1. Understanding Logistics in Disaster Response
NPS-LM-11-188 ^`nrfpfqflk=obpb^o`e= pmlkploba=obmloq=pbofbp= = Strategies for
Logistics in Case of a Natural Disaster 28 September 2011 by Dr. Aruna Apte, Assistant
Professor, and Dr. Keenan D. Yoho, Assistant Professor Graduate School of Business & Public
Policy Naval Postgraduate School Approved for public release, distribution is unlimited.
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NOTES 14. ABSTRACT The need to effectively and efficiently provide emergency supplies
and services is increasing all over the world. We investigate four policy options?
prepositioning supplemental resources, preemptive as well as phased deployment of assets,
and a surge of supplies and services?as potential strategies for responding to a disaster. We
illustrate the linkage between our four policy options and a disaster classification based
upon disaster localization (dispersed or local) and speed of disaster onset (slow or sudden).
We summarize our work by introducing a matrix that aligns logistics strategies with

2. disaster types in order to assist policymakers in their resource management decisions. 15.
SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: a. REPORT b. ABSTRACT c. THIS PAGE
unclassified unclassified unclassified 17. LIMITATION OF ABSTRACT 18. NUMBER OF
PAGES Same as Report (SAR) 43 19a. NAME OF RESPONSIBLE PERSON Standard Form 298
(Rev. 8-98) Prescribed by ANSI Std Z39-18 The research presented in this report was
supported by the Acquisition Chair of the Graduate School of Business & Public Policy at the
Naval Postgraduate School. To request Defense Acquisition Research or to become a
research sponsor, please contact: NPS Acquisition Research Program Attn: James B. Greene,
RADM, USN, (Ret.) Acquisition Chair Graduate School of Business and Public Policy Naval
Postgraduate School 555 Dyer Road, Room 332 Monterey, CA 93943-5103 Tel: (831) 656-
2092 Fax: (831) 656-2253 E-mail: jbgreene@nps.edu Copies of the Acquisition Sponsored
Research Reports may be printed from our website www.acquisitionresearch.net =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= Abstract The need to effectively and efficiently provide
emergency supplies and services is increasing all over the world. We investigate four policy
options— prepositioning supplemental resources, preemptive as well as phased
deployment of assets, and a surge of supplies and services—as potential strategies for
responding to a disaster. We illustrate the linkage between our four policy options and a
disaster classification based upon disaster localization (dispersed or local) and speed of
disaster onset (slow or sudden). We summarize our work by introducing a matrix that
aligns logistics strategies with disaster types in order to assist policymakers in their
resource management decisions. Keywords: logistics, natural disaster, humanitarian
assistance, humanitarian aid, disaster response = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
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INTENTIONALLY LEFT BLANK = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v k^s^i=mlpqdo^ar^qb=p`elli= – ii – About the
Authors Dr. Aruna Apte has successfully completed various research projects, involving
application of mathematical models and optimization techniques that have led to over 20
research articles and one patent. Her research interests are in developing mathematical
models for complex, real-world operational problems using optimization tools. She values
that her research be applicable. Currently her research is focused in humanitarian and
military logistics. She has several publications in journals, such as Interfaces, Naval
Research Logistics, Production and Operations Management. She has recently published a
monograph on Humanitarian Logistics. Aruna has over twenty years of experience teaching
operations management, operations research, and mathematics courses at the
undergraduate and graduate levels. She has advised emergency planners in preparing for
disaster response. She is the founding and current president for a new college (focus group)
in Humanitarian Operations and Crisis Management under the flagship academic
professional society in her intellectual area of study, Production and Operations
Management Society. Dr. Keenan Yoho’s primary research activities are in the area of
analyzing alternatives under conditions of uncertainty and resource scarcity. Keenan’s
primary research activities lie in the analysis of alternatives for capital purchases under
conditions of resource scarcity, supply chain management, risk analysis, humanitarian

3. assistance and disaster response, and resource management in environments that exhibit
high degrees of uncertainty. Dr. Aruna Apte Graduate School of Business and Public Policy
Naval Postgraduate School Monterey, CA 93943-5000 Tel: 831-656-7583 Fax: (831) 656-
3407 E-mail:auapte@nps.edu Dr. Keenan D. Yoho Graduate School of Business and Public
Policy Naval Postgraduate School Monterey, CA 93943-5000 Tel: 831-656-2029 Fax: (831)
656-3407 E-mail: kdyoho@nps.edu = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
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LM-11-188 ^`nrfpfqflk=obpb^o`e= pmlkploba=obmloq=pbofbp= = Strategies for Logistics
in Case of a Natural Disaster 28 September 2011 by Dr. Aruna Apte, Assistant Professor, and
Dr. Keenan D. Yoho, Assistant Professor Graduate School of Business & Public Policy Naval
Postgraduate School Disclaimer: The views represented in this report are those of the
author and do not reflect the official policy position of the Navy, the Department of Defense,
or the Federal Government. = = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
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PAGE INTENTIONALLY LEFT BLANK = = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v k^s^i=mlpqdo^ar^qb=p`elli= = – vi – Table
of Contents I. Introduction …………………………………………………………………………………. 1 II.
Literature Review …………………………………………………………………………. 5 III. Disaster Life
Cycles ……………………………………………………………………… 7 IV. Disaster Classification
………………………………………………………………….. 9 V. VI. A. Indian Ocean “Boxing Day” Tsunami
of 2004 ………………………….. 10 B. Haiti 2010 Earthquake
…………………………………………………………. 11 C. Hurricane Katrina
……………………………………………………………….. 12 D. Influenza “Swine Flu” Epidemic of 2009
…………………………………. 12 Discussion
…………………………………………………………………………………. 15 A. Prepositioning
…………………………………………………………………….. 15 B. Proactive Deployment
…………………………………………………………. 17 C. Phased Deployment
……………………………………………………………. 18 D. Surge Capacity
…………………………………………………………………… 20
Conclusion…………………………………………………………………………………. 21 List of References
………………………………………………………………………………… 25 = =
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k^s^i=mlpqdo^ar^qb=p`elli= – viii – I. Introduction In 2009 there were 335 natural
disasters reported worldwide that killed 10,655 persons, affected more than 119 million
others, and caused over $41.3 billion in economic damages (Vos, Rodriguez, Below, & Guha-
Sapir. 2009). The number of natural disasters reported between 1900 and 2010 has
increased significantly and, with it, the number of requests for aid and humanitarian
assistance (see Figure 1). While the trend in the number of disasters reported shows an
increase, it is not clear that there has been a commensurate response in terms of

4. preparedness. The United States Agency for International Development (USAID) reports
that of all funds used to support disaster operations, 90% are spent for response, whereas
10% are spent on preparedness activities and investments and risk reduction (A. Giegerich,
personal communication, September 21, 2010). The United Nations estimates that every
dollar spent to prepare for a disaster saves seven dollars in disaster response (United
Nations Human Development Program, 2007). 550 500 450 400 350 300 250 200 150 100
50 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 Figure 1. Number
of Disasters Reported from 1900–2010 (EM–DAT, 2011) = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = -1- Although the objective of all the organizations and
agencies involved in humanitarian assistance is to reduce human suffering and casualties,
the duration and severity of the human toll during a natural disaster is largely dependent
upon the speed and scope of the response, which is often a function of the level of
preparedness that has been established prior to the disaster event. While there are no
internationally agreed upon metrics by which to judge or measure the effectiveness of a
response to a disaster, scholars working in the humanitarian and disaster response
research area have found that improvement is desirable (Apte, 2009; Van Wassenhove,
2006). An effective and efficient humanitarian response depends “on the ability of
logisticians to procure, transport and receive supplies at the site of a humanitarian relief
effort” (Thomas, 2003). In this research we focus on the response to a disaster area in the
form of distributing supplies, and strategies that will enhance the effectiveness of such a
response. For the purpose of this research, we accept the Center for Research on the
Epidemiology of Disasters’ (CRED) definition of disaster, which is “a situation or event
which overwhelms local capacity, necessitating a request to a national or international level
for external assistance.” The unpredictability of the timing of a disaster, as well as the scope
of its human and material destruction, raises several serious questions for emergency
planners and first responders. For example, how can a state of supply preparedness be
established and maintained? How should adequate prepositioned disaster relief inventory
be established and sustained over time, to include the rotation of perishable stocks? How
can information regarding the location, quantity, and condition of prepositioned inventory
be shared, and what effect would this information sharing have on the total investment of
prepositioned stocks? Is prepositioning the best strategy for all types of disasters? How
reliable are the potential supply lines if it is determined that supplies should be virtually
stockpiled (that is, a detailed list or database of supplies by type and quantity is created and
maintained, as well as reliable sources that can provide the supplies quickly)? = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = -2- Should the supplies be sourced locally or from outside
the disaster zone? Answers to these questions depend on the expected onset speed of the
disaster, the volume and weight of supplies to be moved, the expected magnitude of
humanitarian relief required, and the expected likelihood of a disaster in the area. As part of
our investigation we explore four policy options: (1) prepositioning supplemental resources
in or near the incident location; (2) proactive deployment of assets in advance of a request;
(3) phased deployment of assets and supplies, analogous to the “just in time” inventory

5. control philosophy practiced by many commercial manufacturers; and (4) “surge”
transportation of manpower and equipment from locations outside the disaster area. = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
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k^s^i=mlpqdo^ar^qb=p`elli= = -4- II. Literature Review One of the major issues in a
response supply chain in case of a natural disaster is to coordinate the operations and relief
inventories over a large number of stages, locations, and organizations. This has to be done
while providing the emergency supplies and services to the affected population under
extreme conditions. Decisions regarding the types of provisions that should be
prepositioned, as well as their location, should be made well before a disaster strikes in
order to provide quick response. To some extent, without such a high level of uncertainty
and an adverse environment, it is similar to the core question in supply chain management
of coordinating activities and inventories over a spectrum of stages of the supply chain and
facility locations of the inventory (Schoenmeyr & Graves, 2009). In the private sector, it has
been found that if each individual stage in a serialsystem of the supply chain operates with a
designated base stock policy with service guarantees, then the optimal safety stock strategy
is to maintain inventory at certain key locations, which results in separating the stages of
the supply chain; this type of policy allows each stage to operate independently by
minimizing the need for communication and coordination amongst players (Simpson, 1958;
Graves & Willems, 2002). Models available in supply chain management literature are
predominantly with unlimited capacity for storage. In cases where there is unlimited
capacity, the amount of safety stock needed is less than the level needed with capacity
constraint (Schoenmeyr & Graves, 2009). The determination of the optimal placement of
safety stock in a supply chain has been addressed by Simpson (1958) and Schoenmeyr and
Graves (2008), where there are evolving or predetermined forecasts, and by Graves and
Willems (2002), where there is uncertain, as well as non-stationary, demand. This concept
can explain the response supply chain where there exists uncertainty for the quantity
required, as well as what is required (Apte, 2009; Ergun, Karakus, Keskinocak, = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = -5- Swann, & Villareal, 2009). Rawls and Turnquist (2010)
developed a model for determining the location and quantity of supplies that should be
prepositioned when there is uncertainty with respect to whether a disaster will occur and
where it will occur, and built upon this work by adding service quality constraints (Rawls &
Turnquist, 2011) to ensure the probability of meeting demand and the average shipment
distance is within a specified parameter. In addition to the prepositioning of relief
inventories, a disaster response may require the formulation of policies that require the
expansion of warehouses, medical facilities, and temporary shelters, while infrastructure
preparation may include the provision of airstrips and ramp space at existing airfields
(Salmeron & Apte, 2010). Koavacs and Spens (2009) weighed the difference between
traditional commercial logistics and humanitarian logistics. With humanitarian logistics, it
is imperative to go beyond the profitability of commercial logistics. Within the domain of
humanitarian logistics, suppliers have different motivations for participating, and

6. customers do not generate voluntary demand. It is clear that in most cases a “repeat
purchase” is not a possibility. Thus, supply networks must take into account the lack of true
demand. Demand is dictated by the relief agencies that are the primary actors within this
framework. Therefore, it is the responsibility of the agency to “push” the supplies to the
disaster location in the immediate response phase, which is different from the commercial
philosophy of pull-based demand. Humanitarian logistics focuses on getting the greatest
volume of supplies to the points where they are needed, and there may be lessons learned
in the commercial sector that could be used to improve the planning and execution of
strategies that could be implemented during a disaster response. = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = -6- III. Disaster Life Cycles The life cycle of a disaster from
the perspective of Humanitarian Assistance and Disaster Relief (HADR) is divided into three
stages (as illustrated in Figure 2): being prepared in the pre-disaster stage, response as the
disaster strikes, and recovery in post-disaster (Apte 2009; Van Wassenhove, 2006).
RESPONSE PREPAREDNESS RECOVERY Asset Prepositioning Infrastructure Preparation
Pre-Disaster Ramp Up Ramp Down Sustainment Disaster Event Post-Disaster Figure 2. Life
Cycle of Disasters (Apte, 2009) Disaster preparedness is the first step in mitigating the
adverse impacts of any unforeseen catastrophic event. Preparedness on an individual level
is defined by the creation of an escape and survival plan, as well as the procurement and
storage of supplies that will enable an individual to act on the plan. Preparedness at an
organizational or institutional level translates to the planning and preestablishment of
adequate capacity and resources that will enable efficient relief operations. Prepositioning
of war reserve and contingency stocks, such as that practiced by each of the U.S. Armed
Services, has proven an effective means of increasing the speed of response to a conflict
(Abell et al., 2000; Button, Gordon, Hoffmann, Riposo, & Wilson, 2010; Hura & Robinson,
1991). The private commercial sector, too, has been involved in prepositioning strategic
safety stocks in supply chains with evolving forecasts (Schoenmeyr & Graves, 2008),
capacity = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
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constraints (Schoenmeyr & Graves, 2009), and non-stationary demands (Graves & Willems,
2002, 2008). Disaster response is a function of the preparation that took place prior to the
disaster event, as well as the coordination of available supplies and distribution capacity.
The first part of the response consists of gaining situational awareness of events and
conditions on the ground in the disaster area through the collection of available
information, and then using this information and awareness to generate an operational
picture that will inform the nature, scale, and timing of the response. The result of this
collection of information and establishment of situational awareness is a needs assessment
or requirement for assistance. The response itself is largely comprised of the tactical
activities that must take place to move needed supplies to those parts of the disaster area
that have the most critical demand, given the available resources at hand. Disaster recovery
consists of stabilizing the disaster area and improving the living and economic conditions of
those affected by the catastrophic event. The recovery phase means different things to
different organizations. For the military, the recovery phase likely signals the beginning of

7. drawn-down or redeployment operations, whereby military personnel and equipment are
withdrawn and responsibility turned over to civil authorities. For non-governmental and
non-military aid organizations, the recovery phase may consist of establishing semi-
permanent camps, aid stations, or warehouses to shelter displaced persons; delivering
critical services that cannot be provided by other civil authorities; and coordinating the
storage and distribution of supplies that are otherwise unavailable or in short supply to the
local population. Studying the life cycle of recent disasters offers insight into both short-
term and long-term consequences. It also provides us with numerous lessons to form
effective strategies for mitigating future disasters. However, in order to formulate such
strategies, we need to understand disasters in terms of their speed and scope. = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = -8- IV. Disaster Classification Disasters are often classified
based on the speed of onset and the source or cause of the disaster (Ergun, Heier, & Swann,
2008; Van Wassenhove, 2006). However, in our research we focus on four disaster
scenarios that are combinations of the geographic dispersion of the disaster (dispersed or
localized) and its speed of onset (slow or sudden), as discussed by Apte (2009) and
described in Figure 3. We differentiate local from dispersed disasters in terms of the
number of civil administrative districts impacted, such as cities, counties, townships,
parishes, prefectures, provinces, or states. As the number of civil administrative districts
increases, so does the geographic area impacted, resulting in an increase in the complexity
associated with responding to the disaster. It is the coordination of effort across multiple
districts, coupled with the size of the relief requirement, which frustrates the effectiveness
of humanitarian assistance and disaster response operations. Slow-onset disasters are
defined as those that allow potentially affected populations time to react in order to
mitigate the impact of the disaster, whereas sudden-onset disasters allow little to no time to
react to the disaster event. The disaster classification suggests that the level of difficulty in
the logistics execution is less onerous in the case of localized, slow-onset disasters (depicted
in quadrant III of Figure 3) because there may be adequate lead-time and local resources to
prepare for the response. We next discuss four specific disaster cases that exhibit different
onset and localization characteristics, as illustrated in Figure 3, and serve as exemplars of
strategies that are appropriate to specific disaster types, as described in the discussion
section. = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = -9-
Dispersed Localized IV 2009 H1N1 Flu Pandemic I 2004 Indian Ocean Tsunami III 2005
Hurricane Katrina II 2010 Haiti Earthquake Slow Onset Time Sudden Onset Figure 3.
Classification of Disasters (Apte, 2009) A. Indian Ocean “Boxing Day” Tsunami of 2004
Dispersed and sudden-onset disasters (depicted in quadrant I of Figure 3) tend to be the
most catastrophic in humanitarian terms because they lack warning in advance of their
onset, and they impact large geographic areas that often cross multiple civil administrative
areas, making coordination critical and difficult. The Indian Ocean Tsunami of 2004 was the
result of a 9.1 magnitude earthquake and was responsible for more than 227,000 deaths,
more than 500,000 injured, over 2 million missing, and more than 1.5 million displaced
persons across more than 12 countries (Greenfield & Ingram, 2011). The destruction was

8. primarily limited to the coastal regions (Samek, Skole, & Chomentowski, 2004), but was
dispersed across so many countries that relief efforts were frustrated by the lack of
complete reports of the damage to those countries affected and of the specific types of aid
and assistance needed most. = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = – 10 – Most
of the people affected by the tsunami did not actually know it was coming. Because the
earthquake occurred far offshore, those affected on land were not aware of it and had no
way of knowing the tsunami was coming. The earthquake occurred so far away that it was
not felt. The key problem was notification. Agencies that did sense the earthquake were not
able to effectively notify those areas that might be potentially affected and even if they did
the agencies did not have adequate means of disseminating the potential threat of a tsunami
to all those that might be affected. It should be noted at this juncture that there was no
tsunami warning system in the Indian Ocean. Some areas, particularly the Banda Aceh
region of Sumatra in Indonesia, lacked a basic, functioning transportation infrastructure,
which imposed severe capacity constraints on the flow of inbound supplies. B. Haiti 2010
Earthquake A sudden-onset disaster, even if localized (depicted in quadrant II of Figure 3),
creates operational difficulties that are greater than circumstances where the onset is slow,
but less than if the catastrophe were both rapid in its onset and geographically dispersed.
Sudden-onset disasters deny authorities and the public time to prepare for the
consequences of the disaster event and, therefore, tend to exact a much higher human cost.
The earthquake that struck Haiti on January 12, 2010, measured 7.0 in magnitude on the
Richter scale, resulting in more than 200,000 dead (United Nations, 2010). Poorly designed
and constructed buildings, bridges, and other infrastructure resulted in significant losses,
the creation of large debris fields and obstructions to transportation, and a need for large-
scale rescue efforts of those trapped alive underneath concrete and steel wreckage. The
government of Haiti was immobilized with a significant percentage of the national
leadership dead or missing as a result of the earthquake. With little ability to assess damage
or mobilize and manage the few resources that were not destroyed in the quake, the
surviving population were left to rely on the response of other nations to help rescue those
trapped in collapsed buildings and to provide = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = – 11 – food,
water, medicine, and shelter. Lack of physical infrastructure, especially in underdeveloped
and poor countries, causes long lead-times in transportation, which was evident in Haiti.
The consequences of poor governance and weak institutions were evident in the Haiti
disaster, and so, in spite of the proactive deployment from the rest of the world, suffering
persists. C. Hurricane Katrina On August 29, 2005, Hurricane Katrina struck the city of New
Orleans. It was known days in advance that the hurricane might make landfall in New
Orleans, and although the city had warned residents, there were many who remained and
were killed, stranded, or left homeless as a direct result of the storm’s violence or the failure
of the levee system that otherwise protected the city from flooding. Hurricane Katrina was a
slow-onset, localized disaster (see quadrant III of Figure 3) and one of the most devastating
and costly hurricanes to strike the United States. Once the storm had passed, more than
80% of the city of New Orleans was under water, approximately 1,700 people were dead, 1

9. million persons were displaced, and an estimated $135 billion in damage along the Gulf
coast was incurred (Plyer, 2010). The official plan for the city was for displaced residents to
gather in the New Orleans Superdome football arena in the downtown center as a refuge of
last resort. However, due to failed infrastructure and lack of planning for needed supplies to
be delivered to the affected area, those who sought refuge during the critical first week
following the landfall of the storm found thousands of people confined in a large open
building whose roof was torn open and which had no functioning utilities, such as electricity
or water. The state of Louisiana activated the National Guard and after several days, buses
were organized to begin evacuating those still in the city to outlying areas. D. Influenza
“Swine Flu” Epidemic of 2009 Quadrant IV describes a context where the onset is slow but
the affected area is geographically dispersed. When the disaster area consists of a large or
scattered = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = – 12 –
geographical area, it may take substantial planning, resource allocation, and coordination
among the military, humanitarian organizations, and local, federal, and perhaps even
foreign, government representatives. The 2009 influenza epidemic is an example of a slow-
onset, geographically dispersed disaster event affecting multiple countries (see Figure 4).
The epidemic was responsible for more than 14,000 known deaths (European Centre for
Disease Prevention and Control [ECDC], 2010), which occurred throughout the world.
Subsequent research has shown that the seriousness of the influenza cases was not
necessarily greater than other influenza outbreaks (Centers for Disease Control and
Prevention [CDC], 2010), but the population affected was different, with children affected in
much higher numbers than other influenza outbreaks on record at the time (Belongia et al.,
2010). Although the numbers of people who have died from the H1N1 influenza have been
modest since the pandemic in 2009, there remains a significant threat that the disease could
mutate into an antibiotic resistant strain that could eventually kill millions of people
worldwide; the CDC has stated that H1N1 and H3N3 influenza strains are both highly
resistant to two of the four licensed influenza antiviral agents (CDC, 2011). The public
health response to the 2009 pandemic faced challenges in the form of educating the public
about the severity of the epidemic, managing initial shortages of vaccine inventories in the
initial weeks of the declared pandemic (Responding to the 2009–2010 Influenza Season,
2009), as well as determining distribution points for the vaccines. Effective vaccine
distribution is dependent upon the ability of public health officials to detect virulent strains
that might result in a pandemic. Once a strain is identified that might result in a pandemic
or once a pandemic has been declared, public health officials must decide when to begin the
mass production of a vaccine. Because influenza mutates rapidly, it is not feasible to
stockpile vaccines for long periods in anticipation of a particular, currently identified strain.
Instead, surge capacity must be established to respond to a potential pandemic, and then
distribution networks must be capable of moving the vaccines to where they are needed. = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = – 13 – Figure 4. 2009 Confirmed Cases of H1N1 Flu by
Country (ECDC, 2010) One of the key problems with vaccines for influenza is that they
cannot be prepositioned far in advance because the influenza strains mutate, making it

10. necessary for epidemiologists to forecast what they believe will be the dominant strain of
influence in advance. So, essentially the responders must rely upon availability of the
vaccines. If there is none available it has to be produced and then distribute the produced
vaccine as quickly as possible and ensure that the most vulnerable and/or necessary people
get it first. The Strategic National Stockpile (SNS), which is jointly run by the CDC and the
Department of Homeland Security (DHS), contains an inventory of antibiotics, antidotes,
and vaccines for rapid deployment in case of an emergency. = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = – 14 – V. Discussion The disasters we have discussed in the
previous section illustrate the strategic, as well as operational, difficulties faced when
responding to a disaster. Though the disasters are classified into four quadrants, we believe
the terms slow, sudden onset, localized, and dispersed are relative. A hurricane is slow in
onset because there is some forecast available and, hence, it is imminent but not necessarily
sudden. A pandemic, on the other hand, is very slow compared to the time between when a
hurricane is identified and when it makes landfall. At the other end of the spectrum is an
earthquake, which is instantaneous, with aftershocks in the category of slow, since they are
imminent. The geographic dispersion of a disaster is also relative since a disaster can be
considered to be localized if only one governing entity or administrative district (such as a
city, town, or county) is involved or several communities are affected. Such granular
classification could be a topic for further research; however, in our work we confine our
analysis to the general categories of sudden and slow when discussing onset, and to
localized and dispersed when considering geographic dispersion. We next consider four
fundamental strategies an organization could employ to respond to natural disasters in the
context of the exemplars presented in the previous section: prepositioning, proactive
deployment of assets in advance of a request, phased deployment of assets and supplies,
and “surge” capacity planning of manpower and equipment from locations outside the
disaster area to the area of most need. A. Prepositioning The success of the military in using
prepositioned stocks has developed interest in the prospect of using such a strategy to
support operations other than war (Brown, Schank, Dahlman, & Lewis, 1997; Salmeron &
Apte, 2010). Prepositioning = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = – 15 –
supplemental resources in or near the incident location most resembles the military
practice of storing defense inventory ashore or at sea to be used in the event of a conflict;
the Army prepositioned stocks (APS) in southwest Asia (APS–5), Korea (APS–4), and the
Indian Ocean (APS–3) are good examples (see Figure 5). Figure 5. Army Prepositioned Stock
Locations (Headquarters, Department of the Army, 1999) Non-governmental organizations
also preposition items in advance of a disaster to reduce the response time of providing
relief (Duran, Gutierrez, & Keskinocak, 2011). Prepositioning supplies is appropriate when
the lead-time to respond with supplies exceeds the time frame in which the supplies are
needed, or when it is important to preserve transportation assets, such as airlift, for other
purposes, such as personnel or higher priority movement. When determining where to
preposition supplies, organizations must consider the trade-offs between placing stocks
close to a potential disaster area so that the distribution time is reduced, and the risk

11. associated with being adversely impacted by the disaster if they are too close to the
potential danger zone. Campbell and Jones (2011) described a method for determining
where to preposition supplies in anticipation of disaster, considering several different
scenarios. The authors sought to incorporate the risk associated with placing supplies in an
area that might be affected by the disaster, as well as the = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = – 16 – inventory that is required to respond effectively to a
disaster. Prepositioning would be a desirable logistics strategy for disaster events such as
the 2004 Indian Ocean tsunami, the 2010 Haiti earthquake, and Hurricane Katrina because
it would shorten the lead-time to provide supplies. However, locating the supplies outside
the potential disaster impact zones would be necessary, and the investment in such
inventories could be large. The feasibility of maintaining large stocks of food, water, and
other emergency supplies for a long period of time in countries that are poor and have high
levels of corruption should also be considered; if the stores of prepositioned stocks cannot
be secured, then prepositioning is ineffective. Prepositioning vaccines, antibiotics, and
antidotes is desirable when the biological or chemical agent to be combated is stable and
not mutating. The key questions of interest are where, exactly, to position the stocks, and
who shall receive treatments. When it is impracticable to preposition supplies well in
advance of a disaster, it may be desirable for excess production capacity to be obtained
through capital planning, contracting, or collaboration so that capacity itself is
“prepositioned” to respond in the time of need. In cases of an influenza epidemic, for
example, it is not known well in advance which strain might be dominant and, therefore,
excess production capacity has been established at the national level to produce the right
vaccine when needed. In cases where it may be economically infeasible to preposition
supplies, it may still be possible to arrange for excess production or distribution capacity to
be established in order to support a rapid, or “surge,” response, which we discuss later in
this section. B. Proactive Deployment An alternative to prepositioning is the early
deployment of assets in advance of a local government request. For example, as federal
government officials see a hurricane approaching the Gulf of Mexico, they could mobilize
food, water, and temporary shelters and stage them close to, but not in, the expected
disaster zone so that when these supplies are needed, the lead-time necessary to deliver
them is reduced (see Figure 6). = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = – 17 –
Supply Warehouse Days until landfall 1 2 3 4 5 Figure 6. An Example of Proactive
Deployment of Supplies in Advance of a Hurricane It was known that Hurricane Katrina
might make landfall in New Orleans days in advance of the disaster, and this offered time for
the proactive deployment of supplies. Unfortunately, public authorities tended to be
reactive rather than proactive and did not effectively preposition medical supplies prior to
the hurricane’s landfall (U.S. House of Representatives, 2006). Another problem is related to
displaced persons. Companies may take care of the shortage of private goods but cannot
adequately manage or deal with the shortage of public goods such as shelters for the
displaced population. C. Phased Deployment Phased deployment of assets refers to timing
the delivery of inventory to a disaster area as it is needed and in the quantity in which it is

12. needed. This disaster response is analogous to “just in time” inventory control practiced by
commercial manufacturers and has the advantage of not committing excess inventory to a
specific region before knowing precise types and quantities of supplies needed. = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = – 18 – Phased deployment also prevents the disaster zone
from being inundated or saturated with inbound materiel that might otherwise reduce the
overall effectiveness of the disaster response due to inadequate infrastructure or limitations
in personnel, handling equipment, storage space, or some combination of all three.
Following the earthquake in Haiti in 2010, the lack of runway capacity, as well as
equipment, slowed the movement of supplies and specialized personnel such as physicians,
nurses, and search and rescue teams. Additionally, there were capacity limitations at the
ports, in terms of the number of containers that could be processed and the amount of
available dry warehouse space (see Figure 7). It was undesirable to push supplies into the
area because the ports were not capable of handling the flow of materiel. Max cargo per
vessel: 200 TEUs 7,000 MTs bulk/break bulk Warehouse capacity: 13,000 MTs Max cargo
per vessel: 400 TEUs 15,000 MTs bulk/break bulk Figure 7. Limited Port and Warehouse
Capacity May Necessitate Phased Deployment After the tsunami in the Indian Ocean, there
were enough supplies donated by the world’s richest countries, but there was only one
airstrip and one forklift in Banda Aceh, the regional capital of Aceh, Indonesia. When
disaster strikes an area = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = – 19 – with
limited port capacity, the phased deployment of supplies is not only prudent, but necessary,
in order to prevent the cessation of the flow of supplies. D. Surge Capacity A surge in
transportation of manpower and equipment from locations outside the disaster area is a
final alternative that, rather than relying on prepositioned physical inventory, plans for
excess capacity to deliver personnel and materiel in case of an emergency; in this instance,
the “prepositioning” is with respect to capacity rather than inventory. Figure 8 illustrates an
example where there is surge capacity reserved at specific locations, labeled “Supply
Warehouse,” outside of an anticipated disaster zone. In this instance the disaster is a
hurricane that has or will very soon make landfall. Surge capacity to distribute resources
from these warehouses that lie outside the anticipated disaster impact area may be utilized
to respond quickly while avoiding the risk of staging goods inside the potentially affected
area. Supply Warehouse Supply Warehouse Supply Warehouse Figure 8. Surge of Supplies
From Regional Warehouses in Response to a Disaster = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = – 20 – VI. Conclusion Localized, slow-onset natural disasters
are at one end of the spectrum with respect to the level of difficulty for humanitarian
logistics whereas dispersed, sudden-onset disasters are at the other. We base our policy
models on the classification of disasters. Disasters that are classified as slow onset provide
time for humanitarian logisticians to plan and prepare for relief operations. A disaster that
strikes suddenly can pose difficulties for response since no organization—military or
humanitarian— can fully prepare for every need that emerges during such an event.
However, prepositioning strategies, such as asset placement, resource allocation,

13. management of disaster relief inventory, and location of such warehouses may help. It is
clear that whether the disaster is localized or dispersed over a large geographical area
dictates the level of difficulty involved in disaster response. To assist policy-makers in their
understanding and decision-making, Figure 9 illustrates which logistics strategies are very
desirable, desirable, or undesirable, when considering the four disaster classifications. The
fully darkened circles indicate that a strategy is very desirable for a particular disaster type.
A partially darkened circle indicates that a strategy is desirable for a particular disaster
type, and an unfilled or hollow circle indicates that the strategy is undesirable for a
particular disaster type. Studying the exemplars of the disasters leads us to one conclusion:
in all the disasters, slow or sudden onset and localized or dispersed, there is likely to be
some type of prepositioning of supplies, but that does not mean this is the most desirable
policy because prepositioning is always costly. Prepositioning may also be difficult for
policy-makers to justify since investments in prepositioned stocks cannot show an
immediate return. Additionally, it is difficult to estimate which supplies to stockpile, as well
as how much will be needed or can be reasonably afforded. Therefore, we propose that
prepositioning is a very desirable policy for sudden-onset disasters (Classifications I and IV)
where logistics = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = – 21 –
transportation response lead-times exceed the time in which the supplies are most needed
following a disaster (see Figure 9). Prepositioning is desirable in those cases where the
disaster may be localized and slow (such as in a hurricane zone) or when the disaster is
dispersed and slow, such as a pandemic. Critical supplies that are prepositioned in likely
disaster zones or in those areas where they will most likely be needed (such as high-density
population centers) will require fewer transportation assets to move those supplies when
the disaster strikes, and the leadtime is reduced between the time needed and the time they
are available. However, in cases of a dispersed, slow-onset disaster, it might be cost
prohibitive to preposition large quantities of supplies over broad geographic areas.
Therefore, we propose that prepositioning is a somewhat desirable policy for Classification
IV (dispersed and slow). In case of Classification IV, localized but sudden, it may not be that
cost prohibitive to preposition since the disaster is anticipated to be contained, and the
faster speed of onset deems it critical to reach the affected region due to time sensitivity.
Thus, when the transportation lead-time or time necessary to increase the capacity is in
excess of the anticipated need, prepositioning may be the suitable strategy. Prepositioning
will also help since transportation means can be spared for use after the disaster, due to
critical and time-sensitive issues in the affected area and the community. We propose that
proactive deployment is the most desirable policy that should be implemented for slow-
onset disasters (Classifications II and III). Slowonset disasters allow for planning and
response and, therefore, allow for authorities and agencies to deploy resources in
anticipation of a disaster, rather than waiting for the request from the potential impact area.
Advanced knowledge of the location of a disaster allows the use of proactive deployment,
whether the disaster area is localized or dispersed. Proactive deployment is particularly
desirable when it is anticipated that the affected region will be unable to mitigate the effects
of a disaster. The director of the Federal Emergency Management Agency (FEMA) recently

14. stated that the federal government should be more proactive in its approach to an imminent
disaster and not wait for a local request for help (The White House, 2011). In the = =
^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v=
k^s^i=mlpqdo^ar^qb=p`elli= = – 22 – case of sudden-onset disasters (Classifications I and
IV), proactive deployment is likely to be less effective, simply because there is not ample
lead-time to place resources in advance of the disaster event. However, in those instances
where there are disasters that are seasonal or imminent, proactive deployment may be both
an efficient and effective means of mitigating adverse impacts. Both of the policies
discussed, prepositioning and proactive deployment, assume that there are resources or
capacity to store supplies, and that personnel are available to distribute the supplies during
the time of need. However, if there are capacity constraints for receiving the necessary
supplies, phased deployment may be a better strategy for getting supplies to the disaster
area. When the needs in the disaster area are unknown or emerging, a phased deployment
strategy may be desirable because supplies that are not needed or are in sufficient
quantities will not be sent to the area; as time passes, the needs in the disaster area become
more clear, and better information can be used to select the right supplies in the
appropriate quantity. Surge is the last resort policy when prepositioning or proactive
deployment is not feasible or affordable. If one takes into account just the cost, this is not
the policy choice for slow-onset disasters. However, this is the most likely policy for
sudden-onset disasters, whether localized or dispersed. This is especially true if there is
inadequate capacity for response and the last resort is surging the capacity for supplies and
services. = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = – 23 –
Logistics Strategy Surge Phased Deployment Proactive Deployment Prepositioning Disaster
Category I II III IV Dispersed & Localized & Localized & Dispersed Sudden Sudden Slow &
Slow Undesirable Disaster Classification Desirable Very Desirable Figure 9. Proposed
Policies = = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã=
do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = – 24 –
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do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= k^s^i=mlpqdo^ar^qb=p`elli= = – 28 – 2003
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www.acquisitionresearch.net Relief Supply Chain Management for Disasters: Humanitarian
Aid and Emergency Logistics Gyöngyi Kovács HUMLOG Institute, Hanken School of
Economics, Finland Karen M. Spens HUMLOG Institute, Hanken School of Economics,
Finland Senior Editorial Director: Director of Book Publications: Editorial Director:

18. Acquisitions Editor: Development Editor: Production Editor: Typesetters: Print
Coordinator: Cover Design: Kristin Klinger Julia Mosemann Lindsay Johnston Erika Carter
Joel Gamon Sean Woznicki Natalie Pronio, Jennifer Romanchak, Milan Vracarich, Jr. Jamie
Snavely Nick Newcomer Published in the United States of America by Business Science
Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA 17033 Tel: 717-
533-8845 Fax: 717-533-8661 E-mail: cust@igi-global.com Web site: http://www.igi-
global.com Copyright © 2012 by IGI Global. All rights reserved. No part of this publication
may be reproduced, stored or distributed in any form or by any means, electronic or
mechanical, including photocopying, without written permission from the publisher.
Product or company names used in this set are for identification purposes only. Inclusion of
the names of the products or companies does not indicate a claim of ownership by IGI
Global of the trademark or registered trademark. Library of Congress Cataloging-in-
Publication Data Relief supply chain management for disasters: humanitarian aid and
emergency logistics / Gyöngyi Kovács and Karen M. Spens, editors. p. cm. Includes
bibliographical references and index. Summary: “This book furthers the scholarly
understanding of SCM in disaster relief, particularly establishing the central role of logistics
in averting and limiting unnecessary hardships”–Provided by publisher. ISBN 978-1-60960-
824-8 (hbk.) — ISBN 978-1-60960-825-5 (ebook) — ISBN 9781-60960-826-2 (print &
perpetual access) 1. Disaster relief. 2. Humanitarian assistance. 3. Logistics. I. Kovacs,
Gyongi, 1977- II. Spens, Karen M., 1963HV553.R373 2011 363.34’80687–dc22 2011015748
British Cataloguing in Publication Data A Cataloguing in Publication record for this book is
available from the British Library. All work contributed to this book is new, previously-
unpublished material. The views expressed in this book are those of the authors, but not
necessarily of the publisher. Editorial Advisory Board Ruth Banomyong, Thammasat
University, Thailand Anthony Beresford, Cardiff University, UK Susanne Hertz, Jönköping
International Business School, Sweden Marianne Jahre, Lund University, Sweden Paul
Larson, University of Manitoba, Canada Tore Listou, Norwegian Defence Command and Staff
College, Norway Peter Schmitz, CSIR, South Africa Peter Tatham, Cranfield University, UK
List of Reviewers Ruth Banomyong, Thammasat University, Thailand Elisabeth Barber,
University of New South Wales, Australia Ira Haavisto, Hanken School of Economics, Finland
Graham Heaslip, National University of Ireland, Maynooth, Ireland Paul Larson,University of
Manitoba, Canada Aristides Matopoulos, University of Macedonia, Greece Stephen Pettit,
Cardiff Business School, UK Joseph Sarkis, Clark University, USA Peter Schmitz, CSIR, South
Africa Per Skoglund, Jönköping International Business School, Sweden Peter
Tathaml,Cranfield University, UK David Taylor, Cranfield University, UK Rolando Tomasini,
Hanken School of Economics, Finland Y-C J Wu, National Kaohsiung First University of
Science and Technology, Taiwan Table of Contents
Foreword…………………………………………………………………………………………………………………………
…… xi
Preface……………………………………………………………………………………………………………………………
……xii Chapter 1 Strategic Partners and Strange Bedfellows: Relationship Building in the
Relief Supply Chain…………. 1 Paul D. Larson, University of Manitoba, Canada Chapter 2
Humanitarian Partnerships ‒ Drivers, Facilitators, and Components: The Case of Non-Food

19. Item Distribution in
Sudan…………………………………………………………………………………………………………….. 16 Rolando
M. Tomasini, Hanken School of Economics, Finland Chapter 3 Relief Supply Chain Planning:
Insights from Thailand………………………………………………………………. 31 Ruth Banomyong,
Thammasat University, Thailand Apichat Sodapang, Chiangmai University, Thailand Chapter
4 Humanitarian Aid Logistics: The Wenchuan and Haiti Earthquakes
Compared…………………………….. 45 Anthony Beresford, Cardiff University, UK Stephen Pettit,
Cardiff University, UK Chapter 5 The Application of Value Chain Analysis for the Evaluation
of Alternative Supply Chain Strategies for the Provision of Humanitarian Aid to
Africa…………………………………………………………. 68 David H. Taylor, Sheffield, UK Chapter 6
Designing Post-Disaster Supply Chains: Learning from Housing Reconstruction
Projects…………….. 90 Gyöngyi Kovács, HUMLOG Institute, Hanken School of Economics,
Finland Aristides Matopoulos, University of Macedonia, Greece Odran Hayes, European
Agency for Reconstruction, Ireland Chapter 7 Local Sourcing in Peacekeeping: A Case Study
of Swedish Military Sourcing……………………………. 103 Per Skoglund, Jönköping International
Business School, Sweden Susanne Hertz, Jönköping International Business School, Sweden
Chapter 8 Military Involvement in Humanitarian Supply
Chains……………………………………………………………… 123 Elizabeth Barber, University of New
South Wales, Australian Defence Force Academy, Australia Chapter 9 Challenges of Civil
Military Cooperation / Coordination in Humanitarian Relief……………………….. 147 Graham
Heaslip, National University of Ireland – Maynooth, Ireland Chapter 10 Developing and
Maintaining Trust in Hastily Formed Relief Networks……………………………………… 173 Peter
Tatham, Griffith University, Australia Gyöngyi Kovács, HUMLOG Institute, Hanken School of
Economics, Finland Chapter 11 A Study of Barriers to Greening the Relief Supply
Chain…………………………………………………………. 196 Joseph Sarkis, Clark University, USA
Karen M. Spens, HUMLOG Institute, Hanken School of Economics, Finland Gyöngyi Kovács,
HUMLOG Institute, Hanken School of Economics, Finland Chapter 12 Disaster Impact and
Country Logistics Performance……………………………………………………………….. 208 Ira Haavisto,
Hanken School of Economics, Finland Compilation of
References…………………………………………………………………………………………………. 225 About the
Contributors……………………………………………………………………………………………………… 244
Index…………………………………………………………………………………………………………………………………
. 249 Detailed Table of Contents
Foreword…………………………………………………………………………………………………………………………
…… xi
Preface……………………………………………………………………………………………………………………………
……xii Chapter 1 Strategic Partners and Strange Bedfellows: Relationship Building in the
Relief Supply Chain…………. 1 Paul D. Larson, University of Manitoba, Canada This chapter is
about relationship building in relief supply chains. Its primary purpose is to present and
discuss the author’s actor-based typology of humanitarian relationships. The framework
includes relationships among NGOs, as well as between NGOs and UN agencies, military
units, and business firms. Examples are used to explore unique issues in the various types of
relationships. One particular NGO, Airline Ambassadors International, is offered as an

20. example of an NGO that builds relationships with a wide variety of humanitarian actors. The
chapter also examines compatibility and complementarity of organizations across the three
phases of humanitarian work: preparation, response and recovery or development.
Research opportunities are discussed in the concluding comments. Chapter 2 Humanitarian
Partnerships ‒ Drivers, Facilitators, and Components: The Case of Non-Food Item
Distribution in
Sudan…………………………………………………………………………………………………………….. 16 Rolando
M. Tomasini, Hanken School of Economics, Finland Through the use of a case study this
chapter discusses the design of a partnership between humanitarian organizations to
understand what are the drivers, facilitators, and components of the partnership. This
research has been designed using a topical literature review and a case study. The practical
implications include a discussion and guidelines for designing partnerships under high
uncertainty and limited resources. Chapter 3 Relief Supply Chain Planning: Insights from
Thailand………………………………………………………………. 31 Ruth Banomyong, Thammasat
University, Thailand Apichat Sodapang, Chiangmai University, Thailand The purpose of this
chapter is to provide a framework for the development of relief supply chain systems. An
illustrative case study is presented in order to help relief supply chain decision makers in
their relief supply chain planning process. Developing simulation models to test proposed
relief supply chain response plans is much less risky than actually waiting for another
disaster to happen and test the proposed relief supply chain model in a real life situation.
The simulated outcome can then be used to refine the developed relief supply chain
response model. Chapter 4 Humanitarian Aid Logistics: The Wenchuan and Haiti
Earthquakes Compared…………………………….. 45 Anthony Beresford, Cardiff University, UK
Stephen Pettit, Cardiff University, UK This chapter contrasts the response to the Wenchuan
earthquake (May 2008) which took place in a landlocked region of China with that of the
January 2010 earthquake in Haiti, which as an island nation, theoretically easily accessible
to external aid provision via air or sea. In the initial period following the Wenchuan
earthquake, the response was wholly internal, as a detailed needs assessment was carried
out. Once the Chinese authorities had established the scale of response required,
international assistance was quickly allowed into the country. Several multimodal solutions
were devised to minimize the risk of supply breakdown. Haiti required substantial external
aid and logistics support, but severe organizational and infrastructural weaknesses
rendered the supply chain extremely vulnerable locally. This translated to a mismatch
between the volume of aid supplied and logistics capability, highlighting the importance of
‘last-mile’ distribution management. The two earthquakes posed extreme challenges to the
logistics operations, though both required a mix of military and non-military input into the
logistics response. Nonetheless, in each case the non-standard logistics solutions which
were devised broadly met the requirements for effective aid distribution in extreme
environments. Chapter 5 The Application of Value Chain Analysis for the Evaluation of
Alternative Supply Chain Strategies for the Provision of Humanitarian Aid to
Africa…………………………………………………………. 68 David H. Taylor, Sheffield, UK The study
reported in this chapter was commissioned in 2009 by the charity ‘Advance Aid’ in order to
provide an independent evaluation to compare conventional methods of supplying

21. humanitarian aid products to Africa from outside the continent, with a proposed model of
local manufacture and pre-positioned stocks. The evaluation was carried out using ‘value
chain analysis’ techniques based on ‘lean’ concepts to provide a strategic evaluation of
alternative supply models. The findings show that a system of local manufacturing and pre-
positioned stockholding would offer significant advantages over conventional humanitarian
supply chains in terms of responsiveness, risk of disruption and carbon footprint, and that
delivered costs would be similar to or significantly better than current non-African supply
options. Local manufacturing would also have important benefits in terms of creating
employment and economic growth, which in the long run would help African states to
mitigate and/or respond to future disasters and thus become less dependent on external
aid. Chapter 6 Designing Post-Disaster Supply Chains: Learning from Housing
Reconstruction Projects…………….. 90 Gyöngyi Kovács, HUMLOG Institute, Hanken School of
Economics, Finland Aristides Matopoulos, University of Macedonia, Greece Odran Hayes,
European Agency for Reconstruction, Ireland Post-disaster housing reconstruction projects
face several challenges. Resources and material supplies are often scarce, several and
different types of organizations are involved, and projects must be completed as quickly as
possible to foster recovery. Within this context, the chapter aims to increase the
understanding of relief supply chain design in reconstruction. In addition, the chapter is
introducing a community based and beneficiary perspective to relief supply chains by
evaluating the implications of local components for supply chain design in reconstruction.
This is achieved through the means of secondary data analysis based on the evaluation
reports of two major housing reconstruction projects that took place in Europe the last
decade. A comparative analysis of the organizational designs of these projects highlights the
ways in which users can be involved. The performance of reconstruction supply chains
seems to depend to a large extent on the way beneficiaries are integrated in supply chain
design impacting positively on the effectiveness of reconstruction supply chains. Chapter 7
Local Sourcing in Peacekeeping: A Case Study of Swedish Military
Sourcing……………………………. 103 Per Skoglund, Jönköping International Business School,
Sweden Susanne Hertz, Jönköping International Business School, Sweden This case study
explores the Swedish armed forces’ sourcing from local suppliers in the area of the
peacekeeping operation in Liberia. The paper discusses why, what, and how the Swedish
armed forces develop local sourcing. For the study, a theoretical framework was developed
with an industrial network perspective based on three cornerstones: supplier buyer
relation development, internationalization, and finally, souring and business development
in a war-torn country. The results of the study show that both implicit and explicit reasons
to source locally exist. Every operation is unique, and therefore the sourcing needs to be
tailored for each operation. Local sourcing was developed in the country based on existing
needs and when opportunities arose. Theoretically, new insights of differences between
business relations in military operations and normal business to business relations were
gained. Practically, this study illustrates the importance to develop and diversify sourcing in
international operations. Chapter 8 Military Involvement in Humanitarian Supply
Chains……………………………………………………………… 123 Elizabeth Barber, University of New
South Wales, Australian Defence Force Academy, Australia The purpose of this chapter is to

22. demonstrate the multitude of activities that military logisticians can provide throughout the
various stages in relief supply chains. Most military joint doctrine identifies humanitarian
assistance (HA) as one of the “Military Operations Other Than War” (MOOTW) that military
personnel are trained to undertake. Part of this HA involves contributing to humanitarian
supply chains and logistics management. The supply chain management processes, physical
flows, as well as associated information and financial systems form part of the military
contributions that play an important role in the relief supply chain. The main roles of the
military to relief supply chains include security and protection, distribution, and
engineering. Examples of these key contributions will be provided in this chapter. Chapter 9
Challenges of Civil Military Cooperation / Coordination in Humanitarian
Relief……………………….. 147 Graham Heaslip, National University of Ireland – Maynooth,
Ireland The term civil military coordination (CIMIC) suggests the seamless division of labor
between aid workers and international military forces. The media coverage from crises
such as New Orleans, Kosovo, the tsunami in Asia, Pakistan, Liberia, Sierra Leone, Chad ,and
more recently Haiti, showing humanitarian organizations distributing food and medicines
under the protection of military forces, or aid workers and military working together to
construct refugee camps, set up field hospitals, provide emergency water and sanitation, et
cetera, has heightened the expectation of a smooth interaction. Due to fundamental
differences between international military forces, humanitarian and development
organizations in terms of the principles and doctrines guiding their work, their agendas,
operating styles, and roles, the area of civil military coordination in disaster relief has
proven to be more difficult than other interagency relationships. This chapter will identify
the many factors that render integration and collaboration problematic between diverse
organizations, and especially so between civilian and military agencies. The chapter will
conclude with proposals to improve CIMIC within disaster relief. Chapter 10 Developing and
Maintaining Trust in Hastily Formed Relief Networks……………………………………… 173 Peter
Tatham, Griffith University, Australia Gyöngyi Kovács, HUMLOG Institute, Hanken School of
Economics, Finland Although there is a vast body of academic and practitioner literature
championing the importance of trust in long-term business relationships, relatively little
has been written which discusses the development and maintenance of trust in networks
that are formed at short notice and that often operate for a limited period of time. Some
models of trust and trusting behavior in such “hastily formed relief networks” (HFRN) do
exist , however, and the aim of this chapter is to consider the theoretical application of one
of the most prominent examples –known as “swift trust” – to a post-disaster humanitarian
logistics scenario. Presented from the perspective of a HFRN, the chapter presents a
discussion of the practical application of the swift trust model. Chapter 11 A Study of
Barriers to Greening the Relief Supply Chain…………………………………………………………. 196
Joseph Sarkis, Clark University, USA Karen M. Spens, HUMLOG Institute, Hanken School of
Economics, Finland Gyöngyi Kovács, HUMLOG Institute, Hanken School of Economics,
Finland Relief supply chain (SC) management is a relatively unexplored field. In this field,
practitioners have shown some interest in greening practices, but little practical or
academic literature exists to help provide insights into combining the two fields. Adoption
of green SC principles in the relief SC requires a systematic study of existing barriers in

23. order to remove these barriers and allow introduction of green practices. The aim of this
chapter is to explore barriers to implementation of green practices in the relief SC. Expert
opinions and literature from humanitarian logistics and green supply chain management
are used to establish a list of barriers and to propose a categorization of barriers. Further
research to evaluate the relationships and importance of these barrier factors is identified.
Chapter 12 Disaster Impact and Country Logistics
Performance……………………………………………………………….. 208 Ira Haavisto, Hanken School of
Economics, Finland The study seeks to answer the question whether a country’s logistics
performance has a correlation with the impacts of a disaster; impact being measured in
average amount of affected, the average amount of deaths, the average amount of injured in
a disaster, or the average amount of economic damage. This is a quantitative study where
the EM-DATs disaster data is analyzed through correlation analysis against the World
Bank’s logistics performance index (LPI). The findings do not show a significant relationship
between countries LPI and the average number of deaths or injured in a disaster. A positive
correlation between the variable LPI and the variable economic damage can be found. A
negative correlation between the LPI and the average amount of affected can be found for
countries with an average ranking LPI. Countries with low LPI and high disaster occurrence
are further identified. Findings encourage the identified countries to take into consideration
their logistics performance when planning and carrying out humanitarian response
operations. Results also encourage humanitarian organizations to pay attention to the
receiving countries’ logistics performance in planning and carrying out of humanitarian
response operations. Compilation of
References…………………………………………………………………………………………………. 225 About the
Contributors……………………………………………………………………………………………………… 244
Index…………………………………………………………………………………………………………………………………
. 249 xi Foreword For some years now, the major insurance and re-insurance companies
have been tracking the occurrence of natural disasters. The disturbing findings of all of
these analyses point to the fact that these events have been happening with significantly
greater frequency and severity in recent years. Graphed over a fifty year time-line, the rate
of increase appears to be almost exponential. Whatever the reasons for this increase, the
implication is clear: the need to develop a much higher level of capability for the provision
of relief and reconstruction will become ever more pressing. Underpinning the success of
any humanitarian aid and relief programme are logistics and supply chain processes that
agile and adaptive: agile in the sense that they can respond rapidly to unexpected events,
and adaptive in that they can be configured to meet the needs of specific situations and
contexts. Surprisingly, it is only recently that the need for higher levels of capability in the
practice of humanitarian logistics and supply chain management has been recognised. It
could be argued that the shortage of appropriate logistics management skills and
supporting infrastructure has meant that many aid and relief programmes in the past have
been less effective than they could have been. For this reason, it is opportune that this book
should be compiled and published at this particular time. In the last few years alone, a
tremendous amount of knowledge has been gained into how humanitarian logistics and
supply chain performance can be made much more effective by the application of new ideas

24. and techniques. The issues addressed by the various contributors to this book are critical to
the achievement of the goals of any humanitarian aid and relief programme. The breadth as
well as the depth of the analysis contained within these chapters is impressive, and together
they provide valuable insights into how current practice can be improved. The message to
be drawn from this is that whilst disasters and existential threats from a multitude of
sources will sadly always be with us, at least we can seek to learn how to mitigate their
consequences. Martin Christopher Cranfield University, UK Martin Christopher is an
Emeritus Professor of Marketing and Logistics at the Cranfield School of Management in the
UK. For many years Martin Christopher has been involved in teaching and researching new
ideas in logistics and supply chain management. He has published widely, and his book,
“Logistics and Supply Chain Management,” has become one of the most widely cited texts in
its field. As well as his Emeritus position at Cranfield, Martin Christopher is a Visiting
Professor at a number of leading Universities around the world. xii Preface INTRODUCTION
Relief supply chains are argued to be the most dynamic and agile supply chains, yet
research in this area of supply chain management (SCM) is scant. Relief SCM has recently
gained attention due to many natural and man-made disasters and the recognition of the
central role of logistics in responding to these. Relief supply chains (SC) constitute a
substantial industry that responds to over 500 disasters annually resultant in loss of 75 000
lives and affecting over 200 million people. SC costs are also argued to account for over 80%
of costs incurred in any disaster relief operation. Due to the fact that relief supply chains so
far have received little attention, there seems to be a gap that this book can fill. The
anthology also presents a continuation of a doctoral course in Supply Chain Management for
Disaster Relief given at Hanken School of Economics in the fall of 2009, as many of the
chapters are written by participants, as well as core faculty of this doctoral course. The book
is therefore a collection of chapters by researchers, both junior and senior, in the field of
humanitarian logistics and relief supply chain management. The chapters were, however,
submitted after a broader call for papers and were thereafter peer-reviewed, ending up as a
collection of chapters that were accepted. The interest for courses in this field has continued
to grow since; therefore, the hope is that this anthology will provide a platform for creating
and giving even more courses in the field. More broadly, the anthology is part of a large
research project funded by the Academy of Finland, called Relief Supply Chain Management.
The overall aim of the anthology Relief Supply Chain Management for Disasters:
Humanitarian Aid and Emergency Logistics is to further the understanding of SCM in
disaster relief. As the first book in this field, the hope is that it will serve scholarly thought
as well as provide a textbook for courses introducing this new and exciting area in the field
of logistics. BACKGROUND Supply chain management (SCM) research has developed rapidly
in the past two decades, but is still “a discipline in the early stages of evolution” (Gibson et
al., 2005, p.17). The following most commonly used definition of SCM is provided by the
Council of Supply Chain Management Professionals (CSCMP): ‘Supply Chain Management
encompasses the planning and management of all activities involved in sourcing and
procurement, conversion, and all Logistics Management activities. Importantly, it also
includes coordination and collaboration with channel partners, which can be suppliers,
intermediaries, third-party service providers, and customers. In essence, Supply Chain

25. Management integrates supply and demand management within and across companies’
(CSCMP, 2006). xiii Traditional streams of SCM literature encompass different topics,
ranging from supply chain modelling and optimisation (Lee et al., 2004; Svensson, 2003) to
supply chain performance measurement (Bagchi et al., 2005; Beamon, 1999), supply chain
processes (Croxton et al., 2001; Lambert et al., 1998), portfolio models in SCM (Fisher,
1997), and supply chain collaboration and integration (Barratt, 2004; Fawcett & Magnan,
2002; Min et al., 2005). Portfolio models in SCM discuss different types of supply chains,
contrasting supply chains for functional products with a focus on cost efficiencies to supply
chains for innovative products with a focus on responsiveness to market dynamics (Fisher,
1997). But while this portfolio thinking is at the core of SCM, literature has traditionally
focused on efficient (or “lean”) supply chains only (Lee, 2004). Therefore, the current trend
in SCM literature is towards discussing more innovative and responsive – or “agile” – supply
chains that operate in a highly dynamic environment (Christopher et al., 2006; Towill and
Christopher, 2002). Relief supply chain management has recently gained attention due to a
number of natural and manmade disasters and the recognition of the central role of logistics
in responding to these. Oloruntoba and Gray (2006, p.117) argue that relief supply chains
are “clearly unpredictable, turbulent, and requiring flexibility.” In essence, relief supply
chains can be seen as highly dynamic, innovative, and agile (Oloruntoba & Gray, 2006; van
Wassenhove, 2006), and hereby it can be argued that even (traditional) commercial supply
chains can learn from the high flexibility of relief supply chains (Sowinski, 2003). Especially
in sudden-onset disasters, relief supply chains have to be deployed in situations with a
destabilised infrastructure and with very limited knowledge about the situation at hand
(Beamon, 2004; Long & Wood, 1995; Tomasini & van Wassenhove, 2004). Relief supply
chain management, although arguably much different from business logistics, does also
show similarities. Therefore the definitions,techniques, and approaches used within
business logistics can often be transferred or altered so they fit the purpose of their context.
Notwithstanding the fact that the ultimate goals and purpose of conducting the logistical
activities are different, still many of the definitions relating to the field can be extracted
from current definitions found in the business context. In the following paragraphs, we are
providing an overview of the definitions that the book adheres to. The definitions were
provided to the authors of the chapters at the outset and have been used accordingly
throughout the book. Admittedly, as in the field of logistics, defining concepts is a difficult
task, so authors often tend to use definitions or even define concepts in a way that fits their
purpose. The chapters therefore are the sole responsibility of the authors and do reflect
their views on particular issues and concepts, however, we argue that the definitions
provided in the end of our preface seemingly have gained acceptance among the authors of
the chapters of this book. This anthology is designed to bring together theoretical
frameworks and the latest findings from research with their discussion in particular cases.
Besides a number of frameworks – of types of relationships in the relief supply chain (ch.1),
relief logistics development (ch.3), value chain analysis (ch.5), civil-military co-operation
(ch.9), and trust models in disaster relief (ch.10) – cases range from logistical partnerships
in the Sudan (ch.2), to a comparison of relief supply chains in different earthquakes (Haiti
vs. Wenchuan, ch.4), to local sourcing in Liberia (ch.7), and reconstruction in the Kosovo

26. and the Former Yugoslav Republic of Macedonia (ch.6). This way, insights from theory and
practice are combined. The anthology ends with a chapter on one of the most recent areas
humanitarian logistics research and practice has embraced: questions of sustainability, and
most importantly, the issue of greening the relief supply chain (ch.11). xiv THE
COLLECTION OF CHAPTERS: A SHORT INTRODUCTION In the foreword, Martin
Christopher, Emeritus Professor from Cranfield University, discusses the importance of the
topic more broadly. Professor Christopher is undeniably one of the most well-known
authors and scholars in the field of logistics who has also recently embraced the field of
humanitarian logistics through co-editing a book with Peter Tatham. We hope these two
books will complement each other. In the preface, the editors of the book, Gyöngyi Kovács
and Karen M. Spens, outline the field, provide some key definitions, and provide an
overview of the chapters included. In the first chapter by Paul D. Larson from University of
Manitoba, relationship building in humanitarian supply chains is discussed. The primary
purpose of the chapter, named “Strategic Partners and Strange Bedfellows: Relationship
Building in the Relief Supply Chain,” is to present and discuss the author’s actor-based
typology of humanitarian relationships. The framework includes relationships among NGOs,
as well as between NGOs and UN agencies, military units, and business firms. Examples are
used to explore unique issues in the various types of relationships. One particular NGO,
Airline Ambassadors International, is offered as an example of an NGO that builds
relationships with a wide variety of humanitarian actors. The chapter also examines
compatibility and complementarity of organizations across the three phases of
humanitarian work: preparation, response, and recovery or development. Research
opportunities are discussed in the concluding comments. The chapter serves as a good
introduction to following ones that further discuss some of the types of relationships
outlined here. The next chapter takes up the question of partnerships in the relief supply
chain. Rolando M. Tomasini, Hanken School of Economics, Finland, in his chapter,
“Humanitarian Partnerships – Drivers, Facilitators, and Components: The Case of Non-Food
Item Distribution in Sudan,” uses a case study to discuss the design of partnerships between
humanitarian organizations in order to understand the drivers, facilitators and components,
of a partnership. The research was designed using a topical literature review and a case
study. The practical implications include discussion and guidelines for designing
partnerships under high uncertainty and limited resources. This is followed by another case
study, this time of disaster preparedness and management in Thailand. At the same time,
Ruth Banomyong from Thammasat University, Thailand and Apichat Sodapang from
Chiangmai University, Thailand present a more general framework for relief supply chain
management in the third chapter. Their “Relief Supply Chain Planning: Insights from
Thailand” builds on and evaluates a general framework for humanitarian logistics. The
chapter highlights the need for planning and preparedness prior to a disaster. Further cases
are presented and contrasted in chapter 4, “Humanitarian Aid Logistics: The Wenchuan and
Haiti Earthquakes Compared,” by Anthony Beresford and Stephen Pettit from Cardiff
University, UK. The comparison of a similar disaster in different environments helps to
highlight common features in humanitarian logistics and set these apart from contextual
factors such as infrastructural weaknesses. Access to a disaster area is contrasted between

27. islands and landlocked countries. Furthermore, as in chapter one, the cases show the
importance of co-ordination in the logistics response of humanitarian and military
organizations. Chapter 5, called “The Application of Value Chain Analysis for the Evaluation
of Alternative Supply Chain Strategies for the Provision of Humanitarian Aid to Africa,” is a
prime example of presenting a framework and discussing it on a particular case. David H.
Taylor, from Sheffield, UK is an expert in value chain analysis. The study reported in this
chapter was commissioned in 2009 by the charity “Advance Aid” in order to provide an
independent evaluation to compare conventional methods of sup- xv plying humanitarian
aid products to Africa from outside the continent, with a proposed model of local
manufacturing and pre-positioned stocks. The findings show that a system of locally
manufactured and pre-positioned stockholding would offer significant advantages over
conventional relief supply chains in terms of responsiveness, risk of disruption, and carbon
footprint, and that delivered costs would be similar to or significantly better than current
non-African supply options. Local manufacture would also have imp…