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Risk Management for Asphalt Road Construction and
Maintenance under Performance-Based Contracts
Article in International Journal of Construction Education and Research · January 2015
DOI: 10.1080/15578771.2014.990121
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Risk Management for Asphalt Road
Construction and Maintenance under
Performance-Based Contracts
a
b
Mohammed S. Hashem M. Mehany Ph.D. & Angela Guggemos Ph.D.
a
Missouri State University, Springfield, Missouri, USA
b
Colorado State University, Fort Collins, Colorado, USA
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To cite this article: Mohammed S. Hashem M. Mehany Ph.D. & Angela Guggemos Ph.D. (2015): Risk
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International Journal of Construction Education and Research, 00:1–24, 2015
Copyright © Associated Schools of Construction
ISSN: 1557-8771 print/1550-3984 online
DOI: 10.1080/15578771.2014.990121
Risk Management for Asphalt Road Construction
and Maintenance under Performance-Based
Contracts
MOHAMMED S. HASHEM M. MEHANY, PH .D.
Downloaded by [Missouri State University] at 07:08 09 February 2015
Missouri State University, Springfield, Missouri, USA
ANGELA GUGGEMOS, PH .D.
Colorado State University, Fort Collins, Colorado, USA
Contractors have been the main risk bearers in most road construction and maintenance projects, especially when they are working under higher-risk delivery systems
such as Performance Based Contracts (PBC), where the contractors are more likely
to be responsible for both the construction and maintenance of the road for a certain
warranty period. This research identified and analyzed the risks that the contractor
is subject to under PBCs for hot mix asphalt (HMA) road construction and maintenance projects. The study used a mixed methods research design and was divided into
three phases. In the first phase, employing a detailed literature review along with industry interviews, twenty-nine risks were identified in the construction and maintenance
phases. In the second phase, risk severity rankings were calculated using probability and impact data that was collected from several contractors and a state agency.
In the final phase, a correlation analysis was conducted. The results of this analysis
will enable contractors to make adjustments and modifications to address the highest
and most severe risks.
Keywords asphalt contractors, asphalt road construction, asphalt road maintenance,
performance based contracts, risk management
Introduction
Government agencies and the Federal Highway Administration (FHWA) are starting to see
the benefits of using contracts in which a contractor is responsible for both the construction
and maintenance of roadways. This work is often performed under a Performance-Based
Contract (PBC) where payments for the construction and maintenance of roads are explicitly linked to the contractor successfully meeting or exceeding certain clearly defined
minimum performance indicators and measurements stated in the contract specifications
(Stankevich, Qureshi & Queiroz, 2005). To be successful under a PBC, contractors should
take into account most of the risks associated with construction and maintenance throughout the contractual period. Risk in the construction and maintenance industry has increased
with project size and cost. One might even say that today construction is mainly risk management. Risks are found throughout all phases of a project and vary greatly according
Address correspondence to Mohammed S. Hashem M. Mehany, Missouri State
University, Glass Hall 207, 901 South National Avenue, Springfield, MO 65806, USA.
E-mail: mohammedmehany@missouristate.edu
1
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2
M. S. Hashem M. Mehany and A. Guggemos
to the type of construction, the contracts involved, and the type of delivery system. This
article focuses on a very specific subset of the overall industry where the contractors are
contracted to build and maintain hot mix asphalt (HMA) roadways under PBC. For these
conditions, managing risk during the maintenance phase may be even more important than
during construction since risk management for maintenance can be more complex. Also,
the duration of maintenance is much longer than construction; and estimating costs and
risks is more difficult and must take into consideration the time value of money, the fluctuation of markets, as well as inflation. Moreover, road projects have always been among
the riskiest construction projects due to their long duration of construction phase, quality
concerns, and likely cost overruns.
Like any construction project, road construction and maintenance projects have three
main components that can be subjected to risks. These main components are cost, time
and quality. But in road construction, problems and risks in any of these three areas can
be amplified because of project size and duration and a lot more unforeseen conditions.
Material and energy price increases combined with economic problems that raise inflation
worldwide have an impact on all industries. Road construction and maintenance projects
are particularly affected since rising energy costs drive up material costs and when energy
and material prices increase, construction projects decline or slow down. As a result, road
construction and maintenance contractors are facing substantial economic and technical
risks. Specifically, under contracts where they build and maintain HMA roadways such as
PBCs which are fixed price contracts that cover a long span of time with a warranty period
included in the contract. Warranties can be used as part of a PBC to ensure that performance
goals are met for the required maintenance period. One example of a PBC with a warranty
period is the M115 project completed by Michigan DOT (MDOT) where a warranty period
of 5 years was used to ensure the ride quality after construction. As part of the bidding
process, MDOT allowed the bidders to offer a warranty period longer than 5 years, giving
them additional points towards the best value award (Rao, Mallela, & Hoffman, 2009). This
is very different from the more commonly used unit price contracts where the specifications
for the construction or maintenance are literally prescribed rather than performance-based.
The purpose of this research is to develop a better understanding of the risks associated
with the construction and maintenance phases under contracts where the contractors both
build and maintain HMA roadways. The first objective is to identify the most severe risks
and their impact for road construction and maintenance contractors who build and maintain
HMA roadways. The second objective is to quantify the severity/magnitude of those risks.
The scope and application of this study is limited to contractors for HMA road projects
under PBCs for construction and maintenance.
Literature Review
Risk Management
Risk management is the process concerned with planning, identification, assessment, analysis, responses, monitoring, and controlling project risk (PMBOK, 2004). This definition
is fairly comprehensive as it includes the three main steps of any risk management process
which are risk identification, assessment/analysis, and response. Much research focuses
on risk management tools and their use through the risk management process to enable
the creation of project-specific risk response plans (Hall, 2000; PMBOK, 2004). The output of these tools falls under two categories: (1) risk mitigation and/or (2) preventive
actions. Mitigating actions allow the contractor to reduce the probability and impact of the
adverse risks to acceptable limits (e.g., acquiring more expertise on the management team
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Risk Management for Asphalt Road Construction and Maintenance
3
to eliminate some risk from the start of the project procurement process). Contractors use
preventive actions to eliminate threats to safeguard the project’s objectives (e.g., choosing
more stable suppliers).
One of the noted deficiencies in the construction industry is unbalanced risk allocation
in which most of the risk is allocated to the contractor instead of allocating the risk to those
in the best position to carry it because they have the best resources, the best information,
or the best expertise (Diepenbrock, Davison, Lichtig, & Rudolph, 2002). According to
various studies (Bing, Akintoye, Edwards, & Hardcastle, 2005; Gruneberg, Hughes, &
Ancell, 2007; Hartman & Snelgrove, 1996; Kartam & Kartam, 2001), it is apparent that
the contractor is affected by risks of all types including economic and environmental.
Consequently, risk accountability can be higher under PBCs that extend and magnify
the contractor’s risk accountability towards the project. For this reason, this research is
focused on quantifying the risks for contractors involved in both road construction and
maintenance.
Contractor Risk Accountability
In general, the construction industry is highly risky for all participants. The level of risk,
however, varies throughout the life cycle phases of a project and is influenced not only by
the type of contract and its particular specifications, but also by the political and economic
environment. Risk allocation was created to help distribute these risks.
Risk allocation can be defined simply as the “allocation of proportional risk to all
parties of a contract” and that the risk should be borne by those in the best position to
carry it because they have the best resources, the best information, or the best expertise
(Diepenbrock et al., 2002). In reality, most participants try to transfer the risk to others, resulting in disputes, especially between the project owner and the contractor. Many
researchers have shown that the contractor typically bears most of the risk, especially
during the construction phase. Kartam and Kartam (2001) examined risk allocation and
significance in the Kuwaiti construction industry and the study results indicated that the
contractor has some allocation of every risk except the force majeure. Contractors also
had the highest percentage of the most significant risks (e.g., labor, material and equipment availability), including those that are least controllable (e.g., differing site conditions
and inflation). This accountability will be more significant under PBCs where the risks are
allocated for an even longer period of time.
The delivery system of the contract is the vehicle for risk allocation and risk
management in the contract (Molenaar, Ashley, & Diekmann, 2006). Generally, road
projects delivery systems falls under the normal Design-Bid-Build (DBB), Design Build
(DB), Construction Manager at Risk (CM At-Risk) (AGC, 2014). Other delivery systems
coming into the recent decades are the Integrated Project Delivery (IPD), Private Public
Partnership (PPP), Build Operate Transfer (BOT) and Performance Based Contracts
delivery (PBC) along with others. Much Literature discussed the DBB, DB and CM
At-risk risk management allocation in road projects. Much of this literature has been
devoted to comparing the DBB and DB risk management. They mostly pointed that
owner bears a lot more risk in the case of DBB projects such as design and specification
changes, Errors and Omissions (E&O), integration of multiple prime’s contractors risk
and exposure to multi-party disputes. In contrast, most of these risk are transferred to
the contractor (Design-Builder) in the case of DB delivery system (Prieto, 2012). Others
have compared the three delivery systems together and the risk allocation ratios among
the major three delivery systems such as the Utah Department of Transportation (UDOT)
(McMinimee et al., 2009) as in Figure 1.
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4
M. S. Hashem M. Mehany and A. Guggemos
Figure 1. UDOT risk ratios. Source: McMinimee et al. (2009).
The review of the published literature of similar studies suggests that most of the past
efforts were focused either on general risks for different parties or independent phases
of construction or on conventional delivery systems (Ashley et al., 2006; Berdica, 2002;
Perera, Dhanasinghe & Rameezdeen, 2009). No study adopted a holistic approach to examine the construction and maintenance risks under the performance-based delivery system.
The presented research study fills this gap by thoroughly examining the critical risks during the construction and maintenance phases of HMA roadways under the PBC delivery
system that should be considered by contractors.
Methodology and Data Sources
After examining the research methodologies adopted in similar studies, it was decided
that a mixed-methods research methodology would be adopted using both quantitative and
qualitative data to accomplish the research objectives. Mixed-methods research design is a
procedure for collecting, analyzing, and mixing both quantitative and qualitative research
and methods in a single study to understand a research problem (Creswell, 2008). The
qualitative research includes expert interviews to validate risk identification and assist with
the selection of the most significant risks. Quantitative research includes risk probability
and risk impact scores to assess the ranking, frequency, and magnitude of risks as well as
correlation analysis of the most significant risks.
The research design is shown in the methodology framework as illustrated in Figure 2.
The framework is divided into three main phases representing the risk management
framework: risk identification, risk assessment, and risk analysis.
Phase 1 – Risk Identification
Risk identification is the first phase in any risk management process where risks are
identified, shortlisted and documented. It develops the foundation for the next phases of
assessment and analysis and ensures the risk management effectiveness (Tchankova, 2002).
This phase is very important for the success of the risk management process since failure
to identify the significant risks will result in ineffective risk management considering the
fact that those non-identified risks will become non-manageable (Greene, Trieschmann, &
Gustavson, 1991). Elements of this phase include: extensive literature review, creation of a
risk breakdown structure (RBS) tool, and expert interviews to identify the most significant
risks for the HMA construction and maintenance phases.
Risk Management for Asphalt Road Construction and Maintenance
Risk
Identification
using RBS
Shortlisting the
most significant
Risks
Risk Probability
(P) & Impact (I)
Data Collection
Risk Severity
scores
Identification
of the most
severe risks
for HMA
Construction
&
maintenance
phases
Phase 1 – Risk
Identification
5
Correlation
Analysis
Phase 3 –
Risk
Analysis
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Phase 2–Risk Assessment
Figure 2. Research design and methodology framework.
Risks Identification using Risk Breakdown Structure (RBS)
An in-depth literature review in conjunction with the author’s 10 years of road construction
experience were used to identify the risks associated with HMA construction and maintenance. A risk breakdown structure was utilized to identify the risks at different stages of
the construction and maintenance phases.
A RBS is a source oriented grouping of risks to organize and define the total project
risk exposure through the different levels that represent the overall project sources of risk
(Hillson, 2002). It is considered a good fit for this research since it is the best way to
deal with a large amount of data through different processes in the HMA construction and
maintenance phases by providing a hierarchical structuring of risks for different processes
instead of just listing the risks (Hillson, 2003). This is because a simple list of risks cannot
represent the different areas and processes of HMA construction and maintenance project
phases in a comprehensive manner as can be done with a RBS.
Shortlisting the Most Significant Risks
To shortlist the RBS identified risks into the most significant risks for the construction and
maintenance phases, open-ended expert interviews were conducted each of which lasted
for several hours. All of the expert professionals were identified through academic and
industry referrals with the qualifications of having at least 10 years of HMA road construction and/or maintenance project experience and have worked with PBC delivery systems.
The expert interviews were conducted with 3 industry professionals (1 county road and
bridge director, 1 consultant and 1 HMA contractor) who combined have about 60 years of
experience in the road projects industry. They were asked to add, delete, combine or modify the list of risks for both the construction and maintenance phases that resulted from the
RBS process to identify the most significant risks.
Phase 2 – Risk Assessment
Risk assessment is the next phase of the risk management process where the risks are
objectively evaluated and their nature, types, and effects are explored. The risk assessment
can be a determination of quantitative or qualitative values of the risk and in this research,
a quantitative approach was taken to measure the risks’ values.
6
M. S. Hashem M. Mehany and A. Guggemos
Quantitative risk assessment has two main components for the evaluation. The first
component, risk impact (I), measures the magnitude of the risk if it happens while the
second component, risk probability (P), measures the likelihood or frequency that the risk
can occur. All values are measured in percentages.
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Risk Probability and Impact Data Collection
The risk probability and impact data were collected from 5 different HMA contractors and
the Larimer county roads department through different expert interviews where they were
asked to provide P and I scores for every shortlisted risk in the HMA construction and
maintenance phases. This sample size of 6 represents about 60% of the volume ($) of the
road construction and maintenance industry in the state of Colorado which is thought to be
an appropriate sample size to represent the road industry in Colorado.
Risk Severity Scores
After receiving the P and I scores for every risk on the shortlist, the risk severity scores
on which a risk can be assessed were calculated. Severity (S) is calculated as a product of
both probability and impact as in the following equation:
S=P × I
(1)
Identification of the Most Severe Risks for HMA Construction and Maintenance Phases
After the risk severity scores have been calculated in the previous step, the risks were
categorized according to their severity scores where the most severe risks were identified
so as to be further analyzed in the next phase.
Phase 3- Risk Analysis
Risk analysis is usually referred to as quantitative risk analysis. The key purpose of this
phase is to combine the effects of the various identified and assessed risks into an overall
holistic approach to provide the basis for evaluating the effectiveness of the risk management framework and lay the foundation for any future risk allocation strategies and risk
response plans (Ashley et al., 2006). Risk analysis can be achieved using different tools
and methods which are selected according to the nature of the study and the risks measurement capabilities. This research will use one of the most common risk analysis tools,
correlation statistical analysis.
Correlation Statistical Analysis
Correlation analysis is generally defined as a statistical analysis that is used to test, describe
and measure the degree of association between two or more variables and in this research
case, it is the association between the different risks (Creswell, 2008). Correlation analysis
is performed in this research to determine the tendency and the patterns for the occurrence
of different risks in the different processes and express the degree of association between
the risks.
Different types of correlation can be applied. However, a Pearson correlation statistical
analysis was selected rather than a Spearman correlation type since most of the correlations
Risk Management for Asphalt Road Construction and Maintenance
7
of the variables tend to have a linear relationship which was checked and proofed through
several scatter plots drawn between those variables. The end results were represented in the
form of a correlation matrix using Statistical Package for Social Science (SPSS) software
indicating the different risk correlation scores and their association factors.
Data Collection and Analysis
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Phase 1 - Risk Identification using Risk Breakdown Structure (RBS)
The RBS was used to identify the risks for each activity within both the construction and
maintenance phases. As a result of the extensive literature review as mentioned in the
methodology section, the RBS was created to represent the different risks during each
process within the construction and maintenance phases. Figure 3 shows the different processes during the construction phase from the site investigation until the project handover
process. The bold boxes represent the major construction processes; sub-processes are
unboxed, and risks are shown in italics. At the top, risks that occur throughout the construction phase are noted. Using this RBS, the risks associated with the different processes in the
construction phase can be easily identified. For example, during paving, the paving speed is
a risk associated with the sub-process of the laydown operation. It is worthy to note that at
the HMA mixing facility, there are two categories: (1) risks that can occur within the mixer
itself such as the mixing temperature, and (2) risks that can occur for the supplemental
components for the mixing facility such as the operator and the feeding equipment.
Another RBS was created to identify the maintenance phase risks as shown in Figure 4.
However, the maintenance was organized in a slightly different manner to address different types of maintenance. The maintenance phase was divided into two main types of
maintenance, preventive and corrective. Within each maintenance type, there are different
maintenance applications and techniques and the risks associated with each. Finally, some
of the risks identified are associated directly with the equipment crew’s knowledge and
experience during the maintenance project.
After using the RBS to identify the risks for both the construction and maintenance
phases, the risks were listed in Table 1 (construction risks)and Table 2 (maintenance risks).
The risk types, nature, and effects are based on the following definitions and categorization:
Risk Type. The risk type refers to the risk categorization when it happened and materialized
in the construction or maintenance process. In other words, it is how the risk is considered
when it happened. The types of risks can be categorized as economic, technical, time,
safety, and force majeure.
Risk Nature. The risk nature refers to the reason or phenomenon for the origin of the risk.
The nature of risks can be categorized as contractual, technical, timing, hazard, and act of
God.
Risk Effects. The risks in the construction and maintenance phases can affect several
aspects of a HMA road project. Mainly the risks can have an effect as additional cost,
additional time, added extensive maintenance, negative environmental effects and, in some
cases, it can affect the contractor’s portfolio. The categories of the risk effects that were
addressed in Tables 1 and 2 are the following:
1. Cost effect—additional cost to the project and in some cases, a cost to the public
2. Schedule effect—additional time required to complete the project
8
M. S. Hashem M. Mehany and A. Guggemos
Throughout the Construction phase
Risk of innovation
investment
Force
Majeure
Bonding Capacity
Price Fluctuations
Site investigation
Hauling Road conditions
Traffic Adjustments
Available spaces for Equipment
HMA Mixing (Facility)
Mix Temp.
Changing Mixes
Emergency repairs
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Feeding Equipment
Long term storage
Voids control
Operator
Break Down
Absenteeism
Transportation
Plant Positioning
Truck Loading
Lubrication
Dumping segregation
Truck Hauling
inefficient use
Weather
Covering
Distance
Bad covering procedures
Paving
MTV
Waiting time for grading contractor Feeding pavers
Availability
Soft Sub base
Stoppage time
Laydown
paving speed
screed adjustments
Compaction
% of crushed Aggreg.
Mass
Non- Driven drums &
PTR use
Modification of mix
design
Parking HMA cooling
rate
Speed Traffic vibratory
rolls
Distance to
paver
Handing over
PBC end results
Test variability
Go - no go
approach
Q.C & Q.A.
Testing Frequency
Extraction Test Solvent
Core & nuclear gage
Figure 3. RBS for the risks associated with the HMA construction phase.
3. Maintenance effec—additional maintenance with associated maintenance costs
4. Negative environmental effect—in terms of non-environmentally friendly substances
used in testing and inspection processes
5. Portfolio effect—limits the contractor’s financial ability to take on more
projects.
Phase 1 – Shortlisting the Most Significant Risks
Through the expert interviews mentioned in the methodology section and with feedback
and suggestions from the interviewees, a shortlist of the most significant risks was created
and approved by them. As a result, the risks listed in Table 1 and Table 2 were reduced
from 42 to 18 different risks for the construction phase and from 18 to 11 risks in the
maintenance phase as shown in Table 3.
Risk Management for Asphalt Road Construction and Maintenance
9
Table 1. Risks associated with HMA construction
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Risk name
Throughout the project
Risk of investment in
innovation
Prices fluctuation
Bonding capacity
Delayed owner payments
Weather changes
Site investigation
Traffic adjustments
Hauling road condition
Available equipment
spaces
HMA facility
Emergency repairs
Mix temperature
Changing mixes
Voids control
Long term storage
Feeding equipment
breakdown
Operator absenteeism
Transportation
Plant positioning
Segregation at dumping
Distance to site
Inefficient use
Bad covering procedures
Paving
Waiting time for contractor
Soft sub base
MTV-availability
Stoppage time
Paving speed
Screed adjustments
Compaction
Percent crushed aggregates
mass
Usage of non-driven
drums/PTR
Modification of mix design
mistakes
Parking
HMA cooling rate
Compaction speed
Risk type
Risk nature
Risk effect
Economic
Contractual
Cost
Economic
Economic
Economic
Force majeure
Contractual
Contractual
Contractual
Act of God
Cost-Schd.
Portfolio
Cost-Schd.
Cost-Schd.
Technical
Technical
Technical
Location
Location
Location
Cost-Schd.
Cost-Schd.
Cost-Schd.
Technical
Technical
Technical
Technical
Technical
Technical
Technical
Technical
Technical
Technical
Technical
Technical
Cost-Schd.
Cost-Schd.
Cost-Schd.
Cost-Schd.-Maint.
Cost-Schd.-Maint.
Cost-Schd.
Technical
Technical
Cost-Schd.
Technical
Technical
Technical
Technical
Technical
Location
Technical
Location
Technical
Technical
Cost-Schd.
Cost-Schd.-Maint.
Cost-Schd.
Cost-Schd.
Cost-Schd.-Maint.
Time
Technical
Economic
Technical
Technical
Technical
Contractual
Contractual
Technical
Technical
Technical
Technical
Cost-Schd.
Cost-Schd.
Schd.-Maint.
Cost-Schd.-Maint.
Cost-Schd.-Maint.
Cost-Schd.-Maint.
Technical
Technical
Cost-Schd.-Maint.
Technical
Technical
Cost-Schd.-Maint.
Technical
Technical
Cost
Technical
Technical
Technical
Location
Time
Technical
Cost-Schd.-Maint.
Schd
Cost-Schd.-Maint.
(Continued)
10
M. S. Hashem M. Mehany and A. Guggemos
Table 1. (Continued)
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Risk name
Risk type
Risk nature
Risk effect
Traffic effect on joints
Vibratory rolls on long.
joints
Distance to paver
Handing over
Test variability
“Go No-Go” approach
Testing frequency
Extraction test solvent
Technical
Technical
Technical
Technical
Maintenance
Cost-Schd.-Maint.
Technical
Technical
Maintenance
Technical
Technical
Technical
Technical
Contractual
Contractual
Technical
Contractual
Core & nuclear
Technical
Contractual
Cost-Schd.
Schd.
Cost-Maint.
Negative
environmental
Cost-Maint.
Schd. = Schedule, Maint. = Maintenance.
Although most of the risks are clear as listed, some require explanation. For the
construction phase,
• Long-term storage: Problems due to long term storage causing drainage and
oxidation of the asphalt cement.
• Distance to paver: Distance of the compactor to paver affecting the cooling rate of
HMA and length of time the material is hot enough to be compacted.
• Go, No-Go approach: Stopping during the paving process due to rejection by
inspection for not meeting the required performance specifications for the project,
causing delay of the whole construction phase due to a controllable section of the
road being rejected.
For the maintenance phase:
• Cleaning procedure as well as the cleanness of cover aggregate should be done at
its best practices; otherwise the asphalt will form a strong bond with the debris on
the surface instead of the road surface.
• Roughness components consideration: If not taken into consideration, the thin
overlay will not remove that roughness (doesn’t achieve its goal). The total overlay thickness should vary depending on the type of roughness components present
in the road profile in order to allow greater overlay depths when warranted by a
roughness survey.
• Use of 1 size cover aggregate for a chip seal is more expensive but can reduce the
amount of future maintenance required in the performance period.
Phase 2 - Risk Probabilities and Impacts Data Collection
After the risks were identified and categorized (Tables 1 through 3), the probability (P) and
impact (I) scores of the most significant risks were collected through interviews. For each
risk, all the respondents provided both the P and I scores. The respondents were represented
by five HMA contractors and a public works (Larimer County) director. The responses are
shown in Table 4 for construction risks and Table 5 for maintenance risks.
Risk Management for Asphalt Road Construction and Maintenance
11
Table 2. Risks associated with HMA maintenance
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Risk name
Throughout the performance period
Weather changes
Infrastructure deterioration
Preventive maintenance
Excess asphalt application
Non-porous HMA surface
Excess/High viscosity
rejuvenators
Loose aggregate on high
speed/vol. roads
Cleanness of cover aggregate
Use of 1 size aggregate
Binder & cover aggregate quant.
calibration
Cleaning procedure
Excessive aggregate application
Compaction by steel-wheeled
roller
Uniform asphalt binder spray
Adjustment of asphalt binder to
aggregate absorption
Early traffic opening
Use of natural sands when skid
resistance required
Safety issues associated
Corrective maintenance
Insufficient compaction
Edges leveling
Temporary (cold) repair costs
Roughness components
consideration
Levelling courses overruns
Performance LCC
Risk type
Risk nature
Risk effect
Force majeure
Technical
Act of God
Technical
Cost
Cost
Technical
Technical
Technical
Technical
Technical
Technical
Cost
Cost
Cost
Technical
Location
Public cost
Technical
Technical
Technical
Time
Technical
Technical
Cost
Cost
Cost
Technical
Technical
Technical
Technical
Technical
Technical
Cost
Cost
Cost
Technical
Technical
Technical
Technical
Cost
Cost
Technical
Technical
Location
Technical
Cost
Cost
Safety
Hazard
Cost
Technical
Technical
Technical
Technical
Technical
Technical
Technical
Technical
Cost
Cost
Cost
Cost
Technical
Economic
Technical
Contractual
Cost
Cost
One should note the major discrepancies between the different ratings for the P and I
scores not only between the governmental agency and the contractors but also between the
contractors themselves. The weather probability score was high (60% to 100%) from all
the parties surveyed with only one contractor giving it 30%. However, the weather impact
had a very high range from almost nothing to a score of 65% with the majority scoring
the weather fairly low. This can be attributed to the fact that weather is one of those risks
that is almost impossible to account for or to make a contingency account in your bid as a
contractor. The “segregation at dumping” risk had consistent P and I scores (50% to 60%
for both) from all respondents. However, those scores are not as accurate as they seem
since they measure impact or probability on their own. For that reason, a severity score can
make a better assessment for those risks as is discussed in the following section.
12
M. S. Hashem M. Mehany and A. Guggemos
Table 3. Most significant construction and maintenance risks
Level/Process
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Throughout the
construction
phase
Construction
risks
Level/Process
Maintenance
risks
Risk of
investment in
innovations
Price Fluctuation
Bonding
capacity
Delayed owner
payments
Weather changes
Throughout the
maintenance
phase
HMA mixing
facility
Emergency
repairs
Changing mixes
Voids control
Long term
storage
Preventive
maintenance
Cleanness of
cover
aggregate
Binder & cover
aggregate
quant.
calibration
Cleaning
procedure
Excessive
aggregate
application
Transportation
paving
Segregation at
dumping
MTV-availability
Stoppage time
Paving speed
Screed
Corrective
maintenance
Insufficient
compaction
Roughness
components
consideration
Leveling courses
overruns
Compaction
% of crushed
aggregate mass
Compaction
speed
Distance to paver
“Go No-Go”
Approach
Handing over
Weather changes
Infrastructure
deterioration
Non-porous
HMA surface
Excess/high
viscosity
rejuvenators
Phase 2 – Risk Severity Scores
The risk severity scores were used as a bridge between the risk identification and the risk
analysis where each table has the severity scores resulting from the product of probability
and impacts associated with each risk that were provided in Tables 4 and 5. The severity of
each risk was calculated as an average of the different scores of the collected data as shown
13
Risk of investment in innovations
Price fluctuations
Bonding capacity
Delayed owner payments
Weather changes
Emergency repairs
Changing mixes
Voids control
Long-term storage
Segregation at dumping
MTV-availability
Stoppage time
Paving speed
Screed adjustments
% of crushed aggregate mass
Compaction speed
Distance to paver
“Go No-Go” approach
Risk
P%
50
80
80
20
60
4
5
50
5
65
5
60
60
60
50
60
60
5
I%
1
50
4
5
0
10
10
25
50
20
10
20
20
20
20
20
20
10
Larimer
County
P%
50
40
80
1
60
4
50
5
1
65
5
80
80
80
5
10
10
5
I%
1
40
4
15
5
10
5
60
5
60
0
5
5
5
60
10
10
55
Contr.1
Table 4. Construction risk probability (P) and impact (I) raw data
P%
85
90
80
65
30
4
0
50
0
65
5
90
90
90
50
85
85
1
I%
0.5
50
4
4
65
10
5
30
5
50
10
10
10
10
30
5
5
0
Contr.2
P%
10
70
10
5
100
5
10
15
5
70
0
60
60
60
20
50
50
5
I%
5
30
30
15
8
10
10
50
20
35
0
10
10
10
25
20
20
20
Contr.3
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P%
10
65
11
10
100
3
5
20
3
60
10
50
50
50
35
50
50
10
I%
5
40
28
15
5
10
8
50
50
50
10
20
20
20
20
30
30
50
Contr.4
P%
57
80
30
12
100
5
15
20
10
60
10
40
40
40
10
35
35
5
I%
1
43
11
17
10
8
10
25
7
58
2
20
20
20
20
20
20
40
Contr.5
14
Weather changes
Infrastructure deterioration
Non-porous HMA surface
Excess/high viscosity rejuvenators
Cleanness of cover aggregate
Binder & cover aggregate quant. calibration
Cleaning procedure
Excessive aggregate application
Insufficient compaction
Roughness components consideration
Leveling courses overruns
Risk
P%
60
5
4
4
50
10
5
30
10
50
5
I%
0
10
10
11
5
5
10
10
10
60
40
Larimer
County
I%
5
1
15
25
4
4
10
4
25
60
40
Contr.1
P%
5
5
5
8
7
5
25
5
10
50
5
Table 5. Maintenance risk probability (P) and impact (I) raw data
P%
7
5
10
10
3
5
10
5
20
10
85
I%
4
10
9
30
10
8
20
10
27
18
10
Contr.2
P%
40
10
5
10
4
5
20
10
8
50
50
I%
10
8
10
40
20
16
20
8
50
60
40
Contr.3
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P%
30
5
10
10
10
5
20
20
15
20
50
I%
10
20
10
38
15
8
15
5
23
70
30
Contr.4
P%
50
10
5
13
5
5
20
12
10
25
57
I%
4
20
20
20
20
10
18
10
20
80
30
Contr.5
Risk Management for Asphalt Road Construction and Maintenance
15
Downloaded by [Missouri State University] at 07:08 09 February 2015
in Table 6 for the construction risks and Table 7 for the maintenance risks. The risks were
listed in order of decreasing severity.
Based on these severity scores, the two most severe risks during the construction phase
are price fluctuation (30%) and segregation at dumping (29%). A second group of risks
have severity scores in the range of 7% to 9%: voids control, compaction speed, distance
to paver, stoppage time, paving speed, screed adjustments, weather changes and percentage
of crushed aggregates. The remaining risks have severity factors of approximately 3% or
less.
For the maintenance risks, based on the severity scores, the most severe risks are the
roughness components consideration (21%) and the leveling course overruns (11%). The
remaining risks have very low scores (< 3%) compared to the top two risks.
Phase 3 – Correlation Analysis for Construction Phase
The Correlation analysis was performed using SPSS statistical software. The variables
in this research are the shortlisted construction risks listed in Table 3. Those variables
were measured in an ordinal and scale measures since they are not dichotomous variables
to be measured in nominal measurement nor are they intervals to be measured in ratio
measurement. A Pearson correlation statistical analysis was performed after descriptive
statistics were determined for each variable (risk).
A sample of the correlation statistical analysis results is included in the Appendix. The
first table in the appendix provides descriptive statistics (mean, standard deviation, and N)
for the variables to be correlated. The correlation table shows the Pearson correlation coefficients, and two tailed significance (Sig.) levels. As an example, the Pearson correlation
coefficient between “voids control” and “insufficient compaction” is .84; the significance
value is .036. So the correlation between the two risks is statistically significant because
the sig. value (.036) < .05 so we can state that there is an association between “voids control” and “insufficient compaction”. Since the correlation is positive, the more insufficient
compaction happens onsite, the more undesired voids ratios will be encountered in the
project. The same interpretation can be applied to the rest of the variables in the table.
Table 8 demonstrates the relationship between the different construction phase variables (risks), where the first two columns describe the correlated variables, the third column
is the significance value which represents the significance of the relationships (X < .05),
and the last column is the Pearson correlation coefficient which indicates the degree of the
association (correlation) between the variables in the table. It is worthy to note that those
are not only the significant relationships but also they are the most logical correlations
meaning that those relationships are practical to the onsite construction environment.
Phase 3 – Correlation Analysis for Maintenance Phase
In the maintenance phase, however, the research has accounted for only two of the risks
(not included in the correlation analysis) encountered during the maintenance phase since
they are the most common and most severe risks. The first was the roughness component
consideration, where the HMA overlay’s main purpose is to reduce roughness, restoring the
skid resistance and protecting pavement deterioration in parallel. If not taken into account
during the determination of the overlay thickness, a thin insufficient HMA overlay will be
just another inefficient structural layer that will not help in the road improvement process
the way it was intended. The other risk in the HMA overlay is the leveling course application, since it can cause a cost overrun for the contractor due to excess thickness in some
16
Larimer
.50
40.00
3.20
1.00
0
.40
.50
12.50
2.50
13.00
0.50
12.00
12.00
12.00
10.00
12.00
12.00
.50
Construction risks
Risk of investment in innovations
Price fluctuation
Bonding capacity
Delayed owner payments
Weather changes
Emergency repairs
Changing mixes
Voids control
Long-term storage
Segregation at dumping
MTV-availability
Stoppage time
Paving speed
Screed adjustments
% of crushed aggregate mass
Compaction speed
Distance to paver
“Go No-Go” approach
Table 6. Construction risks severity analysis
.50
16.00
3.20
0.15
3.00
.40
2.50
3.00
.05
39.00
0
4.00
4.00
4.00
3.00
1.00
1.00
2.75
Contr. 1
.43
45.00
3.20
2.60
19.50
.40
0
15.00
0
32.50
.50
9.00
9.00
9.00
15.00
4.25
4.25
0
Contr. 2
.50
21.00
3.00
0.75
8.00
.50
1.00
7.50
1.00
25.00
0
6.00
6.00
6.00
5.00
10.00
10.00
1.00
Contr. 3
Individual Severity Scores %
.5
26.00
3.10
1.50
5.00
.30
.40
10.00
1.50
30.00
1.00
10.00
10.00
10.00
7.00
15.00
15.00
5.00
Contr. 4
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.57
34.00
3.30
2.00
10.00
.40
1.50
5.00
.70
35.00
.20
8.00
8.00
8.00
2.00
7.00
7.00
2.00
Contr. 5
.50
30.33
3.17
1.33
7.58
.40
.98
8.83
.96
29.08
.37
8.17
8.17
8.17
7.00
8.21
8.21
1.88
Avg.
.05
11.25
.10
.89
6.83
.06
.91
4.55
.95
9.18
.38
2.86
2.86
2.86
4.86
5.15
5.15
1.83
SD
Severity %
17
Larimer
0
.50
.40
.44
2.50
.50
.50
3.00
1.00
30.00
2.00
Risk name
Weather changes
Infrastructure deterioration
Non-porous HMA surface
Excess or high viscosity rejuvenators
Cleanness of cover aggregate
Binder & cover aggregate quantity calibration
Cleaning procedure
Excessive aggregate application
Insufficient compaction
roughness components consideration
Leveling courses overruns
Table 7. Maintenance risks severity analysis
.25
.05
.75
2.00
.28
.20
2.50
.20
2.50
30.00
2.00
Contr.1
.28
.50
.90
3.00
.30
.40
2.00
.50
5.40
1.80
8.50
Contr.2
4.00
.80
.50
4.00
.80
.80
4.00
0.80
4.00
30.00
20.00
Contr.3
Individual Severity Scores %
3.00
1.00
1.00
3.80
1.50
.40
3.00
1.00
3.45
14.00
15.00
Contr.4
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2.00
2.00
1.00
2.60
1.00
.50
3.60
1.20
2.00
20.00
17.10
Contr.5
1.59
.81
.76
2.64
1.06
.47
2.60
1.12
3.06
20.97
10.77
Avg.
1.67
.67
.26
1.31
.84
.20
1.26
.99
1.56
11.50
7.77
SD
Severity %
18
Table 8. Correlation analysis of significant risk relationships in the construction phase
Variable 2
Sig. value
Pearson
coefficient
Paving speed
Screed adjustments
Screed adjustments
Distance to paver
% of crushed aggregate mass
Stoppage time
Paving speed
Screed adjustments
Insufficient compaction
0
0
0
0
.017
.036
.036
.036
.036
1
1
1
1
.89
.84
.84
.84
.84
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Variable 1
Stoppage time
Stoppage time
Paving speed
Compaction speed
Voids control
Voids control
Voids control
Voids control
Voids control
Throughout the Maintenance Phase
Price Fluctuations
Weather
Preventive Maintenance
Fog Seals
Excess Asphalt
Application
Non-Porous
HMA
surface
Loose Aggregate
on high Vol./
speed roads
Excess/high
Viscosity
rejuvenators
Cleanness of
cover
aggregate
Crack Sealing
Slurry Seals
Rejuvenators
Chip Seals/
Surface treatment
Use of 1 size
cover aggregate
Safety issues
associated with
application
Use of natural
sands when skid
resistance
required
Binder & cover
aggregate
quantities
method of
calibration
Cleaning
Procedures
Compaction
by Steel
Wheeled
roller
Excessive
Aggregate
application
Corrective Maintenance
Patching
Insufficient
Compaction
Edge
Leveling
Thin HMA Overlays
Temporary
repair costs
Roughness
components
consideration
Leveling course
overruns
Performance LCC
Typical Construction problems arise from maintaining equipment Crew’s knowledge
Uniform Asphalt
binder Spray
Adjustment of Asphalt binder
to aggregate absorption
Early Traffic
opening
Figure 4. RBS for the risks associated with the HMA maintenance phase.
Risk Management for Asphalt Road Construction and Maintenance
19
sections due to surface irregularities where the builder must apply more HMA material
than estimated. The contractor can avoid or mitigate those risks by designing an overlay
thickness that varies depending on the type of roughness components in the road profile and
may use milling machines to mill the old road to a lane surface rather than using leveling
courses (Roberts, Kandhal, Brown, Lee, & Kennedy, 1996).
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Conclusions
Currently, Design-Bid-Build (DBB) contracts are used extensively in road construction.
However, the use of modern delivery systems represented in PBCs introduces a new challenge for contractors in terms of risk allocation due to the increased risks they have to bear
for a longer project commitment through warranty and maintenance periods stated in their
contracts. For that reason, risk management has never been more important to contractors since they are taking on more responsibilities that can exploit more risks whether by
triggering more risks or dealing with more severe ones.
This study identified the most significant risks for HMA contractors during construction and maintenance. During the construction phase, it was found that voids control is
one of the most significant risks that have an adverse effect and association with: stoppage time, paving speed, screed adjustment and percent of crushed aggregate mass in the
construction phase and insufficient compaction in the maintenance phase. This risk can
be mitigated and hopefully eliminated by the contractor by enforcing more quality control
procedures in their mixing facility which in turn eliminates a series of dependent risks in
the paving, compaction, and corrective maintenance processes and makes those risks more
controllable, too. Another important finding is that most of the associated significant risks
happen in the paving process: stoppage time, paving speed, and screed adjustments which
stress the need for a high level of monitoring and control to be applied during this process.
For the maintenance phase, it was found that there are two severe and significant risks
which are the roughness components consideration and the leveling course overruns. This
is due to the fact that the HMA overlay is the most frequent maintenance procedure applied
and most of the contractors treat it as a standard thickness that they apply regardless of what
triggers these two risks. Close attention to the roughness component coefficient along with
the milling process is essential to mitigate and eliminate these two risks.
Some of the most severe and significant risks such as weather, risk of innovation, and
price fluctuations were excluded from the correlation analysis due to their nature since
they are outside the contractor’s influence to control. However, these risks can be mitigated or transferred through other channels like contractual modifications, variation and
change orders, or insurance. Most of the contracting agencies and the contract experts have
developed many contractual provisions and clauses to avoid these kinds of risks during construction because of their negative effect on both the owner and the contractor. Based on
the above discussion, a contractor should be mindful of such contract language in the first
place to avoid these uncontrollable risks.
Finally, it is worthy to note that most of these risks can be considered long-term risks
and that is the main reason behind their effect under performance-based contracts. Their
effect will take place in the performance of the road and its condition, especially if there
is a warranty period included in the PBC. However, through the data collection efforts,
it was noted that only a few contractors are involved or even willing to be involved in
projects under performance-based contracts since they are a relatively new type of delivery
system where a lot of risks and responsibilities are allocated to the contractor. There are
also some limitation on this study represented in the HMA road and highway industry, the
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20
M. S. Hashem M. Mehany and A. Guggemos
contractors, the area of Colorado and the PBC delivery system. Although, those limitations
constrict some of the results of this study, it is still a great step towards the addition to the
body of knowledge within this new delivery system.
There are several areas of continuing research for this study. One of the most important ones is the study of the risk effects on the costs of the projects and specifically the
Life Cycle Cost (LCC) of the project since the PBCs specify a construction period along
with maintenance or a warranty life for the project. Another area of expansion on this
research is the duplication of this research to study other road types such as concrete roads
or other delivery systems such Design-Build (DB) or Integrated Project Delivery (IPD).
Finally, studying other key risk items such as safety can be very beneficial for all the parties involved since safety does affect time, cost and speaks to the quality of the job from
each of the participants (owner, engineer, subcontractor and contractor). However, it will
be quite a challenge since it is one of those risks that very hard to quantify accurately
because of its high variability between different jobs and contractors.
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22
Risk of investment in
Prices fluctuations
Bonding capacity
Owner delayed payments
Weather
Emergency repairs
Changing mixes
Voids control
Long term storage
Segregation at dumping
MTV-availability
Stoppage time
Paving speed
Screed adjustments
% of crushed aggregate mass
Compaction speed
Distance to paver
“Go No-Go” approach
Valid N (listwise)
Table A1. Descriptive statistics
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
N
Statistic
Appendix
SPSS – Statistical Data Output Results
RISKS STATISTICAL ANALYSIS
0.43
16
3
0.15
0
0.3
0
3
0
13
0
4
4
4
2
1
1
0
Minimum
Statistic
0.57
45
3.3
2.6
19.5
0.5
2.5
15
2.5
39
1
12
12
12
15
15
15
5
Maximum
Statistic
2.97
182
19
8
45.5
2.4
5.9
53
5.75
174.5
2.2
49
49
49
42
49.52
49.25
11.25
Sum
Statistic
Descriptive Statistics
0.495
30.3333
3.1667
1.3333
7.5833
0.4
0.9833
8.83333
0.9583
29.0833
0.3667
8.1667
8.1667
8.1667
7
8.2083
8.2083
1.875
Mean
Statistic
0.0493
11.25463
0.10328
0.88638
6.82947
0.06325
0.90646
4.54606
0.94679
9.17833
0.38297
2.85774
2.85774
2.85774
4.85798
5.15368
5.15368
1.82859
Std.
Deviation
Statistic
Downloaded by [Missouri State University] at 07:08 09 February 2015
0.002
126.667
0.011
0.786
46.642
0.004
0.822
20.667
0.896
84.242
0.147
8.167
8.167
8.167
23.6
26.556
26.556
3.344
Variance
Statistic
0.409
0.056
−0.666
0.19
0.982
0
0.952
0.09
0.769
−0.466
2.446
−0.25
−0.25
−0.25
0.895
−0.142
−0.142
0.313
Statistic
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
0.845
Std.Error
Skewness
23
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
Pearson Correl
Sig. (2-tailed)
Person Correl
Sig. (2-tailed)
Person Correl
Sig. (2-tailed)
Person Correl
Sig. (2-tailed)
Emergency
Person Correl
repairs
Sig. (2-tailed)
Changing mixes Pearson Corel
Sig. (2-tailed)
Voids control
Pearson Corel
Sig. (2-tailed)
Long term
Pearson Corel
storage
Sig. (2-tailed)
Segregation at
Pearson Corel
dumping
Sig. (2-tailed)
a
a
a
a
Prices fluctuations
Pearson Correl
Sig. (2-tailed)
Rist of
investment in
innovations
Prices
fluctuations
Bonding
capacity
Owner delayed
payments
Weather
Table A2. Ordinal correlation results
Risk of investment
in innovations
Downloaded by [Missouri State University] at 07:08 09 February 2015
Bonding capacity
a
a
a
a
a
a
a
a
a
a
Owner delayed
payments
a
a
a
Weather
−0.707 0
0.116
1
0.686 0.086
0.132 0.872
0 −0.35
1
0.492
a
a
0.125
0.813
0.125
1
0.813
a
a
1
a
a
a
Emergency repairs
a
a
a
a
a
a
a
a
a
a
Changing mixes
Voids control
a
a
a
0.686
0
0.132
1
0.086 −0.35
0.872 0.492
a
a
a
a
a
Long term storage
−0.728 −0.33
0.101 0.519
−0.728 1
0.243
0.101
0.643
−0333 0.243
1
0.519 0.613
a
a
a
1
−0.707
0.116
0
1
a
a
a
a
Segregation at
dumping
a
a
a
a
a
a
a
a
a
a
MTV-availability
Stoppage time
Paving speed
a
a
a
Screed
adjustment
a
a
a
% of crushed
aggregate mass
a
a
a
a
a
a
Compaction speed
a
a
a
a
a
a
0.612 0.612 0.612 0.433 0.433 0.433 −0.17
0.196 0.196 0.196 0.391 0.391 0.391 0.745
−0.306−0.306−0.306 0 −0.433−0.433 0.171
0.555 0.555 0.555
1
0.391 0.391 0.745
a
a
a
a
a
a
a
a
a
a
Distance to paver
(Continued)
−0.447−0.577−0.577−0.577 −.816 −0.408−0.408 0.243
0.374 0.23 0.23 0.23 0.047 0.422 0.422 0.643
−0.108 .840∗ .840∗ .840∗ .891∗ 0.297 0.297 −0.65
0.383 0.036 0.036 0.036 0.017 0.568 0.568 0.165
0.447 0.577 0.577 0.577 0.408 .816∗ .816∗ 0.243
0.374 0.23 0.23 0.23 0.422 0.047 0.047 0.643
a
a
a
a
a
a
a
a
0.316
0.541
0.158
0.765
a
a
a
a
“Go No-Go”
approach
24
View publication stats
Pearson Corel
Sig. (2-tailed)
Pearson Corel
Sig. (2-tailed)
Pearson Corel
Sig. (2-tailed)
Pearson Corel
Sig. (2-tailed)
Pearson Corel
Sig. (2-tailed)
Pearson Corel
Sig. (2-tailed)
Pearson Corel
Sig. (2-tailed)
Pearson Corel
Sig. (2-tailed)
Pearson Corel
Sig. (2-tailed)
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
Risk of investment
in innovations
a
Prices fluctuations
a
a
a
a
a
a
a
a
a
a
Bonding capacity
∗∗
Correlation significant at the .05 level (2-tailed).
Correlation significant at the .01 level (2-tailed).
a. Listwise N = 6.
∗
Screed
adjustment
% of crushed
aggregate
mass
Compaction
speed
Distance to
paver
“Go No-Go”
approach
Paving speed
Paving speed
MTVavailability
Stoppage time
Table A2. (Continued)
Downloaded by [Missouri State University] at 07:08 09 February 2015
Owner delayed
payments
0.158
0.765
−0.31
0.555
−0.31
0.555
−0.31
0.555
−0.31
0.555
0
1
Weather
0.433 −0.43
0.391 0.391
0.433 −0.43
0.391 0.391
−0.171 0.171
0.745 0.745
0.316
0.541
0.612
0.196
0.612
0.196
0.612
0.196
0.612
0.196
0.433
0.391
Emergency repairs
a
a
a
a
a
a
a
a
a
Voids control
Changing mixes
−0.408 0.297
0.422 0.568
−0.408 0.297
0.422 0.568
0.243 −0.647
0.643 0.165
−0.447−0.108
0.374 0.838
−0.577 .840∗
0.23 0.036
−0.577 .840∗
0.23 0.036
−0.577 .840∗
0.23 0.036
−0.577 .840∗
0.23 0.036
−816∗ .891∗
0.047 0.017
Long term storage
.816∗
0.047
.816
0.047
0.243
0.643
0.447
0.374
0.577
0.23
0.577
0.23
0.577
0.23
0.577
0.23
0.408
0.422
a
a
a
a
a
a
a
a
0.548
0.261
0.548
0.261
0.759
0.08
0
1
0
1
0
1
0
1
0
1
a
Segregation at
dumping
1
MTV-availability
a
Screed
adjustment
Paving speed
0.707
0.116
0.707
0.116
−0.42
0.407
0.707
0.116
0.707
0.116
−0.42
0.407
% of crushed
aggregate mass
0
1
0.707
0.116
0.707
0.116
0.707
0.116
0.707
0.116
1
Compaction speed
0.548
0.261
0.707
0.116
0.707
0.116
0.707
0.116
0.707
0.116
0.25
0.633
0.48
0.261
0.707
0.116
0.707
0.116
0.707
0.116
0.707
0.116
0.25
0.633
Distance to paver
0.707 0.25
1 1.000∗∗
0.116 0.633
0
0.707 0.25 1.000∗∗ 1
0.116 0.633
0
−0.42 −0.594 0.297 0.297
0.407 0.214 0.568 0.568
0
0
1
1
1.000∗∗1.000∗∗
0
0
1.000∗∗ 1 1.000∗
0
0
1.000∗∗ 1 1.000∗
0
0
1.000∗∗1.000∗∗ 1
0
0
0.707 0.707 0.707
0.116 0.116 0.116
Stoppage time
0
1
1
0.297
0.568
0.297
0.568
1
0.759
0.08
−0.42
0.407
−0.42
0.407
−0.42
0.407
−0.42
0.407
−0.59
0.214
“Go No-Go”
approach