Utility-based multicriteria model for evaluating BOT projects/Sep projektu vertinimo modelis pagristas daugiakriterine naudingumo teorija.
Yan, Min-Ren ; Pong, Cheng-Sheng ; Lo, Wei 等
1. Introduction
Public infrastructures have been conventionally delivered by the
public sector using the design-bid-build procurement system. With the
increasing demands for new developments and maintenances of the existing
infrastructures, public sectors are unable to provide sufficient funds
to deal with the challenge (FHA 2005; Augenblic and Cluster 1990). To
resolve the financial limitation and time pressure, the concept of
public private partnership (PPP) has been adopted by many public sectors
to launch infrastructure projects for private financial initiatives
(PFI), which are collective terms for build-operate-transfer (BOT),
build-operate-own (BOO), build-own-operate-transfer (BOOT),
build-transfer-operate (BTO), built and transfer (BT), and operate and
transfer (OT) etc. (Kumaraswamy and Morris 2002).
Traditionally, most of government projects are procured by
competitive bidding system or qualification-based selection system,
while price and contractors' qualifications are considered as
critical factors in the contractor selection process (Lo and Yan 2009).
For the public fundraising projects, rigorous contractor selection
process is expected to find right contractors and to assure quality
products as well as successful projects. However, in addition to
contractor selection, a successful BOT project requires more favorable
conditions than public fundraising projects. The project promoters
should ascertain that the project be politically, socially, legally,
economically, and financially viable (Abdel Aziz 2007). Before
implementing BOT projects, the government must effectively evaluate the
feasibility of each project to eliminate unqualified projects and
execute the selected project progressively according to its
capabilities. However, previous studies have indicated that existing
feasibility studies were insufficient for detecting inappropriate BOT
projects (CRANA 2002). The major challenge for BOT project evaluation is
not only the considerations of financial factors but non-financial
factors such as construction efficiency, service efficiency, local
government's financial ability and etc. In the past BOT practices,
governments depended upon project feasibility studies conducted by
private consultants and mainly relied on experts' group decisions.
Therefore, how to establish an objective BOT project evaluation model to
comprehensively assess the feasibility of each project and determine the
priority of implementation has become an important issue. Since the
allocation of BOT projects induces significant capital investments and
impacts on a country's economy, factors including economics and
social developments should be broadly considered (Ginevicius and
Podvezko 2009). In addition, multicriteria analysis method enables broad
perspectives for the assessment and risk valuation is essential during
the decision-making process (Sliogeriene et al. 2009; Shevchenko et al.
2008). Thus, this paper aims to develop a multi-criteria decision model
by incorporating analytic hierarchy process (AHP) and utility theory to
manage the visible, invisible or unquantifiable factors that affect the
effectiveness of BOT projects. Through this research, the feasibility
and priority of each planned BOT projects can be evaluated objectively.
A real case of the national BOT sewerage system plan in Taiwan will be
used to demonstrate the usefulness of the proposed model. The result is
expected to be a valuable reference for both administrators and
legislators to manage future BOT projects.
2. Model Overview
The whole process of the evaluation of BOT projects comprises of 4
steps as shown in Fig. 1. The practices of the evaluation of BOT
projects are demonstrated by the case of BOT sewerage systems selection
in Taiwan.
[FIGURE 1 OMITTED]
Step 1: To sort out the influential factors for evaluating BOT
projects based on literature review. In this paper, the criteria would
be developed specifically for evaluating sewerage systems.
Step 2: To sum up the suitable criteria for establishing a
systematic hierarchy as the source of questionnaire survey. AHP is
applied to obtain the weighting ([w.sub.i]) of each criterion.
Step 3: To define the content and quantifiable evaluation on range
of each criterion, apply utility theory to build utility functions, and
then use utility functions to determine numerical ratings ([u.sub.ri]).
Step 4: To determine the weighted global utility (WGU) of each
project; therefore WGU = [summation] [w.sub.i] x [u.sub.ri]. WGU is used
for evaluating the feasibility of a target BOT project which is taken as
the source of quantitative comparisons among all projects.
3. The Example Case
In Taiwan, the Executive Yuan has approved 36 BOT sewerage system
projects and also initially reviewed the feasibility of adopting the BOT
model for another 53 projects (CPAMI 2003). All these projects, 89 in
total, are large in scale with a total cost over 100 billion US dollars
and the completion of all projects is scheduled on 2014. However,
according to the procedure specified in The Civil Participation in
Sewerage System Construction Promotion Program, each project should be
reviewed based on the feasibility evaluation and initial plans. Based on
the framework described in section 2, the national plan of sewerage
system in Taiwan is used as the example case of the model application.
4. Measurements of Evaluation Criteria
The US Environmental Protection Agency and International
Development Institute have provided a list of criteria for state
government to follow in the introduction of civil participation into
construction of sewerage systems (USEPA 2000; IDI 2002). Based on the
previous studies, a hierarchy of criteria can be developed. The
hierarchy comprises of the overall goal, two groups of criteria
(financial and non-financial) and finally eight evaluation criteria
identified as follows:
A. Financial criteria
1. Initial construction cost of the sewerage treatment plant:
Since a sewerage system can involve significant capital investments
and construction works, the construction would usually be divided into
several phases for handling the project risks and delivering sewerage
system services phase by phase. The initial construction cost of a
sewerage treatment plant can be evaluated by the following formula:
ICC = CCFP/DCWP,
where ICC = initial construction cost of the sewerage treatment
plant ($), CCFP = the first phase construction cost of the sewerage
treatment plant ($), DCWP = designed capacity of wastewater to be
processed after the first phase construction (ton).
Although the initial construction cost for most wastewater
treatment plant is usually high, a project should not be prioritized if
ICC is excessively high. Civil institutions may show higher efficiency
in design, purchasing, and engineering of the systems with a lower value
of ICC.
2. Cost of construction per household
CCH = TCC/NH,
where CCH = cost of construction per household ($), TCC = total
construction cost ($), NH = number of households to be served
(household).
CCH reflects the overall assessment of the cost related with many
impact factors such as construction difficulty, geologic structure, and
others indirectly affect the construction cost.
3. Cost of prevalence rate improvement
CPRI = SDCCC/RH,
where CPRI represents cost of prevalence rate improvement ($), SDCC
represents sum of discounted construction costs in all years ($), RH
represents ratio of households to be served to the total households
around the nation (1%).
According to the government's estimation, the cost of
enhancing 1% prevalence rate nationwide (including construction cost,
interest cost of civil funds, and return) can be decreased by 5% each
year until the same timeframe. CPRI can be used as an index of
government investment efficiency. A lower total cost indicates a higher
effectiveness of prevalence rate improvement.
4. Unit charges of wastewater treatment
UCWT = UCWTP x PTCP/PTTC,
where UCWT = unit charges of wastewater treatment ($), UCWTP = unit
charges of wastewater treatment in each construction phase of the
sewerage system ($), PTCP = planned treatment capacity in each
construction phase of sewerage system($), PTTC = planned total treatment
capacity (ton).
UCWT is an important parameter for reflecting the cost of
wastewater treatment services. It involves construction amortization
rates, operation and maintenance amortization rates, and household pipe
connection amortization rates. For the government, lower UCWT implies
higher investment efficiencies.
B. Non-financial criteria
1. Construction efficiency:
Construction efficiency of a sewerage system is measured by the
duration required to accomplish 10,000 household connections after
contracting (10,000 household is considered as 1 unit by the
government). This parameter reveals the investment efficiency to be
presented by a civil contractor. If the sewerage system can serve fewer
than 10,000, this duration is estimated according to the proportion of
the total household number of 10,000. When ranking the sewerage systems,
those with a shorter duration would have a higher priority.
2. Pipeline service efficiency: tpl
PSE = TPL/TNH,
where PSE = pipeline service efficiency, TPL = total pipeline
length (meter), TNH = total number of households.
PSE can reveal the unit service efficiency of each sewerage system,
and also how much waste per unit can be carried by the sewer system. A
low value of PSE indicates higher concentration of population and also
better service efficiency.
3. Design and construction quality:
DCQ = OMC/UCWT,
where DCQ represents design and construction quality, OMC
represents operation and maintenance cost ($).
Experiences suggest that a well-designed and constructed sewerage
system shows a relatively lower DCQ.
4. Local government's financial ability:
When the central government is unable to subsidize wastewater
treatment and the user fee collected from the residents does not cover
the expenses, the local government is still obliged to continuously
operate the sewerage system. In this case, the wastewater treatment cost
becomes a financial burden to the local government. Local
government's financial ability can be measured by the ratio of the
unit charges of wastewater treatment to the total budget of the local
government as follows:
LGFA = UCWT x AVW1/AB,
where LGFA represents local governments' financial ability,
AVW1 represents annual volume of wastewater treated in the first phase,
AB represents the average current account revenue budget of the recent
three years
A lower value of LGFA implies a lighter financial burden on the
local government.
5. Weighting of Evaluation Criteria
An effective way to obtain group judgments for evaluating a complex
problem is using a questionnaire to collect different viewpoints from a
number of individuals. The statistics of the group response from the
questionnaire may reflect the consensus of opinion and may be used as
the basis of evaluation (Chao and Skibniewski 1992).
In this section, the opinions expressed by experts and evaluations
on the weighting of each criterion are obtained through an AHP-based
questionnaire survey. The questionnaires for collecting the consensus of
opinion were mailed to 31 experts and scholars including (1) members of
the sewerage system promotion committee in Construction and Planning
Agency of Ministry of the Interior, (2) construction consulting firms
involved in the design and execution of the current 36 sewerage systems,
and (3) central government officials in charge of BOT sewerage systems
administrations. Fourteen experts have completed and returned the AHP
questionnaire survey. Opinions of all experts are aggregated to
determine a set of weighting value of evaluation criteria ([w.sub.i]) by
four steps. First, on the basis of professional knowledge from the
experts, pair comparison and matrix comparison of criterion items at
each level in the hierarchy framework are carried out. Second,
consistency of the eigenvector derived from the comparison matrix is
examined. Third, the weighting of each criterion item can be identified.
Because the priority of each element is developed systematically and
objectively, the AHP results are reliable to provide problem solutions
for multi-factors decision-making situations. Finally, a set of average
weighting values is then calculated based on individual expert's
results. The calculated results using AHP, which are listed in Table 1,
show that the weighting value of each criterion is equal to the
weighting of the main classification multiplied by weighting of
sub-classification (CPAMI 2007).
6. Utility Function of Each Criterion
Utility theory has been an accepted approach used to provide an
objective decision based on subjective, qualitative data (Cheung et al.
2002; Shen et al. 1998). The concept of "utility" was
originally proposed in economics to measure the preferences of consumers
as a unit of personal welfare. Utility theory requires utility functions
that quantify qualitative decision criteria. Utility functions are used
here for considering individual preference and attitude towards risk by
decision makers when selecting an appropriate scale within the risk
ranges. The utility functions can also be used to convert the evaluation
score of each criterion into comparable ratings.
The utility function for each criterion has been built by applying
the utility function technique of straight-line relationship (Dozzi et
al. 1996). Based on the historic records of public fund-raising sewerage
system projects, the threshold and the most preferred point of previous
experience for each criterion are calculated so that the utility
functions can be determined.
If [y.sub.m] is the most preferred point of previous experience,
then [u.sub.ri]([y.sub.m]) = 1; [y.sub.T] is threshold point,
[u.sub.ri]([y.sub.T]) = 0; moreover, utility function of straight-line
relationship is [u.sub.ri]([y.sub.i]) = A[y.sub.i] + B. Thus, constants
A and B can be calculated and the computation is shown as following
equation:
[u.sub.ri]([y.sub.m]) = 1 [u.sub.ri]([y.sub.T]) = 0
[u.sub.ri]([y.sub.i]) = A[y.sub.i] + B = [1/[y.sub.m] - [y.sub.T]] x -
[y.sub.T]/[y.sub.m] - [y.sub.T], (1)
where [y.sub.T] = threshold point, [y.sub.m] = the most preferred
point of previous experience.
The utility function for each criterion is identified and listed in
Table 2. Since all the coefficients in Table 2 are extracted from the
historic records of public fund-raising sewerage systems, these utility
functions are representative to be the basis for evaluating BOT projects
based on the weighted global utility (WGU) as shown in Eq. (2):
WGU = [n.summation over (i=1)] ([u.sub.ri] x [w.sub.i]). (2)
The WGU of each evaluated project can be calculated using the above
equation. Decisionmakers can make judgments on each BOT project
according to WGU; a higher WGU indicates more overall project
feasibility for BOT approach.
7. Model Application
In this section, 8 BOT projects (respectively for the north,
central, and south Taiwan) listed in the third-phase national
construction plan are used to illustrate how the proposed model can be
applied to objectively select feasible projects and determine the
implementation priority for supporting the government's policy.
Each BOT project is evaluated using the proposed model to derive the
utility value of each criterion and WGU.
As shown in Table 3, the original BOT plans are arranged
sequentially by locations. Although the government has gathered the
necessary information regarding financial and non-financial
perspectives, the original BOT plans are difficult to evaluate and
compare objectively on the same basis. Thus, the government should
heavily rely on the group decision making mechanism based on invited
experts' opinions, even though each expert's decision is
subjective. Since the decision mechanism incorporated less supporting
quantitative models and numerical analysis, the mechanism would be a
descriptive decision model that the rationale and consistency of
decisions can't be properly justified.
Different from the aforementioned descriptive decision model, the
proposed model enables decision makers to implement a normative decision
model. The expected performance of each project from different aspects
is listed in Table 3. Every project's expected performance is then
converted to a WGU shown in Table 4. Based on the WGU of BOT projects,
the project feasibility and utility can be evaluated objectively. Since
the proposed model is developed by benchmarking previous public
fund-raising projects, a project with positive WGU represents a feasible
BOT plan which is expected to generate more benefits than using public
fund-raising method. On the contrary, a project with negative WGU
represents that the project is not favor BOT approach and might generate
worse performance than using public fund-raising method. According to
the aforementioned decision rules, 4 feasible BOT projects are
identified, while the other 4 projects are not considered beneficial for
the government by adopting BOT approach. Clearly, the proposed decision
model generates useful signals for the government to re-evaluate
unfavorable BOT plans before implementation.
In addition to supporting the evaluation of BOT project
feasibility, the evaluated WGUs of BOT projects can be used to support
the decision of priority setting. A project with higher WGU is suggested
to be implemented with prior order. According to the decision rule, the
priority of all BOT plans can be objectively and efficiently reordered
based on their WGUs.
As shown in Table 4, Taichung sewerage system project has the
highest expected utility by BOT approach (WGU = 1.240). This BOT project
should have the first priority to be implemented. The project that has
the second priority for implementation is Dansui sewerage system project
(WGU = 0.636). For other projects, the government can easily set their
sequences for implementation based on their WGU ranking. Although some
projects having negative WGUs would not be expected as effective via
BOT, those projects still can be ranked and properly arranged a sequence
for other considerations, such as promotion on specific region
development, whether the BOT project is feasible or further evaluations
needed.
Note that the same BOT plans shown in Table 4 have been evaluated
by the government's research based on experts' group
decisions, which is the formal and a prudent evaluation taken by
Executive Yuan (CPAMI 2007). In the group decision process, the same
evaluation criteria and weightings were adopted. For each criterion,
every project was individually reviewed and ranked by the expert group.
Thus, the overall ranking of projects can be determined, even though
experts' judgments were one of the critical parts in the group
decision process. As shown in Table 4, we found that the priority set
based on the proposed model with WGU generates a very similar result as
the original evaluation made by the government's research (Among 8
BOT projects been evaluated, 6 projects have the same ranking, while the
other 2 projects have switched rankings).
In summary, the case study reveals three major advantages of the
proposed model in supporting the government's decisions. First, the
proposed model can save significant time and cost consumed by the
process of experts' group decisions, including expert invitations,
meeting and communications, and other administration procedures. Thus,
the proposed model can improve the efficiency of the decision-making
process. Second, the proposed model enables decision-makers to examine
their preferences and the decisions can be logically reviewed. Thus,
human errors and mistakes can be reduced and the consistency of
decisions can be improved. Third, the WGUs derived from the proposed
model can reveal the advantages and shortcomings of each BOT project on
the same basis. It can provide the rationale as well as the justice of
the public policy and reduce underlying political burdens.
8. Conclusions
BOT projects usually induce huge capital investments and affect the
national economic development significantly. To promote and ensure the
success of a government's BOT policy, rational, consistent, and
transparent decisions for selecting appropriate projects constitute
critical factors, while sufficient numbers of responses from related
experts can't be ignored as well. The proposed evaluation model
using the utility function shows the advantages that it can overcome the
difficulties of building a multicriteria model for supporting BOT
project selections so that the rationale, consistency, and transparency
of decisions can be improved.
With the aid of the utility-based model, the case study
demonstrates that decision-makers can improve the quality and efficiency
of their decisions because of full participation by all members involved
in the evaluation process and the integration of their opinions. Since
the proposed model standardizes the evaluation process and enables
decision-makers to adjust decisions according to their preference and
considerations, the conclusions made in the decision-making process can
be logically reviewed to ensure consistent decisions. This advantage
would be specifically critical for getting consensus and improving the
effectiveness of the public decision-making.
doi: 10.3846/20294913.2011.580585
References
Abdel Aziz, A. M. 2007. Successful delivery of public-private
partnerships for a infrastructure development, Journal of Performance of
Constructed Facilities 133(12): 918-931.
Augenblic, M.; Cluster, B. S. 1990. The build, operate, and
transfer (BOT) approach to infrastructure project in developing country.
WPS498, World Bank, Washington, D.C.
Chao, L. C.; Skibniewski, M. J. 1992. Evaluation of advanced
construction technology with AHP method, Journal of Construction
Engineering and Management ASCE 118 (3): 577-593.
Cheung, S-O.; Seun, H. C. H.; Ng, S. T. 2002. A Multi-attribute
utility model for dispute resolution strategy selection, Construction
Management and Economics 20(7): 557-568. doi:10.1080/01446190210157568
Construction and Planning Agency of Ministry of Interior (CPAMI).
2007. A Study on Priority Evaluation of Sewerage Rehabilitation. Taipei,
Taiwan: Hwang.
Construction and Planning Agency of Ministry of Interior (CPAMI).
2003. The Third Phase of Sewerage System Construction, Construction and
Planning Agency of Ministry of Interior. (Chinese Version). Taiwan.
CRANA Corporation. 2002. Privatization in Egypt. Privatization
Coordination Support Unit (PSCU).
Dozzi, S. P.; AbouRizk, S. M.; Schroeder, S. L. 1996.
Utility-theory model for bid markup decisions, Journal of Construction
Engineering and Management 122(2): 119-124.
doi:10.1061/(ASCE)0733-9364(1996)122:2(119)
Federal Highway Administration (FHA). 2005. Manual for using
public-private partnerships on highway projects. Washington, D. C.:
Department of Transportation.
Ginevicius, R.; Podvezko, V. 2009. Evaluating the Changes in
Economic and Social Development of Lithuanian Counties by Multiple
Criteria Methods, Technological and Economic Development of Economy
15(3): 418-436. doi:10.3846/1392-8619.2009.15.418-436
International Development Institute (IDI). 2002. Guidelines for
Management of Sewerage Facilities in Developing Countries. Tokyo, Japan.
Kumaraswamy, M. M.; Morris, D. A. 2002. Build-operate-transfer-type
procurement in Asian Maga projects, Journal of Construction Engineering
and Management ASCE 128(2): 93-102. doi:10.1061/
(ASCE)0733-9364(2002)128:2(93)
Lo, W.; Yan, M. R. 2009. Evaluating qualification-based selection
system: a simulation approach, Journal of Construction Engineering and
Management ASCE 135(6): 458-465. doi:10.1061/(ASCE)CO.1943-7862.0000013
Shen, Q.; Lo, K-K.; Wang, Q. 1998. Priority setting in maintenance
management: A modified multiatribute approach using analytic hierarchy
process, Construction Management and Economics 16(6): 693-702.
doi:10.1080/014461998371980
Sliogeriene, J.; Kaklauskas, A.; Zavadskas, E. K.; Bivainis, J.;
Seniut, M. 2009. Environment Factors of Energy Companies and their
Effect on Value: Analysis Model and Applied Method, Technological and
Economic Development of Economy 15(3): 490-521.
doi:10.3846/1392-8619.2009.15.490-521
Shevchenko, G.; Ustinovichius, L.; Andruskevicius, A. 2008.
Multi-attribute Analysis of Investments Risk Alternatives in
Construction, Technological and Economic Development of Economy 14(3):
428-443. doi:10.3846/1392-8619.2008.14.428-443
United States Environmental Protection Agency (USEPA). 2000.
Guidance on the privatization of federally funded wastewater treatment
works. Washington D.C. USA.
Min-Ren Yan (1), Cheng-Sheng Pong (2), Wei Lo (3)
(1) Department of International Business Administration, Chinese
Culture University (SCE), No. 231, Sec. 2, Janguo Rd., Da-an District,
Taipei City, 106, Taiwan
(2) National Kaohsiung First University of Science and Technology,
Institute of Engineering Science and Technology, 2 Jhuoyue Rd., Nanzih,
Kaohsiung City, 811, Taiwan
(3) National Kaohsiung First University of Science and Technology,
Department of Construction Engineering, 2 Jhuoyue Rd., Nanzih, Kaohsiung
City, 811, Taiwan
E-mails: (1) mjyen@sce.pccu.edu.tw (corresponding author); (2)
cspong40@gmail.com; (3) roylo@ccms.nkfust.edu.tw
Received 10 December 2009; accepted 07 September 2010
Min-Ren YAN. PhD, Assistant Professor and Deputy Director of the
Department of International Business Administration at Chinese Culture
University (SCE), Taipei, Taiwan. Dr Yan is concurrently the Director of
Quality Centre for Business Excellence in his college and business
consultant in web technology, marketing, and services industries. His
research interests focus on strategic alliances, game theoretical
analysis, project business economics, and decision models. The research
results have received several academic honors such as Affiliated Scholar
Award and research funding from National Science Council, Executive
Yuan, Taiwan, the Annual Outstanding Research Paper Award from Chinese
Institute of Civil and Hydraulic Engineers, and the Best Conference
Paper Award in Government Procurement and Public Private Partnership.
Cheng-Sheng PONG. PhD, Executive Director of Taiwan Sewerage
Association. Dr. Pong is specialized in government procurement, public
private partnership, and the construction and management of sewerage
systems. He is a senior expert for government committees and policy
evaluation boards in Taiwan.
Wei LO. PhD, Professor of the Department of Construction
Engineering at National Kaohsiung First University of Science and
Technology, Kaohsiung, Taiwan. Dr. Lo is specialized in construction
management, project scheduling models, and construction disputes
resolutions. He is the committee member of the Complaint Review Board
for mediation, Public Construction Commission, Executive Yuan, Taiwan.
Table 1. Weighting value of each criterion
Code of Code of Code of Criteria
the first the second the third
level level level
C C1 C11 Initial 0.1500
construction
cost of the
treatment plant
C12 Cost of 0.1404
construction
per household
C13 Cost of 0.1546
prevalence rate
improvement
C14 Wastewater 0.1751
treatment rates
C2 C21 Construction 0.1125
efficiency
C22 Pipeline 0.0875
service
efficiency
C23 Operation and 0.0795
maintenance
cost ratio
C24 Local 0.1002
government's
financial
ability
Total 1.0000
Table 2. Utility function of each criterion
Code
of the
criterion [y.sup.T] [y.sub.m] Utility Function
C11 19323.644 29.834 [u.sub.i] ([y.sub.i]) =
-0.0000518[y.sub.i] +
1.001546306
C12 58599.235 62.572 [u.sub.i] ([y.sub.i]) =
-0.0000171 [y.sub.i]
1.001068932
C13 685.600 463.960 [u.sub.i] ([y.sub.i]) =
-0.0045118 [y.sub.i]
+ 3.093304458
C14 31.173 26.070 [u.sub.i] ([y.sub.i]) =
-0.1959824 [y.sub.i]
+ 6.109260167
C21 5.250 5.000 [u.sub.i] ([y.sub.i]) =
-4 [y.sub.i] + 21
C22 1.557 0.928 [u.sub.i] ([y.sub.i]) =
-1.59 [y.sub.i]
+ 2.47
C23 0.296 0.242 [u.sub.i] ([y.sub.i]) =
-18.6667455 [y.sub.i]
+ 5.525271643
C24 0.018 0.008 [u.sub.i] ([y.sub.i]) =
-98.2604796 [y.sup.i]
+ 1.772848292
Table 3. Estimated performance of different BOT projects
Criteria
Project Project
location name C11 C12 C13 C14
North Taiwan Dansui 29.41 62.57 439.4 28.01
(Taipei area) Rueifang 50.23 112.2 943.4 49.26
Sanying 31.14 78.27 623.2 36.57
Central Taiwan Taichung 28.51 46.44 340.9 23.17
(Taichung area) Fengyuan 30.33 71.99 472.5 28.71
South Taiwan Shihlong river 37.18 89.78 701.0 38.15
(Kaohsiung area) Daliao 39.53 118.3 822.6 54.21
Gangshan- 33.38 103.4 716.6 37.16
Chiautou
Criteria
Project Project
location name C21 C22 C23 C24
North Taiwan Dansui 5 0.93 0.44 0.01
(Taipei area) Rueifang 8 2.82 0.26 0.01
Sanying 5 1.38 0.24 0.01
Central Taiwan Taichung 4 1.01 0.21 0.05
(Taichung area) Fengyuan 5 1.62 0.49 0.02
South Taiwan Shihlong river 6 2.65 0.24 0.02
(Kaohsiung area) Daliao 7 3.41 0.22 0.02
Gangshan- 6 2.83 0.22 0.02
Chiautou
Table 4. Decision supports for BOT project selection
Project Project WGU Feasibility
location name of the
BOT plan
North Taiwan Dansui 0.636 Feasible
(Taipei area) Rueifang -1.791 Not recommended
Sanying 0.448 Feasible
Central Taiwan Taichung 1.240 Feasible
(Taichung area) Fengyuan 0.320 Feasible
South Taiwan Shihlong -0.365 Not recommended
(Kaohsiung river
area) Daliao -1.548 Not recommended
Gangshan- -0.358 Not recommended
Chiautou
Project Project Ranking Ranking based
location name based on experts'
on WGU group
decisions
North Taiwan Dansui 2 2
(Taipei area) Rueifang 8 8
Sanying 3 4
Central Taiwan Taichung 1 1
(Taichung area) Fengyuan 4 3
South Taiwan Shihlong 6 6
(Kaohsiung river
area) Daliao 7 7
Gangshan- 5 5
Chiautou
