systems
Article
Application of System Dynamics to Evaluate the Social
and Economic Benefits of Infrastructure Projects
Tiep Nguyen, Stephen Cook * and Vernon Ireland
Entrepreneurship, Commercialisation and Innovation Centre (ECIC), The University of Adelaide,
South Australia, SA 5005, Australia; [email protected] (T.N.);
[email protected] (V.I.)
* Correspondence: [email protected]; Tel.: +61-418-829-946
Academic Editor: Robert Cavana
Received: 20 December 2016; Accepted: 24 March 2017; Published: 29 March 2017
Abstract: Cost-Benefit Analysis (CBA) is often employed to inform decision makers about the
desirability of transport infrastructure investment options. One of the main limitations of traditional
CBA approaches is that they do not provide a dynamic view that explicitly illustrates the cost
and benefit relationships between component entities over time. This paper addresses this issue
by describing a System Dynamics (SD) approach that can perform transport infrastructure CBA
through the application of systems thinking to develop a causal-loop model that can subsequently be
operationalised into an executable stock-and-flow model. Execution of this model readily enables
sensitivity analysis of infrastructure investment options and visualisation of the cost-benefit behaviour
of each variant over time. The utility of the approach is illustrated through a case study, the Co Chien
Bridge project in Vietnam, using a model that incorporates conventional economic metrics and factors
that measure indirect project benefits, such as impact on gross domestic product, unemployment rate,
and total taxes gained from affected economic sectors.
Keywords: Cost-Benefit Analysis; transport infrastructure project; System Dynamics; social and
economic factors
1. Introduction
Physical infrastructure projects currently have an extremely important role in integrating transport
networks among states and different countries. Furthermore, these infrastructure projects have been
identified as a major contributing factor to economic growth. Infrastructure projects often consume a
huge amount of capital and other resources, and, as such, it is vital to select them with care and to
understand all of the potential benefits and risks. Otherwise they may suffer from common issues
such as cost overrun and benefit shortfalls [1]. Furthermore, decision making at the initiating stage
has been highlighted as a critical problem during infrastructure planning [2]. At present, to deal with
this issue, planners often use tools, such as Cost-Benefit Analysis (CBA), which have been developed
over several decades, to produce evidence to support investment decisions. CBA also enables project
managers to allocate resources efficiently and to mitigate project risks.
Studies have identified links between transport infrastructure developments and various
economic benefits [3]. When making investment cases, most practitioners focus on using static
models that are based on data regarding direct costs and the benefits to society of a particular project
and then use the discounted cash flow (DCF) technique and its indices, such as net present value
(NPV), internal rate of return (IRR), and cost-benefit ratio (B/C), in order to assess project financial
performance. In terms of the economic and social aspects, a number of studies have proposed models
that attempt to measure project impacts on the local economy and the community; for example,
the General Social Impact Model [4], Leontieff’s Input-Output (IO) [5], the Residential Model [6],
Systems 2017, 5, 29; doi:10.3390/systems5020029
www.mdpi.com/journal/systems
Systems 2017, 5, 29
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Computed General Equilibrium (CGE) Models [7], and macro economic analyses [8,9]. Particularly
in guidelines provided by the European Commission [10] and the Asian Development Bank [11],
experts and practitioners refer to ‘conversion factors’ used to transfer observed prices or public tariffs
into shadow prices that better reflect the social opportunity cost of goods before applying the DCF
technique to evaluate project performance.
However, some authors claim that these financial tools of the DCF technique are complicated to
understand and may lack benefit and useability [12]. Furthermore, these authors claim that financial
tools concentrate on model development and can omit the fundamental essence of the problem.
In addition, from the point of view of microeconomic scholars, cost-benefit analysis (CBA) does not
demonstrate the real benefits of transport improvements to shippers, including cost savings and service
improvements [3]. Despite the fact that numerous performance measurement systems (PMS) have been
designed to support planners in identifying the costs and benefits of investing infrastructure projects,
many obstacles arise during the process of applying and implementing these systems in practice [13].
Bourne et al. [13] presented the concept of performance as ‘doing today what will lead to an outcome
of measured value tomorrow’. In other words, the authors emphasised the ‘measured value tomorrow’
concept, which requires planners to have a different view in identifying the benefits and costs of an
infrastructure project. Similarly, Lebas and Euske [14] claim that performance is a complex concept,
which needs to be explained by a set of parameters or indicators that are complementary, and in some
cases may be contradictory, in order to describe complicated processes with various types of outcomes
and results.
The above indicate that it would be advantageous to apply an alternative approach that has the
capacity to address critical issues including the omission of critical project factors and the practical
difficulties in conceiving, implementing, and using the underlying models. This paper presents
background information regarding cost-benefit analysis in transport infrastructure projects and the
need for newer approaches, which can cope with difficulties in project evaluation. The paper describes
a research methodology based upon system dynamics (SD) to analyse the relationship between
socio-economic factors of CBA in both qualitative and quantitative terms. The final section of the paper
discusses the application of this approach to provide insights on CBA in a selected case study.
2. Literature Review
Population pressure coupled with high levels of transport congestion and, hence, travel delays
are driving demand for transport infrastructure projects. Such projects involve large investments
in capital and related resources and, not surprisingly, are subject to substantial project appraisals.
Evaluation of projects can be expensive, which is why many decision-making personnel tend to fall
back on tried-and-trusted methods like Cost-Benefit Analysis (CBA). CBA is a systematic method
to evaluate investment options in terms of costs and benefits, such as ongoing cost-reduction and
labour saving [15]. For infrastructure projects, Nickel et al. [16] declare that CBA is among the common
methods utilised in performance assessment in the government sector for high-value projects.
CBA was first mentioned in the report of Albert Gallatin in 1808 in the United States [17].
Gallatin was U.S. Secretary of the Treasury at that time and he recommended comparisons in terms
of costs and benefits in water infrastructure projects. Perhaps the first widespread use of CBA
was instituted by the ‘Federal Navigation Act—1936’ of the U.S.A., which mandated the usage of
cost-benefit analysis to assess proposed waterway infrastructure [18]. In 1939, the use of CBA was
significantly expanded when the ‘Flood Control Act’ required CBA analysis for all new projects. By the
end of 1960s, CBA had become popular and was used in both developed and developing countries.
CBA has been used in the decision-making processes of policy makers; for example, CBA was used to
estimate both demand and cost functions for public paratransit in the United States [19] and to identify
the net benefit of implementing urban road pricing policy [20]. A number of contributions discuss the
inclusion of socio-economic factors in CBA. The first contribution came from Stewart [21] when he
presented the critical points of using social cost-benefit (SCB) analysis to evaluate proposed projects,
Systems 2017, 5, 29
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and he claims that the outcome of SCB highly depends on the values adopted. Next, Beesley et al. [22]
studied changes in London Transport Executive policies to provide insights into the significance of
social cost-benefit analysis in examining the impacts of project investment. Regarding the macro-micro
economy, Mohring [23] considers CBA in the contexts of a closed and open economy. Furthermore,
scholars then focused on specific aspects of transport infrastructure projects such as using cost-benefit
ratios to rank road project priorities [24], the relationship between political attitudes and changes in
analytic results [25], and the influences of CBA results on investment decisions [26,27]. Although CBA
has brought many benefits to policy-decision makers, the Transit Co-operative Research Program
found that there are major limitations related to the use of CBA in evaluating project impacts on the
local community [28].
Criticism has been reported by many eminent persons regarding the systematic approach adopted
by CBA, including the requirement to be comprehensive and accurate while undertaking an analytical
method [29]. Furthermore, some authors criticize CBA for lacking a full appreciation of all the factors to
be included [30], the need to better combine repercussions related to the environment [31,32], the need
for interpretation of CBA results, especially to gain benefits which are hard to quantify [33], and the
nature of the outcome presentation [33]. On the same note, Layard et al. [34] (p. 3) state that ‘the right
decision only results if the prices used by the decision makers correctly reflects the social values of
inputs and outputs at the social optimum or shadow prices’. Thus, the CBA process can incorporate
bias that arises from assumptions used to frame the problem. Given the above-mentioned issues,
the goal of this research is to produce an improved method for CBA that builds on its strengths and
overcomes reported implementation limitations.
In summary, CBA is a valuable decision support method, but it has a number of limitations.
Perhaps the first is that it is seen as an expert-driven process that does not allow stakeholders to interact
readily with the model. This makes it hard for stakeholders to conduct what-if analysis and sensitivity
analysis with respect to the key model parameters. Secondly, the implementation of CBA tends to be
formulaic and prescriptive [35] and devoid of systems thinking, and, as such, it is easy for practitioners
to miss important social, environmental, and even economic factors. Thirdly, CBA is essentially a
functionalist and often reductionist approach that seeks to provide optimal answers to investment
problems through the work of expert analysts. Many important authors, including Jackson [36] and
Hitchins [37], advocate the use of systems approaches to tackle management challenges and provide a
range of approaches, methods, and techniques that can be employed. The first step in such approaches
it to identify the stakeholder needs. For an improved CBA, this would include the application of system
thinking, the use of multi-methodologies that incorporate functionalist and interpretive approaches to
tackle the problem of interest, the explicit inclusion of social and environmental factors in a transparent
way, the ability of stakeholders to exercise the model and perform sensitivity analysis, and intuitive
and visual ways of displaying the output information. Of the approaches discussed by Jackson [36],
system dynamics is the most well suited.
System Dynamics (SD) is a computer-aided approach to policy analysis and design [38]. The SD
approaches uses user-friendly software that produces mathematical models in which the system
of interest is described by sets of differential equations [39,40]. The elements of system dynamics
models are flows (these can be material, information, money, etc.), accumulation of flows into stocks,
feedback between the stocks that is also represented as flows, and time delays. The System Dynamics
Society [41] describes the utility of SD in an organizational context thus:
‘System dynamics is a technique for strategic and policy simulation modeling based on
feedback systems theory. It was invented in the late 1950s by Jay Forrester, a pioneer in
engineering and computer design. Since then, SD has developed as its own field, distinct from
the larger fields of operations research and management science to which it is related.
SD unites social and behavioral science with the nitty-gritty details of planning and
accounting, and requires the careful design and construction of original models with
many interacting variables.
Systems 2017, 5, 29
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SD is used by organizations facing high-stakes decisions and seeking an integrated view
of the major forces that can affect key outcomes years or decades into the future. It helps
these organizations to better weigh the pros and cons of various options they have been
considering or might consider’.
One of the key reasons to apply SD to transport infrastructure projects is its ability to capture and
explain system behaviour and its temporal variations [42]. SD can produce simulations that enable
researchers to evaluate ‘what-if’ cases and policy tests under varied situations [43]. Rodrigues and
Bowers [44] state that in a project management context SD helps to surface and simulate the impact of
complicated interrelationships between system elements [44].
SD has been applied to problems similar to the one of interest. Forrester [45] expanded SD beyond
its organizational modeling origins to investigate the reasons for urban decay in US cities in the 1960s.
Stave [46] used SD to provide the framework for improving public participation in the decision making
processes regarding environmental policy. Yang et al. [47] have applied SD to model the redevelopment
of old urban areas. In these works, a number of outcomes were uncovered through exercising SD
models of old urban areas that were counterintuitive; for example, the policy of building low-cost
public housing in decayed inner cities was making poverty and unemployment worse not better.
In 2011, Yuan et al. [48] used SD to construct a cost-benefit analysis model for waste chain
management. Yuan et al. were successful in setting up both causal loop and stock-flow diagrams to
provide quantitative assessments. In addition, Wei et al. [49] used SD to set up a complex system
model to demonstrate component relationships and non-linear interactions between water resources,
the natural environment, and social-economic aspects. Mavrommati et al. [50] dealt with critical
issues regarding sustainable development in urban coastal systems by using the SD approach. In 2014,
Shih and Tseng [51] reported their Air Resource Co-benefits model, which provides estimates of the
social benefits of incorporating renewable energy (RE) and energy efficiency improvements (EEI) into
Sustainable Energy Policy.
Thus, there is strong evidence that SD is a promising modeling approach from both a systems
practice perspective and a CBA perspective.
3. Research Approach
This research employs SD to produce a cost-benefit evaluation for a given transport project.
The case study that follows is set in Vietnam. The process is given in Figure 1 and starts with
the application of systems thinking to identify the key variables (nodes) in the system and the
relationships between them. At this time, the costs and benefits of undertaking the project are
uncovered. The production of two types of models follows; a casual-loop model and stock-and-flow
model. The main purpose of the causal-loop model is to depict the relationship between the variables
in the system and the direction of the influence they have on each other [52]. Many variables have
been identified in the case study, such as the total budget spent on the project, the number of vehicles,
and the effects of project investment on the local economy. The stock-and-flow model is built from
the casual-loop model through the selection of appropriate modelling elements and relationships and
through direct or indirect quantification of the model [52]. In the case study this model is used to
model the CBA of the system of interest under different conditions related to different internal and
external environments and to produce the findings.
Vensim software is used to implement the CBA SD model in the case study system. This software
was developed by the Ventana Systems Inc. of Harvard, Massachusetts in 1985 [53]. The Vensim
software is designed to enable a person with minimal mathematical modelling skills to produce an
executable differential equation model of a real-world system that contains nested feedback loops and
non-linearity. SD models in Vensim and similar tools are then used to evaluate systems variants in
terms of their performance and behaviour across a range of contexts in order to gain knowledge about
the system and to identify configurations that possess desirable characteristics.
Systems 2017, 5, 29
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Identify variables including costs and benefits
5 of 21
Identify variables including costs and benefits
Identify relationships between variables (+ or -)
Identify relationships between variables (+ or -)
Create the causal loop model
Create the causal loop model
Create the SD model
Create the SD model
Design alternative options for project investment
Design alternative options for project investment
Evaluate the value over time of investment options
Evaluate the value over time of investment options
Test and validate research results
Test and validate research results
Make recommendations
Make
recommendations
Figure 1. Generic Flow
chart
for System Dynamics (SD) modelling.
Figure 1. Generic Flow chart for System Dynamics (SD) modelling.
Figure 1. Generic Flow chart for System Dynamics (SD) modelling.
4. Case Study
4. Case Study
In the
last five years, all trading goods from Tra Vinh Province to the big cities in the South of
4. Case
Study
In
the
last
years, allvia
trading
goods from
Tra Vinh
theboats;
big cities
in the 2.
South
Vietnam werefive
transported
river transport
systems
suchProvince
as ferriestoand
see Figure
This of
Inwere
the last
five years,via
allriver
trading
goods from
Trasuch
Vinhas
Province
to the
big cities
in the2.South
of
Vietnam
transported
transport
systems
ferries
and
boats;
see
Figure
This
was
was a significant barrier to local economic growth because travelling by ferry or boat involves
Vietnam
were
transported
via
river
transport
systems
such
as
ferries
and
boats;
see
Figure
2.
This
a significant
to local
economic
growth
because travelling
by ferryAccording
or boat involves
significant
significant barrier
time and
economic
cost for
both producers
and passengers.
to the National
was
a significant
barrier
local
economicand
growth
because According
travelling by
or boat involves
time
and
economic
cost
fortoboth
producers
passengers.
to ferry
the National
Centre
for
Socio-Economic
Information
and Forcast
[54], the Gross
Domestic
Product
(GDP)Centre
growthfor
significant time and economic cost for both producers and passengers. According to the National
Socio-Economic
Information
and
Forcast
[54],
the
Gross
Domestic
Product
(GDP)
growth
rate
of Tra
rate of Tra Vinh Province during the five year period from 2010 to 2015 was less than the national
Centre for Socio-Economic Information and Forcast [54], the Gross Domestic Product (GDP) growth
average
GDP
because
under-development
of 2015
transport
infrastructure.
To address
such
Vinh
Province
during
the of
fivethe
year
period from 2010 to
was less
than the national
average
GDP
rate of Tra Vinh Province during the five year period from 2010 to 2015 was less than the national
transport
network
needs in the provinces,
the Transport
Ministry
Vietnam
announced
to
because
of the
under-development
of transport
infrastructure.
To of
address
such
transportplans
network
average GDP because of the under-development of transport infrastructure. To address such
invest
in
and
construct
the
Co
Chien
Bridge
with
the
aim
of
connecting
rural
areas,
particularly
in
needs in the provinces, the Transport Ministry of Vietnam announced plans to invest in and construct
transport network needs in the provinces, the Transport Ministry of Vietnam announced plans to
Province,
to more
areas. rural areas, particularly in Tra Vinh Province, to more
theTra
CoVinh
Chien
Bridge
with
the developed
aimChien
of connecting
invest
in and
construct
the
Co
Bridge with
the aim of connecting rural areas, particularly in
developed
Tra Vinhareas.
Province, to more developed areas.
Figure 2. The main road connecting Tra Vinh Province to Ho Chi Minh City, Vietnam. Adapted from
Google Maps [55].
Figure 2. The main road connecting Tra Vinh Province to Ho Chi Minh City, Vietnam. Adapted from
Figure 2. The main road connecting Tra Vinh Province to Ho Chi Minh City, Vietnam. Adapted from
Google Maps [55].
Google Maps [55].
Systems 2017, 5, 29
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6 of 21
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The
would reduce
reducethe
thetravel
traveldistance
distancebyby
and
around
hours
a round
trip
The bridge
bridge would
7070
kmkm
and
around
twotwo
hours
for afor
round
trip [56],
[56],
allowing
people
and entrepreneurs
the opportunity
ship products
larger
allowing
local local
people
and entrepreneurs
the opportunity
to shipto
products
directly directly
to largertomarkets
markets
such
as
in
Can
Tho,
Vung
Tau
and
Ho
Chi
Minh
City.
The
trading
route
from
Tra
Vinh
to
such as in Can Tho, Vung Tau and Ho Chi Minh City. The trading route from Tra Vinh to the larger
the
larger
cities
is
illustrated
by
the
red
line
in
Figure
2.
The
construction
of
the
bridge
was
expected
cities is illustrated by the red line in Figure 2. The construction of the bridge was expected to provide
to
provide benefits
significant
toeconomic
the majorsectors
economic
sectors
TraBen
Vinh
and
Ben Tre,agriculture,
including
significant
to benefits
the major
of Tra
Vinhofand
Tre,
including
agriculture,
tourism,
and
general
industry,
as
well
as
to
the
real
estate
market
[56].
Furthermore,
the
tourism, and general industry, as well as to the real estate market [56]. Furthermore, the geographic
geographic
location
of
these
provinces
is
suitable
to
develop
industries
such
as
fisheries
and
rice
location of these provinces is suitable to develop industries such as fisheries and rice growing,
growing,
given improved
accessmarkets.
to larger markets.
given improved
transport transport
access to larger
In
our
analysis
of
this
case
study,
we
In our analysis of this case study, we identified
identified all
all the
the benefits
benefits and
and costs
costs associated
associated with
with the
the
construction
of the
thebridge
bridgeand
and
examine
where
benefits
appear
the 30-year
construction of
examine
where
the the
costscosts
and and
benefits
appear
duringduring
the 30-year
period
period
from
from 2015
to2015
2045.to 2045.
5.
5. Findings
Findings and
and Discussion
Discussion
5.1. CBA
CBA Qualitative
Qualitative Analysis
Analysis
5.1.
A causal-loop
causal-loop diagram
diagram (CLD)
(CLD) was
was constructed,
constructed, see
see Figure
Figure 3,
3, that
that illustrates
illustrates the
the impact
impact of
of travel
travel
A
distance, cost,
onon
thethe
industrial
development
and supply
chain capacity
of Tra Vinh
Province.
distance,
cost,and
andtime
time
industrial
development
and supply
chain capacity
of Tra
Vinh
The modelThe
canmodel
clarifycan
problems
and facilitate
holistic understanding
of an infrastructure
project in
Province.
clarify problems
andafacilitate
a holistic understanding
of an infrastructure
its context.
project
in its context.
Traffic
Congestion
Transport
Infrastructure Project
Investment
-
R_S1
+
Industrial
Development
++
Travel Time
Travel
Distance
-
Supply chain
capacity +
R_S2
+
Transport
Cost
Figure 3. The relationship between project investment, travel cost saving, and industrial development.
Figure 3. The relationship between project investment, travel cost saving, and industrial development.
In such diagrams, the ‘+’ signs at the arrow-heads indicate that the effect is positively related to
In such
the ‘+’ signs
at theAarrow-heads
indicate that the in
effect
is positively
related
the cause
(an diagrams,
increase/decrease
in variable
leads to an increase/decrease
variable
B), the ‘−’
signs
to the cause
increase/decrease
A leads
an increase/decrease
in variable
B), the for
‘−’
indicate
the (an
opposite,
‘R’ indicatesina variable
reinforcing
loop,toand
S1, S2 stands for the
loop number;
signs
indicate
the
opposite,
‘R’
indicates
a
reinforcing
loop,
and
S1,
S2
stands
for
the
loop
number;
example, S1 refers to supply chain loop no. 1, and S2 refers to supply chain loop no. 2. Figure 3
for example,
refers to supply
chain
no. 1, and
refers toproject
supplyand
chain
loop chain
no. 2.capacity.
Figure 3
illustrates
theS1
relationship
between
an loop
investment
in aS2
transport
supply
illustrates
the relationship
between an
in a transport
and supply
chain
capacity.
The
‘exponential
growth’ behaviour
of investment
this loop points
to positiveproject
effect that
investing
in transport
The ‘exponential
growth’
behaviour
of this
loop points
to positive
effect
that
investing
transport
projects
has on supply
chain
capacity.
Transport
projects
improve
street
capacity
by in
allowing
a
projects
has on of
supply
chain
capacity.
Transportroute.
projects
improve
street
capacity
allowing
a larger
larger
number
vehicles
to travel
a particular
In the
case of
the Co
Chienby
Bridge
project,
the
numberallows
of vehicles
to travel
a particular
In and
the case
of the Co
Chien
project, the
bridge
bridge
each truck
to save
one hourroute.
per trip
US$193,983
per
year Bridge
when travelling
between
allows
each
truck to
save
per trip
yeartime
when
Tra
Tra
Vinh
Province
and
Benone
Trehour
Province
[56].and
TheUS$193,983
decrease inper
travel
andtravelling
transportbetween
cost would
Vinh Province
and Ben
Province
decrease
travel time
and transport
directly
influence
the Tre
capacity
of [56].
the The
supply
chaininsystem,
which
is one ofcost
thewould
vital directly
factors
influence the to
capacity
of thedevelopment
supply chainin
system,
which countries.
is one of the
vital factors
to
contributing
industrial
developing
According
to contributing
the Report of
industrial development
in developing
countries.
According
to the
of Transport
Engineering
Transport
Engineering Design
Inc. [56],
the Tra Vinh
and Ben
TreReport
industrial
growth rates
have a
Designrelationship
Inc. [56], the
Trainfrastructure
Vinh and Ben
Tre industrial
ratesinhave
a direct relationship
direct
with
development,
sogrowth
an increase
the industrial
growth ratewith
will
infrastructure
development,
so
an
increase
in
the
industrial
growth
rate
will
lead
to
the
need
to
extend
lead to the need to extend and improve infrastructure. Thus, local governments should pay attention
and
infrastructure.
Thus,planning
local governments
should
pay attention
the industrial
loop R_S1areas.
when
to
theimprove
loop R_S1
when developing
strategies for
transport
projects intonew
developing
planning
strategies
for
transport
projects
in
new
industrial
areas.
In Figure 4, the reinforcement loop, R_T1, illustrates the ‘exponential growth’ behaviour of a
In Figure
4, the
reinforcement
loop, R_T1, illustrates the ‘exponential growth’ behaviour of a
component
group
related
to the tax system.
component group related to the tax system.
Systems 2017, 5, 29
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Number of
vehicles
Tourism
Revenue
+
+
Revenue from the
real esate market
++
Road tax
+ Tax System +
Industrial
revenue
+
+
++
+
Transport
operation revenue
R_T1
Retail Market +
Agricultural
revenue
+
R_T2
Immigration
+
Public services
+ Life expectancy
Figure 4. Reinforcement loop R_T1 and R_T2; T1 and T2 stand for Tax loop no. 1 and Tax loop no. 2.
Figure 4. Reinforcement loop R_T1 and R_T2; T1 and T2 stand for Tax loop no. 1 and Tax loop no. 2.
In Figure 4, an increase in the number of vehicles travelling across Co Chien Bridge leads to an
In Figure
an increase
in the number
of vehicles
across
CoDue
Chien
Bridge
leads to an
increase
in tax4,revenue,
particularly
in terms
of road travelling
and vehicle
taxes.
to the
advantages
of
increase in taxthe
revenue,
particularly
in terms
of roadof
and
vehicletravelling
taxes. Due
of
implementing
new transport
project,
the number
vehicles
on to
thethe
Coadvantages
Chien Bridge
implementing
the
new
transport
project,
the
number
of
vehicles
travelling
on
the
Co
Chien
Bridge
from the local area to surrounding areas will significantly increase and contribute a large amount of
from the
area budget.
to surrounding
areas
significantly
increase
andcapital,
contribute
a large
amount
of
money
tolocal
the local
As a result,
thewill
local
government
has more
which
can be
used for
money to the
localservices,
budget. an
Asimportant
a result, the
localcontributing
governmenttohas
capital, which
canlocal
be used
for
improving
public
factor
themore
life expectancy
of the
people.
improving
public
services,
an
important
factor
contributing
to
the
life
expectancy
of
the
local
people.
Also, as public services are improved, there is the potential for a new trend of immigration from
Also, as
public
services
improved,
the potential
for apopulation.
new trend of
from
other
other
areas
to Tra
Vinhare
Province
thatthere
will is
increase
the local
Animmigration
immigration
increase
areas toa Tra
Vinh Province
that
will
increase
local population.
An immigration
increase
causes
causes
‘positive’
change in
the
number
of the
vehicles;
thus the positive
effect in the
loop R_T1
is
a
‘positive’
change
in
the
number
of
vehicles;
thus
the
positive
effect
in
the
loop
R_T1
is
reinforced.
reinforced. In addition to loop R_T1, loop R_T2 reflects the relationship between the tax system,
In addition
to loop
loop R_T2
reflects the
relationship
between
the
taxpoint
system,
public
services,
public
services,
life R_T1,
expectancy,
immigration,
and
the retail market.
The
key
of loop
R_T2
is the
life
expectancy,
immigration,
and
the
retail
market.
The
key
point
of
loop
R_T2
is
the
relationship
relationship between immigration and the retail market. When the population in a place increases,
between
immigration
and the retail
market.the
When
population
a place increases,
thisrole
creates
this
creates
good opportunities
to develop
retailthe
market,
whichinprovides
a convenient
for
goodpeople
opportunities
to develop
theand
retail
market, which provides a convenient role for local people in
local
in agricultural
trade
export.
agricultural
trade and export.
The reinforcement
loop R_L1 in Figure 5 focuses on the relationship between the elements of
loopofR_L1
Figure
5 focuses
on the investment,
relationshipand
between
the elements
of
GDP The
per reinforcement
capita; livelihood
the in
local
people,
agricultural
agriculture
revenue.
GDP per capita;
the local
people,
agricultural
investment,
agriculture
revenue.
Implementing
thelivelihood
Co ChienofBridge
project
in Tra
Vinh Province
directlyand
leads
to an increase
in
Implementing
Chien Bridge
Tra Vinh
leads toleads
an increase
in revenue
revenue
from the Co
industrial
sector project
and theinreal
estateProvince
market directly
and indirectly
to an increase
in
fromGDP
the industrial
andpeople.
the realAccording
estate market
indirectly
leadsby
to Transport
an increaseEngineering
in the GDP
the
per capitasector
of local
to aand
feasibility
report
per capita
of local
According
a feasibility
report
by Transport
Engineering
Design
Inc.have
[56],
Design
Inc.
[56], people.
Tra Vinh
Provinceto is
one of eight
areas
in the South
of Vietnam
that
Tra
Vinh
Province
is
one
of
eight
areas
in
the
South
of
Vietnam
that
have
advantages
for
exporting
rice
advantages for exporting rice to many countries. However, a major issue is that young people tend
many to
countries.
major
issue
is that young
people [57].
tendIncreasing
to move tothe
bigGDP
cities
incapita
order
to move
big citiesHowever,
in order toaseek
jobs
to improve
their income
per
to
seek
jobs
to
improve
their
income
[57].
Increasing
the
GDP
per
capita
for
local
people
can
be an
for local people can be an alternative solution that reduces this trend and preserves the labour
alternative
solution
that reduces
this local
trendpeople
and preserves
the labour
supply. When
livelihood
of
supply.
When
the livelihood
of the
is subsidised
in comparison
withthe
moving
to big
the local
subsidised
in comparison
with moving
to big
cities for work,
they
canthe
concentrate
cities
forpeople
work, isthey
can concentrate
on investing
in the
agricultural
sector,
and
revenue
on investing
in the
sector,
and the
revenue
from thisthe
sector
has anrate
influence
generated
from
thisagricultural
sector has an
influence
on GDP
per generated
capita. In addition,
illiteracy
in Tra
on GDP
per capita.
Incompared
addition, to
theother
illiteracy
rate in[58],
Tra so
Vinh
Province
is livelihood
high compared
to other
Vinh
Province
is high
provinces
increasing
the
opportunities
provinces
[58], socan
increasing
the livelihood
for local
canpeople
help resolve
this issue.
for
local people
help resolve
this issue.opportunities
When the number
ofpeople
educated
increases,
local
When
the
number
of
educated
people
increases,
local
government
has
advantages
in
implementing
government has advantages in implementing new policies to support the local people and to
new policies
to support
the This
localispeople
andintoreinforcement
increase the loop
average
income. This is depicted in
increase
the average
income.
depicted
R_L2.
reinforcement loop R_L2.
Systems 2017, 5, 29
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8 of 21
Revenue from the
real estate
Revenue from the
real estate
GDP per
capita
Education+
+
GDP per
capita
Education+
+
+
R_L2 Livelihood of R_L1 Agriculture
+
Revenue
commoner
+
R_L2 Livelihood
+ of R_L1 Agriculture
Revenue
commoner +
Agriculture
+
+
Investment
+
Agriculture
Investment
Figure 5. The two
livelihood loops.
Industrial
revenue
Industrial
revenue
8 of 21
Figure 5. The two livelihood loops.
Figure 5. The two livelihood loops.
After designing the small causal loop diagrams, the next step was to combine these loops with
After
designing
the asmall
causal loop
diagrams,
the picture
next step
wasimpact
to combine
these loops
with
other
factors
within
provide
a holistic
the
of the
project
within
After
designing
theCBA
smallsystem
causalto
loop
diagrams,
the next
stepofwas
to combine
these
loops
withits
other
factors
within
a
CBA
system
to
provide
a
holistic
picture
of
the
impact
of
the
project
within
context.
Figure
6 below
relationships
feedback
components
other
factors
within
a CBAillustrates
system to the
provide
a holisticand
picture
of theprocesses
impact ofbetween
the project
within its ofits
theFigure
project.
context.
6 below
illustrates
and feedback
feedbackprocesses
processes
between
components
context.
Figure
6 below
illustratesthe
therelationships
relationships and
between
components
of of
the project.
the project.
Transport
Infrastructure
Travel
- Traffic
Project
Investment
Transport
Distance
R_S1
Congestion
Infrastructure
+
Travel
-+ Traffic
+
Project Investment
Distance R_S2 Travel
Industrial R_S1Supply chain
Congestion
Development+
+
capacity+ +Time
Pollution+
+
+
B_C1
Industrial
Supply chain
+
R_S2 Travel
Transport
Cost
Development+
++
Travel Safety
Time capacity
Agricultural Savings
+
Pollution+
B_C1
Development
Number
of ++
+
+
+
Transport Cost
Labour Market
- VehiclesTravel Safety
Agricultural Tourism
Savings
Development
Development Revenue
Number of + +
+
+
+
+
+
Labour
Market
Vehicles
+
Tourism
The Real Estate
Industrial
Development
Revenue
Market
Road
Tax + +
+
+
+
Revenue
+
Development +
Transport
The Real Estate
+ Tax System ++
+ The Real Estate
Industrial
Operation
Market
+
+
Revenue Revenue
+
+
+ + + Road Tax
- Development
Revenue
Unemployment's
Agriculture
Transport
+ Tax System +
+ The Real Estate + +
Naturual
Revenue
rate
Operation
+
RevenueGDP per +
+
++
Environment
Revenue
R_T1
+
Unemployment's
Agriculture
capital
++
Education
Naturual
+
Revenue
Retail
rate
GDP
per
+
Environment
Immigration
R_L1
+
+
+ Market R_T1
+
capital
Education
+
R_L2
+
Agriculture
Retail
Social
Public
+
Immigration
R_L1
Investment
Market R_T2
+
Livelihood
of
+Crime +
+
+
Services
+
+ +
R_L2
+
commoner
Agriculture
Poverty
Social
Public
+
Investment
Life
R_T2
Crime + Livelihood
of
+
+
Services
+
+
+ +Expectancy
- Safety
commoner
Poverty
+
Life
+
Safety
+
+ +Expectancy
Food Safety
Health - +
Status
+
+
Food Safety
Health
Status
Figure 6. Causal model for the Co Chien Bridge Project.
Figure 6. Causal model for the Co Chien Bridge Project.
Figure 6.
model for
Co Chien
Bridge
Project.
Figure 6 was created
byCausal
synthesizing
thethe
causal
model
shown
in Figures 3–5 to provide a
holistic
the casual
relationshipsthe
between
investment
Co Chien
Project
Figurepicture
6 wasofcreated
by synthesizing
causalthe
model
shown in
in the
Figures
3–5 toBridge
provide
a
and
the
investment’s
impact
on
local
economy
and
community.
These
include,
for
example,
Figure
6
was
created
by
synthesizing
the
causal
model
shown
in
Figures
3–5
to
provide
holistic picture of the casual relationships between the investment in the Co Chien Bridge Projectthe a
indirect
relationship
between
project
investment
andin
transport
costfor
saving,
the direct
holistic
picture
of the casual
relationships
between
the
investment
the Co
Chien
Bridge
Project
and
the investment’s
impact
on transport
local economy
and
community.
These
include,
example,
the and
relationship
between
transport
cost
saving
and
supply
chain
capacity
improvements,
and
the
indirect relationship
investment and
transport
saving, the
direct
the investment’s
impactbetween
on localtransport
economyproject
and community.
These
include,cost
for example,
the
indirect
relationship
between
supply
chain
capacity
and
the
development
of
economic
sectors
in
Tra
Vinh
relationship
between
transport
saving and
supply chain
capacity
andbetween
the
relationship
between
transport
projectcost
investment
and transport
cost saving,
theimprovements,
direct relationship
Province. Based
onsupply
group chain
discussions
between
experts
and invited
team members
from
the Co
relationship
between
capacity
and
the
development
of
economic
sectors
in
Tra
Vinh
transport cost saving and supply chain capacity improvements, and the relationship between supply chain
Chien Bridge
Project,
these
relationships
were not only and
identified butteam
determined
to from
have athe
positive
Province.
Based
on group
discussions
between
members
Co
capacity
and the
development
of economic
sectorsexperts
in Tra Vinh invited
Province. Based
on group
discussions
impact
(+)
or
negative
impact
(−).
Chien Bridge Project, these relationships were not only identified but determined to have a positive
between experts and invited team members from the Co Chien Bridge Project, these relationships were
impact (+) or negative impact (−).
not only
but determined
5.2.identified
CBA Quantitative
Analysis to have a positive impact (+) or negative impact (−).
5.2. CBA
Quantitative
Analysis
After
creating
the causal-loop diagram, the next step was to use this to inform the creation of
5.2. CBA Quantitative
Analysis
what
is known
a stock-flow
model
setinform
of relationships.
Inof
this
After
creatingasthe
causal-loopquantitative
diagram, the
next that
step covers
was tothe
usesame
this to
the creation
After creating the causal-loop diagram, the next step was to use this to inform the creation of what
what is known as a stock-flow quantitative model that covers the same set of relationships. In this
is known as a stock-flow quantitative model that covers the same set of relationships. In this type of
Systems 2017, 5, 29
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9 of 21
model, stocks are things that accumulate, such as water in a cloud, body weight, and anger, and such
type represent
of model, stocks
are things
that
as water
in aare.
cloud,
weight,
andrepresent
anger,
stocks
conditions
within
a accumulate,
system; thatsuch
is, how
things
In body
contrast,
flows
type
of
model,
stocks
are
things
that
accumulate,
such
as
water
in
a
cloud,
body
weight,
and
anger,
and
such stocks
represent
conditions
within asuch
system;
that is, how things are. In contrast,
flows
theand
activities
that represent
cause
conditions
to change,
as that
evaporating/precipitating,
gaining/losing,
such stocks
conditions
a system;
is, such
how things
are. In contrast,
flows
represent
the activities
that
cause within
conditions
to change,
as evaporating/precipitating,
and
building/venting.
By that
usingcause
the reinforcing
loops
R_S1, R_S2,
and
R_T1, the authors selected
represent
the activities
conditions
to reinforcing
change,
such
as R_S1,
evaporating/precipitating,
gaining/losing,
and building/venting.
By using the
loops
R_S2, and R_T1, the
key
factors
from
the
project
to
include
in
this
new
model,
including
travel
time,
congestion
volume,
gaining/losing,
using
reinforcing
loopsmodel,
R_S1,
R_S2,
andtravel
R_T1,
the
authors selectedand
keybuilding/venting.
factors from the By
project
to the
include
in this new
including
time,
travel
average
speed,
transport
cost,the
supply
chain
capacity,inthe
number
of vehicles,
and the
taxtime,
system
authors
selected
key
factors
from
project
to
include
this
new
model,
including
travel
congestion volume, travel average speed, transport cost, supply chain capacity, the number of vehicles,
to congestion
set up stock-flow
processes.
Thespeed,
resulttransport
of this process
is shown
incapacity,
Figure 7.
travel
average
cost,
supply
chain
the number
of7.vehicles,
and the taxvolume,
system to
set up
stock-flow
processes. The
result
of this
process
is shown
in Figure
and the tax system to set up stock-flow processes. The result of this process is shown in Figure 7.
Vehicle
occupancy
Vehicle rate
occupancy rate
Total travel
demand
Total
travel
demand
Volume of personal
Volumevehicles
of personal
vehicles
Population
growth rate
Population
growth rate
The need of
Thetravelling
need of
travelling
Population
Change in
Population
population
Change
in
population Other factor 1
Use of mass transit
Agriculture
alternative
Other factor 1
Useand
of modes
mass
transit
Congestion
growth rate
Agriculture
and alternative
Other growth rate
volume/capacity
modes
Congestion
factor 2
Goods
Other
volume/capacity
Agriculture
factor 2
inventory
Goods
Street and
revenue
Change in
Agriculture
The percentage of inventory
highway
Street capacity
and
agricultural
revenue
Change revenue
in
sucessful
delivery
The
percentage
of
Supply chain
highway capacity
agricultural revenue
sucessful delivery
capacity
Supply
chain
System-wide
Industrial growth
capacity
average speed
System-wide
rate
Industrial
growth
Orders to
Industrial
average speed
rate
be released
The percentage of Orders to
revenue
Industrial
be released
Change in industrial
successful
orders
The
percentage
of
revenue
The percentage of successful orders
Changerevenue
in industrial
transport
cost saving
revenue
The percentage
of
transport cost saving
Figure7.7.The
Therelationship
relationshipbetween
between
transport
project
investment
industrial
sectors.
Figure
transport
project
investment
andand
industrial
sectors.
Figure 7. The relationship between transport project investment and industrial sectors.
breakingdown
downthe
theCBA
CBAvariable
variable into
into sub-level
sub-level activities,
ByBy
breaking
activities, the
theauthors
authorsinvestigated
investigatedthethe
By breaking
down
theactivities
CBA variable
into of
sub-level
activities,
the authorsThe
investigated
the
relationship
between
these
via
a
range
small
research
investigations.
full
stock-flow
relationship between these activities via a range of small research investigations. The
full
stock-flow
relationship
between
these
activities
via
a
range
of
small
research
investigations.
The
full
stock-flow
diagram
shownininFigure
Figure8,8,and
andAppendix
Appendix A
A provides
provides some
initial
diagram
isisis
shown
some of
of the
theparameters
parametersand
andtheir
their
initial
diagram
shown
in used.
Figure 8, and Appendix A provides some of the parameters and their initial
conditions
that
were
conditions
that
were
used.
conditions that were used.
Figure 8. Stock-Flow Model for Transport Infrastructure Project.
Figure
Model for
forTransport
TransportInfrastructure
InfrastructureProject.
Project.
Figure8.8. Stock-Flow
Stock-Flow Model
Systems 2017, 5, 29
10 of 21
The main contribution of the Co Chien Bridge project was to connect Tra Vinh province with
the big cities in the South of Viet Nam and improve the street and highway capacity, which is a vital
factor to reduce congestion as well as to improve the vehicle system-wide average speed (see the red
rectangle area in Figure 8).
Congestion volume/Capacity =
Volume of personal vehicles
Street and highway capacity
(1)
The vehicle operating cost (VOC) includes some main costs such as the labor cost, fuel cost,
repairing cost, maintaining cost, and depreciation cost. Depending on the speed of vehicle travelling
through the bridge, the operating cost for each vehicle is different, and thus the savings to VOC
can be measured. In addition, the relationship between VOC savings and supply chain capacity
would be explained via the percentage of successful orders and the successful percentage of delivery
(see Appendix B). In practice, transport cost, on average, accounts for 6.5% of market revenue and
44% of logistics costs [59], and these figures are varied according to particular contexts. In the case
of the Co Chien Bridge project, the relationship between supply chain capacity and the development
of economic sectors in Tra Vinh province was set up based on initial conditions and some project
assumptions regarding development growth rate (Appendix A). In the context of developing countries,
Lean et al. [60] indicates that the ratio of the logistics cost accounts for 18% of total GDP in China,
so we assume that the supply chain capacity would contribute 18% to the growth rate of industrial
sectors in Tra Vinh province. (These assumptions need to be justified by practical surveys and further
research.) The original cost-benefit analysis of the Co Chien Bridge project was carried out by Transport
Engineering Design Inc. [56]. In the company’s CBA report, two traditional methods were used for
CBA; financial analysis and economic analysis. The financial analysis focused on comparing the direct
benefits (revenue from project operation) and direct costs (construction and maintenance costs) over
a 30-year period. The economic analysis in the report referred to estimated indirect benefits from
time savings, cost savings, and accident reduction, and these benefits were compared with direct
costs (construction and maintenance costs) at the initial stage. Both traditional methods also used the
DCF technique to discount all future cash flow to the present value before calculating indices like
Net Present value (NPV) and Payback Period.
In contrast, this research concentrates more on indirect costs (Appendix C) and indirect project
benefits generated from different sectors of Tra Vinh Province such as tax, the unemployment rate,
and GDP to provide analyses. The System Dynamics (SD) technique enables us to model and visualize
the behavior of a CBA system. All system components of CBA are interconnected and experts can
investigate our assumptions or test investment policy via adjusting initial variables such as construction
cost, population, ticket price, street capacity, and the number of vehicles (Appendix D). Under the scope
of this research, the cost-benefit analysis (CBA) system is set up to model influences of the Co Chien
Bridge project on the local area across a 30-year period from project implementation. This research
focuses on the main costs during the project life cycle, consisting of construction cost, land acquisition,
project management cost, project operation cost, and environmental protection cost. As the report
provided by Transport Engineering Design Inc. [56] states, the direct project cost was approximately
US$200 million, but the total project cost (see Figure 8), which includes direct cost, project operation cost
(over 30 years), and environmental protection cost (Appendix C), is estimated to reach US$604 million.
The benefits of the project mainly come from tax contributed from different industrial sectors and the
transport operation revenue. All estimated project benefits at different time points were discounted
to present values before comparing them with the costs of the project at the initial stage. The CBA
below was identified by using the total present values of the project benefits minus the total project
costs. The CBA value was accumulated by time, and, when the CBA reaches the zero value (Figure 9),
it means that the total benefits are equal with the total cost. In other words, the payback period was
identified at the time point of 12 at which NPV is zero.
Systems 2017, 5, 29
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Figure
Cost-benefitanalysis
analysis of
Project
in Vietnam.
Figure
9. 9.Cost-benefit
of the
theCo
CoChien
ChienBridge
Bridge
Project
in Vietnam.
Based on a feasibility report by Transport Engineering Design Inc. [56], some financial indices
a feasibility
report
bybe
Transport
Design
Inc.
some
financial
indices
ofBased
the Coon
Chien
Bridge
can
determined
traditional
methods.
The
net present
value
Figureproject
9.
Cost-benefit
analysis
ofEngineering
theusing
Co Chien
Bridge
Project
in [56],
Vietnam.
of the
Co
Chien
Bridge
project
can
be
determined
using
traditional
methods.
The
net
present
value
(NPV) of the Co Chien Bridge project is US$ 22 million, the interest internal rate of return (IRR) is
Based
a feasibility
Transport
Engineering
Design
Inc.internal
[56], some
indices
(NPV)
of the
Coon
Chien
Bridge
is US$22
million,bytheusing
interest
ratefinancial
of return
(IRR) is
10.97%,
and
payback
time report
isproject
19.3byyears.
In contrast,
the
system
dynamics
approach
of and
the Co
Chienthat
Bridge
beIndetermined
using
traditional
methods.
Thetime
net
present
value
described
herein
draws
on years.
acan
wider
set
of criteria,
our
model
gives
a dynamics
payback
of 12.1 years,
10.97%,
payback
time
isproject
19.3
contrast,
by
using
the system
approach
described
(NPV)
of the Co
Bridge
project
isisUS$
million,
the interest
internal
rate
of
return
(IRR)
is is
which
is draws
significantly
shorter.
The
reason
that
the
SD approach
intime
this
paper
considers
the
herein
that
onChien
a wider
set
of
criteria,
our22
model
gives
a outlined
payback
of
12.1
years,
which
10.97%,benefits
and payback
time
is 19.3 economic
years. In contrast,
by using
the system
dynamics
approach
indirect
gained
by
different
sectors,
such
as
agriculture,
industry,
tourism,
the
significantly shorter. The reason is that the SD approach outlined in this paper considers the indirect
described
herein
that
draws
on a market.
wider setHowever,
of criteria, ourquestion
model gives
payback
time
of
12.1 years,
retail
market,
the real
estate
‘howa much
NPV
isthe
enough
benefits
gained
byand
different
economic
sectors, such as the
agriculture, industry,
tourism,
retailand
market,
which isfor
significantly
The reason
is that
the SD
approach
outlined
in this paper
considers the
sufficient
making anshorter.
investment
decision?’
needs
to be
investigated
in further
research.
and the
real estate
market. However,
the economic
question ‘how
much
NPV
is enough industry,
and sufficient
for making
indirect
benefits gained rate
by different
sectors,
such labor
as agriculture,
tourism, and
the
The unemployment
is the percentage
of the total
force that is unemployed
an investment
decision?’
needs
to
be
investigated
in
further
research.
retail
market,
and
the
real
estate
market.
However,
the
question
‘how
much
NPV
is
enough
and
actively seeking employment and willing to work [50]. According to The World Bank [61], the total
The
unemployment
rate
is the percentage ofneeds
the total
labor
force that
is unemployed
and actively
sufficient
for making rate
an investment
to be
investigated
in further
research.
youth
unemployment
in Vietnamdecision?’
in 2013 was 5.4%,
while
the unemployment
rate in Tra Vinh
seeking
employment
and
willing
work
[50].10,
According
to
The
World
Bank
[61], the
total
youth
Thewas
unemployment
rate
istoyear.
the
percentage
of
the total
forcethe
that
unemployed
and
Province
16.67%
in the
same
Figure
produced
bylabor
running
SDismodel,
shows
that
actively
seeking
employment
and
willing
to
work
[50].
According
to
The
World
Bank
[61],
the
total
unemployment
rate
in
Vietnam
in
2013
was
5.4%,
while
the
unemployment
rate
in
Tra
Vinh
Province
implementing and operating the Co Chien Bridge project brings direct and indirect benefits for local
youthbecause
unemployment
rate
in Vietnam
in the
2013project
was
unemployment
inimplementing
Tra Vinh
waspeople
16.67%
in the same
year.
Figure
10, produced
by 5.4%,
running
thethe
SD
model,
showsrate
that
jobs are
created
through
and while
across
a range
of economic
sectors.
The
Province
was
16.67%
in
the
same
year.
Figure
10,
produced
by
running
the
SD
model,
shows
that
andmodel
operating
the Co
Bridge projectrate
brings
andfrom
indirect
benefits
for local
people
because
predicts
thatChien
the unemployment
willdirect
decrease
16.67%
to 13.33%
(Figure
10) as
a
implementing and operating the Co Chien Bridge project brings direct and indirect benefits for local
of the investment
in the
project.
jobsresult
are
created
through the
project
and across a range of economic sectors. The model predicts that
people because jobs are created through the project and across a range of economic sectors. The
the unemployment rate will decrease from 16.67% to 13.33% (Figure 10) as a result of the investment in
model predicts that the unemployment rate will decrease from 16.67% to 13.33% (Figure 10) as a
the project.
result of the investment in the project.
0.20
0.175
0.20
0.15
0.175
0.125
0.15
0.10
0.125
0.10
Figure 10. Unemployment rate in Tra Vinh Province over a 30-year period from the opening of the
bridge.
Figure 10. Unemployment rate in Tra Vinh Province over a 30-year period from the opening of
Figure 10. Unemployment rate in Tra Vinh Province over a 30-year period from the opening of the
the bridge.
bridge.
Systems 2017, 5, 29
12 of 21
Systems 2017, 5, 29
12 of 21
Gross
It is
is defined
defined as
as ‘an
Gross domestic
domestic product
product (GDP)
(GDP) is
is aa measure
measure of
of the
the size
size of
of an
an economy.
economy. It
‘an
aggregate
measure
of
production
equal
to
the
sum
of
the
gross
values
added
of
all
resident,
institutional
aggregate measure of production equal to the sum of the gross values added of all resident,
units
engaged
in production’
According
The WorldtoBank
theBank
GDP[61],
of Vietnam
institutional
units
engaged in [62].
production’
[62].toAccording
The [61],
World
the GDPwas
of
US$186.2
billion
in
2014
from
a
total
population
of
90.73
million
people.
The
GDP
of
Tra
Vinh
Vietnam was US$ 186.2 billion in 2014 from a total population of 90.73 million people. The GDP of
Province
was US$1.58
in 2014
from
1.028
million
this figure
is projected
to reach
Tra Vinh Province
wasbillion
US$ 1.58
billion
in 2014
from
1.028people,
millionand
people,
and this
figure is projected
US$12.5
in billion
the next
In order
holistic aview
of GDP
Vinh
to reach billion
US$ 12.5
in30
theyears.
next 30
years. to
Inprovide
order toaprovide
holistic
viewfor
of Tra
GDP
for Province,
Tra Vinh
the
graphs
in
Figure
11
were
generated
by
the
model
to
assess
the
impact
of
the
Co
Chien
Province, the graphs in Figure 11 were generated by the model to assess the impact of the CoBridge
Chien
project
on the different
economic
sectors,sectors,
including
the realthe
estate
the agricultural
sector,
Bridge project
on the different
economic
including
real market,
estate market,
the agricultural
the
retail
tourism,
and general
industry.
sector,
themarket,
retail market,
tourism,
and general
industry.
Base Run
No Bridge
Base Run
No Bridge
"Gross Domestic Product (GDP)"
12,700
9819
Revenue from the estate market
9605
7333
6939
4060
5061
2789
1181
Agriculture revenue
245.7
240.5
517
Revenue from the retail market
2150
1685
235.4
230.2
1220
755.4
225.1
Industrial revenue
249
217.4
290.5
The tourism revenue
448.4
342.8
185.8
154.2
122.6
237.1
131.4
0
15
Time (Year)
30
25.7
0
15
Time (Year)
30
Figure 11. Economic sectors’ revenue of Tra Vinh Province from the opening of the bridge.
Figure 11. Economic sectors’ revenue of Tra Vinh Province from the opening of the bridge.
In the base case of the opening of Co Chien bridge, two main economic sectors, tourism and
In
thereceive
base case
of theeconomic
opening value
of Co from
Chienthe
bridge,
two maindevelopment.
economic sectors,
tourism
industry,
the most
infrastructure
During
the firstand
10
industry,
receive
the
most
economic
value
from
the
infrastructure
development.
During
thetimes
first
years, the revenue gained from tourism is projected to reach US$ 400 million, which is four
10
years,than
the revenue
gained
fromfirst
tourism
projectedrevenue
to reachgenerated
US$400 million,
which is
is forecast
four times
greater
the revenue
in the
year. isSimilarly,
by industry
to
greater
than
the
revenue
in
the
first
year.
Similarly,
revenue
generated
by
industry
is
forecast
to reach
reach approximately US$ 250 million in 2045, which is three times greater than revenue in 2015.
The
approximately
millioneconomic
in 2045, which
is three
greater
revenue
in 2015.
reasons
reasons for theUS$250
significant
growth
ratestimes
are that
Trathan
Vinh
Province
has The
favourable
for
the significant
growth
rates are such
that Tra
Vinh
Province
has favourable
conditions
for the
conditions
for theeconomic
development
of tourism,
as its
location
between
two of the
largest cities
in
development
of
tourism,
such
as
its
location
between
two
of
the
largest
cities
in
the
south
of
Vietnam,
the south of Vietnam, a diverse ecological environment, traditional food, and numerous historical
abuildings
diverse ecological
environment,
traditional
food,advantages
and numerous
historical
buildings
[63]. agriculture,
Along with
[63]. Along
with the tourism
industry,
related
to human
resources,
the
tourism
industry,
advantages
related
to
human
resources,
agriculture,
forestry,
and
fisheries
are
forestry, and fisheries are also in evidence in this region and are a strong motivation for industrial
also
in
evidence
in
this
region
and
are
a
strong
motivation
for
industrial
development.
In
contrast,
the
development. In contrast, the growth rate of the agricultural sector in the first 10 years after project
growth
rate of thetends
agricultural
sector
in the
first 10
years
projectslightly
implementation
to increase
implementation
to increase
more
slowly
and
thenafter
increases
faster as tends
industrial
zones
more
slowly
and
then
increases
slightly
faster
as
industrial
zones
are
established
to
export
agricultural
are established to export agricultural products. In comparison with the case of not implementing Co
products.
In comparison
with thefrom
casedifferent
of not implementing
Co Chien
Bridge
project, the
Chien Bridge
project, the revenue
economic sectors
declines
significantly,
andrevenue
the real
from
different
economic
sectors
declines
significantly,
and
the
real
estate
market
would
be
one
of the
estate market would be one of the most affected sectors due to its contributed revenue. The reason
most
affected
sectors
due
to
its
contributed
revenue.
The
reason
for
these
declines
is
because
the
Co
for these declines is because the Co Chien Bridge project is a main connection between Tra Vinh
Chien
Bridge
is ainmain
connection
betweenWithout
Tra Vinhthe
Province
andbridge
big cities
in thetwo
South
of
Province
and project
big cities
the South
of Vietnam.
Co Chien
project,
main
variables of the CBA system, including street capacity and population growth rate, would have
major changes and create significant impacts on the supply chain capacity in Tra Vinh Province.
Systems 2017, 5, 29
13 of 21
Vietnam. Without the Co Chien bridge project, two main variables of the CBA system, including street
capacity and population growth rate, would have major changes and create significant impacts on
the supply chain capacity in Tra Vinh Province. Without project investment, it clearly shown that the
revenue from industrial sectors increases slowly and directly affects the total GDP of Tra Vinh province
(Figure 11). To sum up, the visualization capability of SD provides us with a holistic picture of the
project impacts on the local economy, and the difference between growth rates for different industries
should be considered a critical factor used for evaluating and deciding on project prioritisation.
Validation is the next step used to ensure that the model supports the objective truth [40]. As no
model exactly represents the real world, the model was verified and validated based on a set of
limitations and assumptions. Instead of reflecting exactly historical data, variables of the system should
show the meaningful relationship with others in the whole system. In line with this, the CBA model
in this research was built based on specific constraints and assumptions (Appendix A) to provide
insights on CBA in transport infrastructure projects and to support policy makers in optimizing
investment options.
6. Conclusions and Recommendations
This research focused on researching the indirect impacts of transport project investment on the
local economy to improve the comprehensiveness of CBA and support decision-making processes.
SD provides a causal model, which can help policy-makers to recognise the relationships between
transport infrastructure projects and benefits to the local economy. The interactions between CBA
components were shown using a number of different feedback loops. Understanding these interactions
allows policy-makers to determine the key factors of the system to inform necessary changes during
the decision-making process. In addition, the stock-flow model of the CBA system allows experts
to measure the impact of project investment on the local economy and determine how individual
economic sectors will be affected. By setting the input data for the stock-flow model, together with
using the Vensim software, experts can make quantitative evaluations for the economic and social
benefits of an infrastructure project.
In order to improve the process of model development in the CBA system and to improve the
effectiveness of decision-making processes, some practical suggestions should be implemented. Firstly,
the CBA system needs to be discussed by experts, along with specific conditions and assumptions
to identify the costs and benefits of investing in a transport infrastructure project. Any changes in
environmental conditions or assumptions can lead to changes in outputs, so policy-makers should pay
attention to this factor in the early project stages in order to effectively set up the working conditions
used for modelling the CBA system before moving to the next stages. Next, the research results should
be connected to the planning process after CBA because this allows CBA practitioners to discuss the
results of CBA with the people who will use the CBA results. Differences in understanding problems
can be solved by direct discussion between experts and local planners. This ensures that policy-makers
have a full understanding of the issues of the project (costs), as well as being able to recognise the
impact of the project in terms of benefits to the local economy, before making important investment
decisions. Finally, human resources are key factors contributing to the success of any project, so it
is important to select people who have sufficient understanding of system dynamics and project
management for the project team.
7. Limitation and Future Work
While this research has provided an alternative approach to evaluating the economic and social
benefits generated from transport infrastructure projects, some uncertainties and several limitations
have been identified. Firstly, system dynamics is an approach that is effective for modelling complex
systems in the real world, but this approach primarily relies on assumptions and constraints to set
up the conditions used for modelling. As these assumptions and constraints will be different for
every project, the project team will need to consider these carefully while establishing and identifying
Systems 2017, 5, 29
14 of 21
the boundary of the CBA system. Secondly, the database of the CBA system is based on project
information provided by team members of the Co Chien Bridge project and local government,
so there is a slight difference between the economic indices used during project evaluation. Thirdly,
resource constraints were also a limitation of this research. It is recommended that future modelling
efforts be implemented with the support of additional experts in areas such as system dynamics,
project management, and social-economic statistics.
Reflecting on the research limitations mentioned in the previous section, further research is
recommended in the following areas. Firstly, breaking down the CBA variable into sub-level activities
and studying their dynamics individually could be a fruitful area for future research. Secondly,
the methodology used in this research should be applied to different countries, thereby increasing
the data available for future comparisons of cost-benefit factors in infrastructure projects in different
cultural contexts. Thirdly, it would be useful to organise workshops for practitioners and academics in
order to increase their mutual understanding of the application of system dynamics for cost-benefit
analyses. Finally, it would be useful to capture the information from the above activities in a generic
SD model that can be parameterized for a wide range of situations.
Acknowledgments: We would like to thank many people from Transport Engineering Design Inc. (TEDI) in
Vietnam, who provided various data, reports, and information to support this research.
Author Contributions: T.N. contributed to the professional development, data collection and analysis;
S.C. contributed to the development of the framework, writing and editing; V.I. contributed to the data analysis.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A
Table A1. Variables and Model Parameters.
List
Parameter
Initial Value Set
Unit
Source
1
Land acquisition cost
10.8
USD Million
Transport Engineering
Design Inc. [56]
2
Construction cost
183.6
USD Million
Transport Engineering
Design Inc. [56]
3
Project management cost
14.2
USD Million
Transport Engineering
Design Inc. [56]
4
Project operation cost
305
USD Million
Transport Engineering
Design Inc. [56]
5
Environment protection cost
93
USD Million
Appendix C
6
Local Population
1,360,300
People
General Statistics Office of
Vietnam [64]
7
Population growth rate
0.8
%/year
General Statistics Office of
Vietnam [64]
8
Number of vehicles travelling
before bridge built
3,123,000
vehicles/year
Transport Engineering
Design Inc. [56]
9
The vehicle growth rate
5.5
%/year
Transport Engineering
Design Inc. [56]
10
Vehicle occupancy rate
80%
%
Transport Department
11
Use of mass transit and
alternative modes
12%
%
Transport Department
12
Street and highway capacity
9,061,800
vehicles/year
Transport Engineering
Design Inc. [56]
13
System wide average
speed options
40; 60; 80
km/h
Transport Engineering
Design Inc. [56]
Systems 2017, 5, 29
15 of 21
Table A1. Cont.
List
Parameter
Initial Value Set
Unit
Source
14
Goods inventory in Tra
Vinh Province
361,000
Tons
General Statistics Office of
Vietnam [64]
15
Order to be released in Tra
Vinh Province
520,000
Tons
General Statistics Office of
Vietnam [64]
16
Agriculture revenue
225.1
USD Million
General Statistics Office of
Vietnam [64]
17
Agriculture growth rate
3.44
%/year
General Statistics Office of
Vietnam [64]
18
Industry revenue
122.6
USD Million
General Statistics Office of
Vietnam [64]
19
Industry growth rate
27.8%/year
N/A
General Statistics Office of
Vietnam [64]
20
Transport cost saving
Transport Engineering
Design Inc. [56]
+ v = 40 km/h
15
%
Appendix
+ v = 60 km/h
25
%
Appendix
21
Tourism revenue
26.7
USD Million
[64]
22
Tourism service development
13.1
%/year
[64]
23
The retail market revenue
290.5
USD Million
[64]
24
The retail market growth rate
20.9
%/year
[64]
25
The real estate market revenue
517.9
USD Million
[64]
26
The growth rate of the
real estate
34.1
%/year
[64]
27
The unemployment rate of Tra
Vinh Province
13.4
%/year
[64]
28
Ticket price of toll road
2
USD
Local policy
29
Tax of transport operation
2
%/revenue/year
General Department of
Taxation (GDT) 2013
30
Agriculture income tax
1
%/revenue/year
GDT 2013
31
Average tax of industrial
sector
2
%/revenue/year
GDT 2013
32
Tourist tax
3
%/revenue/year
GDT 2013
33
Property tax
2.5
%/revenue/year
GDT 2013
34
Retail tax
3
%/revenue/year
GDT 2013
Appendix B. Scripts and Model Equations
Formal
Stock(t) =
Z t
0
[Inflow(t) – Outflow(t)] ds + Stock (0)
Script
Stock = INTEG (rate1-rate2, Stock_0)
where Stock (0) is the stock at the initial time
R 30
•
Number of vehicles (t) = Number of vehicle (t0) +
•
Number of vehicle (0) = 3,123,000 (vehicle)
R 30
Agriculture revenue (t) = Agriculture revenue (0) + 0 [Increasing agricultural revenue] dt
0
[Increasing number of vehicle] dt
Systems 2017, 5, 29
•
Agriculture revenue (0) = 225.1 (US Million)
R 30
Industrial revenue (t) = Industrial revenue (0) + 0 [Increasing industrial revenue] dt
•
Industrial revenue (0) = 122.6 (US Million)
R 30
Tourism revenue (t) = Tourism revenue (0) + 0 [Increasing tourism revenue] dt
•
Tourism revenue (0) = 26.7 (US Million)
R 30
Real estate revenue (t) = Real estate revenue (0) + 0 [Increasing real estate revenue] dt
•
Real estate revenue (0) = 517.9 (US Million)
R 30
Retail market revenue (t) = Retail market revenue (0) + 0 [Increasing retail revenue] dt
•
16 of 21
Retail market revenue (0) = 290.5 (US Million)
GDPin = ∑1n QinPin = ∑30
1 (Agriculture Revenue + Industry Revenue + Tourism Revenue
+ Retail Revenue + Revenue of the Real Estate Market) (US Million)
According to the report of the Ministry of Planning and Investment [65], the labour market of
the Mekong Delta in Vietnam is mainly supplemented by three main economic sectors, which are
agriculture (49.5%) and the industrial and real estate markets (17.2%), as well as tourism and the retail
market (33.3%). Based on these statistics, the unemployment rate of the Tra Vinh Province is suggested
in following equation.
•
The unemployment rate = the current unemployment rate (0.167) − 0.495 * agriculture growth
rate − 0.172 * (industrial growth rate + real estate market growth rate) − 0.333 * (retail market
growth rate + tourism growth rate).
Supply chain activities comprise the transformation of natural resources, raw materials,
and components into a finished product that is delivered to the end customer [66]. This relationship
can be illustrated in the following equations.
•
•
•
•
•
•
Supply chain capacity = Orders to be Released/Good Inventory;
System-wide average speed = IF THEN ELSE (‘Congestion volume/capacity’< 1, 60, 40) (km/h);
The percentage of successful delivery = IF THEN ELSE (‘System-wide average speed’ ≥ 60%,
80%, 50%);
The percentage of successful orders = IF THEN ELSE (The percentage of transport cost
saving ≥ 25%, 80%, 50%)
Orders to be Released = The percentage of successful orders * Orders to be Released
Goods Inventory = The percentage of successful delivery * Goods Inventory
Cost-benefit analysis of the Co Chien Bridge project is defined using the total discounted benefits
minus the total costs of the project. The relationship between the total costs and total benefits is
calculated in following equations.
•
•
Total present values of benefits = ∑30
0 PV ( t )
1
PV(t) = benefit(t) * Current time
PV (t)
•
•
•
Current time PV = (1 + Discount rate * TIME STEP)ˆ((Time − INITIAL TIME)/TIME STEP)
Discount rate = 10%/year
Total cost(0) = Land acquisition cost + construction cost + project management cost + Project
operation & maintain cost + pollution cost.
Net present value (NPV) = Total present values of benefits − Total cost(0)
Total Cost
Payback period = Total present
values of benefits × 30 (year).
•
•
Systems 2017, 5, 29
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Appendix C
Table A2. Environmental Risk Assessment Matrix.
Cost ($ Million)
Likelihood
Risk Categories
Risk Scenario
Quantitative
Qualitative
Quan
Qual
Quan
Qual
Visual Amenity
Degraded visual amenity due to untidy construction site and presence of plant and
equipment
50%
Moderate
10
High
5
Extreme
Dust generated through excavation works and traffic movement
100%
Almost certain
6
Moderate
6
Extreme
Plant, equipment and vehicle emissions during construction
75%
Likely
2
Minor
1.5
Moderate
Temporary elevated noise emissions during construction of substation and cable
vault (during weekdays and on the weekend) at neighboring residential and
commercial properties
25%
Unlikely
6
Moderate
1.5
Moderate
Traffic disruption due to partial closure of the project during the construction of the
cable vault
50%
Moderate
2
Minor
1
Low
Increase in vehicular traffic on local road network during construction of the
substation and cable vault
75%
Likely
6
Moderate
4.5
High
Inefficient use of resources, plant and equipment during construction
25%
Unlikely
6
Moderate
1.5
Moderate
Emissions associated with use of resources during construction
75%
Likely
6
Moderate
4.5
High
Discharge of ‘dirty’ water and pollution of waterways and drainage lines
100%
Almost certain
14
Extreme
14
Extreme
Discharge of contaminant laden runoff from accidental spillage of chemicals and
fuels from the operation and maintenance of construction plant and equipment
25%
Unlikely
14
Extreme
3.5
Extreme
Contamination of soil, surface water and groundwater from spills and leaks
associated with the inappropriate storage and handling of chemicals, oils and fuel
75%
Likely
14
Extreme
10.5
Extreme
12
Localized contaminated material that is excavated during cable vault works
25%
Unlikely
10
High
2.5
High
13
Amenity (including traffic, noise and visual) impacts on the surrounding residents
and stakeholders during construction
75%
Likely
10
High
7.5
Extreme
14
Safety and access impacts associated with the construction of the bridge
75%
Likely
10
High
7.5
Extreme
15
Potential contamination of land and water due to inappropriate handling and
disposal of waste materials
50%
Moderate
10
High
5
Extreme
Extreme
Risk ID
1
2
3
4
Air Quality
Noise and vibration
5
Traffic and access
6
7
8
9
10
11
Sustainability and
climate change
Water quality
and hydrology
Contamination
Socio-economic
Waste management
16
17
Heritage
18
Flora
19
Cumulative impacts
Consequence
Risk Level
Nonconformance with waste hierarchy and principles of the local government
75%
Likely
10
High
7.5
Impact to any item of historic during construction
50%
Moderate
6
Moderate
3
High
Spread of exotic species
25%
Unlikely
6
Moderate
1.5
Moderate
Cumulative impacts on environment and community due to cumulative
construction projects in the immediate vicinity
50%
Moderate
10
High
5
Extreme
Total
93
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21of 21
Appendix D
Appendix D
Figure D1. Assumptions and Policy Test.
Total travel
demand
Vehicle
occupancy rate
.8
Volume of personal
vehicles
Population
growth rate
Street and
highway capacity
500000
.12
System-wide
average speed
The percentage
of successful
orders
The percentage of
transport cost saving
Increase in
population
Other factor 1
Increase in number
of vehicles
Other factor 2
Supply chain
capacity
Orders to
be released
Increase in
agricultural revenue
.02
Increase in
industrial revenue
Gross Domestic
Product (GDP)
Tax from
agricultural
sector
Agriculture
revenue
Tax from
project
operation
Average tax of
industrial sector
Industrial growth
rate
The
unemployment
rate
Tax of transport
operation
.01
.278
Goods
inventory
Revenue from
transport
operation
Agriculture
income tax
.034
Agriculture
growth rate
.02
Industrial
revenue
Tourist tax
Increase in benefit
Tax from
industrial
sector
Total of benefits
Total received
taxes
.03
<INITIAL TIME>
Tourism service
development
0
Increase in tourism
revenue
The retail market
growth rate
2.0e-6
Number of
vehicles
Population
Use of mass transit and
alternative modes
The percentage
of sucessful
delivery
Ticket price of
toll road
3.123 M
.002
The need of
travelling
.75
Congestion
volume/capacity
Initial number of
vehicles
The vehicle
growth rate
Tax from
tourism
sector
The tourism
revenue
Property tax
.025
RE growth rate
Tax from the
real estate
market
Revenue from
the estate
market
<Time>
1
Land Acquisition
Construction Cost
Cost-benefit
analysis
183.6
Project
Management Cost
14.2
Retail tax
.03
Revenue from the
retail market
Total present
values of benefits
.1
10.8
Increasing RE
revenue
Increae in the retail
revenue
current time PV
<TIME STEP>
Other factor 3
.341
The need of
accommodations
Discount
rate
Tax from the
retail market
Environmental
protection Cost
93
Project Operation
Cost
305
Figure A1. Assumptions and Policy Test.
Total Costs
Systems 2017, 5, 29
19 of 21
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