TECHNOLOGY ADOPTION BY SMALL MEDIUM ENTERPRISES IN KENYA

STUDENT NAME:

Research Proposal Submitted in Partial Fulfillment of The

Requirement for the Award of the Degree of Masters of Business

Administration, Department of Business Finance. Nairobi University

i

DECLARATION

I, the undersigned, declare that this proposal is my original work

and that it has not been presented in any other university or

institution for academic.

Name: your name here Reg. No

Signed……………… Date………………

Supervisor

This proposal has been submitted for examination with my approval

as university supervisor.

Dr Adunda

Signed……………………………….. Date………………………….

ii

ACKNOWLEGMENT

Many thanks go to almighty God for His abundant grace that has

enabled us to go through the entire course and in particular, this

research project.

Our utmost gratitude’s goes to our entire families for their moral

and financial assistance that ensured the completion of this

project successfully and with the best education possible.

Our heartfelt gratitude also goes to our supervisor, Dr Adunda for

his guidance, support and tireless effort to ensure that this

project comes out successfully.

God Bless you all.

iii

DEDICATION

To our dear parents, brothers and sisters

iv

ABSTRACT

Banks in Kenya for along have had a high rate of loan default

from the borrowers which have caused significant losses to them.

This is due to the fact that the respective banks have different

credit information about their borrowers and therefore these loan

applicants have taken this loop-hole to get multiple loans from

these banks which increase their rate of default due to the fact

that they might fail to service back all these loans. Small

businesses are the backbone of the Kenya. Economy, accounting for

more than half of total employment and over eighty percent of

employment growth in the past decade. The general objective of

this study will be to investigate the levels of technology

adoption in Kenya by small medium enterprises The research will

be carried out from the Small medium enterprises located in

Nairobi County The researcher will use purposive and correlation

sampling design to select the respondent. The sample size

v

includes 40 respondents 8 in each bank. Both primary and

secondary source of data will be used. Questionnaires will be

used to collect primary data from the respondent and data

collected will be analyzed using frequency tables and

percentages.

TABLE CONTENT

Contentsvi

DECLARATION...........................................................ii

ACKNOWLEGMENT........................................................iii

DEDICATION............................................................iv

ABSTRACT..............................................................iv

CHAPTER ONE: INTRODUCTION..............................................1

Background of the Study................................................1

1.2 Problem Statement..............................................2

1.3 Research Questions..............................................3

1.4 Objectives of the Study..........................................3

1.4.1 General Objective..............................................3

1.5 Justification...................................................4

CHAPTER TWO............................................................5

LITERATURE REVIEW......................................................5

2.1. Introduction....................................................5

2.2 Theoretical Background..........................................5

2.3 Factors Influencing Technology Adoption..........................6

CHAPTER THREE.........................................................18

RESEARCH METHODOLOGY..................................................18

3.0 Introduction...................................................18

3.1 Research Design................................................18

3.2  Data collection method.........................................19vii

3.3 Data Entry and Data Processing................................19

3.4 Data Analysis and Interpretation..............................19

References............................................................20

viii

CHAPTER ONE: INTRODUCTION

Background of the Study

The term information communication technology evolved in the

1970s. It illustrates any technology which helps manufacture,

manipulate, accumulate, communicate or broadcast information. In

late 1970s the concept became more advanced with the development

of microcomputers. Since then technology has been used world over

in business, medicine, science and engineering and in integrated

information systems. Kenya developed its technology national

policy in 2005 which focused on development of technology

infrastructure, skills, legislation, coordination and monitoring

(Gok,2011).

In the developed world, technology has been fully integrated in

the all sectors from government, large corporation as well as SME.

Equally newly industrialized nations have shown that technology

can enhance health service delivery ( unaids 2011). In western

countries one can identify several examples of technology-based

solutions. People from sub-saharan africa have not received the

1

same benefits from technology as people in industrialized nations.

There is significant untapped potential to use technology in order

to improve SME in developing countries (bada et al, 2011).

Technological advancement witnessed by the corporate sector

during the nineties has changed the way business needs to be

conducted. Information communication technology (technology) has

introduced new paradigms and is increasingly playing a significant

role in improving the service delivery in both corporate and

health sectors. Esnet (2011) argues that continuous advances in

information and communications technology (technology) as well as

it’s decreasing costs have afforded institutions the impetus to

explore alternatives and to incorporate technology into their

operational processes and strategies. Vision 20-30 was developed

in 2008 as the blue print for national development. One of the

major objectives is to have technology integrated in all sectors

of the economy. According to tove et al (2008), technology has

helped corporate and other institutions to increase productivity

and enhance service delivery to clients. It has helped to improve

the quality of services offered and decreases lead-times and

costs. According to banda et al (2011), technology is seen as one of

2

the most important solutions in order to do business and other

related services for all members of the society.

1.2 Problem Statement

Small businesses are the backbone of the Kenya. Economy,

accounting for more than half of total employment and over eighty

percent of employment growth in the past decade (wheelen & hunger,

1989). Small firms are also often innovative and challenging to

manage strategically (dollinger, 1985; bracker & pearson, 1986;

carter, 1990). Consequently, it is important to assess the value

of techniques like strategic planning for improving the

performance of these firms.

Small businesses are the backbone of the Kenya. Economy,

accounting for more than half of total employment and over eighty

percent of employment growth in the past decade. The general

objective of this study will be to investigate the levels of

technology adoption in Kenya by small medium enterprises

There is a growing body of literature examining the effects of

formal strategic planning on the financial performance of small

firms (e.g., Robinson, Pearce, Vozikis, & Mescon, 1984; Bracker,).

There are also numerous field studies examining the effects of3

various forms of strategic and operational planning activities on

a variety of financial performance measures for both large and

small firms (Robinson & Pearce, 1984). Researchers who have

undertaken these studies, especially those of small firms, have

drawn conclusions: some claim that formal strategic planning

provides structure for decision making, helping small business

managers take a long-term view, and, in general, benefits small

firms; others conclude that formal strategic planning has no

potential payoff for small firms because it is a heady, high-

level, conceptual activity suited solely to large firms and

therefore has no effect on the financial performance of small

firms. The Kenya technology board was established under state

corporations act cap. 446 on 19th February 2007 to help harness

and integrate technology in all sectors of the economy.Literature

review has shown that technology coverage in Kenya is below

accepted levels in the world. It is far below other emerging

African economies such as Egypt, south Africa, Nigeria and

Tunisia. Technology coverage is also low in SME, while remarkable

strides have been made in adopting technology in sectors like

education and banking, little has been realized in the SME in

Kenya (Makau 2010). 4

1.3 Research Questions

i. What are the levels of technology adoption by small medium

enterprises in Kenya?

ii. What are the factors influencing technology adoption by small

medium enterprises in Kenya

1.4 Objectives of the Study

1.4.1 General Objective

The general objective of this study will be to investigate the

levels of technology adoption in Kenya by small medium

enterprises

1.4.2 The specific objectives will include

i. To determine the levels of technology adoption by SME in

Kenya?.

ii.To determine factors influencing technology adoption by SME in

Kenya?

1.5 Justification

5

According to Makau (2010), adoption and integration of technology

in by SME will enhance uptake of SME in our national economy and

social fabric. This will move Kenya towards middle level income

country as envisaged in the vision 2030. In spite of the

foregoing, limited research has been conducted on technology

adoption by SMES. Studies focus has largely been on other Big

enterprises.. As a result little attention has been given to

technology adoption by SMES hence the purpose of this study.

6

CHAPTER TWO

LITERATURE REVIEW

2.1. Introduction

This chapter reviews the literature related to the topic of study.

It specifically looks at SME and technology adoption in relation

in Kenya.

2.2 Theoretical Background

This study was guided by the following diffusion of innovation

theory. One of the models that have received much attention for

the study of technology adoption in businesses is the diffusion of

innovation (doi) (rogers, 1995). This model suggests that there

are three main sources influencing the adoption and diffusion of

innovation: perceptions of innovation characteristics;

characteristics of the adopter; and contextual factors (berwik,

2003). According to a review of numerous empirical studies

7

(rogers, 1995), perceptions of the characteristics of an

innovation are the most critical factors for its diffusion. There

are five perceived characteristics of innovation: 1) relative

advantage is the degree to which the innovation is perceived as

better compared to the status quo; 2) compability is the degree to

which the innovation is perceived as being consistent with

existing values and practices among potential adopters; 3)

complexity is the degree of difficulty perceived regarding the use

of the innovation; 4) triability represents the possibility for a

potential adopter to experiment the innovation on a small scale;

and 5)observability is the degree to which the result of the

innovation are visible to the potential adopters.

With respect to individual factors, the doi proposes five

categories of adopters that are based on the distribution curve

of the diffusion process, which follows a relatively normal

distribution. These are: (1) innovators, (2) early adopters, (3)

early majority, (4) late majority, (5) laggards. Individuals in

each category present specific characteristics and personality

traits that have been found to influence their adoption behavior.

The doi also suggests that contextual factors, such as

8

organizational culture, resources and leadership, influence the

rate of diffusion of innovations. However these factors are not

considered in this synthesis since the focus is on technology

adoption at the individual decision-making level.

One of the main critiques that have been expressed with regard to

this model is its lack of specificity. As chau et al (1997) argue,

the doi was developed to explain the diffusion of any innovation

and the relationship it posits between concepts such as

innovation’s characteristics and adoption behavior are not

explicit.

2.3 Factors Influencing Technology Adoption2.3.1 Individual factors

Successful technology adoption by enterprises requires the active

participation of the ceo or owner (raymond et al 1982).this is

because the ceo makes most of long-term planning decisions

including technology decision and has overall control of the

organization financial and human resource .it is usually the

responsibility of the in charge to recognize opportunities and

threats within the chosen target (mathay 2000). This argument was

9

supported by rashid et al( 2001) that the ceo innovation affects

technology adoption.

Lacks of knowledge on how to use technology and low computer

literacy were contributory factor s to non adoption of technology

(kirby et al (1993).kiarie et al (2006)indicates that the in charge

lack of awareness of technology and its perceived benefits is a

major barrier to take up of e-commerce /e- health .organizations

generally lack the human and technological resources needed for

technology adoption because they follow on day to day operations

and lack the tim e to understand the benefits of new technologies

(bresnahan et al, 2002).those firms that adopt technology have

within them someone who has a reasonable amount of knowledge of

the specific technology in general.

The development of technology related skills is central toprocess

of organizational change. Ednar et al (2005) suggests that

organization investment in assets that are complimentary to

technologys may contribute to more raising the relative demand for

stalled labour than the diffusion of technologys themselves.in

this context, firms with relatively high proportions of stalled

workers would be expected to have a comparative advantage in

10

minimizing the cost both technology adoptions and learn how to

make the best and most intensive use of technologys. Highly

education workers, for example are likely to be better equiped in

responding to the new product development opportunities made

possible by technologys. In the areas of new products and

services, highly skilled workers would be expected to adapt more

quickly to the new forms of work organization than low skilled

workers. Regarding investment in technology training, all other

factors being equal, less of such training will be necessary in

firms with pre-existing high level of skill (makau,2010)

A skilled and knowledgeable work force is closely assocciated to

the successful implementation of technology (allison ,1999).

Indeed a highly skilled work force is the key to increased competi

tiveness and sustainable growth (gaskill et al 1993). Demand for

highly knowledgeable and skilled work force places enormous

pressure upon organization to improve or update their current

knowledge and skills. This is particularly so especially in health

care systems where new ideas and challenges are frequent (bingi et

al ,2000). However, shortage of skills has been cited as one of

the challenges facing technology adoption and coping with rapid

11

changes about by technologys demands continues education and

training which cccs may not be able to provide because of their

limited resources(makau, 2010).

The department of trade and industry (it) observed that most sale

managers were not aware of the opportunity presented to them by

advanced information technology and especially newly emerging e-

health and internet health information (dti 1998, 1999). Rushid et

al (2001) indicates that closely linked awareness, understanding

and acceptance of technology was a distinct lack of technology

skills by organization manager with the latter being perceived to

be the most significant factor to upkate of technology. While

examining the dilemma of african countries in the wake of the

technologys, sonaike (2004) asserts that the ongoing effort s by

western companies to expand connectivity in the continent are

entirely driven by profit motives. This could create dangerous

form of techno-dependence. This also makes organizations techno-

dependent and could be a factor in developing technology

application s that are customized to health related organizations

particularly in kenya context and thus reducing their ability to

adopt technology (makau 2010).

12

The age of works was also found to have significant influence of

technology adoption. According to rice et al (2003) ,technology

users in usa tend to be young. Age, however may not be significant

factor in determining the use of all technology. Some studies in

usa have shown that with respect to the use of mobile phone, age

did not appear to be significant predtechnologyor even though with

respect to the internet a clear age thresh hold existed whereby

inclusion fall after age of 55 (waham etal 2004) .this mans that

internet and mobile users are not necessarily the same group of

people with the difference being attributed by to the fact that

mobile phones and the internet do not necessarily fulfill the same

needs. In regard to the significant influence of age, venkalesh

etal (2000),found a high intention to use technology by men than by

women.

Morris et al (2005) notes that the subjects of prior technology

acceptance research have been predominant male but currently

females are joining the field of technology and work in a female

dominated environment. However, the studies were based on

developed countries like usa but the situation might be different

in developing countries such as kenya where there is still gender

13

inequality in many spheres (makan 2010). Morriss et al (2005)

asserts that in a country where the work force is relatively young

and homogenous and is specifically in the 31-40 age range across

both public and private sectors, technology is more likely to be

adopted. The effect of age as demography variable is usually

minimal because it is expected that younger people would be more

motivated to use technology especially now that technologies like

the computer have only recently been introduced in the school

curriculum in kenya (makau, 2010).

Although the studies reviewed have given vital insight into the

effects of individual factors on technology adoption, they are

based on organizations in the developed countries and little seem

to have been done on african countries and more to kenya c.c.c.s.

2.3.2 Organizational factors

Organizational factors such us size, quality systems, information

intensity, specialization, management support, voluntaries and

organizations readiness facilitate technology adoption.

The size of organization is a determining variable in the decision

to adopt technology (igbaria et al ,1996) .the size of an

14

organization is the key parameters hindering adoption of

technology, large organization have the resources and

infrastructure necessary to facilitate the adoption of innovation.

Small one s by contrast are less likely to adopt technology

because they often lack resources (karki et al 2004). He further

asserts that this situation is brought out by such factors as

operating in a strong competitive environment, major financial

constraints and lack of professional expertise.

The systems quality is an important driver behind user

satisfaction, end users’ intention to use and actual usage (delone

et al 2003). Organization that are connected to internet commerce

tend to be more entrepreneurial risk taker, innovative and

creative (poon et al 1999).the relative or proactive approach of

owners/managers to rapid technological changes is crucial to

technology adoption and implementation and managerial commitment

and perception of technology benefits and are a key features in

this process (poon etal 1999).

Moore et al (1991) , argue that behaviors are more directed by the

perception of voluntariness than by actual voluntariness because

users may still feel some compulsion to adopt technology even when

15

the setting is not strtechnologyly compulsory. Venkash et al (2003)

asserts that voluntariness has been often assumed as binary by

some authors while others have treated it as a continuous

variable. The problem with the binary view is that it ignores

different functions of the system. Therefore the requirements to

use the system among different employees might make it

challenging to think of voluntariness in strtechnologyly binary

terms (makau ,2010).

Agarwal et al (1997) have suggested that in practice users may

perceive different degrees of voluntariness in using an

innovation. Therefore, voluntariness may be empirically ordinal

concept (either mandatory or voluntary) in academic research.

Given that perceived voluntariness is a rang e of various levels

of choice it would be wrong to conclude that a system is mandatory

only when users do not want to use it at all but must use it

(venkatesh et al ,2000).

They further argue that the theoretical role of voluntariness in

technology acceptance has been examined in multiple ways. When use

of a system is perceived as mandatory in the organization, the

intention of using the system may be predtechnologyed by

16

subjective norms. This view of voluntariness observes that

attitude is more important when adoption is a matter of individual

choice and less so when organizational pressure is applied (makau,

2010).

2.3.3 Technological factors

The third set of factors influencing technology adoption are the

technological aspects. They include complexity, compatibility,

relative advantage. Financial and human resources together with

trust in technology by end users will ultimately determine

technology adoption (chan et al 2002). Among the technology adoption

models examined by researchers, the technology acceptance model

(davis, 1989), is the most explicit in information technology.

It’s major strength is the fact that it decomposes the attitudinal

construct found in other models into two separate factors, namely

technology ease of use and it’s usefulness. It has also been

applied to understand technology acceptance among healthcare

professionals (croteau et al, 2002). However some authors have

criticized the applicability of tam to the study healthcare

professionals.

17

various efforts have been made to extend the theory by

introducing other variables from other theoretical models or by

investigating moderators and antecedents of perceived ease of use

and perceived usefulness (gagnon, 2006). Enterprises normally

choose forms of technology that conform to certain internal values

and experience. This enables them to reduce the perceived risks

and make minimal adjustments and therefore less resistant to

adoption (makau, 2010).

rogers (1995) observed that in health related organizations,

compatibility of a technology with work needs, values and

experiences of the user becomes a crucial determinant in

acceptance decision making. He further noted that the high value

placed on the therapeutic relationship between a patient and a

therapist cannot be underestimated as it is a crucial tool in the

therapeutic process. Moreover, an innovation that is perceived to

be in compatible with this process will finally lead to rejection

by health care professionals (rogers, 1995). Teo et al (2002) assert

that the incompatibility of a new technology system with existing

work procedures, value systems and infrastructures negatively

affects the attitudes of the users and increase their resistance

to change which hinders technology adoption. Chau et al (2002),18

notes that compatibility may influence behavioral intension

directly through performance expectancy and effort expectancy.

They further observed that compatibility of tele-medicine

technology has significant influence on its perceived usefulness.

The relative advantage of a given technology influences its

acceptance and adoption. Rashid et al (2001), poon et al (1999) and

seyal et al (2003) have it that a positive perception of a

technology should provide a motivation for its adoption. They

further argue that the degree of relative advantage is normally

expressed in terms of profits, cost reduction, worldwide client

database, rapid access and distribution of information and

improvement of services.

Thong (1999) argues that financial, human and technological

resources play a very important role in adoption of new

technologies. In the case of health institutions, even if the

health workers perceive the adoption of technology as important,

the facilities may not have enough resources to adopt. This poses

a major obstacle to cccs in adopting technology. Acute financial

and organizational constraints often cause health workers in

developing world to lag behind in technology adoption as compared

to their counterparts in developed world.19

According to singh (1986), innovation is more likely to take place

in the presence of organizational slack because it buffers its

downside risk and also because the legitimacy of experimenting is

less likely to be questioned in amore resource controlled

environment, thus lack of resources encourages innovation. Nolan

(1979) asserts that organizations should encourage innovations by

maintaining low control and high slack. High levels of uncommitted

resources is a factor that positively affects innovation in

response to organizational decline while lack of resources and

expertise are assumed to be a major hindrance to technology

adoption (mone et al, 1998).

When end-users perceive the use of technology devise as enhancing

their status within their work place it is likely they will adopt

technology. Van heerden et al , (1995) argue that organizations try

improve their images in order to increase their credibility among

customers. Succi et al (1999) found that a customer’s perception is

essential for success and that a strong image is an effective

means of differentiation and therefore end-users are more likely

to be influenced by the impact of the use of new technology on

their professional status. But research has shown that social

process of subjective norm and image may not significantly20

influence the decision to adopt technology. This could be

attributed to pragmatic nature of end users in decision-making as

well as reliance on their own assessment rather than that of

others (makau, 2010).

Trust in the technology in relation to patient information,

confidentiality and maintaining health worker and patient

relationship has considerable influence upon decision makers of

health facilities in technology adoption. According to haynes et al

(1998), trust can result in positive networking with other

businesses, governments and consumers.

2.3.4 External environment factors

External environment factors such as external competition, current

state of infrastructure, relationship between providers and

consumers, political systems, culture and national values form the

last set off factors influencing technology adoption. Palvia et al

(2002), observes that political systems and government policies

are particularly most crucial in influencing technology adoption.

Cultural factors such as norms, values and attitudes of a society

are also an important determinant of technology adoption (straub

21

1994). The influence of the external environment is important

throughout the adoption decision making process (makau, 2010).

Several authors have studied the possible effect of competition

pressure on the adoption of new technologies (cragg et al,1993 and

iacovou et al, 1995). However, thong (1999) argues that competitive

pressure has little influence on technology adoption. Competitive

pressure on adoption decisions arises when organizations presume

that competitors may have comparative advantage as a result of

technology adoption ( tung et al, 2005). This contradtechnologyion

leaves room for more research in this area.

Despite the fact that african countries are expanding and

extending communications systems, the current state of the

infrastructure is still a major problem and remains a threat to

continents full participation in the information society (mansell

et al, 1m998). Cash constrained national treasuries and limited

investment opportunities are two major factors reducing

infrastructural developments. Nevertheless, despite severe

constraints in telecommunication and infrastructural developments

the most dynamic is the internet, which is growing rapidly (makau,

2010).

22

Lack of telecommunications infrastructure includes poor internet

connectivity, lack of fixed telephone lines for end user dial-up

access and the underdeveloped state of the internet service

providers (kapuruandara et al,2004). According to wicander et

al( 2006), although many african countries have taken steps to

improve their technology infrastructure ,great variation still

exists between regions and countries. In africa over 30 countries

still have less than one telephone line per 100 people (tele-

density). Compared to the average global penetration of 13

telephone lines per 100 inhabitants (evusa ,2005). Low tele-

density of fixed telephone lines has led to low technology usage

in kenya (kashorda,2007). Many countries in africa are however

expanding telecommunication networks but coverage in rural areas

where 70-80 percent of population live is uncovered (ochara et

al ,2008).

Kenya’s telecommunications monopoly policy approach would be

incompatible with the co-operative’s objective (mulunga ,1994).

However, this policy and the organizational structure have

followed the postal and telegram telecommunication (ptt) monopoly

approach traditionally followed in european countries and most of

23

asfrica. Nevertheless, the telecommunication policy in kenya is

fast beginning to be influenced by wave of change towards

increased competition that swept across advanced economies of the

world. According to kp and tc (2000), the motivation to initiate

the move towards liberalization was a desire to improve

efficiently by introducing competition and to have the private

sector share the increasing financial burden of supplying terminal

equipment.

According to makau ( 2010), in regard to provision of services,

multiple operators are competing in various market segments based

on policy of private sector operating in a competitive environment

that ensures consumer interests. While the growth of technology

sector in kenya has been significantly influenced by global trends

it can be examined in terms of fixed and mobile telephone lines

(evusa ,2005). Telkom kenya is today the only fixed national

operator with bell communications ltd. Operating in northern

kenya. The kenya government has liberalized the mobile cellular

market which has four operators namely: safaricom limited, airtel,

orange and yu mobile networks .external pressure is primarily

from customers although suppliers also have some influence.

24

Influence of customer pressure has been recognized as a major

factor in technology adoption (sillence et al, 1998).

The relationship between the pressure of suppliers and that of

buyers on the adoption of technology is an important factor.

Rashid et al (2001), notes that this factor depends on the

characteristics of the suppliers and buyers such as the

geographical distance, habits, tradition and purchase behavior.

Another common form of external pressure affecting technology

adoption comes from customer demands such as branded firms

requiring technology adoption.

According to chepaities (1996), there is evidence that problems

caused by the impact of a political system such as control and

pressure by authorities may affect technology adoption. According

to rashid et al (2001), governments could be the most powerful

institutions affecting innovation. According to (ilo 2001), the

internet is used more widely where political and civil freedoms

are in place. The political will affect the conditions in which

technology is managed and developed (pelvia et al ,2002).

25

According to evusa (2005), the greatest handicaps for development

of internet services has been the regulatory restrtechnologyions

since access to the customers and international bandwidth is

through telecom kenya limited. These sentiments have been

supported by kasharda (2007) who has suggested that the problem of

technology adoption is partly caused by inadequate legal and

regulatory framework. Since legislation differs for every

country , so will its influence on technology. According to makau

(2010), in some countries certain types of telecommunication

equipment may be banned in order to protect local data and

information processing industries while some other countries may

require that hardware and software be purchased locally. In a

review of mobile telephony, munith (2003) found that there is need

for policies aimed at removing barriers to the implementation of

telecommunications infrastructure.

Hodas (1993) argued that cultural factors play an important role

in creating a negative attitude towards computers. This is because

of the tendency for computers to make life too mechanized thus

building up resistance from employees in accepting them. Straub

(1994) found that an important reason for disappointing results in

26

transferring technology from one culture to another is that the

decision makers who engage in such transfers lack sufficient

knowledge of either the importers cultural conditions or nature of

technology or both. He argued that importing a technology into

developing countries without enough understanding of national

culture can result in incompatibility between the culture and the

technology.

Silverstone et al (1996) and straub et al (1997), maintain that all

individuals live and work within a cultural environment in which

certain values, norms, attitudes and practices are more or less

dominant and serve as shared source of socialization and social

control. Hofstede (1997) and martinez (1999), observed that of the

major challenges facing developing countries is to make technology

an essential part of the people’s culture . Erumban et al (2006),

concluded that the significant variation in internet diffusion

and it implementation and acceptance between countries could be

attributed to national culture. Unfortunately, very few studies

have tried to examine the effect of national culture on the

adoption of technology in kenya. Given this gap in literature,

27

this study aimed at testing the effect of national culture on

technology adoption within hiv and aids cccs in nairobi county.

28

CHAPTER THREE

RESEARCH METHODOLOGY

3.0 Introduction

Research methodology refers to a description on data collection

methods, sampling design and statistical technique use for data

analysis. This section focuses on the research method and sample

design, the subject studied, the administration produce of the

questionnaires and measurement used in analyzing data. It shows

the flow process in gathering the data start from determining the

designing of the research used until the data is successfully

gathered.

3.1 Research Design

According to malhotra (2007) research design is a framework or

blueprint for conducting the marketing research project. It

details the procedures necessary for obtaining the information

needed to structure or solve marketing research problem. The

researcher used the descriptive research method in this study.

The descriptive research is the type of the conclusive research

that has as its major objective the description of something,

usually the market characteristics or functions (malhotra,29

2007). By using descriptive research, it is appropriate that the

survey method will be used in order to gather information on

technology adoption by SME in Kenya

3.2  Data collection method

Collection is the process of gathering, assembling and

accumulation of information, there are two method of data

collection generating has been implemented, that is the primary

data and secondary data. For the purpose of this study, the

researcher used primary data collected using questionnaire

3.3 Data Entry and Data Processing

The procedure of data analysis will be done after the data

collection is collected from the respondents. Then the data

30

collected will be keyed in and analyzed through the SPSS programs

after being coded in.

3.4 Data Analysis and Interpretation

There are several of analysis methods were used by the

researcher for this research to achieve the objectives and

answer the research questions. To interpret the data, the

researcher used statistical packaged for social science (SPSS)

17.0. There are three procedures for analysis of data chosen

in order to evaluate and interpret the data, frequency

distribution,. Descriptive statistics computed include the

means, standard deviations, and rank orders of the study

population’s response on the principal independent, and

dependent variables. Descriptive analysis is used to measure

how varied the respondents are in answering each item in the

questionnaire.

31

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48

Work plan: appendix 1

Activity period

Jan.-mar.2012

April-may2012

June-oct.

2012

Nov.-dec.2012

Jan.-jun.2013

July-dec.

2013

Jan.-march

2014

Aprl.-june2014

July-aug.

2014

Provisionalregistration,conceptpaper,proposaldefence

Approval bygraduateschool,substantive registration

Preparation andtesting ofinstrumentsresearch permitsand piloting

Data collectionand analysis

49

Thesiswriting /noticeand submission

Oral/presentation,thesis defence

Revision andsubmission ofcorrected thesis

Thesisediting/submission of finalthesis

Appendix 2 budget

Item Description CostProposalpreparationand defense

1 ) typesetting @20/= per page;40 pages

800/=

2) printing for defense (40pages,4 copies @ 10/= per page)

1,600/=

3) photocopy for defense (40pages, 14 copies each @3/= perpage)

1,680/=

4) printing for submission todepartment and school. (40 pages,8 copies @ 10/= per page)

3,200/=

5) binding (26 copies @50/=)Sub-total

1,300/=8,500/=

Allowances 1 ) 2 research assistants @ 500 90,000/= 50

for researchassistance

for 180 daysSub-total 90,000/=

Pre-testing

Transportcosts

1) photocopy questionnaires 600copies, (20 pages each @ 10/=)

sub-total

12,000/=

100,000/=

112,000/=

Questionnairesand datacollection

1) photocopy questionnaire 600copies, (10 pages each @ 10/=)Sub-total

12,000/=

12,0

00/=Data analysis 1) printing paper - 5 reams @

400/=2) cost of data analysisSub-total

2,000/=10,000/=12,000/=

Thesis writing 1 ) typesetting (@ 20/= for 150pages ) 2) printing for defense (150 pages, 8 copies@ 10/=)Sub-total

3,000/=12,000/=

15,000/=

Thesissubmission

1) printing copies for departmentand school ( 150 pages, 8 copies@ 10/= per page

15,000/=

2) binding (hard cover, 10 copies@ 2000 sub- total) 20,000/=

Unforeseencosts

1) Allow 10% of total cost 30,000/=

Grand total 314,580/=

51