School of Business

A210A0200 Empirical Strategy Research

Kaisu Puumalainen & Ari Jantunen

Impact of Social Enterprises in Health Issues We would like to take part in the final seminar on Tuesday 21.4. because of Elina’s

mother’s 50th birthday on the 22.4.

0423635 Krystsina Selviasiuk

0423583 Elina Innanen

Table of Contents

1 Introduction ............................................................................................................................................... 4

2 Literature review ....................................................................................................................................... 5

1.1 Differences according to geographical region and metaphors ......................................................... 7

2.1 Measurement of performance .......................................................................................................... 8

3 Methodology ........................................................................................................................................... 10

4 Results ..................................................................................................................................................... 12

5 Discussion and Conclusions ..................................................................................................................... 21

REFERENCES..................................................................................................................................................... 23

3

List of Figures

Table 1 Regions of impact ............................................................................................................................ 11

Table 2 Focus of Groups .................................................................................................................................. 12

Table 3 Amount of beneficiaries classified by focus of the project ................................................................ 12

Table 4 Amount of beneficiaries classified by region of impact .............................................................. 13

Table 5 Frequency for region of impact ...................................................................................................... 14

Table 6 Frequency for the focus of the project. ......................................................................................... 15

Table 7 Equality of variances ....................................................................................................................... 16

Table 8 Variances are equal ......................................................................................................................... 17

Table 9 Differences between genders ........................................................................................................ 18

Table 10 ANOVA test for Regions of Impact .............................................................................................. 18

Table 11 ANOVA test for Focus of the Project .......................................................................................... 19

Table 12 Bartlett’s test of homogeneity for amounts of beneficiaries variable ...................................... 19

Table 13 Welch’s test for number of beneficiaries variable ..................................................................... 19

Table 14 Mean comparison between different countries of origin for dependent variable ................. 19

Table 15 Bartlett’s test of homogeneity of number of beneficiaries classified by region of impact ... 20

Table 16 Welch’s test for number of beneficiaries .................................................................................... 20

Table 17 Mean comparison between different regions of impact for dependent variable................... 20

Table 18 The variance of dependent variable............................................................................................ 21

List of Figures

Figure 1 Regions of impact ........................................................................................................................... 15

Figure 2 Focus of the project ........................................................................................................................ 16

4

1 INTRODUCTION

Many developing countries are struggling with issues such as social and political instability and

criminality due the insufficient governance and poor planning of future within them. These countries

have been aided by charities and philanthropy organizations for years but this is not the only and

perhaps not the most efficient way to gain sustainable growth and stability in these places. (Knife

et al. 2014, 1-2) Although social enterprise have some commonalities with charities they are not

unnecessary, however. Both types of organizations strive to tackle social issues voluntarily and at

least in most cases both also receive external funding to aid with the reaching of their goals.

However, there are also significant differences. For example the idea of social enterprises is to

generate sustainability and actual changes in the ways in which a society functions whereas

charity often offers on “band-aids” to the problems and thus creates dependency. For the wellbeing

of societies social enterprises are thus much more important than charities. (Acs et al. 2013, 795)

The fishing metaphor or feeding the hungry explains this difference quite well. The charity is only

gives the hungry some fish which solves the short term problem of being hungry but creates no

sustainable solutions. The social enterprise on the other hand teaches the hungry how to fish

which not only solves the problem of hunger today but also gives the hungry tools to remove the

problem in the future. Not only can the hungry no aid themselves by eating the fish, they can also

generate income by selling the left over catch. Thus the benefit of teaching one how to fish is

exponentially larger to giving one fish.

Moreover, it is valuable to note that the core need for social entrepreneurship rises from the

inadequacy of market power and governments in meeting societies’ social needs. Therefore it does

not matter whether a country is considered developing or developed, the social stability and

wellbeing is always important for it to function properly. The existence and presence of social

enterprises is not only meaningful in developing countries but in all economies. (Kostetska &

Berezyak 2014, 569)

The academic understanding of social enterprises is vast and includes many themes and topics.

However, individual themes may only be supported by a handful of studies that are not

generalizable or comparable with other studies due to the nature of the samples they use.

Therefore no clear and unanimous theory can be built on the existing studies. (Hoogendoorn et al.

2010, 32)

The significance of social enterprises, however, has been noted for decades and their role has

been growing both in Europe and the United States. Their popularity has grown since the 80’s in

both continents. (Kerlin 2006, 247-248) Although social entrepreneurship is not a new topic and it

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has been researched and written about for years there are still many gaps in the research. The

measurement of effectiveness or productivity of social enterprises and projects has been

discussed and studied widely (Urban 2013, 17; Young & Lecy 2014, 1309; Knife et al. 2014, 2) but

empirical research of social enterprises is still taking the baby steps. Not only is the amount of

studies low but the variation between them is also low. Studies conducted are mostly based on

secondary data and are quite narrow. (Hoogendoorn et al. 2010, 31)

In this research we aim to look at how successful social enterprises are in achieving their goals of

improving various social issues. We use the amount of people affected as the measure of success.

Further it is studied whether there is differences in the effectiveness of the enterprises depending

on their place of origin or the gender of the entrepreneur behind the enterprise.

Although there is variation in the group of companies involved in our study they also have the

commonality that all of them have been established to benefit some social issue. Even more all of

them have listed to be involved in the improving health issues somehow, although this may be just

one of their goals and they may have many others as well.

2 LITERATURE REVIEW

Even though the term “social entrepreneurship” is widely discussed there still is no singular

definition of it (Certo & Miller 2008, 268; Young & Lecy 2014, 1308-1309). A simple definition of a

social enterprise is to view them as business like or non-governmental methodologies to tackle

social problems or concerns. (Kerlin 2006, 247-248) Just like commercial entrepreneurship social

entrepreneurship may stem for an idea of any individual. The difference is that the idea of a social

entrepreneurs has to do with bettering the lives of others in some manner and creating social

value. These ideas may be utilized locally or scaled to many locations. (Westley & Antadze 2010,

2)

Social value is not equivalent or comparable to monetary value or profit. It refers to meeting the

elementary needs of human beings, such as need for nutrition, education and a roof over one’s

head. (Certo & Miller 2008, 267) Many have studied the creation and measurement of social value

(Clark & Brennan 2012, 17-18). There are many variations in how this social value is created. In

Europe the production of products or services already involves the social value creation trough

employment of disabled or otherwise lesser qualified people. In other words the social value is not

necessarily created through distributing products that bring it but already in the production phase.

(Defourny & Nyssens 2010, 45)

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However, there is no clear understanding of what is a social cause and to what degree it has to be

tackled to earn the right to call oneself a social entrepreneur. The same vagueness goes for the

profitability of a social enterprise. How is financial success in this context defined and how must it

be achieved? How should the prioritizing between these two aspects happen i.e. to what degree

the enterprise should concentrate on the social issues compared to being profitable? (Young &

Lecy 2014, 1309)

Social enterprise as a term is not equal to a non-profit although that is one form of a social

enterprise. Mostly it is agreed, however, that social enterprises combine aspects from both non-

profit and for-profit actors. Further definitions of social enterprises vary greatly and there is no clear

understand of what is included and what excluded. (Young & Lecy 2014, 1309)

There is no clear line between social and regular entrepreneurship either. Rather their purest forms

could be seen as the opposite ends of the same line that still are not completely unalike. To explain

further this means that even charity organizations much take economic issues into consideration

somehow and even the most hard of businesses bring some social value at least through creating

jobs. (Austin et al. 2006, 3-4; Acs et al. 2013, 794-795)

There are differences but also similarities between regular enterprises and social enterprises. Both

aim to bring growth, whether it is in terms of business and profits or in terms of social wellbeing.

(Austin et al. 2006, 1) In social entrepreneurship both features of for-profit business and volunteer

work are present. This makes it hard to make a clear definition of what is a social enterprise and

what is not. (Certo & Miller 2008, 270) Even further, it makes it hard to study, compare and

measure them and their impact (Young & Lecy 2014, 1308-1309).

Although both social and commercial businesses create both social and commercial value they

differ in the degree to which they put emphasis on each of these. It is also important to note that

the creation of either type of value does not shut the other type out. Thus social value can be

created simultaneously to commercial value and wise versa. (Acs et al. 2013, 794-795) However,

even the for-profit activities of a social enterprise are often if not always somehow connected to the

core goal of bringing about social value. In the case of not-for-profit organizations any profitable

actions are loudly justified to keep the organizations reputation clean. (Young 1998, 295) Not-for-

profit organizations may still have sales activities to generate income to support their core

activities. The selling of products can also improve the value of the organization through more wide

spread knowledge of it. (Young 1998, 290)

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In some definitions of social entrepreneurship great emphasis is put on providing individual

examples of social entrepreneurs. They are seen as the core and base of the social enterprise and

moreover even the soul around which the whole enterprise is built. (Bloom & Chatterji 2009, 114-

115) Thus one of the various ways of defining a social enterprise is seeing it as a construction build

by a social entrepreneur (Young & Lecy 2014, 1312). The persona of the entrepreneur is often

seen of importance to the success of a social enterprise. For example the relationship between

effectiveness of social enterprises and the self-efficacy of the entrepreneur have been studied.

Further it has been found that self-efficacy of the entrepreneur positively correlates with the social

effectiveness and scalability of the social enterprise. (Urban 2013, 167, 173) One of the various

ways of defining a social enterprise is seeing it as a construction build by a social entrepreneur.

(Young & Lecy 2014, 1312)

Young and Lecy (2014, 1327) criticize the way in which individual social entrepreneurs are lifted to

a pedestal. They argue that the overall impact is much more important and significant than the

story of a single good doer, no matter how good they may be and how amazing the story is. This

does not mean that the entrepreneur is not important. However, caution should be used in

evaluating a project or company based on the person behind it.

One commonality of many definitions of social entrepreneurship is the mention of the word

innovation in the discussion. It is also widely agreed that social enterprises combine creating social

and financial value simultaneously. (Austin et al. 2006, 2; Kostetska & Berezyak 2014, 571)

1.1 Differences according to geographical region and metaphors

Many studies have compared the views of Europeans and Americans (Hoogendoorn et al. 2010, 6;

Defourny & Nyssens 2010, 32) and found that there are differences in how social entrepreneurship

is understood in each continent. Also other geographically located discussions are briefly

mentioned (Defourny & Nyssens 2010, 32). The definitions and usage of the terms social

enterprise and social entrepreneurship vary also within the regions which makes it hard to come up

with any solid definition. (Kerlin 2006, 247-248)

In the United States the definition of social enterprise is much wider than it is elsewhere within the

fields of both practitioners and academics. There these groups have slightly different ideas of what

constitutes a social enterprise. For academics the key is that a social enterprise is a profit making

entity or at least one that strives for making profit. Beyond that it can be anything from a company

that is anyway involved in social issues to a not-for-profit organization that has some profit-making

motions merely to support its core activities. In Europe the definition is also wide but does not differ

8

so greatly between the groups of academics and practitioners. A social enterprise can also be a

regular company that starts to desire to engage more in social issues and bring about social

wellbeing through their actions. (Kerlin 2006, 248-249) In Europe social enterprises are traditionally

part of the third sector. (Defourny & Nyssens 2010, 46) However, it is also argued that by nature

they are not bounded to a single sector but can also act within for example the business sector. In

fact they can also work across different sectors. (Austin et al. 2006, 2)

Various metaphors have also been built to better understand and define social enterprises. For

example the Innovation metaphor and the Spectrum metaphor, but not one of them gives a

comprehensive definition of the term. For example the spectrum metaphor states that social

enterprises combine social and monetary targets, but does not give guidelines to how this should

be done in order to qualify as a social business. This makes it difficult to understand the limits

between social enterprises and charities or business and social businesses. Even further social

enterprises can be mishmashes of not-for-profit organizations and businesses. (Young & Lecy

2014, 1313)

Young and Lecy (2014,1320-1322) introduce a metaphor of a zoo where different types of social

enterprises are like different animals in a zoo. These animals act in different manners and have

different reasoning behind their actions. They may or may not be in contact with each other, just as

they may or may not compete or cooperate with each other. Thus there as many forms of a social

enterprise as there are of different types of animals in a zoo. (Young & Lecy 2014, 1320-1321)

In conclusion, there is no single form or shape of a social enterprise nor does there need to be

one. Also it is valuable to note that a social enterprise is not necessary a single unit but can be

formed as a partnership of several actors. Therefore the definition of the term and especially the

comparing and measurement of the effectiveness of a social enterprise is difficult. (Young & Lecy

2014, 1319-1320) Rather than trying to reach a solid definition for the term the emphasis should be

put on resolving social issues. (Young & Lecy 2014, 1310) Although there are different ways of

understanding and defining social enterprises the commonality in all of these is that compared to

regular enterprises these are distinguished by their main goal of generating social value instead of

revenue. In other words the social value created should not be the side effect of some other task

but the core around which other tasks are build. (Defourny & Nyssens 2010, 44)

2.1 Measurement of performance

There is great pressure on social enterprises to measure and show their effectiveness in improving

social issues (Ebrahim & Rangan 2014, 118). Especially in the developing countries it has been

9

questioned whether the organizations taking money from outside and putting it towards bettering

the social problems within these countries actually do so. The main goal of a social enterprise is

not to generate revenue but to bring about social value. This is something that is hard to measure.

(Knife et al. 2014, 5)

Some argue that more often than not the impacts of social enterprises are short term and do not

make magnificent changes in societies. When, however, revolutionary changes to social systems

are made the idea can be considered a social innovation. (Westley & Antadze 2010, 2) The

reasons for why impact measurements are so important are multifaceted. Just as for commercial

businesses it is important for a social enterprise to measure its performance to improve it and

assess whether it is meeting its goals. They should also communicate this measuring to outside

parties to show proof of their results. (Ebrahim & Rangan 2014, 135; Urban 2013, 173) Any

organizations that are funded by outside parties should take good care of projecting and explaining

how these funds are used and what good is achieved with them. This, however, is not always the

case. In fact many have no systematic way of measuring their achievements and the social benefit

born through them. If these things are not measured it becomes almost impossible to set goals for

the organization. Further this makes difficult to remain any stability in the level of providing social

benefits. (Knife et al. 2014, 2)

Just as regular, for-profit businesses also social enterprises need to be able to be rated based on

their effectiveness and compared against each other. This becomes truer and truer as more and

more social businesses are born. This means that ways to calculate social value are needed. This

is not an easy task as there are so many different forms of social value. This is not only important

for the companies themselves but also for parties such as academics, economies, societies and

politicians. (Kroeger & Weber 2015, 43) Compared to for-profit business the efficiency measures

for social entrepreneurship are more scattered, however. There is no uniform way to measure how

well a social enterprise is doing but rather the measures vary according to specific businesses.

This stems from the fact that different social enterprises tackle different types of social issues

which are not easily comparable to each other. (Certo & Miller 2008, 268) Therefore the manners

in which social enterprises should measure their impact and the measures they should use are not

standardized. Depending on the goals of the organization some should measure the long term and

others the short term impacts for example. (Ebrahim & Rangan 2014, 118)

Studies have shown that companies can and do measure the value they create. However, the

manners of doing so are not standardized but often invented by the companies themselves. Also,

many companies are not willing to share their results regardless of measuring them which is

10

alarming. It can steer suspicion towards the company which directly affects their activity as well

through diminishing support from outside parties. (Knife et al. 2014, 14-15)

Young and Lecy (2014,1322-1323) propose four different ways of measuring the successfulness of

a social enterprise: 1. by profits 2. by amount of members in the project 3. by the size of the social

undertaking 4. by how well the balance between social influence and profitability is achieved.

These measures are meant for different types of social enterprises. For example a not-for-profit

organization should obviously not strive for a balance between social influence and profit as it is

not in their nature to make profit. Therefore in order to study the efficiency or impact of a social

enterprise it is important to first define which type of enterprise is in question. (Young & Lecy 2014,

1322-1323)

Ebrahim and Rangan on the other hand provide three simple steps to be taken in order to measure

the social impact of the actions of any organization. These are 1. make clear what the mission of

operations is 2. make clear the tasks which are performed in order to achieve this mission and 3.

measure and define the size of the target group hence the vastness of the problem to be tackled.

These are so general in nature that they should be applicable to any type of social enterprises.

However, these clear steps are not often realized in practice and in fact their use may not be as

simple as it might seem at first. (Ebrahim & Rangan 2014, 134)

There are suggestions that the impact measurement should be reached as far down the line as

possible. Meaning that not only direct beneficiaries but also indirect ones should be included.

However, this might be easier said than done and its meaningfulness also dependable on the type

of social issues the organization is trying to solve. It can also be questioned how long living the

initial impacts are. The further away one goes from the core activities of the organization the harder

it becomes to measure the impacts. The long term effects are hard to measure and estimate

because they may vary greatly after the organization’s exit from the area. For example establishing

long term jobs or lowering poverty rates is difficult to measure and pinpointing the effects as the

accomplishment of a single party is not simple. (Ebrahim & Rangan 2014, 122-123)

3 METHODOLOGY

Analysis of the paper was based on data collected from Schwab Foundation. This data was

derived from the questionnaires filled in by the social enterprises worldwide. The Schwab

Foundation for Social Entrepreneurship is a non-for-profit, independent and neutral organization.

The purpose of the Foundation is to advance social entrepreneurship and to foster social enter

11

prises as an important catalyst for innovation and progress. The Foundation provides unique

platforms at the regional and global level to highlight and advance leading models of sustainable

social innovation. It identifies a select community of social entrepreneurs and engages it in shaping

global, regional and industry agendas. The main activities consist of identifying and highlighting the

world’s leading social enterprises, community building, connecting social enterprises, generating

solutions in partnership and collaborating with leading academic institutions. (Schwabfound, 2014)

Coding scheme was created and each venture was described. The selection criteria chosen for

further analysis of companies is health sector. Health is thus present in all the firms, however wide

variety of other focuses are involved. Main groups of sectors are shown in Table 2. Primarily, 55

companies were selected, however due to lacking of information on important points such as

number of beneficiaries and percentage earned revenue, 4 companies were erased, thus 51

companies were analyzed.

The main topics to consider include name of the organization, year of foundation, type of the

business model, country of origin, area of impact, focus of the project, amount of beneficiaries,

gender of the founder and percentage earned revenue. However, for the sake of quantifying data

further only appropriate variables were selected. Country of origin, area of impact, focus of the

project and gender of the founder were coded in order to be able to use it as an input for analyzing

software, SAS Enterprise Guide.

International Human Development Indicator was applied as categorizing criteria for countries of

origin of the social enterprises. The Human Development Index (HDI) is a complex measure of

average achievement in key dimensions of human development: a long and healthy life, being

knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized

indices for each of the three dimensions. (United Nations Development Programme, 2015) Thus,

the countries of the established companies are classified into four groups: countries with very high

HDI, high HDI, medium HDI and low HDI.

Countries in which the activities of the organizations take place were grouped in regions based on

United Nations Statistics Devision classification. (UNSD, 2013) Table 1 shows the exact regions

and countries which were assigned to them.

Table 1 Regions of impact

Number Region Countries

1 Latin

America

Argentina, Brazil, Chile, Ecuador, Peru, Venezuela, El Salvador, Haiti, Guatemala, Mexico,

Honduras, Colombia, Paraguay, Bolivia, Panama, Nicaragua

12

2 North

America

USA, Canada

3 Africa Egypt, Nigeria, Rwanda, Zimbabwe, South Africa, Kenya, Uganda, Ghana, Tanzania, Zambia,

Somalia, Malawi, Mozambique, Namibia, Lesotho, Swaziland

4 Asia &

Oceania

Israel, Afghanistan, Pakistan, South Sudan, India, Nepal, Sri Lanka, Vietnam, Laos, China,

Thailand, Indonesia, Myanmar, Cambodia, Philippines, Bangladesh, Papua New Guinea

5 Europe Spain, Portugal, Hungary, Germany, France, Belgium, Spain, Ireland

Due to wide range of focuses of the project and for the sake of ease the analysis, they were

merged into larger groups. Table 2 presents the distribution of the focus of projects.

Table 2 Focus of Groups

Number Group Focus

1 Health Health, HIV/AIDS

2 Disabilities Disabilities, Ageing, Social inclusion, Civic participation

3 Technology Technology, Communications and Media

4 External conditions Environment, Water, Food, Nutrition

5 Economic

development

Enterprise, Business development, Microfinance, Financial inclusion, Rural

development, Homelessness, Labor conditions, Unemployment

6 Human/People Women, Children and Youth, Education

In the next sections of our paper we will take closer look at the data and analyze it in more detailed

way.

4 RESULTS

As it has already been mentioned, in the paper, social impact of social enterprises oriented on

health issues is going to be analyzed. More precisely the amount of beneficiaries, percentage

earned revenue, focus of the project and region of impact will be taken into consideration. For the

investigation of those two variables, few independent variables are taken:

The gender of the entrepreneur

Country of origin of an enterprise

First, summary statistics is presented in Table 3. Amount of beneficiaries variable is analyzed

grouped by focus of the project.

Table 3 Amount of beneficiaries classified by focus of the project

Focus of the Project N Mean Std Dev Minimum Maximum

13

Health/HIV 12 1 229

731.92

3 139

669.97

2138.00 10 800 000.00

Disabilities/Ageing 4 40 212.00 39

745.14

1830.00 75018.00

Technology 2 7 001

500.00

9 897

373.62

3000.00 14 000 000.00

Environmental circumstances 2 262 000.00 336

582.83

24000.00 500 000.00

Economic development 3 535 022.67 380

663.80

265568.00 970 500.00

Human development 5 1 183

320.00

2 415

768.10

22000.00 5 500 000.00

Economic + People 7 418 892.86 506

458.37

40000.00 1 500 000.00

Disabilities/Ageing + Economic 2 6 800.00 4 525.48 3600.00 10 000.00

Environmental + Economic + People 7 250 540.86 361

227.57

2500.00 1 000 000.00

Others with more than one focus 8 3 485

375.25

6 325

261.55

702.00 16 000 000.00

The next largest number of observations after Health belongs to projects with more than one focus,

mostly three sectors of influence. Moreover, there are numerous projects, which focus on

economic and human aspect at the same time; and with focus on all three aspects such as

environmental, economic and human. Among single focus projects, biggest portion belongs to as

expected Health and Human Development issues.

As for mean value, the largest mean of amount of beneficiaries is in the project with focus on

Technology/Communications and Media, however standard deviation is quite high here. Group 10

where there are more than one focuses of the projects has second highest mean values, also with

high standard deviation. It can be explained by companies’ multiple aspects addressed. Mean

value of more than 1 million beneficiaries features Health and Human Development projects, yet

standard deviation is high as well.

As amount of beneficiaries depicts real social impact measured in number of directly and indirectly

affected people, it is also analyzed from region of impact perspective in Table 4.

Table 4 Amount of beneficiaries classified by region of impact

Region of impact N Obs Mean Std Dev Minimum Maximum

Latin America 12 148 250.08 162 479.17 4600.00 500000.00

North America 3 7 533.33 3 442.87 3600.00 10000.00

14

Africa 7 5 477

274.43

6 876

927.04

30000.00 16000000.00

Asia &Oceania 16 381 978.56 440 476.72 1830.00 1500000.00

Europe 4 30 360.00 35 512.00 702.00 74000.00

Global 2 1 559

650.00

2 178

383.86

19300.00 3100000.00

Two or three regions

of impact

8 2 506

752.25

5 016

060.66

3000.00 14000000.00

The largest number of observations is in the Asia & Oceania region. This region tackles largest

amount of beneficiaries, which need help. Latin America is second largest region of impact in terms

of analyzed variable. Similar results of 8 and 7 have African region and multiple regions of impact.

In can be concluded that social entrepreneurship covers mainly developing countries where there

are millions of people need support in wide range of matters.

The largest average amount of beneficiaries belongs to African region of impact with highest

standard deviation at the same time. Other two high mean values characterize global and more

than one regions of impact.

The next step is to look at one-way frequencies as they show percentage of distribution. This is

presented in Table 5.

Table 5 Frequency for region of impact

Region of impact Frequency Percent Cumulative

Frequency

Cumulative

Percent

Latin America 12 23.08 12 23.08

North America 3 5.77 15 28.85

Africa 7 13.46 22 42.31

Asia &Oceania 16 30.77 38 73.08

Europe 4 7.69 42 80.77

Global 2 3.85 44 84.62

More than one region 8 15.38 52 100.00

Asia &Oceania has highest percent and is the main region of attention of enterprises. Latin

America is placed second and more than one region of impact scores over 15 percent followed by

Africa. Figure below represents this data in clear and comprehensive way.

15

Figure 1 Regions of impact

Same analysis is conducted for the focus of the project. Frequency and percentage of the projects

are important variables to look at in Table 6.

Table 6 Frequency for the focus of the project.

Focus of the Project Frequency Percent Cumulative

Frequency

Cumulative

Percent

Health 12 23.08 12 23.08

Disabilities/ Ageing 4 7.69 16 30.77

Technology/Communications and Media 2 3.85 18 34.62

Environmental conditions 2 3.85 20 38.46

Economic development 3 5.77 23 44.23

Human 5 9.62 28 53.85

Economic development + Human 7 13.46 35 67.31

Disabilities/Ageing/Civic participation + Economic 2 3.85 37 71.15

Economic + Environmental + Human 7 13.46 44 84.62

Others with two or three focuses 8 15.38 52 100.00

Obviously as the selection criteria for the social enterprises was Health, the largest percentage of

projects are with this very focus. Next high percentage is represented by the projects, which tackle

two or three issues simultaneously. Within economic and human focus (7) as well as

environmental, economic and human focus (9) projects are distributed evenly with around 13.50

percent. Same type of information is portrayed below in form of a pie chart.

16

Figure 2 Focus of the project

In order to see whether gender influences the percentage of earned revenue t-test must be carried

out.

The independent-groups t-test helps to determine if the means of exactly two independent

distributions are significantly different. Because a one-way between subjects analysis of variance

(ANOVA) design is the general case of the independent groups t test, and because t 2 = F, it is

common practice to defer to the ANOVA for two-group as well as multigroup designs. (Meyers, et

al., 2009)

In order to test whether male entrepreneurs have higher percentage earned revenue, t-Test

analysis must be conducted. The test has two parts. First, the test of equality of variances across

the groups must be carried out.

Table 7 Equality of variances

Equality of Variances

Method Num DF Den DF F Value Pr > F

Folded F 12 31 1.27 0.5633

This table gives the results of the comparison of group variances. One of the assumptions

underlying the t test is that the group variances are equal (not significantly different); this is known

17

as homogeneity of variance. We tested this assumption as part of the analysis by using what SAS

labels as a Folded F procedure. The results of the Folded F procedure indicated that the two

variances were incomparable (Pr > F = 0.5633).

Table 8 Variances are equal

Method Variances DF t Value Pr > |t|

Pooled Equal 43 -1.12 0.2686

Satterthwaite Unequal 20.079 -1.06 0.3000

The table above provides the t-test results, which are provided for the case in which the group

variances are equal and in which the variances are unequal. Our data meet the equal variances

assumption, and so we can read from the first row of the table (labeled as Pooled). Based on 24 df,

the computed t value of -1.120 is statistically significant (Pr > |t| < .26863). Looking at the two

means, we can therefore conclude that there are no differences between men and women in

percentage of earned revenue.

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Table 9 Differences between genders

Gender of the Founder Method Mean 95% CL Mean

Female 39.6154 14.5736 64.6572

Male 53.6563 40.4223 66.8902

Diff (1-2) Pooled -14.0409 -39.3029 11.2211

Analysis of variance helps to determine if the means of two or more distributions are significantly

different. One-way between subjects ANOVA designs is analyzed.

The ANOVA procedure performs analysis of variance (ANOVA) for balanced data from a wide

variety of experimental designs. In analysis of variance, a continuous response variable, known as

a dependent variable, is measured under experimental conditions identified by classification

variables, known as independent variables. The variation in the response is assumed to be due to

effects in the classification, with random error accounting for the remaining variation. (Meyers, et

al., 2009)

The ANOVA procedure is designed to handle balanced data (that is, data with equal numbers of

observations for every combination of the classification factors).

The aim is to do analyses of social impact of social enterprises within health sector. Social impact

is measured by amount of beneficiaries affected. The first assumption is that enterprises’ country of

origin defines the region of impact and amount of beneficiaries varies according to it. To check that

ANOVA one-way must be applied. As independent variable country of origin is taken, on the other

hand amount of beneficiaries, focus of project and region of impact are dependent variables.

First step is to look at the Bartlett’s test for homogeneity of amount of beneficiary’s variance. The

tests have not yielded a statistically significant outcome. Thus, we can treat the assumption of

homogeneity of variance as having been met and we can ignore the Welch ANOVA that we ran just

in case we had unequal variances. For region of impact p is 0.47 which indicates that variances

are equal, thus ANOVA can be applied.

Table 10 ANOVA test for Regions of Impact

Source DF Anova SS Mean Square F Value Pr > F

Country of origin 3 7.98776224 2.66258741 0.65 0.5885

From the table above one can notice that Pr>F is higher than 0.05 consequently there are no

differences between regions of impact in terms of the country of origin of the entreprise. Similar

19

results were received for focus of the project dependent variable. There are no differences

between the groups within country of origin criteria of analysis because Pr > F is higher than 0.05.

Table 11 ANOVA test for Focus of the Project

Source DF Anova SS Mean Square F Value Pr > F

Country of origin 3 35.97 11.99 1.04 0.3814

Same procedure is applied to the amount of beneficiaries variable, however output is different.

Bartlett’s test for homogeneity shows that p < 0.05 (Pr > ChiSq < .0001) meaning that variances

are unequal.

Table 12 Bartlett’s test of homogeneity for amounts of beneficiaries variable

Bartlett's Test for Homogeneity of Amount

of Beneficiaries Variance

Source DF Chi-Square Pr > ChiSq

Country of origin 3 71.6975 <.0001

Therefore one must refer to Welch’s test. It presents that variables are different across the groups

because p < 0.05 (Pr > F = 0.02), however the question arises between which groups?

Table 13 Welch’s test for number of beneficiaries variable

Welch's ANOVA for Amount of Beneficiaries

Source DF F Value Pr > F

Country of origin 3.0000 4.08 0.0173

From the table below, it can be assumed that enterprises originated from the country with high

human development index such as USA and European countries have higher social impact and

transfer the practices to developing world. Moreover social enterprises from medium human

development indexed counties such as India, South Africa and Paraguay also affect large amount

of beneficiaries. Perhaps more educated and well-off members of society try to improve the

situation in the country and launch project to fight with various issues.

Table 14 Mean comparison between different countries of origin for dependent variable

Level of

Country of origin

N Amount of Beneficiaries

Mean Std Dev

Very high HD 22 2 220 875.27 4 839 234.13

High HD 12 97 737.50 119 737.32

Medium HD 16 1 217 676.94 2 723 734.50

Low HD 2 17 000.00 9 899.49

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Another assumption is that region of impact explains the amount of beneficiaries. In Africa, Asia

and Latin America is presumed that there are larger number of potential people in need. Therefore,

ANOVA test is conducted taking region of impact as independent variable and number of affected

people as dependent variable.

Table 15 Bartlett’s test of homogeneity of number of beneficiaries classified by region of impact

Bartlett's Test for Homogeneity of Amount

of Beneficiaries Variance

Source DF Chi-Square Pr > ChiSq

Region of impact 6 146.8 <.0001

Bartlett’s test for homogeneity of amount of beneficiaries shows that variances are unequal

therefore Welch’s test must be carried out.

Table 16 Welch’s test for number of beneficiaries

Welch's ANOVA for Amount of Beneficiaries

Source DF F Value Pr > F

Region of impact 6.0000 3.58 0.0429

It can be concluded that because p is under 0.05, there are differences in amount of beneficiaries

variable between regions of impact. To answer the question between which groups there is a

difference, statistically significant differences are marked and mean values are compared. Table 17

shows that there is significant difference in amount of beneficiaries between group 3 and 4 (Africa

and Asia) and between group 3 and 1 (Africa and Latin America).

Table 17 Mean comparison between different regions of impact for dependent variable

Comparisons significant at the 0.05 level are

indicated by ***.

Region of impact

Comparison

Difference

Between

Means

Simultaneous 95% Confidence

Limits

3 – 4 5 095 296 390 253 9 800 339 ***

3 – 1 5 329 024 391 084 10 266 965 ***

Mean values are depicted from Table below. African region obtains the highest mean value of over

5 million people. In comparison with Asia where the largest number of organizations is, it is 15

times more. Latin America region even though is second in terms of number organizations situated

there has even lower average value of around 150 000 people.

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Table 18 The variance of dependent variable.

Level of

Region of impact

N Amount of Beneficiaries

Mean Std Dev

Latin America 12 148 250.08 162 479.17

North America 3 7 533.33 3 442.87

Africa 7 5 477 274.43 6 876 927.04

Asia &Oceania 16 381 978.56 440 476.72

Europe 4 30 360.00 35 512.00

Global 2 1 559 650.00 2 178 383.86

More than one region 8 2 506 752.25 5 016 060.66

In the nest section the outcomes will be discussed in more detailed way.

5 DISCUSSION AND CONCLUSIONS

Evaluation of social enterprises shows that activities of enterprises are oriented towards

developing regions of the world such as Africa, Latin America, Southern Asia, South-Eastern Asia.

In matter of the focus of the project the most popular was health group, however it is the limitation

of the paper because all the companies were selected using this criteria. Also majority of

companies tackle human development issues related with children and youth and women.

Commonly social enterprises’ operations address few areas of issues at the same time. Economic

development in combination with human capital and the combination of economic, environmental

and people focus are frequently repeating.

Surprisingly it was found out that there is no differences between genders in matter of percentage

earned revenue. The expectations that men might have higher percentage did not meet the results.

Assumption that projects which country of origin is in developing part of world has larger amount of

beneficiaries and more regions. However there were no differences found between countries of

origin of the enterprises in focus of the projects neither in regions of impact group. In amount of

beneficiaries between counties of origin, differences were identified. It can be concluded that social

enterprises originated from the country with high human development index such as USA and

European countries have higher social impact and transfer the practices to developing world.

Furthermore social enterprises from medium human development indexed counties such as India,

South Africa and Paraguay also affect large amount of beneficiaries. Perhaps more educated and

well-off members of society try to improve the situation in the country and launch projects to fight

with various issues.

22

Another assumption that projects with area of impact in Asia, Africa and Latin America have larger

amount of beneficiaries reflects the results of ANOVA test for amount of beneficiaries among

different regions of impact. The major statistically significant differences were identified between

Africa and Latin America; and Africa and Asia.

Main limitations of the research include relatively small sample size consisting of 51 businesses.

Moreover not all enterprises provided necessary data to be able to conduct complete analysis of

variables, and provided data differed in terms of period among enterprises. The fact that the data

was gathered from a secondary source also influenced the outcomes. Concentration only on health

sector as well limits the application of findings into other areas, so called generalizability of the

results.

The implications of this seminar work provide insights for social enterprises into the scale of social

impact of ventures oriented to improve situation in developing countries. As implications for

government it shows that it is worth to invest and support social entrepreneurs who are

enthusiastic about solving social issues and can have real impact in addressing problems.

Apart from Schwab Foundation there are few other supporting, integrating and awarding social

initiatives. Skoll Foundation is one of the biggest with its mission "to drive large scale change by

investing in, connecting and celebrating social enterprises and the innovators who help them solve

the world's most pressing problems." (Skoll Foundation, 2015) Ashoka – innovators for public – is

the largest network of social enterprises around the world.(Ashoka, 2015) Omidyar Network is "a

philanthropic investment firm dedicated to harnessing the power of markets to create opportunity

for people to improve their lives." The firm makes a number of investments in the "consumer

Internet and mobile" sector in order to "enhance individuals' quality of life by enabling them to

connect with others, make more informed decisions, access products and services efficiently, and

take action on what matters to them." (Omidyar, 2015) Echoing Green identifies, funds and

supports emerging social enterprises. The foundation focuses on "very early stage support of new

and untested ideas in the hands of visionary social entrepreneurs." (Echoinggreen, 2015)

Therefore, social enterprises can have support and join networks because by connecting and

cooperating bigger change in systems will occur. Also more data enables researches to investigate

the phenomena deeper and calculate real influence.

23

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