EP3 P1 P2 P3 P4PRIORITY VECTOR
RANKING VECTOR
P1 1.00 0.50 0.50 1.50 P1 0.18 0.18 0.18 0.18 0.176 0.50
P2 2.00 1.00 1.00 3.00 P2 0.35 0.35 0.35 0.35 0.353 1.00
P3 2.00 1.00 1.00 3.00 P3 0.35 0.35 0.35 0.35 0.353 1.00
P4 0.67 0.33 0.33 1.00 P4 0.12 0.12 0.12 0.12 0.118 0.33
SYNTHESIZED MATRIX
FP 1 0.21 0.32 0.26 0.21
FP2 0.18 0.35 0.35 0.12
FP3 0.18 0.35 0.35 0.12
FP 4 0.15 0.38 0.38 0.10
FP 5 0.18 0.35 0.35 0.12
TP1 0.38 0.19 0.19 0.25
TP2 0.43 0.14 0.14 0.29
TP3 0.22 0.44 0.22 0.11
TP4 0.50 0.13 0.13 0.25
TP5 0.50 0.13 0.13 0.25
EP1 0.27 0.27 0.27 0.18
EP2 0.38 0.19 0.19 0.25
EP3 0.21 0.43 0.21 0.14
EP4 0.38 0.19 0.19 0.25
EP1 0.18 0.35 0.35 0.12
EP2 0.38 0.19 0.19 0.25
EP3 0.18 0.35 0.35 0.12
Attributes Promoter 1 Promoter 2 Promoter 3 Promoter 4
7.6 AGGREGATION PROCEDURE
The weights matrix for various alternatives (Promoters) and the weights for various packages are
shown in Table 7. 13.
Table 7.13. Weights of various alternatives (Promoters)
180
7.6.1 Ranking the Applicants
After obtaining the relative importance matrix of applicant promoters with respect to the various
attributes and their relative weights at level 4, level 3 and level 2, the aggregated score of each
promoter is calculated as follows :
For example, if the weights at level 2 for managerial package = 0.1 (entrepreneur – 0.67 and
environment – 0.33), weight for financial package = 0.6 and weight for technical package = 0.3,
and weights at level 3 and 4 are as shown in second last column of tables 7.4 to 7.8. And at level
5 as shown in table 7.13 then,
Aggregate score of Promoter 1
= 0.6 [0.21 x 0.25 + 0.18 x 0.13 + 0.18 x 0.13 + 0.15 x 0.25 + 0.18 x 0.25] + 0.3 [0.38 x 0.24 +
0.43 x 0.12 + 0.22 x 0.12 + 0.5 x 0.16 + 0.5 x 0.37] + 0.1 x 0.67 [0.27 x 0.44 + 0.38 x 0.22 +
0.21 x 0.15 + 0.38 x 0.20] + 0.1 x 0.33 [0.18 x 0.44 + 0.38 x 0.22 + 0.18 x 0.15] = 0.26
Aggregate score of Promoter 2
= 0.6 [0.32 x 0.25 + 0.35 x 0.13 + 0.35 x 0.13 + 0.38 x 0.25 + 0.35 x 0.25] + 0.3 [0.18 x 0.24 +
0.14 x 0.12 + 0.44 x 0.12 + 0.13 x 0.16 + 0.13 x 0.37] + 0.1 x 0.67 [0.27 x 0.44 + 0.19 x 0.22 +
0.43 x 0.15 + 0.19 x 0.20] + 0.1 x 0.33 [0.35 x 0.44 + 0.19 x 0.22 + 0.35 x 0.15] = 0.29
Aggregate score of Promoter 3
= 0.6 [0.26 x 0.25 + 0.35 x 0.13 + 0.35 x 0.13 + 0.38 x 0.25 + 0.35 x 0.25] + 0.3 [0.19 x 0.24 +
0.14 x 0.12 + 0.22 x 0.12 + 0.13 x 0.16 + 0.13 x 0.37] + 0.1 x 0.67 [0.27 x 0.44 + 0.19 x 0.22 +
0.21 x 0.15 + 0.19 x 0.20] + 0.1 x 0.33 [0.35 x 0.44 + 0.19 x 0.22 + 0.35 x 0.15]= 0.27
Aggregate score of Promoter 4
= 0.6 [0.21 x 0.25 + 0.12 x 0.13 + 0.12 x 0.13 + 0.10 x 0.25 + 0.12 x 0.25] + 0.3 [0.25 x 0.24 +
0.29 x 0.12 + 0.11 x 0.12 + 0.25 x 0.16 + 0.25 x 0.37] + 0.1 x 0.67 [0.18 x 0.44 + 0.25 x 0.22 +
0.14 x 0.15 + 0.25 x 0.20] + 0.1 x 0.33 [0.12 x 0.44 + 0.25 x 0.22 + 0.12 x 0.15]= 0.17
181
Through the aggregation process the alternatives can be prioritized as shown in Table 7.14. The
promoter P2 having the highest aggregate score is ranked at number 1.
Table 7.14: Ranking of Applicant Promoters
S.NO PROMOTER NAME AGGREGATE SCORE RANK
1 PROMOTER 1 0.26 3
2 PROMOTER 2 0.29 1
3 PROMOTER 3 0.27 2
4 PROMOTER 4 0.17 4
7.7 SENSITIVITY ANALYSIS
The owner/governments may wish to know as to how the ranking of applicants will change, if
the weights assigned to criteria at various levels are altered. The sensitivity analysis is made by
altering the weights of criteria at level 2 and level 3. By keeping one of the weights as constant
(say management package and its sub packages), the weights of the other criteria are varied from
0.1 to 0.8. The variation of aggregated value of promoters can be obtained and a graph can be
plotted for each constant value of management package weight and changing the weights of
financial package and technical package. Table 7.15 to 7.22 gives the score values of promoters
for different values of weights of financial package and technical package and value of
management package changing from 0.1(sub package value 0.067 and 0.033) to 0.8 (sub package
value 0.536 and 0.264) respectively. The graph showing the variation of aggregate score values
with respect to each table is shown in Figure 7.5 to Figure 7.12. MS-Excel has been used for the
sensitivity analysis.
182
weight for financial package 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80
weight for Technical package 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10
Promoter 1 0.39 0.36 0.34 0.31 0.29 0.26 0.24 0.21Promoter 2 0.21 0.22 0.24 0.26 0.27 0.29 0.31 0.33Promoter 3 0.18 0.20 0.22 0.24 0.25 0.27 0.29 0.31Promoter 4 0.22 0.21 0.20 0.19 0.18 0.17 0.16 0.15
weight for managerial Package EP1 - 0.067 and EP2 - 0.033
Table 7.15 Score Values of Promoters for different values of weights of financial and technical
package and when value of managerial package EP1 = 0.067 and EP2 = 0.033
Figure 7.5 Variations of Aggregate Values when MP = 0.1
183
weight for financial package 0.10 0.20 0.30 0.40 0.50 0.60 0.70weight for Technical package 0.70 0.60 0.50 0.40 0.30 0.20 0.10
Promoter 1 0.37 0.35 0.32 0.30 0.27 0.25 0.22Promoter 2 0.22 0.23 0.25 0.27 0.28 0.30 0.32Promoter 3 0.19 0.21 0.23 0.25 0.26 0.28 0.30Promoter 4 0.22 0.21 0.20 0.19 0.18 0.17 0.16
weight for managerial Package EP1 - 0.134 and EP2 - 0.066
Table 7.16 Score Values of Promoters for different values of weights of financial and technical
package and when value of managerial package EP1 = 0.134 and EP2 = 0.066
Figure 7.6 Variations of Aggregate Values when MP = 0.2
184
weight for financial package 0.10 0.20 0.30 0.40 0.50 0.60weight for Technical package 0.60 0.50 0.40 0.30 0.20 0.10
Promoter 1 0.36 0.33 0.31 0.28 0.26 0.23Promoter 2 0.23 0.24 0.26 0.28 0.29 0.31Promoter 3 0.20 0.22 0.24 0.26 0.27 0.29Promoter 4 0.21 0.20 0.19 0.18 0.17 0.16
weight for managerial Package EP1 - 0.201 and EP2 - 0.099
Table 7.17 Score Values of Promoters for different values of weights of financial and technical
package and when value of managerial package EP1 = 0.201 and EP2 = 0.099
Figure 7.7 Variations of Aggregate Values when MP = 0.3
185
weight for financial package 0.10 0.20 0.30 0.40 0.50
weight for Technical package 0.50 0.40 0.30 0.20 0.10
Promoter 1 0.34 0.32 0.29 0.27 0.24Promoter 2 0.24 0.25 0.27 0.29 0.30Promoter 3 0.21 0.23 0.25 0.27 0.29Promoter 4 0.21 0.20 0.19 0.18 0.17
weight for managerial Package EP1 - 0.268 and EP2 - 0.132
Table 7.18 Score Values of Promoters for different values of weights of financial and technical
package and when value of managerial package EP1 = 0.268 and EP2 = 0.132
Figure 7.8 Variations of Aggregate Values when MP = 0.4
186
weight for financial package 0.10 0.20 0.30 0.40
weight for Technical package 0.40 0.30 0.20 0.10
Promoter 1 0.33 0.30 0.28 0.25Promoter 2 0.25 0.26 0.28 0.30Promoter 3 0.22 0.24 0.26 0.28Promoter 4 0.20 0.19 0.18 0.17
weight for managerial Package EP1 - 0.335 and EP2 - 0.165
Table 7.19 Score Values of Promoters for different values of weights of financial and technical
package and when value of managerial package EP1 = 0.335 and EP2 = 0.165
Figure 7.9 Variations of Aggregate Values when MP = 0.5
187
weight for financial package 0.10 0.20 0.30
weight for Technical package 0.30 0.20 0.10
Promoter 1 0.32 0.29 0.27Promoter 2 0.25 0.27 0.29Promoter 3 0.23 0.25 0.27Promoter 4 0.20 0.19 0.18
1.00 1.00 1.00
weight for managerial Package EP1 - 0.402 and EP2 - 0.198
Table 7.20 Score Values of Promoters for different values of weights of financial and technical
package and when value of managerial package EP1 = 0.402 and EP2 = 0.198
Figure 7.10 Variations of Aggregate Values when MP = 0.6
188
weight for financial package0.10 0.20
weight for Technical package0.20 0.10
Promoter 1 0.30 0.28Promoter 2 0.26 0.28Promoter 3 0.24 0.26Promoter 4 0.19 0.18
weight for managerial Package EP1 - 0.469 and EP2 - 0.231
Table 7.21 Score Values of Promoters for different values of weights of financial and technical
package and when value of managerial package EP1 = 0.469 and EP2 = 0.231
Figure 7.11 Variations of Aggregate Values when MP = 0.7
189
weight for financial package0.10
weight for Technical package0.10
Promoter 1 0.29Promoter 2 0.27Promoter 3 0.25Promoter 4 0.19
weight for managerial Package EP1 - 0.536 and EP2 - 0.264
Table 7.22 Score Values of Promoters for different values of weights of financial and technical
package and when value of managerial package EP1 = 0.536 and EP2 = 0.264
Figure 7.12 Variations of Aggregate Values when MP = 0.8
190
7.8 CLOSURE
Best Value procurement aims at using price and other technical factors in the evaluation and
selection process to enhance the long term performance of projects during and after construction.
This process ensures that the selected promoter will provide the best value to the public for the
money spent. In this chapter a multi criteria decision framework has been used to solve the BOT
promoter prequalification issues. The model developed is flexible enough to take full advantage
of the experts’ knowledge, experiences and makes the decision maker feel comfortable to give
judgment on prequalification issue. The framework includes decision criteria analysis, weights
assessment and ranking order determination of project promoters. The AHP model can consider
the relevant factors in making the decision. These factors can be chosen according to specific
project needs and the decision reflects the owners need and preferences.
Successful selection of the most suitable concessionaire depends on number of issues, which
includes the quality of (i) the general arrangement of selection process, (ii) definition of project
objectives and core requirements, (iii) identifying and defining project specific criteria, (iv) the
prequalification and tender evaluation methodology, (v) the understanding of what these tenders
can achieve, and (vi) the negotiation skills. Interested parties should be short listed before asking
them to submit tenders in order to minimize overall tendering costs in the industry. This chapter
provides a core concessionaire ranking protocol that incorporates public procurement principles,
best value selection approach and multi-criteria tender evaluation.
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