INTRODUCTION:

Construction megaprojects like that of a mass transit system development in India are generally complex which deploy complex technologies and operate in a dynamic environment. Hence they are vulnerable to failure in terms of time, cost and quality achievement. The failures are the outcomes of challenges generated from social, technical, economic, environmental and political issues (STEEP) and the interactions among them. Although attempts are taken to mitigate the risks of cost overrun, schedule slippage and quality achievement during project planning stage, the challenge of understanding exists on how risk interactions can be modelled dynamically which impact project performance. In this paper an attempt has been made to analyse the suitability of system dynamics to model the interactions of 'STEEP' Risks within the dynamic environment of megaprojects.

MATERIAL AND METHODS:

STEEP risks refer to Social, Technical, Economic, Environmental, Political (STEEP) risks in a complex dynamic environment of a construction megaproject. Each of them is described briefly below:

Social Risks: Megaproject constructions are complex and have relatively large effects on people and environment compared to other construction projects. Due to the capital intensity of such projects, they often require diversion of traffic, and also sometimes they are required to divert rivers. This, in turn, affects existing user rights and access to some parts of roads. These have significant impact on livelihoods and the environment. Evidence in literature proved that the effects of such large developmental projects on socioeconomic activities and the archaeological historical sites of every nation are enormous. Thus, social risks may be defined as national and local-level factors that contribute to social (in) stability (such as levels of governance, security and population size) as well as project specific issues (the nature of the project approval process, the outcomes of similar projects previously conducted in the area, bad sub-contractor qualification, communication and low labour productivity, inexperience project manager, confusion of personnel management etc.)

Technological risks: Technological or Technical risk is the most common and well understood form of risk. These risks are mainly threats that prevent the operations of the contracting companies to develop, deliver, and/or manage its services, and to support operations. Tatum (1987)^[2]defined construction technical risks as risks associated to the combination of construction methods, construction resources, work tasks, and project influences that define the manner of performing a construction operation to “unaccomplished desired aim necessary for human sustenance and comfort” (Shin, Watanabe, and Kunishima, 1989)^[3]. Some of the technical risks that can impact megaproject performance include: supply chain breakdown, scheme design risk such as difficulty of engineering, defective design, inefficient optimized construction scheme, large percentage of new technology adopted; too advanced scheme, unqualified technology, insufficient estimation, over-evaluation of one's own strength, underestimate rivals, risk of construction quality, poor time management during project control, the confused financial administration and many others.

Economic risks: Economic risks for megaproject development are mostly risks of project finance that evolve during the project delivery (Baloi and Price, 2003^)[4]. These risks arise as a result of the adjustments of national economic policy, inflation, fluctuate of price, interest rate and exchange rate due to the relative long period of delivery of such projects. In transportation megaproject such as underground corridor for metro rail construction, financing the nature and level of risks vary during the life cycle of the project and fall into two broad areas of completion and market (Opler et al., 1997)^[5]. Completion risks may arise during investment phase, while market risk is associated with the operational one.

Environmental risks: Environmental risks are risks to the natural health and productivity of environmental systems and risks to human health stemming from alteration and/or degradation of environmental systems’ (Lerche and Glaesser, 2006 as cited in Chen, Z., et al., 2011^)[6].These are natural risks such as unfavourable climatic conditions (continuous rainfall, snow, temperature, wind), force majeure (thunder and lightning, earthquake, flood, hurricane, etc.) that have tremendous influence on the project and the bad environmental conditions (pollution, traffic, etc.) of construction activities on the physical environment. For construction projects, several aspects of environmental issues have been identified by academic researchers in the literature. According to Chen et al. (2000)^[7], dust, harmful gases, noise, solid and liquid wastes, fallen objects, and ground movements are types of pollution and/or hazards sources from construction activities which impact on the environment. Failure to mitigate these risks can result in serious impacts such as erosion, permanent loss of wild life, community severances, increased accidents, and destruction of indigenous lifestyles. Fig. 1indicates the major effects of the construction industry on the natural environment.

Fig. 1. The main environmental effects of constructional activities (Griffith, 1994)

Political risks: Many projects are delayed because of the difficulties of acquiring right-of-way or environmental clearances that both the governments and the operators underestimate. Mass transit infrastructure project mostly belonging to a state (country) or the government, are easily influenced by the adjustment of state laws, regulations, and government policy. Political risk concerns government actions that affect the ability to generate earnings. These could include actions that terminate the concession, the imposition of taxes or regulations that severely reduce the value to the investors, restrictions on the ability to collect or raise tolls as specified in the concession agreement etc. Government generally agrees to compensate investors for political risks, although in practice, governments may cite justifications for their action to delay or prevent such payments.

Interactions of steep risks:

In the context of strategic management, risk is recognized as an essential component of planning and decision-making (Ruefli et al. 1999)^[8]. Strategy developers often apply risk as a prognostic indicator for the consequences of decisions and plans. For construction projects, the consequences of decisions are often associated with the emergent dynamics associated with the interactions of multiple actors which include the STEEP risks. These dynamics prove to be challenging in the risk management of projects since they are often undermined in analysis models. In the construction industry, risk is frequently addressed in a static approach through deterministic models, neglecting behavioural patterns and social interactions that come from the outcomes of projects, on the other hand, are often determined through power trade-offs or political and institutional arrangements (Flyvbjerg et al. 2003)^[9].These determinants are not fully reflected in project planning and risk governance. On the other hand, the actual impact of emergent dynamics is significant and influences the responses of the projects as a complex system of actors. Several megaprojects and infrastructure in the global arena have been stalled due to emergent dynamics despite very accurate risk analysis and cost assessment. Therefore, there is a need for complementary analysis to current procedures to integrate emergent dynamics that arise from the interactions of actors into the existing risk governance methodologies. The STEEP risks together interact with one another (Fig. 2) to influence relationships and generate risk landscapes of unparalleled complexities.

Fig. 2.Effects of Interactions and belongingness of STEEP Factors in Megaprojects (After P Boateng et al., 2012)

Hence, analysis of the synergic dynamics of complex settings, such as global construction, should not underrate the interactions as the main source of the dynamics. A further increase of such interactions with one another can produce system disturbances with severe consequences and would in turn generate collateral effects via spreading and cascading failures within project interrelated subsystems (Boateng et al., 2012^)[10]. The results will then be crippling losses of public invested funds and valuable time that were previously thought to be uncorrelated and unforeseeable (Kytle and Ruggie, 2005)^[11].

The system dynamic model (SD) for risk assessment

System dynamics is an approach to understanding the nonlinear behaviour of complex systems over time using stocks and flows, internal feedback loops and time delays^[12]. In recent years, the SD has been used by researchers and project managers to understand various social, economic and environmental systems in a holistic view (Rodrigues, 1996^[13];Towell, 1993^[14]; Sycamore, 1999^[15]; Mawby, 2002^[16]; Love, 2002^[17]; Ogunlana, 2003^[18], Williams, 2003^[19] and Naseena, 2006^[20]). The model is tested rigorously before being deployed for policy experimentation on user satisfaction.

A SD model of the project can be used as an effective tool for risk monitoring and control and to identify early signs of risk appearance. The implementation of risks and their consequences can be monitored by analysing the aspects of the project causing concern to both the system management and users. Effectiveness may also be evaluated through SD models (Ogunlana et al., 2003^[18]). In addition, the dynamic nature of the project can be managed better than in other projects which did not benefit from modelling.

System Dynamics approach is primarily based on cause-effect relationship. This cause-effect relationship is explained with the help of stock, flow and feedback loops. Stocks and flows are used to model the flow of work and resources through the project. Feedback loops are used to model decisions and project management policies. System Dynamics can be used to model processes with two major characteristics (1) those involving change over time, and (2) those that involve feedback (Ogunlana, 2003)^[18].

Causal loop diagrams aid in visualizing a system’s structure and behaviour, and analyzing the system qualitatively. To perform a more detailed quantitative analysis, a causal loop diagram is transformed to a stock and flow diagram. A stock and flow model helps in studying and analyzing the system in a quantitative way; such models are usually built and simulated using computer software.

A stock is the term for any entity that accumulates or depletes over time. A flow is the rate of change in a stock.

Fig 3: Stock and flow relation

The central concept of System Dynamics is to understand how the parts in a system interact with one another and how a change in one variable affects the other variable over time (Senge, 1990)^[21]which in turn affects the original variable (Fig. 4). Systems can be modelled in a qualitative and quantitative manner. The models are constructed from three basic building blocks: positive feedback or reinforcing loops, negative feedback or balancing loops, and delays. Positive loops (called reinforcing loops) are self-reinforcing while negative loops (called balancing loops) tend to counteract change. Delays introduce potential instability into the system.

Fig. 4.The three components of system dynamic model

A reinforcing loop produces either growth or decline and feeds on itself(Fig 4a). Variable 2 increases as variable 1 increases. This is indicated by the polarity and in represented by the + sign. The “+” sign does not mean the values necessarily increase, only that variable 1 and variable 2 will change in the same direction (polarity). Reinforcing loops generate growth, amplify deviations, and reinforce change.

The dynamic models thus generated consists of numerous variables and equations. Due to space limitation only social risk is taken into consideration out of the STEEP risks. It basically captures the dynamics of social risk impacting on project performance during the construction phase of the project. The model boundary chart (Table 1) indicates detailed results of the variables under the system considered. Endogenous variables are those represented within the model with values determined or influenced by one or more of the independent variables in the system. Exogenous variable on other hand, are factors which are outside of the model.

Fig. 5: .Cause and Effect feedback loop for Social Risks

Table 1: Model variables

ENDOGENOUS	EXOGENOUS
Multi-player/level decision making	Construction disruptions
Social issues	Need to relocate
Social acceptability	Pedestrian and bicycle safety
Social grievances	Accessibility to families, friends and community resources
Legal action	Choice of travel modes
Reputational risks	Linkage between residence and job
	Land and property value
	Waste generation
	Pollution
	Transport issues
	Stakeholders satisfaction
	Regulatory environment

CONCLUSION:

The success parameters for any project are on time completion, within specific budget and with requisite performance (technical requirement). The main barriers for their achievement are the changes in the project environment (Chapman 2006)^[22].The problem multiplies with the size of the project as uncertainties in project outcome increase with size (Zayed et al. 2008^)[23].The SD methodology may be used for modelling and analyzing the behaviour of complex social systems in an industrial context (Sterman, 2000)^[24]. Unlike the conventional approach (PERT/CPM), where planners use human judgement to interpret their own mental models, the SD approach according to Sterman (1992^)[25], uses computer models to overcome limitations of the mental models. Sterman established that, the SD computer models are explicit and open to all to review; capable to compute the logical consequences of the modeller’s assumptions; able to interrelate many factors simultaneously and finally, can be simulated under controlled conditions for analysts to conduct experiments outside the real system. Hence for a complex system like megaprojects construction, It may help decision-makers learn about the structure and dynamics of the system and design high leverage policies for sustained improvement, and to catalyse successful implementation and change. This present paper has systematically examined major Social risks affecting the megaproject. The risk model developed in this paper, using system dynamics provides an effective insight and clear picture of the Social risks involved in megaproject development and construction.

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Received on 04.11.2015 Accepted on 05.12.2015

Int. J. Tech. 5(2): July-Dec., 2015; Page 86-90

DOI: 10.5958/2231-3915.2015.00002.4