Application of System Dynamics to Evaluate the Social and ... - MDPI

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

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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,

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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.

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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.

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Identify variables including costs and benefits

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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].

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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.

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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.

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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

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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

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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

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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.

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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.

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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.

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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

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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]

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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

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•

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).

• •

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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

Systems 2017, 5, 29 Systems 2017, 5, 29

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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



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



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



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

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