Managing supply chain risks and delays in construction project

Published date13 August 2018
Pages1413-1431
DOIhttps://doi.org/10.1108/IMDS-09-2017-0422
Date13 August 2018
AuthorYulia Panova,Per Hilletofth
Subject MatterInformation & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems
Managing supply chain risks and
delays in construction project
Yulia Panova
Department of E-Commerce, Luoyang Normal University, Luoyang, China and
Department of Logistics and Supply Chain Management,
National Research University Higher School of Economics,
St Petersburg, Russia, and
Per Hilletofth
Department of Industrial Engineering and Management, School of Engineering,
Jönköping University, Jönköping, Sweden and
Department of Industrial Engineering and Management, University of Gävle,
Gävle, Sweden
Abstract
Purpose The purpose of this paper is to investigate models and methods for managing supply chain risks
and delays in construction projects.
Design/methodology/approach The study mainly employs quantitative analysis in order to identify
disruptions in construction supply chains. It also uses paradigms of simulation modeling, which are suitable
for risk assessment and management. Both qualitative and quantitative data were collected through a
literature review and details of specific construction projects, respectively. A dynamic modeling method was
used, and the model was provided with an event-based simulation. Simulation modeling was used to measure
the performance of the system.
Findings The study shows the benefits of applying the dynamic modeling method to a construction
project. Using event-based simulation, it was found that construction delays influence both the magnitude
and the probability of disruption. This method contributes to the existing theoretical foundations of risk
management practices, since it also considers the time factor. This method supplements the Monte Carlo
statistical simulation method, which has no time representation. Using empirical analysis, the study proposes
increasing the safety stock of construction materials at the distribution center, so as to mitigate risks in the
construction supply chain.
Research limitations/implications The research considers a single case of a hypothetical construction
project. The simulation models represent a simple supply chain with only one supplier. The calculations are
based on the current economic scenario, which will of course change over time.
Practical implications The outcomes of the study show that the introduction of a safety stock of
construction materials at the distribution center can prevent supply chain disruption. Since the consideration
of risks at all stages of construction supply chain is essential to investors, entrepreneurs and regulatory
bodies, the adoption of new approaches for their management during strategic planning of the investment
projects is essential.
Originality/value This dynamic modeling method is used in combination with the Monte Carlo
simulation, thus, providing an explicit cause-and-effect dependency over time, as well as a distributed value of
outcomes.
Keywords Risk management, Construction projects, Construction delays, Simulation modelling
Paper type Research paper
1. Introduction
Construction pr ojects are inevit ably related to a futu re period of time so th at it is
problematictopredicttheresultsoftheirimplementation.They depend on how accurately
the amount of material and their associated flows during the project are forecasted.
Insufficient information is a problem, and stochastic materials flow through the value
stream likewise hinder the universal application of lean principles to the construction
supply chain (Fearne and Fowler, 2006; Forsman et al., 2012; Eriksson, 2010). In essence,
the lean concept focuses substantially on the process flow, and a synchronization of
Industrial Management & Data
Systems
Vol. 118 No. 7, 2018
pp. 1413-1431
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-09-2017-0422
Received 25 September 2017
Revised 23 February 2018
Accepted 29 April 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
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Managing
supply chain
risks
demand and production. Therefore, it is difficult to implement this in the construction
industry, due to its inherent uncertainty and complexity, both of which cause
disintegration in its supply chains (Voordijk et al., 2006; Briscoe and Dainty, 2005; Fearne
and Fowler, 2006). Hence, the construction supply chain should be developed within the
framework of the agile paradigm(Vrijhoef and Koskela, 2000). Nevertheless, this study
supports the idea of using a material inventory to avoid supply chain disruption in the
construction industry.
Difficulties in planning construction projects result in the work flow variability
causing inefficiency in downstream processes that result in delays and the associated
costs. Accordingly, it is crucial to consider all possible outcomes and the influence
of risk factors due to disruptions in the construction supply chain. Risk factors affect the
value of investment in construction projects, by inducing a deviation of futur e cash flows
from the expected flow within the project, which results in firms exceeding their
budget goals. For so-called megaprojects, risks may result in cost overruns during the
process of their implementation with more than 100 percent overspending from
the expected budget appraisals, and the incurring of additional costs even before the
construction begins.
The actual financial cost of the longest underwater railway, the Channel Tunnel, was
sharp 140 percent higher than the estimated investment cost (Flyvbjerg et al., 2003). The
increase in cost by 55 percent of the Great Belt Bridge (Denmark) was noted three years
before the expected date of completion of the project, while the change in the cost
(+10 percent) of the Öresund Bridge (Sweden) was recorded even before the start of its
construction (Bruzelius et al., 2002). The underestimation of risk factors for projects,
especially capital-intensive ones, at the stage of their feasibility study, leads not only to
unexpected financial losses, but also delays in projects commissioning. However, the
number of studies that address the delays and cost overrun issues simultaneously in
construction projects is not sufficient. Previous studies focus on the delays alone and not on
cost overruns or both (Ramanathan et al., 2012).
A risk-free asset is a case of hypothetical construction, which is widely used in the theory
of finance, however, in the real life is impractical to achieve (Black et al., 2012; Shapkin and
Shapkin, 2013). It is essential to restrain the previously mentioned types of risk, which have
numerous causes, primarily construction delays (Ramanathan et al., 2012). Some authors
note that the cause of these risks is rooted in close deadlines due to changes in construction
schedules, incorrect forecasts of traffic volumes, an easing of bidding rules and possibly
corruption as well. Other authors emphasize that failure factors are rooted in inaccurate data
and irrational research methods (Panova and Hilmola, 2016; Bruzelius et al., 2002; Flyvbjerg
et al., 2003). From this point of view, the development of methods and models that consider
and assess construction risks in terms of their initial cost estimate is a fundamental task
from both a practical and theoretical points of view.
The probabilistic nature of risks is difficult to consider on the basis of analytical
formulae. The inappropriateness of some methods for assessing the investment in
infrastructure projects has led to a combination of different methods (e.g. deterministic and
stochastic approaches using the Monte Carlo analysis (MCA); Esipova et al., 2010; Salling,
2013; Lorenzo et al., 2012; Ambrasaite et al., 2011). The Monte Carlo test is one of the most
suitable methods of quantitative risk assessment, since it can deal with the greatest possible
number of risk factors (Panova and Hilmola, 2016). However, the method has no explicit
time representation and aims to solve the deterministic problem probabilistically. Therefore,
in order to describe the dynamic system, which is represented by the construction project,
the application of dynamic modeling is proposed. In particular, by means of an event-based
simulation of construction delay issues, the magnitude and the probability of the disruption
can all be explained explicitly.
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