American College of California Hospital Risk Management Plan Implement IT system in the new medical branch of the WellToDo clinic in Al Ain. Develop a Proj

American College of California Hospital Risk Management Plan Implement IT system in the new medical branch of the WellToDo clinic in Al Ain. Develop a Project Risk Management Plan as to assess the foreseeable risks. Management estimates the IT system should be fully operational within 120 days, 10 to 15 activities should be considered.

The following approaches/techniques must be used.

RBS
RACI
Matrix/Probability
Occurrences/Impact graph(s)
Decision Tree(s)
Break Even Analysis
Monte Carlo Simulation

only using the attached articles as reference for the literature review part and the QM program for the result Article
Assessment of Environmental Risk
from the Project Team’s Perspective
in Electrical Transmission Line
Installation Projects
Vision
21(2) 1–10
© 2017 MDI
SAGE Publications
sagepub.in/home.nav
DOI: 10.1177/0972262917700985
http://vision.sagepub.com
Shwetank Parihar1
Chandan Bhar2
Nishit Kumar Srivastava1
Abstract
This article represents a methodology in which the overall environmental risks can be assessed without much need of secondary
data. The method exemplifies on collection of risk data on the basis of pre-decided risk factors in which the project team members
are asked to give opinion about various risk factors. Since the main risk management team has already given various pre-defined risk
sectors the collective opinion derived gives true value of risk, and the involvement of local workers give an edge over others since
they have vast knowledge of geographical factors and this is how their knowledge can be scientifically used to determine environmental
risk which is a very true estimation of real risk value. This article has successfully identified factors and scaled them up with the help
of a questionnaire-based study. Moreover, different levels of management also pose different environment risk priorities which is also
analysed in this paper.
Key Words
Environmental Risk Management, Electrical Transmission Line, Risk Management, Risk Assessment for Transmission Line Installation
Introduction
Construction projects are usually handling a large amount
of risk especially related to environmental changes. In the
case of electrical transmission line projects a huge amount
of construction work on sites, which are distributed over
wide geographical boundaries, is needed. Therefore, we
can say that the level of environmental risk is even more in
such projects. In this article we have devised risk management methodology for such environmental risks using a
questionnaire-based study which improves the risk management by evaluating various environmental risk methods
based on the feedback of the workers and supervisors
involved in the project. This methodology requires very
less secondary data but the accuracy and flexibility are
maintained.
The primary aim of this article is to develop a mechanism for environmental risk assessment in which the
1
2
overall risk assessment is done by using the information
collected from the workers and on-site supervisors and
contractors, since they are well experienced and directly
associated with the construction site; moreover, they are
residents of that area. In spite of having very less secondary data, this process provides us with a very justified environmental risk assessment.
The environmental risk constitutes very high values of
impact in total risk management but the data availability
for assessing this risk is very low and hence it was necessary to develop such a method in which the requirement of
historical data should be less and resources required to
assess the risk should be low. This method combines both
the qualities of low historical data need and cost input for
risk assessment plan.
The methodology discussed uses very simple basics
and is employed for electrical transmission line installation projects, which are mainly civil work based, and these
Doctorate, Department of Management Studies, IIT (ISM) Dhanbad, Dhanbad, Jharkhand, India.
Professor, Department of Management Studies, IIT (ISM) Dhanbad, Dhanbad, Jharkhand, India.
Corresponding author:
Shwetank Parihar, Department of Management Studies, Indian School of Mines, Dhanbad 826004, Jharkhand, India.
E-mail: shwetankp@gmail.com
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Vision 21(2)
projects are simultaneously started on different geographical
locations with the span of several hundred kilometres (in
case of long transmission lines) and hence environmental
risks play very important role in such projects.
Literature Survey
Environmental risk factors are given much concern by
various authors. The studies mainly revolve around the collection of risk factors under which the environmental risks
are covered as a single factor but a dedicated study for
environmental risk is scarce and the same problem of secondary data arises whenever a new project is undertaken.
Our study deals very efficiently with this problem. The
major studies conducted for collection of environmental
factors are listed in Table 1.
Regos (2012) has given a comparison of power plant’s
risks with multi-criteria decision models in which the
health risks in addition to the environmental risks are taken
into consideration. Olaru (2014) proposed a method for
risk assessment with special emphasis on environmental
risks in which the investment projects are dealt with the
assessment for the degree of uncertainty with the help of
Monte Carlo simulation, and has a very positive impact on
the project objectives. The determination of impact is
hence derived as a crucial factor for risk assessment and
project success. Similarly, Dey (2010) proposed an analytical hierarchy process combined with risk map to have risk
management process intact, and in this study the risk management is done in a very efficient manner and during the
assessment of environmental risk both environmental risks
impacts and social impacts were considered. The framework devised in the study allows the calculation of risk
level in the construction project of pipelines, in which four
alternatives for pipelines were considered and the best
among the four in terms of risks are selected with consideration on various risks parameters. The same methodology can be applicable in transmission lines also, but the
Table 1. Authors Advocated for the Environmental
Risk Study Project
Environmental risk
Chen, Li, Ren, Xu and Hong (2011)
Iyer et al. (2010)
Thevendran (2004)
Baccarini et al. (2001)
Dey (2001)
Fan et al. (2008)
Regos (2012)
Wu, Wang and Fang (2008)
Erickson & Evaristo (2006)
Dikmen, Birgonul, Anac, Tah and Aouad (2008)
Ping et al. (2010)
Tummala et al. (1999)
Source: Authors’ own.
problem with such an analysis is based on availability of
secondary data which is needed in very scarce amount in
the method devised by us in this study.
Authors like Dey (2001) has given many environmental
factors like natural calamities, in normal and abnormal categories, to be considered important, along with it environmental clearance, land acquisition and other clearance
requirements are necessary factors devised in this study
where risk mitigation is planned accordingly for these
factors. Regos (2012) has given health and environmentbased risks due importance in the study, where risk classification and then weights association are being done for
risk management. Health-related risks are also further subdivided in many categories for dealing separately according to their impact and severity. Similarly, Baccarini
(2001), Chen (2011), Fan (2008) and Iyer (2010) have also
given due importance to environmental risk for total risk
assessment, and the main risk factors that emerge out of the
above-mentioned author’s collection of study are acts of
god, land-related issues, which can be legal, geographical
and social and development-related issues of that area that
can define the risks related to timely completion of the
project in the end. Some authors have named a factor
known as project surroundings that directly indicated the
sum total of land related risks; project justification and
approval also emerge out as the one of the major factors for
risks that are found to be related to environmental risks.
Other authors like Dikmen (2008), Erickson (2006), Ping
(2010), Thevendran (2004), Tummala (1999)and Wu et al.
(2008)have given their viewpoints on risk management
process. In addition, environmental factors are given a
huge importance in their studies, one way or the other. This
reflects the need for a separate dedicated system for environmental risk assessment. The collection of various environmental risk factors is shown in Table 2.
Research Methodology
The study mainly concentrates on the assessment of environment risk factors in a transmission line installation
project. The collection of risk factors is done, which is
important in any transmission line installation project, and
these set of parameters which are identified from the
literature are then analysed by the experts’ view and then
statistical techniques are applied for combining these components into factors. In the end, the individual rating for
each parameter is also studied using mean variation study
and other deviation tracking statistical tools, as well as
tests like ‘One-Sample Kolmogorov–Smirnov Test’ are
also done. The process can be summed up as a collection of
various sub-processes as shown in Figure 1.
On the basis of literature survey, various risk factors
that are primarily involved in any project are selected and
are shown in Table 2. Another point of concern is that
overall the same risk factors can have different impact on
the different projects. Therefore, we need to calculate the
3
Parihar et al.
Table 2. Environmental Risk Factors
Factor
Sub-factor
Supporting Author
Nature driven
Flood
Earthquakes
Dey (2001), Fan (2008), Baccarini (2001), Chen (2011), Erickson (2006), Ping (2010)
Dey (2001), Fan (2008), Baccarini (2001), Chen (2011), Erickson (2006), Ping (2010),
Dikmen (2008)
Dey (2001), Baccarini (2001), Chen (2011), Erickson (2006), Ping (2010)
Dey (2001), Chen (2011), Erickson (2006), Ping (2010)
Dey (2001), Fan (2008), Chen (2011), Erickson (2006), Ping (2010)
Dey (2001), Chen (2011), Erickson (2006), Ping (2010)
Dey (2001), Chen (2011), Erickson (2006), Ping (2010)
Dey (2001), Chen (2011), Erickson (2006)
Regos (2012), Chen (2011)
Chen (2011), Ping (2010)
Regos (2012), Baccarini (2001), Chen (2011), Ping (2010)
Regos (2012), Baccarini (2001), Chen (2011), Ping (2010)
Regos (2012), Chen (2011), Ping (2010)
Baccarini (2001), Chen (2011), Ping (2010), Dikmen (2010), Thevendran (2004)
Baccarini (2001), Chen (2011), Erickson (2006)
Baccarini (2001), Chen (2011), Erickson (2006)
Dey (2001), Fan (2008), Baccarini (2001), Chen (2011), Erickson (2006), Dikmen
(2010), Thevendran (2004)
Regos (2012), Iyer (2010), Baccarini (2001), Chen (2011), Erickson (2006), Ping
(2010)
Regos (2012), Iyer (2010), Baccarini (2001), Chen (2011), Erickson (2006)
Tummala (1999), Erickson (2006), Ping (2010), Dikmen (2010)
Baccarini (2001), Tummala (1999), Ping (2010)
Iyer (2010), Baccarini (2001), Chen (2011), Tummala (1999), Wu et al. (2008),
Erickson (2006), Ping (2010), Dikmen (2010)
Man driven (health
and social)
Land related
Tsunami
Volcano activity
Hurricane
Forest fires
Tornado
Storms
Chemical
Biological
Radioactive
Accidents (leakage etc.)
Epidemics
Chaos
Terrorist activity
Theft, etc.
Government approval
Geographical location
Technoenvironmental
Chemical composition
Faulty tower design
Improper soil analysis
Insufficient climate
considerations in blue
print
Source: Authors’ own.
Figure 1. Environmental Risk Assessment Methodology
Source: Authors’ own.
impact of each risk factor particularly for that project and
accordingly the project’s risk mitigation shall be planned.
Data Analysis
The final assessment of risk factors is being done by circulation of questionnaire to various firms undergoing
transmission line installation projects. The survey received
335 valid responses, and the data is collected from personal
interviews, mail and phone. The factor analysis of the
questionnaire shows that 10 components can explain 62
per cent of the variation. The result is shown in Table 3.
The factor analysis shows that some components are more
important than the other ones, so we need to find the
4
components in the same way for each project we are
undertaking. The data analysed through SPSS is shown in
Table 3.
Table 3 shows that components numbered 1–10 are able
to explain more than 60 per cent of the variations present,
which shows that the selection of these 10 components is
sufficient to explain the variations and hence they are the
most important factors. The component matrix is shown in
Table 4.
The components that are extracted through it are also
given in Table 5. These components are derived with the
help of rotated component matrix shown in Table 5 and if
the parameter is having the value greater than .5 against
each component, then that parameter is selected under that
component. In this way each parameter is identified under
each component and they are shown in Table 5. The major
categories of risk in environmental risk analysis are shown
in Table 5, and in risk mitigation plan these are given more
importance and for any modelling or simulation purpose
they can be used as a guideline.
The mean value of importance level is given in Table 6,
in which the parameters like improper soil analysis, insufficient climate considerations, radioactivity, chemical
composition and geographical location are found to be
most high-impact environment risk factors.
The factors identified are then asked by the experts to
rate and they are asked to check it against the data available
with them and this study has been validated by installing
these factors on the project risk management modules. All
the experts are asked to comment on the results of this
factor analysis and they all agreed that these factors influence their project. The experts are asked to provide the data
points in which the environmental risks which are occurring are judged in previous projects, and it was found that
these are also important in most of the previous projects.
This pilot study validates the results of factor analysis.
The graphical study of importance forecasted by different designation holders is shown in Figure 2 where contractors, engineers, managers and supervisors have given
more emphasis and importance on site-related technical
risk factors. Workers have given little variation over the
impact issue for different factors.
The graph shown in Figure 2 explains the variations in
the means and most of them show very few variations. This
figure indicates that most of them are given a rating under
the range of 3.1–2.8 as their mean values. This clearly indicates that the majority of the respondents and experts think
that most of these factors hold importance in such projects,
and due to the nature of such risks, it is always advisable to
keep them in mind while designing the risk mitigation
plans since they are always in a constant mode to occur and
can strike at any time with variable intensity. This nature is
depicted by the graph and for this reason it can be seen that
the graph shows less variance in terms of these mean values
and prefigures that most of them are important and equally
probable to occur and this fact is stated by many experts
Vision 21(2)
during our discussion. The experts also express that
environmental risks can occur at any time with high-impact
value, which is reflected in the values shown in the graph
in Figure 1.
The comparison between the ratings is done using the
graph shown in Figure 1, and the validation is done by
One-Sample Kolmogorov–Smirnov Test shown in Table 7
in which the normal parameters are matched and all the
Kolmogorov–Smirnov Z scores are positive and hence
they follow the normal curves, because of which the bar
graphs were not showing a considerable difference but the
standard deviation is calculated in Table 6 which shows
that parameters like earthquakes, insufficient climate considerations, radioactivity, faulty tower design, geographical location, theft, tsunami, chaos and forest fires are
showing a higher standard deviation in their mean risk
values given by experts. So this explanation analyses indicates the reason for high mean values with less variances
shown by the graph in of the mean value of overall impact
level of these risks.
Hence the study generates those factors which are to be
included in environmental risk mitigation planning. The 10
factors are given in Table 5 and hence we can say that the
study was able to arrange the environmental risk factors
Table 3. Factor Analysis
KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
Bartlett’s Test of Sphericity Approx. Chi-Square
df
Sig.
.501
614.803
231
.000
Communalities
Flood
Earthquakes
Tsunami
Volcano_activity
Hurricane
forest fires
tornado
Storms
Chemical
Biological
Radioactive
Accidents_Leakage_etc)
Epidemics
Chaos
Terrorist_Activity
Theft_etc
Government_Approval
Geographical_Location
Chemical_Composition
Faulty_tower_design
Improper_soil_analysis
Insufficient_Climate_considerations
Initial
Extraction
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
.654
.568
.670
.759
.665
.647
.578
.655
.787
.733
.657
.400
.549
.469
.639
.611
.530
.636
.582
.559
.661
.679
5
Parihar et al.
Total Variance Explained
Initial Eigenvalues
Extraction Sums of Squared Loadings
Component
Total
% of Variance
Cumulative %
Total
% of Variance
Cumulative %
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
1.989
1.832
1.554
1.380
1.331
1.197
1.178
1.132
1.082
1.011
.955
.924
.830
.808
.742
.737
.696
.632
.589
.544
.456
.402
9.040
8.328
7.066
6.273
6.049
5.440
5.354
5.146
4.917
4.595
4.342
4.202
3.771
3.673
3.372
3.351
3.163
2.872
2.676
2.471
2.073
1.826
9.040
17.368
24.434
30.706
36.756
42.196
47.550
52.695
57.612
62.208
66.550
70.752
74.523
78.196
81.568
84.919
88.081
90.954
93.630
96.101
98.174
100.000
1.989
1.832
1.554
1.380
1.331
1.197
1.178
1.132
1.082
1.011
9.040
8.328
7.066
6.273
6.049
5.440
5.354
5.146
4.917
4.595
9.040
17.368
24.434
30.706
36.756
42.196
47.550
52.695
57.612
62.208
Source: SPSS data and output files.
Note: Extraction Method: Principal Component Analysis.
Table 4. Rotated Component Matrix
Component Matrixaa
Component
Flood
Earthquakes
Tsunami
Volcano_activity
Hurricane
forest fires
tornado
Storms
Chemical
Biological
Radioactive
Accidents_Leakage_
etc)
Epidemics
Chaos
Terrorist_Activity
Theft_etc
Government_
Approval
Geographical_
Location
Chemical_
Composition
1
2
3
4
5
–.133
.115
–.001
.190
.028
.169
.335
.000
.041
.057
.068
–.030
–.136
.115
.023
–.038
–.075
.327
.097
.234
.242
.377
.579
.436
–.167
.107
.306
.166
.156
.281
.442
.482
.252
.223
.229
–.127
.127
.356
.357
.145
.458
.371
.208
.161
–.241
–.560
–.172
–.082
–.362
.093
.227
.250
.033
–.286
–.136
.173
.392
.262
–.092
.090
–.330
–.160
–.089
.488
.506
–.099
–.161
–.318
–.110
.153
.040
–.026
6
.032
–.471
–.300
–.359
.397
.409
.025
.036
.447
.065
–.299
–.230
7
.494
–.372
.154
.434
.093
.109
.155
–.226
–.119
.301
.222
–.206
8
.058
–.056
.450
.011
.000
.010
–.084
–.292
.232
–.167
–.232
.278
9
.292
–.077
.268
.235
–.033
–.154
–.376
.269
.414
–.098
–.180
–.068
10
–.046
–.160
.162
.391
.509
.485
.355
.475
.357
–.002
–.330
–.382
–.304
–.334
–.370
.046
.335
.218
.076
–.035
.241
.109
–.044
–.248
.147
–.054
.202
.211
–.109
–.245
.127
–.033
.139
–.052
.005
.129
.006
–.249
.150
.206
.286
.007
–.233
–.177
.076
–.156
–.071
.255
.289
–.042
.521
–.138
–.174
.106
.376
–.324
.114
.060
.019
–.202
.267
–.343
–.069
.152
.510
–.054
.027
.105
–.298
–.041
(Table 4 continued)
6
Vision 21(2)
(Table 4 continued)
Component Matrixaa
Component
Faulty_tower_design
Improper_soil_
analysis
Insufficient_Climate_
considerations
1
.543
.585
2
–.197
.014
3
–.096
.198
4
–.123
–.190
5
–.054
–.366
6
.198
.020
7
–.046
–.073
8
–.191
–.046
9
–.288
.244
10
.195
.203
.569
–.074
.052
–.097
–.117
.278
.045
–.220
.402
–.185
Source: SPSS data and output files.
Note: Extraction Method: Principal Component Analysis, Rotation Method: Varimax with Kaiser Normalization, aRotation converged in 13 iterations.
Table 5. Components and Parameters Analysed
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