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Drivers of Government Restrictions on Humanitarian Supply Chains: An
Exploratory Study1
Nathan Kunz,2 University of North Florida, Jacksonville, United States
Gerald Reiner, Alpen-Adria-Universitat Klagenfurt, Klagenfurt, Austria
ABSTRACT
Purpose
Foreign governments do not always welcome international humanitarian organizations
responding to a disaster in their country. Many governments even impose restrictions on
humanitarian supply chains through import barriers, travel restrictions or excessive
bureaucracy. We analyze these restrictions and try to identify the government characteristics
that best explain the tendency to impose such restrictions.
Design/methodology/approach
Through a multiple case study among four international humanitarian organizations we identify
and analyze the restrictions imposed on humanitarian supply chains in 143 different programs.
We compare the average number of restrictions per country with different governmental and
socio-economic situational factors.
Findings
We find that state fragility, a combination of government ineffectiveness and illegitimacy, is
the characteristic that best explains the tendency of a government to impose restrictions on
humanitarian supply chains.
Practical implications
Knowing that fragile states tend to impose a high number of restrictions helps humanitarian
organizations to prepare adequately before entering a country with a fragile government. The
1 Accepted manuscript, please cite as: Kunz, N. & Reiner, G. (2016), "Drivers of Government Restrictions on
Humanitarian Supply Chains: An Exploratory Study", Journal of Humanitarian Logistics and Supply Chain
Management, Vol. 6, No.3, pp. 329-351.
This work was partially supported by the Swiss National Science Foundation (FNS grant 143578).
An early version of this paper was presented at 20th EurOMA Conference 2013, Dublin, Ireland.
2 Corresponding author
2
organization can for example anticipate possible concerns and establish trust with the
government. Commercial companies starting to do business in such country can learn from this
knowledge.
Originality/value
Multiple studies have mentioned the strong impact of governments on humanitarian supply
chains, but no paper has yet analyzed this problem in detail. Our paper is the first to identify
the characteristics that explain the number of restrictions governments impose on humanitarian
supply chains, and what humanitarian organizations can do to address them.
Keywords: Government Restrictions, Customs Clearance, Humanitarian Logistics
Article Classification: Case study
1. Introduction
When a large scale disaster hits an area, local communities cannot cope alone with the
consequences of the catastrophe. In countries with enough financial resources and disaster
management capabilities, the government takes over the disaster assistance through its
emergency management organization (e.g., Federal Emergency Management Agency in the
USA). When government resources are scarce, such emergency management organizations are
inexistent or underfunded. In such case, the disaster response effort relies on international
humanitarian organizations that bring their assistance to help affected communities. According
to humanitarian principles, these organizations have to serve all affected people in the same
way, without consideration of race, religion or political affiliation. In case of war for example,
humanitarian organizations are required to be neutral and cannot take a stance in the conflict.
Some governments do not agree with these principles, and therefore do not appreciate the
actions of humanitarian organizations. Allowing humanitarian organizations to operate in their
country may also be seen as an implicit recognition of an ongoing crisis, which governments
do not necessarily want.
3
These reasons explain why governments do not always welcome humanitarian
organizations, even when they are not able to help their own population. As a result, some
governments impose severe restrictions on the activities of these humanitarian organizations.
Some countries impose import barriers that seriously affect humanitarian supply chains. Other
governments even deny access to humanitarian organizations, as in Myanmar following
Cyclone Nargis in 2008 (Seekins, 2009; Day et al., 2012).
This paper intends to analyze the problem of governmental restrictions on humanitarian
supply chains based on empirical evidence, and to find what characteristics of a country explain
the tendency to impose such restrictions. Based on these insights, we discuss a number of
implications for humanitarian organizations preparing to respond to a disaster. Through a case
study among four humanitarian organizations we collect data from 18 countries. We identify
and analyze governmental restrictions affecting humanitarian supply chains in these countries.
We compare the number of restrictions in each country with the characteristics of the
government. In particular, we aim to answer the following research questions: (i) What is the
relationship between characteristics of countries and the number of restrictions their
governments impose on humanitarian supply chains? (ii) What are the implications of these
findings for humanitarian organizations?
This paper is organized as follows. In Section 2, we provide an overview of the literature on
government restrictions on humanitarian supply chains. In Section 3, we describe how we use
our case study data to identify the number of restrictions found in each country. In Section 4,
we describe the restrictions we found. In Section 5 we develop propositions that compare the
number of restrictions with several governmental and socio-economic factors in each country.
We discuss these findings in Section 6, and present a number of implications for research and
practice in Section 7. We conclude the paper in Section 8.
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2. Literature review
Natural or man-made disasters affect the local communities’ ability to assist victims of the
disaster. These communities therefore often rely on the external assistance provided by
humanitarian organizations (Holguín-Veras et al., 2012). This external assistance is generally
welcomed by host governments, but some countries are reluctant and react by imposing
restrictions on these organizations. In this section, we analyze what the literature says about the
complex interaction between host governments and humanitarian organizations. We first
identify ways host governments help humanitarian organizations in their efforts. Then we
present examples of how governments restrict the activities of humanitarian supply chains. We
describe what the literature suggests as possible motivations for imposing such restrictions.
Finally, we look into what the commercial supply chain literature says on these restrictions.
Host governments play an important and positive role in humanitarian supply chains. They
may for example coordinate activities of humanitarian organizations (Tomasini and Van
Wassenhove, 2003; Balcik et al., 2010), support the humanitarian effort through the military
forces (Kovács and Spens, 2007), or regulate NGOs in order to increase their professionalism
(Abbey, 2008). Governments often facilitate the imports of disaster response supplies by
declaring a state of emergency and temporarily lifting long customs clearance processes (Kunz
and Gold, 2015). Similarly, governments can also regulate and limit the convergence of self-
initiated, often unprofessional, organizations to the disaster affected area (Day et al., 2012).
Finally, governments have the power to limit the flow of unsolicited donations that strongly
disturb humanitarian supply chains by creating unnecessary bottlenecks (Holguín-Veras et al.,
2012).
The assistance of humanitarian organizations is however not always welcomed by governments
of affected countries. In such cases, governments impose restrictions on humanitarian
organizations. The important impact of these restrictions has been recognized by several authors
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so far (e.g., Bratton, 1989; Long and Wood, 1995; Kovács and Spens, 2009; Seekins, 2009;
Chang et al., 2010; Kovács and Spens, 2011; Day et al., 2012; Kunz and Reiner, 2012; Kunz et
al., 2014; L’Hermitte et al., 2014), but was never studied in depth. Governments sometimes
refuse humanitarian aid, or ban humanitarian workers from entering the country (Seekins, 2009;
Balcik et al., 2010; Day et al., 2012). Restrictions on humanitarian aid can also occur when
there is no government and the area is controlled by rebels. The Al-Shabaab rebel group, which
controlled a large part of the Somali territory during the 2011 famine, did for example not allow
humanitarian organizations to access the populations and distribute food to the victims
(Menkhaus, 2012; L’Hermitte et al., 2014).
Corruption is another form of government restriction impacting humanitarian organizations.
Corruption is endemic in some countries, and any individual, business or humanitarian
organization is expected to bribe officials for government related authorizations it might need.
Corruption diverts funding from populations in need to governmental officials, and has a
negative influence on donors (Altay, 2008; Maxwell et al., 2012). Humanitarian organizations
do generally not pay any bribes. As a result they experience substantial delays and
complications in getting the required authorizations from government entities. Unsurprisingly,
corruption is an even more important problem in emergency situations, because humanitarian
organizations operate under strong time pressure (Schultz and Søreide, 2008).
Host governments often apply restrictions on humanitarian supply chains. They do for
example restrain imports of humanitarian supplies through tariff and non-tariff barriers. Such
import barriers strongly affect the effectiveness and efficiency of humanitarian supply chains,
either by limiting the organizations’ ability to prepare for disasters in a country (Kovács and
Spens, 2009; Richardson et al., 2016), by creating delivery delays (Van Wassenhove, 2006;
Kunz et al., 2014) or by preventing humanitarian supplies from being delivered (Long and
Wood, 1995). In most cases, these restrictions will require the organization to find creatives
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ways to adapt to the restrictions (Bennett, 2003; Kunz and Gold, 2015). In some extreme cases,
these restrictions may even force humanitarian organizations to leave a country (Kunz and
Gold, 2015), or prevent them from delivering critically needed food supplies to disaster victims
(Menkhaus, 2012; Merminod et al., 2014).
Some restrictions on humanitarian supply chains are more difficult to identify, as they are
not based on a specific regulation but are rather a consequence of extremely bureaucratic
procedures. Even though humanitarian organizations usually benefit from duty-free imports of
vehicles, they must however register them through a highly bureaucratic procedure which may
take between three and six months (Pedraza-Martinez and Van Wassenhove, 2013).
There are also situations in which governments do not purposely restrict activities of
humanitarian organizations, but are simply not willing to facilitate the humanitarian work by
adapting their regulations (Akhtar et al., 2012). For example, Chang et al. (2010) found that
market regulation imposed by the Chinese government on building supplies created
disincentives for companies to engage in reconstruction activities after a disaster. Balcik et al.
(2010) note that dysfunctional governments do not often play their coordinating role during
disasters, which leads to an unclear definition of the roles of the different humanitarian
organizations.
There are different motivations of host governments to impose restrictions on humanitarian
organizations. Some governments or rebel groups use famine as a weapon against their
population, and therefore try to control the distribution of food (Murray, 2005). Driven by fears
of foreign influence, governments may prevent humanitarian organizations from accessing the
affected areas (Long and Wood, 1995; Bennett, 2003; Seekins, 2009; Day et al., 2012). Based
on these fears, governments sometimes restrict the import of goods that are considered as
threatening to the government (e.g., satellite phones, armored vehicles). Governments may also
impose duties on humanitarian supplies to generate income, as humanitarian aid spending often
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represents a large source of revenue for these countries (Abuzeid, 2009). Some government
restrictions are motivated by a legitimate willingness to protect the population (e.g., ban on
imports of genetically modified maize during the 2002 hunger crisis in Southern Africa, see
Bennett, 2003). The government may also want to protect its local producers by preventing
humanitarian supplies from being imported (Kunz and Gold, 2015).
One could ask if the problem of government restrictions is specific to the humanitarian
world, or if companies face similar issues when working in some developing countries. In order
to answer this question, we have looked at the literature on commercial supply chains operating
in emerging countries. Davarzani et al. (2015) evoke the high risks of supply chain disruptions
caused by political and governmental risks. Similarly, Kamann and Van Nieulande (2010)
mention supply chain risks related to political instability and unforeseen power shifts in
emerging countries. They also point to the longer lead times observed when delivering to
emerging countries due to administrative requirements imposed by the government on the
import process. Mann (2012) recognizes customs duties and nontariff barriers as impediments
to efficient global supply chain management. Sanderson (2001) demonstrates that government
regulations can strongly influence the power dynamic of a buyer-supplier relationships, and
some governments use this tool to protect their own industries. This problem is particularly
relevant for supply chains in emerging countries, as these governments are increasingly using
such regulations to protect their industry (Wang et al., 2011). The underdeveloped regulatory
infrastructure and lack of central coordination in some emerging countries is another challenge
for supply chain management. In some countries for example up to 10 different government
ministries may be involved in the establishment of standards (Roth et al., 2008). This short
overview demonstrates that commercial supply chains in emerging countries face similar
challenges than humanitarian supply chains.
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While several papers mention the problem of government restrictions imposed on
humanitarian and commercial supply chains, to the best of our knowledge no study has yet
investigated which characteristics of a government explain these restrictions. This is the gap we
intend to fill with this paper, since this knowledge will help humanitarian organizations when
preparing to respond to a disaster in a country. Understanding government restrictions before
entering a country and preparing to address them can significantly decrease the disaster
response time (Kunz et al., 2014).
3. Methodology
Selection of Methodology
The motivation for studying these research questions came from a previous research work with
a humanitarian organization (Schodl et al., 2010). The initial impressions from one organization
were however by no way sufficient to develop useful insights, and we had to collect additional
empirical data in order to confirm our initial findings. Given the lack of previous research
focusing on this topic, we had to take an exploratory approach. Case study research is the most
adequate methodology for such approach for multiple reasons. First, it allows identifying
unexpected variables and relationships (Voss et al., 2002). Second, the case study research
methodology is particularly well fitted for analyzing highly complex subjects (Stuart et al.,
2002), such as the one of governmental restrictions which include several actors (governments,
donors, humanitarian organizations) interacting in different activities (customs clearance,
advocacy, fundraising, etc.). Third, given this high level of complexity and numerous
interactions, this topic cannot be studied out of its context and therefore has to be investigated
in its natural setting. Case study research methodology allows such in-context analysis (Yin,
2009), in opposition to axiomatic research for example where the problem under study has to
be isolated and taken out of its context. Finally, case study research allows to develop theory
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through observation of actual practices (Meredith, 1998), which is particularly useful in an
explorative phase where the relevant theory is not yet known.
Based on the reasons presented above, we found that case study research was the optimal
method for our study, and therefore decided to conduct an exploratory multiple case study
among four humanitarian organizations.
Sampling
The unit of analysis is a humanitarian organization, including its headquarters and all programs
it runs worldwide. We chose our case organizations following a polar type theoretical sampling
mechanism, where cases are selected not for statistical reasons but for their ability to fill
different theoretical categories (Eisenhardt, 1989). We first identified six humanitarian
organizations that are headquartered in Switzerland (in order to facilitate interviews at
headquarters and because this country hosts multiple humanitarian organizations and UN
agencies) and run a program in Chad, West Africa.3 We then selected four among these six
organizations because we wanted to conduct extensive interviews at their headquarters and in
the field. For budget and time reasons we had to limit ourselves to the lowest acceptable number
of case organizations, which is often considered to be four (Eisenhardt, 1989). This selection
process was conducted independently by three research assistants who analyzed annual reports
from the six organizations and selected the four that reported government restrictions most
often. Basing our sampling decision on the occurrence of governmental restrictions ensures that
the problem we wanted to study would be “transparently observable” (Eisenhardt, 1989).
All four organizations accepted to take part in our study and allowed us to interview their
staff members. We present the key characteristics of the selected case organizations in Table 1.
Due to the sensitivity of the topic, we agreed to keep the name of the organizations confidential.
3 The decision to focus on Chad came from the need to compare the four organizations in the same country (for
another paper using this case study data).
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Table 1: Characteristics of the selected case organizations
Org. A
Org. B
Org. C
Org. D
Number of programs (countries of activity)
at time of study 3 80 20 40
Yearly budget, in million USD
2
> 500
150
150
Government funding
55%
92%
25%
35%
Private funding and other donations
45%
8%
75%
65%
Number of international staff worldwide
>10
>1,000
>500
>300
Number of national staff worldwide
>10
>5,000
>3,000
>1,000
Type of imported goods Equipment
General
supplies &
Equipment
Medical
supplies &
Equipment
Medical
supplies &
Equipment
Data collection
We selected interviewees among different functions at the headquarters and the program level
in Chad. We wanted to have several functions represented in our interviewees, and selected
members from the senior leadership and middle management, with representatives from
administration, operations and logistics departments. The list of interviewees and their function
can be found in Appendix A. In total we conducted 22 interviews (5-6 per organization) with
an average length of 61 minutes. We followed a structured interview protocol (see Appendix
B). Combining interviews at the headquarters and one country, Chad, allowed us to collect
information about governmental restrictions in potentially 143 programs (i.e., the sum of the
programs conducted by each of the four case organizations, see first line of Table 1). We asked
the interviewees to describe the restrictions their organization encountered, as well as the
countries in which they occurred. We included each country that was mentioned in our sample.
Since not all countries imposed restrictions, we ended up with a sample of 18 countries that
imposed restrictions on our case organizations. Two researchers took notes during the
interviews, and transcribed their notes independently. They then combined their notes into a
common interview transcript which we stored in a structured database. We used respondent
11
validation and final proofreading of the interview transcripts by each organization, in order to
ensure validity and reliability of the collected data.
Data Analysis
Two researchers analyzed the interview transcripts independently in order to increase
reliability, by coding the interview transcripts and identifying occurrences of the different
governmental restrictions mentioned by interviewees in relation to particular countries. The
structured interview protocol which guided our data collection allowed us to identify, in a
systematic way, all governmental restrictions experienced by each organization in every
country. We initially started with eight types of governmental restrictions we used in the
interview protocol (see question 46 in Appendix B). Based on the answers from the
interviewees, we inductively refined the types into the five categories listed in Table 2: Import
barriers, Access barriers, Control of activities, Corruption and Bureaucracy. We categorized
each restriction identified in the interview protocols into one of these types of restrictions. Due
to the limited number of occurrences of each particular restriction in a given country, we
combined them into a number of restrictions per country. We acknowledge that combining all
forms of government restrictions into one number is a limitation of our method, because the
restrictions do not necessarily have the same effect on humanitarian organizations.
Because each case organization is not active in every country, we calculated the average
number of restrictions faced in every country. We summed up the total number of restrictions
reported in each country by all organizations, and divided it by the number of organizations
which reported issues in this country, as shown in equation 1. This step allowed us to make data
comparable across countries, independently from the number of organizations reporting
restrictions for each country.
12
=
(1)
Once we found the average number of restrictions per country, we identified characteristics
of the countries that could explain these restrictions. For this, we selected a number of
governmental situational factors (state fragility, democracy, political freedom, corruption) and
socio-economic situational factors (ease of doing business, logistics performance) in a country.
We describe the process and motivation for selecting these factors in Section 5.
While the number of case organizations (4) and interviews (22) is optimal for a case study
research methodology, it is by no way sufficient to allow statistical generalization (Yin, 2009),
or in other words, to infer conclusions from a sample to the whole population. We therefore
preferred to apply analytical generalization, where empirical observations are used to generate
theory as recommend by Yin (2009). This was possible due to the theoretical sampling
mechanism we applied for selecting case organizations based on their theoretical contribution
rather than for statistical reasons (Eisenhardt, 1989). However, such an approach does not allow
for inductive inference, as one observation does not allow to generate a theory (Popper, 1959).
For this reason, we selected the deductive method of testing propositions developed by Popper
(1959), which tries to falsify propositions based on empirical evidence rather than verifying
them, and only if the falsification is not possible, can the theory be said to be “corroborated by
past experience” (Popper, 1959). Following this approach, we aimed to invalidate the relations
between the level of restrictions imposed by governments on humanitarian supply chains and
each of the governmental and socio-economic situational factors in a country. Whenever we
found a country contradicting this relation, we invalidated the relation. Only relations for which
we did not find contradicting evidence were considered as corroborated by our empirical
experience.
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4. Results
Through our case study methodology, we identified 44 occurrences of governmental
restrictions experienced by our case study organizations in 18 countries. Table 2 lists the types
of government restrictions on humanitarian supply chains we identified in our sample, as well
as some examples for each of them.
Table 2: Types and Examples of Governmental Restrictions Imposed on Humanitarian Supply
Chains
Type of
restrictions
Examples
Import barriers
Tariffs, Delays at customs clearance, Extreme complexity of clearance
procedures, Rules of origin, Ban of importation on medicines and
satellite communication equipment
Access barriers
Restriction of access of staff (visa) or organization
Control of
activities
Extreme governmental control of NGO activities and movement
Corruption
Bribery requested for customs clearance of humanitarian supplies,
Imaginary taxes created
Bureaucracy
Numerous authorizations needed, Complex administrative procedures
(car registration, labor law, etc.)
Table 3 shows the average number of restrictions experienced by our case organizations in
each country (first column), together with different situational factors that could possibly
explain the number of governmental restrictions on humanitarian organizations. We show these
possible relationships in our theoretical framework in Figure 1. We categorize these factors into
two groups, governmental and socio-economic situational factors (see Figure 1). This
categorization is based on the framework developed by Kunz and Reiner (2012). We use
different indexes to measure these situational factors in each country. The scores of these
indexes are all publicly available from their publishers’ websites (Marshall and Jaggers, 2002;
Freedom House, 2010; The World Bank, 2010; Marshall and Cole, 2011;
Transparency International, 2011; The World Bank, 2012). We describe these indexes and how
we selected them in the next section.
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Table 3: Average Number of Restrictions per Country, Governmental and Socio-Economic
Situational Factors
Country
Average
number of
restric-
tions
GOVERNMENTAL
FACTORS
SOCIO-ECONOMIC
FACTORS
Polity State
Fragility
2010
Polity
Democracy
Score
2010
Freedom
House
Status
2010
TI
Corruption
Perception
2011
WB Ease of
Doing
Business
2012
WB Logistics
Performance
Index
2010
Somalia
2
25
-
Not free
1
-
1.34
Sudan
2
24
-2
Not free
1.6
135
2.21
DRC
2
23
+5
Not free
2
178
2.68
Myanmar
2.3
22
-6
Not free
1.5
-
2.33
Chad
1.8
22
-2
Not free
2
183
2.49
Ethiopia
2
21
+1
Partly-free
2.7
111
2.41
Liberia
2
18
+6
Not free
3.2
151
2.38
Cameroon
1.5
16
-4
Not free
2.5
161
2.55
Pakistan
1
15
+6
Partly-free
2.5
105
2.53
India
1
13
+9
Free
3.1
132
3.12
Colombia
1
12
+7
Partly-free
3.4
42
2.77
Tanzania
1
12
-1
Partly-free
3
127
2.60
N. Korea
1
10
-9
Not free
1
-
-
Senegal
1
9
+7
Partly-free
2.9
154
2.86
Israel
1
8
+10
Free
5.8
34
3.41
Georgia
1
8
+6
Partly-free
4.1
16
2.61
Russia
1
7
+4
Not Free
2.4
120
2.61
Bosnia
1
5
-
Partly-free
3.2
125
2.66
Given the fact that these indexes are compiled and published by various institutions and
following different rules, yearly indexes may cover the previous year, the current year or the
upcoming year. In order to avoid biases due to varying time periods, we decided to use the most
recent figures available for each index at the time when the data collection was conducted (Fall
2011). We had to remove Libya from our sample due to the regime transition in 2011, and most
of the available scores did not yet reflect these changes.
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Figure 1: Possible Factors Explaining Government Restrictions on Humanitarian Supply Chains
5. Analysis
In this section, we analyze the relationship between the average number of restrictions imposed
on humanitarian organizations and different indexes characterizing a country. We group these
indexes into two categories: governmental situational factors and socio-economic situational
factors. These categories are discussed in the following subsections.
5.1. Governmental situational factors
We expect governmental situational factors in a country to have an impact on the number of
restrictions imposed on humanitarian organizations. These situational factors include the type
of regime, the efficiency of the government, or the level of corruption (Kunz and Reiner, 2012).
We assess the governmental situational factors with different indexes commonly used in
political sciences for characterizing governments, the Polity Democracy Score and Polity State
Fragility index (Marshall and Cole, 2011), as well as the Freedom House Status
(Freedom House, 2010), which are considered as the best existing indexes of the political
State Fragility Restrictions on
Humanitarian
Supply Chains
Democracy
Ease of Doing
Business
Political
Rights Logistics
Performance
Corruption
GOVERNMENTAL
FACTORS SOCIO-ECONOMIC
FACTORS
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environment covering most countries of the world each year (Howard and Roessler, 2006). We
use the Corruption Perception Index to measure the level of corruption in a country
(Transparency International, 2011). In the next paragraphs we discuss the selection of each
index.
According to Atack (1999), cooperation with democratic states, which accept the autonomy
and independence of NGOs, is generally easier than with authoritarian states. This relationship
between the level of democracy and the restrictions imposed by governments was also
mentioned by respondents of our case study: “If there is a democracy, you can use the public
opinion as a lever to obtain what you need. If you cannot solve a problem with the government,
there are civil societies which can help you. In a non-democratic country, this is impossible”
(Head of Operational Logistics, Organization C). Based on this finding from development
literature and our empirical evidence, we expect governments with a lower level of democracy
to be more suspicious of humanitarian organizations, and to impose more restrictions than
governments with a higher level of democracy. We develop Proposition 1 to test if the level of
democracy in a country has an impact on the number of restrictions imposed by the government
on humanitarian supply chains:
P1: The more democratic a government, the less restrictions it imposes on humanitarian supply
chains.
We measure the democracy level of a government with the Polity Democracy Score, an index
ranging from -10 (fully institutionalized autocracy) to +10 (fully institutionalized democracy)
(Marshall and Cole, 2011). While we find evidence that autocratic (non-democratic) states such
as Myanmar (-6 democracy level) tend to impose more restrictions on humanitarian supply
chains (2.3 average number of restrictions), there are also countries which contradict these
findings. North Korea is for example considered as strongly autocratic (-9 democracy level) but
shows a relatively low average level of restrictions (1 restriction). On the other hand, rather
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democratic governments such as Liberia (+6 democracy level) or the Democratic Republic of
the Congo (+5 democracy level) impose high level of governmental restrictions on
humanitarian supply chains (2 restrictions). Due to these contradicting observations we reject
this proposition.
We expect the fragility of a government to have an impact on the level of restrictions it
imposes. This was also mentioned by a respondent, who believes that governments impose
restrictions on humanitarian organizations because they want to “keep the control, as the
country is politically not very stable” (Logistics Coordinator Chad, Organization C). Based on
this, we develop Proposition 2 to test if the fragility of the government in a country explains the
number of restrictions it imposes on humanitarian supply chains:
P2: The more fragile a government, the more restrictions it will impose on humanitarian supply
chains.
We test the fragility of a government with the Polity State Fragility index (Marshall and
Cole, 2011). According to this index, which ranges from 0 (no fragility) to 25 (extreme
fragility), state fragility is defined as a combination of state effectiveness and state legitimacy
(Marshall and Cole, 2008). When comparing the Polity State Fragility scores for each country
with the average number of restrictions (see Figure 2), we see that fragile states clearly impose
more restrictions on humanitarian supply chains than states with lower fragility scores. The
grey line in Figure 2 depicts this tendency. In order to test this proposition, we identify countries
in the sample that diverge from this pattern. There is no country with a fragility score of over
20 with fewer than 1.8 restrictions. Also, no country with a fragility score equal to or lower
than 15 imposes more than one restriction.
Based on the absence of contradictory evidence, we cannot reject this proposition. This
allows us to conclude that in our sample of countries, fragile states (i.e., low effectiveness and
legitimacy) tend to impose more restrictions on humanitarian supply chains than states which
18
are less fragile. In other words, the more ineffective and illegitimate a government is, the more
it tends to impose restrictions on humanitarian supply chains on its territory. All case
organizations confirmed this high level of control and restrictions in fragile states (e.g., ban of
import of satellite communication equipment, authorization required for internal travels,
complex customs clearance procedures).
0.0
0.5
1.0
1.5
2.0
2.5
0 5 10 15 20 25 30
Average number of restrictions
Polity State F ragility Index
Figure 2: Average Number of Restrictions and State Fragility Indexes of Countries
Next, we test if a government that does not give much rights and freedom to its citizens
would impose more restrictions on humanitarian organizations. We develop Proposition 3, in
which we compare the level of political rights and civil liberties in a country with the number
of restrictions imposed on humanitarian organizations:
P3: The more political rights and civil liberties a government provides to its population, the
less restriction it will impose on humanitarian supply chains.
The Freedom House Status is an indication of the level of political rights and civil liberties
citizens have in a country (Freedom House, 2010). It can be either Not Free, Partly Free or
(low fragility)
(high fragility)
19
Free. When testing the relationship based on our sample, we find that countries imposing a high
level of restrictions on humanitarian supply chains are generally categorized as Not Free.
However, the case of North Korea (Not Free, 1 restriction) and Ethiopia (Partly Free, 2
restrictions) contradict this pattern. Therefore we reject this proposition.
Several respondents mentioned a strong link between corruption in a country and the level
of restrictions imposed on humanitarian supply chains: “Sometimes customs invents taxes,
which are in the end corruption” (Head of Operational Logistics, Organization C). The
restrictions are not always directly imposed by the government, but by governmental employees
who “are not well paid, and try to get additional revenue through corruption” (Logistics
Manager Chad, Organization B). In order to test the suggestion that the level of corruption in a
country explains the number of restrictions it imposes on humanitarian supply chains, we
develop Proposition 4:
P4: The higher the level of corruption in a country, the more restrictions the government will
impose on humanitarian supply chains.
We test this proposition with the Corruption Perception Index (CPI) developed by
Transparency International (2011). This index describes the perceived corruption level in a
country, ranging from 0 (country perceived as highly corrupt) to 10 (country perceived as very
clean). While all countries imposing more than one restriction on humanitarian supply chains
have a high level of perceived corruption (i.e., CPI between 1 and 3.2), there are also examples
such as North Korea or Pakistan which contradict this relationship, as they are considered to be
highly corrupt, but only impose one restriction on average. Based on this contradictory
evidence, we reject this proposition.
20
5.2. Socio-Economic Situational Factors
We expected the socio-economic environment in a country to have an impact on the level of
restrictions imposed by governments on humanitarian supply chains. In particular, we focus on
the economic environment because some of the restrictions imposed on humanitarian supply
chains also apply to businesses. Governments may for example impose restrictions because
they want to “legitimately protect their population, for example by restricting the importation
of GMO food” (Head of Sector Logistics, Central & Southern Africa, Organization B).
Similarly, governments may impose restrictions on imports because they want to “protect their
own industries or monopolies” (Logistics Director, Organization C). Such restrictions apply to
humanitarian and commercial organizations alike, which indicates a possible link between the
business regulatory environment in a country and the level of restrictions imposed on
humanitarian supply chains. We develope Proposition 5 to test this relationship:
P5: The more conducive the regulatory environment is to start and operate a local firm, the
less restrictions the government will impose on humanitarian supply chains.
We evaluate the business regulatory environment in the different countries based on the Ease
of Doing Business index published by The World Bank (2012). This index ranks 183 countries
according to how favorable their regulatory environment is for starting and operating a business.
We find some evidence that the business regulatory environment could explain the level of
restrictions imposed on humanitarian supply chains, but there are countries which contradict
this pattern. Ethiopia for example imposes 2 restrictions on humanitarian supply chains, but is
ranked significantly better on the business regulatory environment (rank 111) than Senegal
which imposes only one restriction (rank 154). If this proposition was always true, a country
ranking high on the Ease of Doing Business index (i.e., difficult business regulatory
environment) would always impose more restrictions than a country ranking low on the Ease
21
of Doing Business index. Based on the contradicting pattern we identify for Senegal and
Ethiopia, we reject this proposition.
As several restrictions imposed by governments on humanitarian organizations are related to
the import process and transportation inside the country, a leading researcher in the field of
humanitarian logistics who read an earlier version of this manuscript suggested that the level of
restrictions imposed by a government on humanitarian supply chains may be related to the
logistics performance prevailing in this country. This is confirmed by several respondents who
mention low logistics performance in some countries due to the number and complexity of
required import documents: “Import procedures are usually very complex, as you really have
to know where to find the specific documents” (Supply Chain Manager, Organization A). In
Ethiopia for example, “extremely high numbers of documents are requested for the import
process” (Desk Officer Africa, Organization D). In order to test if the logistics performance in
a country explains the level of restrictions imposed on humanitarian supply chains, we develop
Proposition 6:
P6: The higher the logistics performance in a country, the less restrictions the government will
impose on humanitarian supply chains.
We test this proposition with the Logistics Performance Index (LPI) published by the World
Bank (2010). This index rates 155 countries from 1 (worst performance) to 5 (best performance)
based on different components such as customs clearance, timeliness, logistics competence
(The World Bank, 2010). We find a relationship between the logistic performance in a country
and the level of restrictions imposed on humanitarian supply chains. However, there are
countries with similar levels of logistics performance (e.g., Pakistan, Cameroon, Chad, all
around 2.5) showing different levels of restrictions imposed on humanitarian organizations
(e.g., 1, 1.5, 1.8). We reject this proposition based on this reason.
22
6. Discussion
We have tried to identify which characteristics of a country explain the level of restrictions its
government imposes on humanitarian supply chains. We tested a number of governmental
situational factors, such as the level of democracy, the state fragility level, the political freedom
level or the level of corruption. We also tested two socio-economic situational factors, the
business regulatory environment and the logistics performance in a country.
While all characteristics we tested showed some links with the level of restrictions
imposed on humanitarian supply chains in different countries, we also found contradicting
examples for many of them. Following the approach suggested by Popper (1959), and because
our relatively small sample size would not be sufficient to generate statistical inference, we
invalidated all relationships for which we found contradicting examples. The invalidation of
propositions based on single examples is a very strict approach, and we do not pretend that it is
the correct method in every situation. We opted for this conservative and cautious approach in
order to guard against possible criticism regarding the limited sample size (18 countries), and
to increase the validity of our findings.
The only relationship we could not invalidate based on our sample was the link between the
number of restrictions and state fragility, a combination of the effectiveness and legitimacy of
a government. This means that the more ineffective and illegitimate a government is, the more
it tends to impose restrictions on humanitarian supply chains. This behavior can be explained
by the fact that such governments face a higher risk of being overthrown, resulting in fears that
autonomous international organizations will challenge their political control (Coston, 1998). As
a consequence, fragile governments impose stronger controls on the activities of humanitarian
organizations. This is confirmed by Bratton (1989) who found that a government with a low
political legitimacy tends to be less permissive towards the voluntary sector. According to this
23
author, such governments often control humanitarian organizations through multiple tools
(registration of NGOs, customs clearance, security clearance) and different government units.
In order to understand the reasons why a fragile government would impose more restrictions
on humanitarian supply chains, we went back to the interview transcripts. We identified several
instances of government restrictions that confirm this link. A frequent restriction encountered
is related to the import of communication equipment: “Satellite phones are banned in several
countries. The government fears that we communicate information about what is going on in
the country to the rest of the world. This is certainly the motivation of governments to set
restrictions on communication equipment” (Head of Operational Logistics, Organization C).
Another respondent confirmed this: “In Ethiopia, there is an interdiction to import satellite
phones and satellite internet equipment. Radio equipment is highly regulated” (Africa Desk
Officer, Organization D). The restrictions on communication equipment can be explained by
the government’s fears that information is shared publicly, which is typical for fragile
governments. Indeed, a government with low legitimacy risks to be overthrown if the public
learns about the government’s inefficiencies. This risk is lower for a highly legitimate and
efficient government, hence the lower restrictions on humanitarian organizations.
Our interviews confirm that fragile governments have a desire to control what happens in
the country: “The government [Chad, high State Fragility Index] wants to control who enters
and works in the country” (Logistics Assistant Chad, Organization B). One respondent
mentioned that the government imposes restrictions because it wants to “keep the control, as
the country is politically not very stable” (Logistics Coordinator Chad, Organization C).
Another respondent said that restrictions are imposed based on a “political motivation, because
the government fears to lose control over a part of the territory or a population” (Head of
Supply, Organization C). In some cases, there is “paranoia of the government towards NGOs.
There is a willingness to control activities” (Africa Desk Officer, Organization D). Controlling
24
activities of non-governmental entities allows fragile governments to identify potential
challengers to its power.
The five other propositions we tested were invalidated. Based on the methodological approach
we selected, it is not possible to draw reliable conclusions about these propositions. Indeed,
invalidating a proposition based on contradicting examples does not guarantee that this
proposition is always false. There is however an interesting finding about the invalidated
propositions. Several of the contradicting examples are from one country, North Korea. With
the highest scores on several indexes, one would expect this country to impose a high number
of restrictions on humanitarian supply chains. However, our data indicates that it imposes only
one restriction on average. This may be explained by the fact that this autocratic government
has such a strong control over its population that it does not feel threatened by humanitarian
organizations. Further research could investigate the reasons explaining the comparatively low
level of restrictions imposed by this country.
7. Implications
Implications for research
Our paper has a number of implications for research. First, it develops propositions that can be
further tested through other research methods. The propositions we invalidated based on
contradicting examples could be tested with empirical data from a survey in order to verify if a
statistical generalization would lead to the same result. Second, our finding that the government
fragility explains the level of restrictions in a country could be further tested through a survey
on a larger sample of countries. Third, the fact that state fragility has an impact on the level of
restrictions imposed on humanitarian organizations is useful for other studies that compare
programs of humanitarian organizations with characteristics of the host government. This
25
finding can also be useful for researchers analyzing commercial supply chains in developing
countries.
Implications for practice
Our paper provides multiple managerial implications for humanitarian organizations. Knowing
that fragile states tend to impose more restrictions on humanitarian supply chains helps
humanitarian organizations to better prepare before entering a new country. They can anticipate
the fears of the local government and take proactive steps to address them.
The state fragility index is composed of two components, government legitimacy and
government efficiency. A closer look at these components allows us to derive interesting
implications of our research. A fragile government feels threatened by humanitarian
organizations which might question its legitimacy. A humanitarian organization entering a
country with a lack of government legitimacy has to clarify the objective of its work, namely
to help beneficiaries and not to take a position against the government. It should meet with key
stakeholders at the government level, and present its activities and objectives. This will defuse
possible doubts of the government about the political neutrality of the organization and its
intended objectives of working in the country. The organization has also to be extremely careful
when dealing with institutions or people from the opposition, since the government could feel
threatened by this. The humanitarian organization also needs to be careful not to publicly
criticize the government. Finally, a humanitarian organization working in such countries should
not engage in advocacy activities, which could reinforce the fears of the government. This is
obviously not to say that advocacy activities are wrong, but a humanitarian organization
involved in operational activities (e.g., providing supplies to beneficiaries) might be extremely
restrained if it engages in advocacy activities as well.
26
The low efficiency of the government is another component of the state fragility index. A
humanitarian organization helping the population of a country with a fragile government might
be seen as a source of competition by the inefficient government. The humanitarian
organization should therefore be careful in how it presents its work, and avoid criticism about
the inaction or poor efficiency of the government. Demonstrating a desire to complement the
government’s efforts, working in collaboration with the government, training government
workers are ways to get the work done while working with the government.
In addition to the implications discussed above, our findings also lead to a number of
operational implications for the humanitarian logistician. When facing a fragile government,
we suggest that the logistician tries to implement pre-clearance procedures, in which the
customs clearance process is handled before the physical delivery of the goods. Doing so gives
the government confidence about the organization’s openness and willingness to respect the
government’s procedures. Procuring relief supplies locally when possible is another way for a
humanitarian organization to demonstrate its willingness to work with and contribute to the
country’s economy. Finally, partnering with a well-regarded local organization for in-country
logistics will also address possible fears of the government.
Our results show that five of the six propositions could not be validated. It is impossible to
develop implications on the five propositions that we refuted, because a lack of validation does
not necessarily mean that the tested relation is always wrong. We can for example not safely
state that the level of corruption is not linked with the level of government restrictions on
humanitarian supply chains. It often is, but there are exceptions.
Our findings also have implications for commercial supply chain management, for example
for companies starting to do business in a new country. In addition to the usual measures of the
business regulatory environment (e.g., the World Bank’s Ease of Doing Business), companies
should also consider the fragility of the government as an important criteria. When entering a
27
country with a fragile government, the company can expect to face a number of restrictions,
and has to work proactively with the government in demonstrating its neutrality and willingness
to help.
8. Conclusion
The influence of governmental restrictions on humanitarian supply chains has been mentioned
by several authors so far, but was never analyzed specifically in academic literature, despite its
practical relevance. This paper intends to fill this gap. In particular, we identified the
characteristics of governments which explain the level of restrictions imposed on humanitarian
supply chains. In order to do so, we tested several governmental situational factors and socio-
economic situational factors of countries. While each of the indexes we tested explained the
level of restrictions to some extent, we found countries contradicting this relationship for all
but one index. We found that state fragility, a combination of government ineffectiveness and
illegitimacy, is the only characteristic which explains the level of restrictions imposed on
humanitarian supply chains in each of the 18 countries in our sample. Based on this finding, we
can state that the more fragile a government is, the more restrictions it will impose on
humanitarian organizations. Not a single country deviated from this pattern in our sample. This
proposition is therefore “corroborated by past experience” (Popper, 1959).
This paper has a number of limitations. First, the small sample size limits the generalizability
of our findings. We overcome this limitation by using a method borrowed from qualitative
research, namely the falsification of propositions instead of statistical generalization. Second,
while the transformation of qualitative data (examples of restrictions mentioned by respondents
during interviews) into quantitative data (average number of restrictions per country) is
supported by literature (e.g., Patton, 2002), it involves a loss of depth of data. Doing so, we
consider each type of restriction having the same importance, which is not necessarily the case.
28
Also, collecting data through a structured interview protocol does not guarantee that all
restrictions occurring in each program have been mentioned, as respondents are biased towards
the experiences which had the highest impact on them. We reduced this bias by interviewing at
least five staff members in each organization, and by requesting respondent validation at
different steps of the research process. Moreover, when collecting data on complex issues such
as government restrictions, there is always a high degree of respondent subjectivity involved.
Finally, because we did only ask interviewees to mention countries in which they encountered
restrictions, we did not consider countries with no mention of restrictions in our analysis.
Further research could overcome this limitation by asking specifically about the number of
restrictions encountered in each of a set of countries, through a survey for example. This would
allow including also countries without restrictions in the sample.
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32
Appendix A: List of interviews
(Source: Kunz and Gold, 2015)
Organisation
Position
Level
A
Administrative Director
HQ
A
CEO
HQ
A
Institutional Advisor
HQ
A
Supply Chain Manager
HQ
A
Program Manager
Field
A
Technical Field Manager
Field
B
Head of Sector Logistics, Central and Southern Africa
HQ
B
Head of Sector Logistics, East and Central Asia
HQ
B
Logistics Assistant Import-Export
Field
B Deputy Head of Delegation Field
B
Logistics Manager
Field
C
Coordinator Procurement Unit
HQ
C
Head of Operational Logistics
HQ
C
Head of Supply
HQ
C
Logistics Director
HQ
C
Logistics Coordinator
Field
C
Finance Coordinator
Field
D
Africa Desk Officer
HQ
D
Head of Logistics Services
HQ
D
General Coordinator
Field
D
Logistician
Field
D
Logistics Assistant
Field
33
Appendix B: Structured interview protocol
##: Questions asked in interviews at headquarters and at project / program level in Chad
A##: Questions asked only at headquarters
B##: Questions asked only at project /program level in Chad
GENERAL QUESTIONS
1
Code
2
Start time
3
What is your position in the organization?
4
What responsibilities are involved in this position?
5
Since when are you in this position?
6
Since when are you working for this organization?
A8
a. When was your organization founded?
A10
a. Can you shortly describe the activities of your NGO?
A11
a. In which phase of disaster do you usually operate? [Preparation / Response /
Recovery]
A12
a. In which context of operation is your organization operating in general? [Disaster
relief / Development aid]
A13
a. In what type of disasters is your organization operating in general? [Natural
disaster / Man-made disaster]
A14
a. What is the size of you NGO, in terms of yearly budget and staff (national +
international worldwide)
B7
b. Country of operation
B8
b. Operation ongoing in this country since
B9
b. Name of your project
B10
b. Can you shortly describe the activities of your project?
B11
b. In which phase of disaster does your current operation work? [Preparation /
Response / Recovery]
B12
b. In which context of operation is your current operation working? [Disaster relief /
Development aid]
B13
b. In what type of disasters is your current operation working? [Natural disaster /
Man-made disaster]
B14
b. What is the size of you operation, in terms of yearly budget and staff (national +
international worldwide)
DONATIONS
A15/
B15
What are the sources of funding of your (a) organization / (b) operation? Which type
of donors do you have? What is the approximate percentage for each type of donor?
16
Do you have any partnerships with donors, which guarantee you a safe and constant
funding for your long term activities? If yes, who are these?
A17/
B17
What is the yearly amount of donations received by (a) your organization / (b) your
operation?
PERFORMANCE
A18
a. How would you define the performance of your NGO (i.e., explain what it is for
you to be performing well as organization)? How can it be measured?
A19
a. How would you rate the performance of your NGO on average over all programs,
in comparison with best in class organization?
A20
a. Can you tell us which organizations you consider as best in class?
34
B18
b. How would you define the performance of your operation (i.e., explain what it is
for you to be performing well as an organization in an operation)? Can it be
measured?
B19
b. How would you rate the performance of your current operation, in comparison with
best in class operations (either from your own organization or others)?
B20
b. Can you tell us which operation/organization you consider as best in class?
27
What part of your performance is due to controlled reasons (e.g., processes,
management, structure) and what percent is rather uncontrolled (e.g., good staff,
opportunities, context, etc.)?
NGO/Resources
A21/
B21
In your opinion, how would you rate [1-5] the number of resources you have in your
(a) organization / (b) operation in terms of
Finances
Staff
IT equipment
Vehicles
Buildings/physical infrastructure
Other resources with strong impact?
A22/
B22
In general, do you feel that you have less, same level, or more resources than most
other NGOs in (a) your field / (b) this country?
A23/
B23
In your opinion, how would you rate [1-6] the quality of the resources you have in
your (a) organization / (b) operation in terms of
Staff
IT equipment
Vehicles
Buildings/physical infrastructure
Other resources with strong impact?
A24/
B24
In general, do you feel that you have lower quality, same quality or better quality of
resources than most other NGOs in (a) your field / (b) this country?
NGO/Logistics Processes
28
Does your NGO use formal logistical processes, and if yes, which one?
29
Are these processes documented?
30
Are these processes regularly updated?
31
Are these processes designed at the HQ level or the program level?
32
How would you rate the number of your logistic processes?
[1 (insufficient , 3 (adequate), 5 (too many)]
33
How would you rate the quality of your logistics processes?
[1 (inadequate), 2 (basic), 3 (acceptable), 4 (satisfactory), 5 (adequate)]
BENEFICIARIES
34
Do you personally know the needs of the beneficiaries of your operation(s)? If yes,
what are these needs?
35
How does your organization usually assess the needs of the beneficiaries?
FIT NGO <-> BENEFICIARIES
36
To which degree do you think does your NGO meet the needs of the beneficiaries?
[1 (poorly), 2 (basically), 3 (acceptable), 4 (satisfactory), 5 (adequate)]
Why?
GOVERNMENTAL FACTORS
A40/
B40
How many people per operation are in contact with the local government
(a) on average / (b) in your operation
35
41
What are the exact functions of these people?
42
Are you personally in contact with local government(s)? If yes, in what kind of
situations?
43
What are the most difficult aspects in your personal contacts with governments?
44
How many times per week/month does a staff of your organization meet with people
of the government?
45
How strong do the following governmental influences affect your operations?
[1 (no impact at all), 2 (weakly), 3 (medium), 4 (strongly), 5 (very strong impact)]
Can you explain why?
Import barriers
Corruption
Bureaucracy
Control of your activities
Taxation
Visa issues
Labor law
Other legal requirements
46
How would you evaluate the effect of each of these governmental influences on your
NGO, the beneficiaries, the government?
[N: Negative / X: Neutral / P: Positive]
Import barriers
Corruption
Bureaucracy
Control of your activities
Taxation
Visa issues
Labor law
Other legal requirements
47
Do you see other governmental influences which have a NEGATIVE impact on your
ability to satisfy the needs of the beneficiaries?
If yes, which one? How do they limit your organization’s ability to conduct your
operations and to answer to the beneficiaries’ needs?
48
Do you see other governmental influences which have a POSITIVE impact on your
operations, and thus increase your ability to meet the beneficiaries’ needs?
If yes, which one? How do they increase your organization’s ability to conduct your
operations?
IMPORT BARRIERS
49
Did you ever experience any entrance barriers / import barriers in your current
program(s)? [yes – no] (a) In which countries?
ban for NGO to enter country
ban for staff to enter country
customs tariffs
complex customs clearance procedures
administrative barriers such as special document requirements
interdiction to import specific equipment
Others, please describe and give country
50
What do you think is the motivation of the government to impose import barriers?
51
Did your organization find ways to by-pass import barriers, and if yes, how?
36
52
Does your NGO have any policy or processes which define how to deal with these
problems?
53
Is there a particular staff in your program(s) which is in charge of dealing with the
import procedures?
54
If yes, what is his title? What are his tasks? What type of employee is he
(national/international? Level in hierarchy?)
56
Do you feel that commercial logistics providers face fewer troubles to import material
in the country than NGOs? If yes, why?
IMPACT OF IMPORT BARRIERS
59
How would you rate the impact of import barriers on your operations
EFFECTIVENESS:
Conducting the operation
[1 (no impact at all), 2 (weak), 3 (moderate), 4 (strong), 5 (very strong impact)]
EFFICIENCY:
Cost
[1 (no impact at all), 2 (weak), 3 (moderate), 4 (strong), 5 (very strong impact)]
Can you estimate the additional cost of import barriers to your organization? In %
of budget or CHF
Delays
[1 (no impact at all), 2 (weak), 3 (moderate), 4 (strong), 5 (very strong impact)]
Can you estimate the time you lost in your operation, due to import barriers? In
month compared to a setting with no import procedure at all (i.e., time between
equipment physically present at border until available for use in country)
60
Do import barrier affect the ability of your organization to fulfill needs of the
beneficiaries? If yes, how?
61
What are the best ways your organization found to reduce the impact of import
barriers on your operations?
62
In your opinion, do import barriers have a POSITIVE impact on one or more of the
following? [yes – no] If yes, why?
On your operation
On the country’s economy
On the government
On particular staff of government
On other stakeholders?
63
Does the ban of re-exporting equipment influence the choices of your organization
during the project setup? (purchase, etc.)
If yes, in which way?
ECONOMIC AND SOCIAL ENVIRONMENT
64
For which services/procurement does your NGO work with local companies?
65
What are the benefits/problems of working with local companies?
OTHER SITUATIONAL FACTORS
66
How strong do these factors affect your operations:
[1 (no impact at all), 2 (weak), 3 (moderate), 4 (strong), 5 (very strong impact)]
Economic and social environment
Government
Infrastructure
Disaster and environmental
37
67
Are there additional situational factors which have not yet been discussed, and which
have a significant impact on your ability to meet the beneficiaries’ needs? If yes,
which are these and how do they affect your operations?
[1 (no impact at all), 2 (weak), 3 (moderate), 4 (strong), 5 (very strong impact)]
