Expanding Direct Marketing in Emerging Markets:Methodological Approach and Cultural Value Analysis

Richard MICHONTed Rogers School of Management, Ryerson University, Toronto

Atul TANDONCEO, Tandon Institute, Bellevue, WA

Outline

Managerial Issues Literature Review Research Objectives Method

Economic Model Cultural Value Model

Discussion Conclusions, Limitations …

DM in Emerging Markets: Why not?

Brazil, China, Indonesia, South Korea and Russia will account for more than half of all global growth by 2025 (Sommerville, 2011).

New wealth and new middle class Fund raising: Some countries are in a position to

give back Few companies are stupid, but many behaved

stupidly in China (The Economist, 1999) Lack of marketing infrastructure Macroeconomic data but not no product/market info. Imperialist approach

Literature Review

Emerging Market Research:

Economics

Macro-economic Indicators

Overall Market Opportunity Index (Cavusgil, 1997)

Comparing GDPs at PPP (Arnold & Quelch (1998) • Q = (P+NP) X (DevGDP – AdjGDP)

Emerging Market Research:

Sociology/Culture

CAGE (Ghemawat & Mallick, 2003): Cultural, Administrative, Geographic, Economic distances

Value Survey Module (Hofstede, 2001): Cultural distances: Power, uncertainty avoidance, individualism/collectivism, masculinity/feminity, time orientation

GLOBE (House et al., 2004): Global Leadership and Organizational Behavior Effectiveness

WVS (Inglehart & Welzel, 2005)

Emerging Market Research:

Issues with Cultural Values

Measuring values or preferences? (Maseland & van Hoorn, 2009)

Some abstract constructs difficult to measure

Values should correlate with practices: negative correlations between VSM and GLOBE

WVS: 84 countries (80% of population), 250 variables, constantly updated, data at individual level, N = 270,000

Emerging Market Research:

Marketing

Product-market subset

Business Model Success factors (Arnold, 2003)

Example:Based on Mary Kay business model, Chinese women were far more motivated than Japanese to become « beauty consultants » and pocket extra income.

DM and Fundraising

“Generosity” index (e.g. CAF)

ODA & global private philanthropy (Hudson Institute)

Cultural clusters (Johns Hopkins’ NPS, 2004) European Vs Anglo-Saxon countries

DM and Fundraising:OECD Donor Countries

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Remittances

Private Giving

ODA

Source: Hudson Institute

DM and Fundraising:Donor Profiles

Compassionate conservative philanthropy (Brooks, 2006) They are politically to the right;

They have strong family values;

They value personal entrepreneurship;

They are skeptical about governments’ intervention into economic life (and into income redistribution);

They are regular churchgoers (irrelevant of denomination).

Research Objectives and Methodology

Research Methodology:

Objectives and Assumptions

Identify new or neglected potential markets for DM fundraising programs

1. Capacity to give (Economic Analysis)2. DM Infrastructure to give (Documentary Analysis)3. Propensity to give (Predictive Modeling)

Research proposition: Individuals ready to support private philanthropy share

some common values

Research Methodology:

Setting

Empirical research:

Christian NGO raising funds in 25 countries

Exploring some 130 new markets for DM expansion

Successful DM Fundraising Markets: Australia, Canada, Germany, New Zealand, South Korea, Switzerland, Taiwan, the UK, the U.S.

Capacity to Give

Capacity to Give

Population estimate

% of urban population

Average household size

Number of urban households

Estimate hhold income

GDP per capita

GDP per household

Hhld spending as % of GDP

Household income

Estimate potential market

% income distribution per decile/quintile

Average incomeper decile/quintile

Define hhld income threshold

Hhld penetration assumptions over 5 years

Estimate number of potential donors

Estimate potential income

Estimate urban households

Estimate hhlds by income

Sources: World Bank Development Indicators CIA World Factbook

Capacity to Give:Hhlds with Income Threshold > $20K

Rank Country World Bank Classification Potential Hhlds (000) Annual Potential Mkt Growth Rate

1 S. Korea High income 7,194 4%2 Brazil Latin America 6,236 3%3 Sweden High income 2,994 3%4 Argentina Latin America 1,996 10%5 Russia Europe & C. Asia 1,863 6%6 India South Asia 1,798 10%7 Poland Europe & C. Asia 1,493 3%8 Indonesia E. Asia & Pacific 1,442 7%9 Greece High income 1,304 4%

10 Colombia Latin America 1,049 7%11 Venezuela Latin America 1,029 11%12 Peru Latin America 952 8%13 Malaysia E. Asia & Pacific 694 7%14 Iran M. East & N. Africa 671 8%15 Thailand E. Asia & Pacific 490 5%16 Hungary Europe & C. Asia 488 4%17 Iraq M. East & N. Africa 348 -%18 Lebanon M. East & N. Africa 330 1%19 Czech Rep. Europe & C. Asia 316 6%20 Romania Europe & C. Asia 277 4%21 Guatemala Latin America 263 6%22 N. Korea E. Asia & Pacific 260 2%23 Ecuador Latin America 240 6%24 El Salvador Latin America 205 5%25 Slovenia High income 198 4%

DM Infrastructure

DM Infrastructure

Infrastructure Telephone mainlines per 1000 habitants Cellular mobile subscribers per 1000 Number of PC's per 1000 Internet servers per million Percentage of households with TV sets Daily newspapers per 1000 (Source: World Bank, Development Indicators)

Economic Freedom: Economic Freedom Index (Source: Heritage Foundation) Political Freedom Index (Source: Freedom House)

Country Risk: Country risk rating (Source: Euromoney)

DM Infrastructure:Ranking of Latin/S. American Markets

Infrastructure Economic Freedom Country Risk All Countries Region All Countries Region All Countries Region

LATIN & SOUTH AMERICA

Chile 48 1 8 2 39 1Mexico 50 3 20 4 42 2Costa Rica 49 2 28 6 53 3Brazil 51 4 44 9 54 4El Salvador 74 10 36 7 56 5Colombia 61 7 59 14 58 6Peru 85 14 15 3 59 7Guatemala 80 12 51 11 67 8Venezuela 65 9 2 1 80 9Bolivia 77 11 71 16 84 10Honduras 81 13 45 10 85 11Dominican Republic 64 8 40 8 87 12Argentina 52 5 51 11 89 13Ecuador 55 6 58 13 95 14Nicaragua 92 15 20 4 107 15Haiti 97 16 69 15 117 16

Propensity to Give

Propensity to Give:Target Markets

Australia Canada Germany New Zealand South Korea

Switzerland Taiwan United Kingdom United States

Propensity to Give:

Selected Indicators

Familism: Family is very important in life Importance of child obedienceChild needs a home with father and motherDivorce is never justifiable

Religiosity: Religion is very important in lifeBelong to a religious organizationSpend time at church, mosque or synagogue weeklyConsider myself as a religious person

Government: People should take more responsibilityGovernment doing enough or too much against povertyGovernment doing enough or too much for less developed countries

Entrepreneurship Owners should be able to run their businessWe need larger income differences as incentivePrivate ownership of business should be increasedWealth can grow so there’s enough for everyone

Conservatism Self positioning on the political scalePeople are poor because of laziness and lack of will power

Source: Brooks (2006)

Propensity to Give: Logistic Regression and Odds Values

FAMILISM

Family is very important in life 1.117Importance of child obedience .929Child needs a home with father

and mother .871Divorce is never justifiable 1.114

RELIGIOSITY

Religion is very important in life .867Spend time at church, mosque

or synagogue weekly 1.026Consider myself as religious

person .955

CAPITALISM

Owners should be able to run their business 1.084

We need larger income differencesas incentive .950

Private ownership of business should be increased 1.117

Wealth can grow so there’s enoughfor everyone 1.161

CONSERVATISM

Conservative: Self positioning onthe political scale .933

People are poor because of lazinessand lack of will power 1.057

RankingCanada 1New Zealand 2Denmark 3China 4Austria 5Switzerland 6Australia 7Ireland 8United States 9United Kingdom 10Taiwan 11Czech Republic 12S Korea 13Germany 14Finland 15Belgium 16Japan 17Israel 18Malta 19Portugal 20Norway 21Netherlands 22Croatia 23Estonia 24Sweden 25

Propensity to Give: Top 25 Markets

Market Map:Capacity and Propensity to Give

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Ranking on countries economic market potential

1112131415161

1

11

21

31

41

51

61

Argentina

AustraliaAustria

Belgium

Brazil

Canada

Chile

China

Colombia

Croatia

Czech Republic

Denmark

Dominican Republic

El Salvador

Estonia

Finland FranceGermany

Greece

Hungary

India

Indonesia

IranIraq

Ireland

Italy

Japan

Jordan

Latvia

Lithuania

Malta

Mexico

Netherlands

New Zealand

Norway

Peru

Philippines

Poland

Portugal

RomaniaRussia

S Korea

Serbia and Mon-tenegro

Singapore

SlovakiaSlovenia South Africa

Spain

Sweden

SwitzerlandTaiwan

Turkey

United Kingdom

United States

Venezuela

III

IVIII

Discussion:Multi-criteria Decision Analysis

Country Capacity Top 5% Propensity Infra- Freedom Risk Weighted to Give Income to Give structure Score

Weights 30% 5% 35% 15% 5% 10% 100%

S. AmericaMexico 5 4 3 3 2 3 72Chile 3 3 3 3 5 3 62Argentina 4 3 3 2 2 1 58Venezuela 4 3 3 2 1 1 57Colombia 4 3 2 2 2 2 53Peru 3 3 3 1 2 2 51Dominican R. 2 2 3 2 2 145El Salvador 2 3 2 1 3 2 39Costa Rica 2 3 1 3 3 2 38Ecuador 2 2 1 2 1 1 30Guatemala 2 3 1 1 1 2 30Bolivia 1 2 1 1 1 1 21Honduras 1 1 1 1 2 1 21Nicaragua 1 1 1 1 2 1 21

AsiaChina 5 1 5 2 1 3 79India 4 1 3 1 2 2 55Indonesia 4 1 3 1 2 2 55Philippines 3 1 3 2 2 2 52Malaysia 3 2 1 3 1 3 43Thailand 3 1 1 3 1 2 40

Discussion:Fund Raising Markets

Weberian Capitalism (Weber, 1904) Protestant Ethic and the Spirit of Capitalism (Weber,

1904) Private philanthropy PE SC MWC IR (Lesnoff, 1981)

Secularization of PE (Carroll, 2009) Asian Drama: An Inquiry into the Poverty of Nations

(Myrdal, 1968): Hindu fatalism, Confucian hierarchy, Buddhist indifference material gains

Confucian capitalism (Fukuyama, 1995; Lew, Choy & Wang, 2011)

Conclusions, Limitations and Future Research

Contribution to methodology Importance of cultural values and predictive validity Multi-attribute and structured approach as decision

support models

Caveat: Western business model Modeling and human judgment Nonprofits’ core values and compromises