Global Expansion Decision Making: An assessment of the
impacting factors for restaurant franchises
by
Mahmood A. Khan, Ph.D.*
Professor, Department of Hospitality & Tourism Management
Pamplin College of Business
Virginia Tech, National Capital Region
7054 Haycock Road
Falls Church, VA. 22043
[email protected]
Maryam Khan, Ph.D.
Director/Assistant Professor
Hospitality Management Program
School of Business – Department of Management
Howard University
th
2600 6 Street, NW, Washington, DC 20059
Abstract:
Franchise businesses are rapidly expanding overseas. Since global expansion
demands considerable capital investment careful decision making is essential.
Considering the lack of available information this study explores factors that
should be considered in decision making pertaining to expansion in foreign
markets. Using data of restaurant franchises particularly McDonald's and KFC
this study outlines some of the factors that are essential in decision making.
From available data an analyses of the presence or absence of selected franchises
in different countries were conducted to (a) assess the number of units in
different countries; (b) correlate the number of restaurant units in different
countries to the available indices measuring economical, social, and political
indicators; (c) use any correlation with existing index or indices to identify
potential factors for selecting foreign markets; (d) identify possible expansion
within existing markets; and (e) identify potential foreign markets. Based on the
results obtained a list of potential markets for restaurant franchising is presented
and the factors that should be considered are outlined for each country or region.
2
Introduction
Global expansion of US-based chains is proceeding with an
unprecedented pace. It was reported that more than ninety percent of the net
new restaurants added by McDonald's and Burger King in the last completed
fiscal years opened overseas. Evidently this underscores the importance of
international expansion, particularly by matured chains (NRN, 2009). While
there are plenty of opportunities available overseas, it is not easy to find a
compatible match. Advances in technology, economic growth, social and
political changes, are all providing market opportunities that were not foreseen
in recent history. A major portion of revenue for the largest restaurant chains
come from international expansion. About 55% of McDonald's revenue comes
from Asia, Pacific Rim, Africa, Middle East and European divisions (Brodsky,
2008). People are becoming aware of different brands and are able to try,
develop taste, and possibly adapt non-traditional foods. This trend my have a
distinct impact on food habits, particularly among children. Among all the
businesses, probably restaurants face the greatest challenge in venturing into a
new global market, since they have to gain acceptance by individuals who are
willing to compromise their social and cultural habits.
Notable trends that favor the increase of international franchises in foreign
markets include (a) increased educational status of the local population; (b)
technological advancement facilitating travel, intercultural cooperation, and
instant dissemination of information; (c) exposure to different foods, the
willingness to try new products and unconventional types of foods; (d) rapid
development of rural areas, construction of highways, improved transportation
methods, and overall industrial development; (e) improved economies and
increased disposable family income; (f) the increased numbers of women in the
workforce and of two-income families; (g) the increased significance of
convenience as a result of one or more factors mentioned above; and (h) the
popularity of take-out or home-delivered meals (Khan, 1999).
Considerable capital investment is needed to find suitable market and
eventually a suitable business partner. Typically the business environment is
very volatile and risky in international markets. Models that work in the USA
may not work in other countries. One of the challenges faced by corporations is
to the extent they can modify the current concept to align with the desired
market. Global market segmentation demands that companies identify
consumers in different countries who share similar needs and desires.
McDonald's Corporation is a fast food legend with prominent international
presence whose famous golden arches are said to be the second most recognized
3
symbol in the world, behind the Olympic rings (Keegan & Green, 2008a).
McDonald's global marketing strategy is based on a combination of global and
local marketing mix elements. A vital element in McDonald's business model is
a restaurant system that can be set up virtually everywhere in the world. It
offers a core menu items – hamburgers, French fries, and soft drinks – in most
countries, and it also customizes menu offerings in accordance with local
customs (Keegan & Green, 2008). McDonald's executives’ credit three strategies
for building sales in key European markets: up grading the customer and
employee experience, building brand transparency, and preserving local
relevance. In traffic-chocked cities from Manila to Montevideo, McDonald's
deploys fleets of motor scooters to get food to customers fast. In Taipei, the
company hires over 1,000 drivers. In Egypt, where the setup was pioneered in
1995, deliveries accounted for 27% to 80% of all McDonald's revenue (Arndt &
Ghobrial, 2007). India, with a soaring economy that is helping to create a huge
middle class, is emerging as the new China for American restaurant brands eager
to expand in Asia. McDonald's also has benefited for the past several years from
deriving strong earnings from its overseas markets, where it operates about half
of its 31,000 locations, a scope that offsets weakness in some markets (Adamy,
2009). Half of the new outlets planned for China in 2008 had drive-through
windows, as McDonald's seeks to further leverage China's status as the world's
fastest-growing major auto market and give itself an edge against rival, KFC,
which is far more popular in China (Fong, 2008).
As evident from the earlier examples, McDonald's does not only enjoy the
first mover advantage in many countries but is also involved in expansion. Their
proven success in identifying profitable markets has led many businesses to
closely observe and follow their patterns of market entry. Considering the lack
of precise instruments to assess foreign markets, this study was undertaken with
the following objectives: (a) assess the presence or absence of McDonald's
restaurants in different parts of the world; (b) correlate the number of
McDonald's in different countries with available indices measuring economical,
social, political, cultural, or environmental parameters; (c) use any correlation
with existing index or indices to identify potential factors for selecting foreign
markets; (d) identify possible expansion within existing markets; and (e) identify
potential foreign markets.
Methodology
Our first task was to collect the exact number of McDonald's in different
countries. As easy as it may sound, this was the most difficult task since it was
impossible to find this information in one publication. Efforts were made to
collect this from McDonald's corporate publications and contacts. Although we
were able to get regional or collective information, the country wide information
4
was incomplete, outdated, or unavailable. For several countries, direct contacts
were made to get as up to date information as possible. Data collected included
the number of McDonald's restaurants in different countries as well as the list of
countries where there are no existing restaurants.
Next task involved exploring different available indices that might
measure the business environmental conditions in different countries. Again the
problem was with the lack of current information, incomplete available
information about countries, and lack of data correlation capabilities. Analyses
were conducted using Hofstede’s Cultural Dimension rankings. One of the
drawbacks in using these rankings was that the current rankings were not
available and many countries where McDonald's exist were not included in
rankings. A review of the FSI (Failed States Index) published jointly by the Fund
for Peace organization (2009) and the magazine Foreign Policy, revealed the
existence of many of the usable parameters and reduced limitations of the earlier
indices. The Fund for Peace is an independent, nonpartisan research and
educational organization that works to prevent war and alleviate the conditions
that cause conflict. FSI index uses 12 indicators of state cohesion and
performance, compiled through a close examination of more than 30,000 publicly
available sources in ranking 177 states in order from most to least at risk of failure.
In this paper the words state (in italics) and countries are used interchangeable.
FSI (2009) consist of 12 indicators as follows:
Social Indicators:
I-1. Mounting Demographic Pressures:
•
•
•
•
I-2.
Pressures deriving from high population density relative to food supply and
other life-sustaining resources
Pressures deriving from group settlement patterns that affect the freedom to
participate in common forms of human and physical activity, including
economic productivity, travel, social interaction, religious worship
Pressures deriving from group settlement patterns and physical settings,
including border disputes, ownership or occupancy of land, access to
transportation outlets, control of religious or historical sites, and proximity to
environmental hazards
Pressures from skewed population distributions, such as a "youth or age bulge,"
or from divergent rates of population growth among competing communal
groups
Massive Movement of Refugees or Internally Displaced Persons
creating Complex Humanitarian Emergencies:
5
•
Forced uprooting of large communities as a result of random or targeted violence
and/or repression, causing food shortages, disease, lack of clean water, land
competition, and turmoil that can spiral into larger humanitarian and security
problems, both within and between countries
Legacy of Vengeance-Seeking Group Grievance or Group Paranoia:
I-3.
•
•
•
•
•
History of aggrieved communal groups based on recent or past injustices, which
could date back centuries
Patterns of atrocities committed with impunity against communal groups
Specific groups singled out by state authorities, or by dominant groups, for
persecution or repression
Institutionalized political exclusion
Public scapegoating of groups believed to have acquired wealth, status or power
as evidenced in the emergence of "hate" radio, pamphleteering and stereotypical
or nationalistic political rhetoric
Chronic and Sustained Human Flight:
I-4.
•
•
•
"Brain drain" of professionals, intellectuals and political dissidents fearing
persecution or repression
Voluntary emigration of "the middle class," particularly economically productive
segments of the population, such as entrepreneurs, business people, artisans and
traders, due to economic deterioration
Growth of exile communities
Economic Indicators:
Uneven Economic Development along Group Lines:
I-5.
•
•
•
Group-based inequality, or perceived inequality, in education, jobs, and
economic status
Group-based impoverishment as measured by poverty levels, infant mortality
rates, education levels
Rise of communal nationalism based on real or perceived group inequalities
Sharp and/or Severe Economic Decline:
I-6.
•
•
•
•
•
A pattern of progressive economic decline of the society as a whole as measured
by per capita income, GNP, debt, child mortality rates, poverty levels, business
failures, and other economic measures
Sudden drop in commodity prices, trade revenue, foreign investment or debt
payments
Collapse or devaluation of the national currency
Extreme social hardship imposed by economic austerity programs
Growth of hidden economies, including the drug trade, smuggling, and capital
flight
6
•
•
Increase in levels of corruption and illicit transactions among the general
populace
Failure of the state to pay salaries of government employees and armed forces or
to meet other financial obligations to its citizens, such as pension payments
Political Indicators:
Criminalization and/or Delegitimization of the State:
I-7.
•
•
•
•
Massive and endemic corruption or profiteering by ruling elites
Resistance of ruling elites to transparency, accountability and political
representation
Widespread loss of popular confidence in state institutions and processes, e.g.,
widely boycotted or contested elections, mass public demonstrations, sustained
civil disobedience, inability of the state to collect taxes, resistance to military
conscription, rise of armed insurgencies
Growth of crime syndicates linked to ruling elites
Progressive Deterioration of Public Services:
I-8.
•
•
Disappearance of basic state functions that serve the people, including failure to
protect citizens from terrorism and violence and to provide essential services,
such as health, education, sanitation, public transportation
State apparatus narrows to those agencies that serve the ruling elites, such as the
security forces, presidential staff, central bank, diplomatic service, customs and
collection agencies
Suspension or Arbitrary Application of the Rule of Law and Widespread
Violation of Human Rights:
I-9.
•
•
•
•
I-10.
•
•
Emergence of authoritarian, dictatorial or military rule in which constitutional
and democratic institutions and processes are suspended or manipulated
Outbreak of politically inspired (as opposed to criminal) violence against
innocent civilians
Rising number of political prisoners or dissidents who are denied due process
consistent with international norms and practices
Widespread abuse of legal, political and social rights, including those of
individuals, groups or cultural institutions (e.g., harassment of the press,
politicization of the judiciary, internal use of military for political ends, public
repression of political opponents, religious or cultural persecution)
Security Apparatus Operates as a “State Within a State”:
Emergence of elite or praetorian guards that operate with impunity
Emergence of state-sponsored or state-supported private militias that terrorize
political opponents, suspected "enemies," or civilians seen to be sympathetic to
the opposition
7
•
•
I-11.
•
•
I-12
•
•
Emergence of an "army within an army" that serves the interests of the dominant
military or political clique
Emergence of rival militias, guerilla forces or private armies in an armed struggle
or protracted violent campaigns against state security forces
Rise of Factionalized Elites:
Fragmentation of ruling elites and state institutions along group lines
Use of nationalistic political rhetoric by ruling elites, often in terms of communal
irredentism, (e.g., a "greater Serbia") or of communal solidarity (e.g., "ethnic
cleansing" or "defending the faith")
Intervention of Other States or External Political Actors:
Military or Para-military engagement in the internal affairs of the state at risk by
outside armies, states, identity groups or entities that affect the internal balance
of power or resolution of the conflict
Intervention by donors, especially if there is a tendency towards overdependence on foreign aid or peacekeeping missions
Evidently, FSI has detailed attributes for developing a comprehensive
index; hence it was used in this study. Each indicator is ranked from zero to ten,
with zero being the most stable and ten being the least stable. The sum of these
indicators is tallied for a total of FSI. The 2009 index results range from 18.3
(Norway) to 114.7 (Somalia); with Somalia being the most failed state. All 12
attributes for each country were analyzed for any correlation with the existing
number of McDonald's. The FSI ranks 177 states and includes only those that
have memberships in the United Nations. Some countries, such as Taiwan that
are recognized as sovereign by some states are excluded from the index until
their membership in the United Nations is ratified.
The strength of the FSI is in the fact that it is not limited to countries for
which statistics are available. Instead, the index is based on thousands of
electronic articles and reports that are processed by the Conflict Assessment
System Tool (CAST). CAST is a flexible model that has the capability to employ
a four-step trend-line analysis, consisting of (a) rating 12, social, economic, and
political/military indicators; (b) assessing the capabilities of five core state
institutions considered essential for sustaining security; (c) identifying
idiosyncratic factors and surprises; and (d) placing countries on a conflict map
that shows the risk history of countries being analyzed. CAST used a powerful
data-collection system that includes international and local media reports and
other public documents, including U.S. State Department reports, independent
studies, and even corporate financial filings. The data used in each index are
collected from January to December of the preceding year. The thoroughness,
general acceptance of the index, and being up-to-date, makes it appropriate for
8
our study. The following calculations and observations were used in analyzing
and presenting the data in tables and figures included in this paper.
Rank: refers to the ranking of the countries used in FSI and shows the
rank of the country among the 177 listed countries.
I-1 to I-12: refers to the number of attribute used in FSI.
McD Index: is calculated by taking the number of McDonald's in each
country and dividing by the population of that country and multiplying it
by 1,000,000.
# of McD: refers to the number of McDonald's restaurants in respective
country.
% Urban Pop: refers to the percentage of urban population in respective
country. This figure is obtained from the data provided in the World Fact
Book by the CIA (United States Central Intelligence Agency).
Pop count: is the number of individuals 0-14 years of age among the total
urban population of the respective country extracted and calculated from
the data included in the World Fact Book by the CIA.
McDensity: is calculated by dividing the number of McDonald's in a
respective country by Pop count and multiplying it by 100,000.
Pop/McD: is calculated by dividing Pop count by the number of
McDonald's in a respective country.
Statistical Analysis
McD index was used as the independent variable in order to account for
the variability based on the population. The reason why this index was
developed was to normalize the numbers. Simple numbers of restaurants were
not used since there were drastic population variances in each country. Taiwan
and Hong Kong are not part of the FSI and therefore the numbers have been
included as part of China. The United States was excluded from the list of
countries examined since it is the country of origin for McDonald's. Countries
with no McDonald's have been included in the study because they provide
relevant data. Of the 176 countries, 86 have zero McDonald's and 90 have at least
one McDonald's restaurant. Based on the preliminary analysis, countries with at
least one restaurant have a lower FSI than those with no McDonald's.
Additionally a box plot was created for the countries with zero McDonald's and
those with at least one McDonald's. The notches in the box plots did not overlap
9
further indicating that there is a statistically significant difference between the
two groups. For all the benefits mentioned for the selection of FSI, it was
selected as dependent variable. In order to assess the relationship between the
two variables, Spearman’s ρ was used. The Spearman’s ρ provides a measure of
correlation between two variables without making any assumptions on the
distribution of the variables. Its use is appropriate when either of the following
conditions are met (a) one variable is an ordinal scale and the other is an ordinal
scale or higher and (b) one of the distributions is markedly skewed. In this study,
both these conditions are met. The variables were made ordinal by ranking them
and the distribution shows that it is not normal and is skewed. Also Spearman’s
ρ is a ranked correlation coefficient and both variables are continuous. When the
correlation coefficient was at or above 0.4, the correlation between the variables
was considered to be significant. For most of the research in social sciences this
is considered to be a standard value. Microsoft Excel 2008 and SAS program,
JMP, were used for analysis.
Findings
The numbers of McDonald’s in each country were tabulated using FSI
listings. The overall expansion proceeded from the United States/Canada to
Europe and Australia during 1970-1974 and then expanded to selected South
American countries during 1975-1979. The rest of the expansion in Eastern,
South Asian, and Far Eastern countries, took place in 1990s. FSI 2009
distinguishes countries into four distinct groups (a) Sustainable; (b) Moderate; (c)
Warning; and (d) Alert. Countries were separated into each of these groups and
compared with the parameters discussed earlier as shown in separate tables later
on in this paper.
McD Index Versus FSI
The correlation between McD Index versus FSI was determined by
Spearman’s ρ analysis. The highest correlation was between the McD index and
“Public Services attribute” (I-8) at -0.8010 and the lowest correlation was for
“Legacy of Vengeance-Seeking Group Grievance or Group Paranoia” (I-3) at 0.4438. The values for each FSI attribute are shown in Table 1. The total
correlation for all attributes had a value of -0.7099. All correlations were found
to be above 0.4 and significant at <0001 level. This coefficient indicates that there
is a strong negative relationship between the two variables. Thus higher the FSI
index, the smaller the McD index. In other words, the worst off a country is, as
indicated by the FSI, the less presence of McDonald's restaurants. The
distribution shows increasing number of McDonald's restaurants with the
decrease in FSI values. After finding strong negative correlations between all the
attributes, the differences between social, economic and political indicators were
10
assessed. The results are shown in Table 1. Means were –0.5936 for social, 0.6636 for economical, and -0.6597 for political indicators. Since the greatest
correlation was found to be for economical indicators, I-5 and I-6 values were
used for further analyses.
Overall presence of McDonald's
The FSI lists countries with FSI scores ranging from 114.7 to 90.0 in a
group titled “alert;” those with scores between 89.8 and 60.1 as “warning;” those
with scores between 59.7 and 31.2 as “moderate;” and those with scores between
29.0 and 18.3 as “sustainable.” The number of McDonald's in all these group of
countries were assessed separately and are shown in respective tables. The most
noteworthy point is that there was no McDonald's presence in the countries with
“alert” status, except in Pakistan (22), Lebanon (17) Sri Lanka (4), and Georgia (3).
The FSI scores for these countries were 104.1; 93.5; 96.7; and 91.8 respectively.
Political unrest was seen during the past years in all these countries and most of
the restaurants opened before occurrence of the current problems. For further
analysis “alert” countries were not included due to their status and relatively
higher FSI scores.
One of the problems associated with using the total population of a
country is that McDonald's restaurants are exclusively located in highly
populated urban cities whereas some countries have large rural population. The
percentage of urban population was therefore used in this study based on the
data provided by CIA’s World Fact Book. The next consideration involved the
selection of the age of the population. The age structures given for the
population in the World Fact Book included groups between 0-14 years; 15-64
years; and 65 years and older. Population representing 0-14 years was selected
since this would be the most likely target market for McDonald's. The numbers
in this age group were calculated from the percentage of urban population and
used for further analysis.
McDonald's and “Sustainable” status Countries
With lower FSI scores these countries represent the most preferred
markets for business. However there may be over saturation of businesses due
to the smaller size of the population. The average for economical indicators was
found to be 5.0 (Table 2). The McD Index for this group of countries was 21.52
which is the highest among countries in all groups. This might be an indication
of market saturation due to the smaller size of the population in these countries,
although there is a high percentage of urban population with an average of 78%.
The value for McDensity is 15.61, which is also very high compared to countries
in other groups. The pop/McD value is 7,991; which means that on an average
11
there is one McDonald's restaurant for every 7,991 individuals. Considering this
ratio, there seems to be a very limited scope for further expansion, except for
some opportunities in Denmark and Luxembourg, where the economic indicator
scores are also low. Canada has the largest density of restaurants compared to
the size of the population in that age group. Netherlands can also be a good
candidate for expansion, however, the economical indicators scores are above
average. Australia and New Zealand also have high restaurant density.
According to the news reports the three McDonald's restaurants in Iceland were
recently closed. Some of the figures in the table are in bold to highlight points
discussed in this paper. Most of the countries in this group belong to the
European Union.
McDonald's and “Moderate” status Countries
Table 3. lists the countries listed as “moderate” by FSI. These countries
have varying degree of economical indicator scores with an average score of 8.7
which is higher than the average for “sustainable” countries. All countries in this
group except Montenegro and Barbados have at least one McDonald's restaurant.
Montenegro has favorable economical indicator scores and can accommodate
few restaurants; whereas Barbados may not due to limited population. Average
McD Index for this group of countries is 10.09, which is lower than that for
“sustainable” countries group. The average number of McDonald's restaurants
in this group is 322 and McDensity is 7.80. This group has a high percentage of
urban population. Based on the population count and the number of
McDonald's, the countries which have the potential for expansion are Belgium,
Chile, Uruguay, South Korea, Mauritius, Argentina, Oman, Lithuania, Slovakia,
and Latvia. Figures for these countries are presented in bold in Table 4.
Considering the scores for economical indicators, the most promising country is
Oman, which has combined economical indicator score of 2.11. Other countries
with considerable economical scores include Belgium, Chile, and South Korea. It
is advisable to look at the economical scores in relation to the number of
McDonald's per population. This group of countries should be considered for
expansion since there are some countries which have good business potential.
McDonald's and “Warning” status Countries
Values for countries listed under “warning” status which does have at
least one McDonald's restaurant are presented in Table 4. This group lists
countries some of which are rapidly developing and therefore deserve careful
consideration for market entry. Since there is considerable variability in figures,
median values and total scores of all 12 attributes are presented in this table. The
average of economical indicator scores is 13.7 with a median of 14; whereas the
average for all 12 attributes is 76.0 with a median value of 78.3. There was a wide
12
variation among McD Index with an average of 3.35 and median value of 1.56.
This difference is due to the fact that some countries have only one McDonald's
restaurant. Countries that deserve consideration for expansion include Paraguay,
Peru, Morocco, Dominican Republic, India, Cuba, Ecuador, Belarus, Indonesia,
Azerbaijan, Egypt, and Columbia. China is included in this group but
considering the existing number of restaurants they seem to be reaching
saturation level. Countries that should be considered carefully for expansion
include India, Indonesia, Egypt, Paraguay, Columbia, Morocco, Dominican
Republic and Azerbaijan, since there are some good potential growth indicators.
“Warning” status Countries with no McDonald's
Countries classified under “Warning” status with currently no
McDonald's are listed in Table 5. Potential and prospects of market entry into
these countries were assessed taking into consideration economical indicators;
total of social, economical, and political indicators; percent urban population;
and population count. The median and average values obtained for countries
listed under this group as shown in Table 4 were used for comparison. Figures
in bold represent values that need consideration. The intent was to examine the
potential for McDonald's entry into these countries based on the parameters used
for this group of countries. Using the median value of 14.0 for economical
indicators, countries with lesser values were highlighted. Similarly for the total
of all indicators the median value of 78.3 was used. For minimum required
urban population 67% was considered. For population count the cut-off point
selected was 79,708. Considering the economical indicators, total of all indicators,
and percentage of population, the countries which deserve consideration for
market entry include Tunisia, Libya, and Gabon. Vietnam has good scores for
attributes and large population but less percentage of urban population. Other
countries which have good economical scores and large population are Algeria,
Tanzania, Madagascar and Laos. Countries with considerably good economic
scores but fair size of population include Turkmenistan and Mauritania. It
should be taken into account that even though the percentage of urban
population may be low there may be concentration of population in urban cities.
By carefully considering all factors markets can be selected from the list of these
countries.
Conclusion
The most important conclusion that can be drawn from this study is that
the FSI can be a good effective tool for comparing different countries for market
entry. Classification used by FSI can be used to select countries from a particular
group. Although McDonald's is used in analysis the indices can be used for any
type of businesses for global entry, particularly those that are service-oriented.
13
Since there may be saturation in the “sustainable” group of countries, other
groups should be considered, which include several up and coming countries
from the economical, social, and political point of view. Although younger
population is used in this study due to the food business, other age groups can
be used for analysis. A stepwise approach can be used in the selection of
countries by looking at total scores, economical scores, total population and
percentage of total population.
Limitations
One of the limitations of this study is that cultural, technological and
environmental attributes are not included in the FSI. Also, information for
countries included in the FSI is based on published information during the year;
there is a chance of countries that are not prominently used in publications, from
getting excluded. Also, only countries which belong to the United Nations are
used for FSI. The political age of the countries is not taken into consideration
thereby the newly formed states may be at a disadvantage. The information
available is time bound and can change drastically with circumstances. Changes
in political situations can adversely affect the conclusions drawn in this study.
Country profiles in light of the discussion could not be included due to the
limited scope of this study.
Assumptions made regarding the age of the selected population and
percentage of urban population may not be accurate for some countries,
particularly where there is a relatively heavy concentration of urban population
such as in large cities. Based on the available information and limitations, all
efforts were made to provide useful information in this paper.
14
Table 1. Overall and Individual values and averages for Social, Economic, and
Political Indicators
15
Table 2. Presence of McDonald's restaurants in countries classified as “Sustainable” by FSI Index 2009
68
% Urban
Pop.
77
15.63
82
63
25.76
233
85
4.6
19.39
147
73
173
5.0
18.05
75
172
4.2
15.13
171
6.5
34.26
170
5.5
37.23
169
5.4
13.16
168
3.7
167
6.0
Canada
166
Iceland
165
Country
Norway
Finland
Sweden
Switzerland
Ireland
Denmark
New Zealand
Australia
Netherlands
Luxembourg
Austria
AVERAGE
Rank
I-5 + I-6
177
3.3
McD
Index
14.64
176
4.0
175
4.3
174
# of
McD
Pop.
Count
664,940
McDensity
Pop/McD
10.20
9779
542,557
15.10
6,617
1,211,922
19.20
5,201
867,365
16.90
5,900
61
535,942
14.00
7,146
83
87
867,968
9.60
10,457
143
87
758,376
18.90
5,303
782
89
3,516,215
22.20
4,496
219
82
2,380,355
9.20
10,869
14.40
7
82
74,595
9.40
10,656
19.74
162
67
797,898
20.30
4,925
6.8
42.57
1414
80
4,310,838
32.80
3,049
5.7
9.86
3
92
58,490
5.12
19,497
5.0
21.52
262
78
1,275,959
15.61
7,991
Table 3. Presence of McDonald's restaurants in countries classified as “Moderate” by FSI Index 2009
Country
Japan
Portugal
Belgium
United Kingdom
Singapore
France
Germany
Slovania
Chile
Uruguay
South Korea
Czech Republic
Spain
Italy
Mauritius
Argentina
Greece
Oman
Lithuania
Slovakia
Rank I-5 + I-6
McD Index
# of
McD
% Urban
Pop.
Pop. Count
McDensity
Pop/McD
164
4.5
29.50
3,755
66
11,318,514
33.17
3,014
163
162
161
160
158
157
156
155
154
153
152
151
6.2
6.2
7.6
5.7
7.7
7.7
8.7
6.5
11.0
7.4
8.8
6.9
11.80
5.57
19.53
23.65
18.58
16.18
7.47
4.25
6.33
4.82
7.63
9.73
59
97
90
100
77
74
48
88
92
81
73
77
1,030,782
1,629,286
9,197,898
672,432
9,215,864
8,316,773
130,419
3,382,702
720,539
6,614,539
1,011,562
4,515,603
12.22
3.55
12.93
16.20
12.30
14.46
11.50
2.06
3.05
3.52
7.71
8.72
8,181
28,091
7,729
6,169
8,127
6,239
8,695
48,324
32,752
28,389
12,969
11,461
150
149
148
147
146
145
144
7.7
8.3
9.5
9.5
3.6
11.4
11.2
6.54
0.78
4.59
4.10
2.11
1.68
2.93
126
58
1,190
109
1,134
1,333
15
70
22
233
78
394
380
1
186
44
7
6
16
68
42
92
61
72
67
56
5,351,754
121,488
9,652,398
933,905
1,050,034
337,370
483,965
7.10
0.82
1.77
4.71
0.66
1.77
3.30
14,084
121,488
51,895
21,225
150,005
56,228
30,248
17
Country
Malta
Poland
Hungary
Estonia
UAE
Qatar
Costa Rica
Latvia
Barbados
Montenegro
Bahrain
Panama
AVERAGES
Rank I-5 + I-6
143
142
141
140
139
138
137
136
135
134
133
132
McD Index
# of
McD
% Urban
Pop.
8.9
11.0
11.1
9.4
9.0
8.6
11.4
11.2
14.1
7.1
9.6
12.3
19.82
5.74
9.97
5.35
12.77
20.61
7.39
2.67
8
221
99
7
59
17
31
6
19.49
11.18
14
37
94
61
68
69
78
96
63
68
40
60
89
73
8.7
10.09
322
73
18
Pop. Count
McDensity
Pop/McD
61,388
3,518,037
1,008,892
133,721
763,866
174,571
716,393
202,390
21,894
64,495
167,734
718,101
13.03
6.28
9.81
5.23
7.72
9.73
4.32
2.96
7,673
15,919
10,191
19,103
12,947
10,269
23,109
33,372
8.34
5.15
11,981
19,408
2,601,228
7.80
27,310
Table 4. Presence of McDonald's restaurants in countries classified as “Warning” by FSI Index 2009
Rank
I-5 +
I-6
I-1 to I-12
McD
Index
Croatia
Bahamas
Romania
Bulgaria
Kuwait
South Africa
Brunei
Darussalam
Malaysia
Cyprus
Brazil
Ukraine
Samoa
Paraguay
131
130
129
128
125
122
10.3
12.6
10.9
12.3
10.4
12.8
60.1
60.9
61.3
61.5
63.4
67.4
3.56
13.01
2.61
3.30
18.87
2.56
16
4
58
24
49
125
118
11.8
68.1
2.62
115
114
113
110
108
106
10.7
13.0
13.9
13.5
15.0
13.9
68.9
68.9
69.1
69.7
71.4
72.0
7.28
20.19
2.86
1.41
13.82
0.88
Suriname
Macedonia
Mexico
Peru
Morocco
Honduras
El Salvador
Saudi Arabia
Dominican
103
100
98
93
92
91
90
89
88
14.8
14.2
15.2
15.5
14.0
14.8
14.7
10.4
16.5
73.2
74.4
75.4
77.1
77.1
77.2
77.2
77.5
77.7
2.10
1.46
3.45
0.65
0.64
1.18
1.42
3.91
0.84
Country
# of
McD
%
Urban
Pop.
Pop. Count
McDensity
57
84
54
71
98
61
398,121
67,237
1,865,226
705,996
695,475
8,634,493
4.01
5.94
3.10
3.39
7.04
1.44
24,883
16,809
32,159
29,416
14,193
69,076
1
75
77,567
1.28
77,567
184
16
561
65
3
6
1
3
379
19
22
9
10
110
8
70
70
86
68
23
60
5,648,008
106,785
45,713,406
4,287,314
19,026
1,538,805
3.25
14.98
1.22
1.51
15.76
0.38
30,696
6,674
81,486
65,959
6,342
256,468
75
67
77
71
56
48
61
82
69
97,979
266,263
24,952,130
6,096,974
5,860,558
1,423,875
1,552,587
8,936,415
2,091,498
1.02
1.12
1.51
0.31
0.37
0.63
0.64
1.23
0.38
97,979
88,754
65,837
320,893
266,388
158,208
155,259
81,240
261,437
19
Pop/McD
Country
Republic
India
Jordan
Turkey
Fiji
Thailand
Serbia
Venezuela
Guatemala
Cuba
Russia
Ecuador
Belarus
Nicaragua
Indonesia
China
Azerbaijan
Moldova
Philippines
Egypt
Colombia
AVERAGES
MEDIAN
Rank
I-5 +
I-6
I-1 to I-12
McD
Index
# of
McD
87
86
85
81
79
78
77
76
74
71
69
66
64
61
57
56
54
53
43
41
15.6
12.4
13.0
14.2
12.2
12.9
14.9
14.9
14.0
14.3
15.3
12.2
15.0
15.3
15.3
13.1
15.0
14.8
13.8
17.0
77.8
77.9
78.2
78.8
79.2
79.2
79.5
80.6
80.6
80.8
81.2
82.3
82.6
84.1
84.6
84.6
85.1
85.8
89.0
89.2
0.14
2.10
1.61
3.22
1.76
1.38
5.15
5.23
0.09
1.50
1.15
0.62
0.69
0.45
1.15
0.61
0.92
2.99
0.59
0.87
161
13
116
3
115
14
136
68
1
211
16
6
4
108
1570
5
4
287
48
39
13.7
14.0
76.0
78.3
3.35
1.56
109
21
%
Urban
Pop.
20
Pop. Count
McDensity
Pop/McD
29
78
69
52
33
52
93
49
76
73
66
73
57
52
43
52
42
65
43
74
105,233,740
1,550,422
14,438,174
149,060
4,521,434
591,087
7,607,204
2,566,161
1,594,585
15,140,086
2,991,772
1,003,830
578,705
35,099,764
11,402,216
1,023,686
288,997
22,436,523
11,218,432
9,769,980
0.15
0.83
0.80
2.01
2.54
2.36
1.78
2.64
0.06
1.39
0.53
0.59
0.69
0.30
13.76
0.48
1.38
1.27
0.42
0.39
653,626
119,263
124,467
49,687
39,317
42,221
55,935
37,737
1,594,585
71,753
186,986
167,305
144,676
324,998
7,263
204,737
72,249
78,176
233,717
250,512
63
67
8,815,276
1,978,362
2.50
1.25
158,737
79,708
Table 5. Countries classified as “Warning” by FSI Index 2009 with no
McDonald's restaurants
Country
Mongolia
Antigua and Barbuda
Ghana
Trinidad
Tunisia
Seychelles
Grenada
Jamaica
Botswana
Libya
Belize
Albania
Micronesia
Kazakhstan
Guyana
Senegal
Armenia
Gabon
Benin
Namibia
Sao Tome
Vietnam
Cape Verdi
Mali
Maldives
Gambia
Djibouti
Algeria
Mozambique
Tanzania
Madagascar
Lesotho
Swaziland
Bosnia
Papua New Guinea
Zambia
Turkmenistan
Angola
Rank I-5 + I-6
127
126
124
123
121
120
119
117
116
112
111
109
107
105
104
102
101
99
97
96
95
94
84
83
82
80
75
73
72
70
68
67
65
63
62
60
59
55
8.1
14.3
14.7
14.7
12.5
11.5
14.7
13.0
13.2
11.1
14.2
13.1
15.3
10.4
15.8
13.1
13.2
13.8
14.4
16.8
13.4
12.5
14.4
14.3
12.2
13.4
13.5
13.3
15.0
12.9
12.6
12.1
12.0
13.1
16.5
14.1
13.2
14.9
I-1 to I-12
61.9
62.8
66.2
66.7
67.6
67.7
67.9
68.6
68.8
69.4
69.5
70.0
71.9
72.5
73.0
74.2
74.3
74.4
75.5
75.6
76.7
76.9
78.5
78.7
78.8
79.0
80.6
80.6
80.7
81.1
81.6
81.8
82.4
83.3
84.1
84.2
84.3
85.0
% Urban
Pop.
57
30
50
13
67
54
31
53
60
78
52
47
22
58
28
42
64
85
41
37
61
28
60
32
38
57
87
65
37
25
29
25
25
47
12
35
49
57
Pop. Count
487,529
6,889
4,448,218
31,304
1,592,612
10,764
8,996
470,521
415,474
1,626,032
60,621
395,432
8,232
1,949,606
55,671
2,431,434
346,412
542,675
1,630,507
280,076
60,794
6,063,205
90,603
1,956,079
33,565
443,447
194,426
5,652,608
3,552,918
4,414,835
2,605,217
185,358
110,710
313,990
268,459
1,870,720
691,351
3,175,701
Country
Comoros
Bolivia
Togo
Cambodia
Bhutan
Equatorial Guinea
Mauritania
Rwanda
Laos
Kyrgyzstan
Solomon Islands
Syria
Rank I-5 + I-6
52
51
50
49
48
47
46
45
44
42
39
40
I-1 to I-12
86.3
86.3
87.2
87.3
87.3
88.3
88.7
89.0
89.0
89.1
89.6
89.8
12.3
15.6
14.4
15.2
15.5
16.4
12.0
14.5
12.6
15.8
13.0
14.8
22
% Urban
Pop.
28
66
42
22
35
39
41
18
31
36
18
54
Pop. Count
88,859
2,289,576
1,049,177
1,039,579
73,001
103,401
525,714
794,282
863,848
580,159
42,300
3,906,874
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