NWACHUKWU, OGBONNAYA PG/MSc/09/54154 OGBONNAY… · NWACHUKWU, OGBONNAYA PG/MSc/09/54154 ... List of Tables x ... effective coordination and control of the enterprise a function he

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NWACHUKWU, OGBONNAYA

PG/MSc/09/54154

THE IMPACT OF LABOUR TURNOVER ON SURVIVAL OF

SMALL AND MEDIUM SCALE ENTERPRISES IN ENUGU

STATE

Institute for Development Studies

A THESIS SUBMITTED TO THE DEPARTMENT OF INSTITUTE FOR

DEVELOPMENT STUDIES, UNIVERSITY OF NIGERIA ENUGU CAMPUS

Webmaster Digitally Signed by Webmaster‘s Name

DN : CN = Webmaster‘s name O= University of Nigeria, Nsukka

OU = Innovation Centre

2011

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TITLE PAGE

THE IMPACT OF LABOUR TURNOVER ON SURVIVAL OF

SMALL AND MEDIUM SCALE ENTERPRISES IN ENUGU

STATE

BEING A PROJECT SUBMITTED TO INSTITUTE FOR

DEVELOPMENT STUDIES, UNIVERSITY OF NIGERIA,

ENUGU CAMPUS

BY

NWACHUKWU, OGBONNAYA

PG/MSc/09/54154

IN PARTIAL FULFILMENT OF THE REQUIREMENTS

FOR THE AWARD OF THE MASTER OF SCIENCE

DEGREE IN DEVELOPMENT STUDIES

SUPERVISOR: MR B.D UMOH

2011

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APPROVAL PAGE

This dissertation has been approved for the department of Development Studies,

Faculty of Institute of Development Studies, University of Nigeria Enugu Campus, by

............................................................................................

MR B.D UMOH

(SUPERVISOR)

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CERTIFICATION

The work incorporated in this project is original and has not been submitted in part or

in full for any other Diploma or Degree of this University or any other Institution of

higher learning.

......................................................................

NWACHUKWU, OGBONNAYA

(STUDENT)

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DEDICATION

This research is strictly dedicated to the Almighty God, the source of my inspiration,

vision, and sense of direction.

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ACKNOWLEDGEMENTS

7

ABSTRACT

The production of goods and services for human consumption are made possible by

two main factors and two principal agents. The two main factors of production are

land and capital while the agents are the entrepreneur and labour. The entrepreneur

provides the land and capital resources while labour works on them to transform

them into finished goods and services for consumption. In this arrangement the

entrepreneur, sometimes referred to as the capitalist plays a pivotal role in that he

provides the productive factors and engages labour to work on them. Labour as a

factor of production involves human elements and may be defined as a form of

physical and mental efforts put into production of goods and services. Small and

medium enterprises have been looked upon as the engine of economic growth and for

promoting equitable development. Small and Medium firms have been praised over

time because of the myth that they have the propensity to employ more labour since

most of them have labour intensive production process than the larger enterprises. In

Nigeria, small and medium scale enterprises sector is seen as a necessary nursery of

innovation and entrepreneurship to jump start the economy. However, high rate of

labour turnover have often been blamed as reason for the slow growth of the small

and medium scale sector, thus this study sought to: ascertain the impact of labour

turnover on the profitability of small and medium scale enterprises in Enugu State;

determine the relationship between labour turnover and small and medium scale

enterprises age in Enugu State and establish the link between labour turnover and

size of small and medium scale enterprises in Enugu state. The survey research design

was adopted to enable the researcher make use of primary data to determine the

impact of labour turnover on the survival of small and medium scale enterprises in

Enugu state using questionnaire. The study covers fifty (50) small and medium scale

enterprises scattered around Enugu State. The Simple linear Regression technique

was adopted to test hypothesis one while the Pearson Moment Correction was used to

test hypothesis two and three using SPSS statistical. While Labour Turnover (LAB)

was the independent variable, Profitability (PAT), Age (AGE) and Size represented by

Total Assets (TA) were the dependent variables for the three hypotheses. The result

revealed that Labour turnover have positive significant impact on profitability of

small and medium scale enterprises in Enugu State; there was positive correlation

between labour turnover and age of small and medium scales enterprises in Enugu

state; and there was positive correlation between labour turnover and size of small

and medium scales enterprises in Enugu state. The findings of this study thus

conforms with existing literature that the high rate of labour turnover impact

negatively on the survival of small and medium scales enterprises therefore owners of

small and medium scale enterprises should desist from indiscriminate sacking of their

labour force as to encourage continuity which in the long run will led to survival.

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TABLE OF CONTENTS

Title Page i

Approval Page ii

Certification Page iii

Dedication iv

Acknowledgements v

Abstract vii

List of Tables x

List of Appendixes xi

CHAPTER ONE: INTRODUCTION

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

1.2 Statement of the Problem. . . . . . . 4

1.3 Objectives of the Study. . . . . . . 5

1.4 Research Questions. . . . . . . . 6

1.5 Research Hypotheses . . . . . . . 6

1.6 Scope of the Study. . . . . . . . 6

1.7 Significance of the Study. . . . . . . 7

1.8 Limitations of the Study. . . . . . . 8

References. . . . . . . . . 9

CHAPTER TWO: REVIEW OF RELATED LITERATURE

2.1 Overview of Small and Medium Scale Enterprises. . . . 11

2.2 Developments in the Theory on Small and Medium Enterprises. . 14

2.3 Socio-Economic Factors Affecting SMEs. . . . . 17

2.4 Small and Medium Scale Enterprises: A Conceptual Discourse. . 18

2.5 Small and Medium Scale Enterprises in Nigeria: Revisiting Government

Intervention . . . . . . . . 21

2.6 Impact of Socio-Economic Factors on the Performance of Small-Scale

Enterprises. . . . . . . . . 24

2.7 Constrain Against the Survival and Growth of SMEs. . . 27

2.7.1 Socioeconomic Constraints. . . . . . . 27

2.7.2 Institutional Constraints. . . . . . . 28

2.7.2.1 Lack of Government Support for SMEs. . . . . 28

9

2.7.2.2 Lack of Private Sector Support for SMEs. . . . . 29

2.7.3 Firm Level Barriers. . . . . . . . 29

2.8 Finance, MSEs and Poverty Reduction. . . . . 30

2.9 Labour Turnover and Firm Performance. . . . . 33

2.10 Labour Scheduling with Employee Turnover and Absenteeism. . 35

2.11 Labour Turnover and Motivation for Workers‘ Behaviour. . . 37

2.12 Employee Turnover and Employee Compensation in Small Business. 40

2.13 The Importance of Managing Human Resources in SMEs. . . 42

2.14 High Performance Work Systems. . . . . . 43

2.15 Human Resources Management and Firm Size. . . . 44

2.16 High Performance Work Systems and Performance in Small Businesses. 46

2.17 High Performance Work Systems and Innovativeness in Small Businesses. 47

2.18 The Microfinance Revolution and SMEs. . . . . 49

References

CHAPTER THREE: RESEARCH METHODOLOGY

3.1 Nature and Sources of Data. . . . . . . 66

3.2 Population and Sample Size/Techniques. . . . . 66

3.3 Description of Research Variables. . . . . . 66

3.3.1 Independent Variable . . . . . . . 66

3.3.2 Dependent Variables . . . . . . . 67

3.4 Model Specification. . . . . . . . 67

3.5 Technique of Analysis. . . . . . . 68

References. . . . . . . . . 69

CHAPTER FOUR: PRESENTATION AND ANALYSES OF DATA

4.1 Presentation of Data. . . . . . . . 70

4.2 Test of Hypotheses. . . . . . . . 74

4.2.1 Test of Hypothesis One. . . . . . . 74

4.2.2 Test of Hypothesis Two. . . . . . . 74

4.2.3 Test of Hypothesis Three. . . . . . . 75

CHAPTER FIVE DISCUSSION OF FINDINGS. . . . 76

References. . . . . . . . . 78

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CHAPTER SIX SUMMARY, CONCLUSION AND

RECOMMENDATIONS

6.1 Summary of Findings. . . . . . . . 79

6.2 Conclusion. . . . . . . . . 79

6.3 Recommendations. . . . . . . . 80

Appendixes. . . . . . . . . 82

Bibliography. . . . . . . . . 92

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LIST OF TABLES

Table 4.1 Summary of Proxies

Table 4.2 Summary of SPSS Result for Hypothesis One

Table 4.3 Summary of SPSS Result for Hypothesis Two

Table 4.3 Summary of SPSS Result for Hypothesis Two

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LIST OF APPENDIXES

Appendix 1 Questionnaire Letter

Appendix 2 Questionnaire

Appendix 3 Extract Fro Questionnaires Distributed

Appendix 4 SPSS Result for Hypothesis One

Appendix 5 SPSS Result for Hypothesis Two

Appendix 6 SPSS Result for Hypothesis Three

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CHAPTER ONE

INTRODUCTION

1.1 Background of the Study

The production of goods and services for human consumption are made

possible by two main factors and two principal agents. The two main factors of

production are land and capital while the agents are the entrepreneur and labour

(Anyae1e, 2003,). The entrepreneur provides the land and capital resources while

labour works on them to transform them into finished goods and services for

consumption. In this arrangement the entrepreneur, sometimes referred to as the

capitalist plays a pivotal role in that he provides the productive factors and engages

labour to work on them (Anyaele, 2003).

The entrepreneur as the owner of the productive enterprise is the risk bearer, and his

reward comes in form of profit (or loss). To maximize his return he carries out

effective coordination and control of the enterprise a function he may also delegate to

the employee. Thus, labour is vital both in productive and administrative functions of

an enterprise. The engagement of labour by an entrepreneur creates a labour relation

which can be referred to as dealing between management and workers about

employment condition. An employer‘s relative power over employee is dependent

upon numerous factors, the most influential being the nature of the employment

relationship. The relationship an employees shares with his employer is affected by

three significant factors namely personal, maintenance and motivation (Fox, 1974).

Personal is known as non-work factor while the last two arc known as job and

organization related factors respectively, and represent the hygiene (maintenance) and

motivators (growth) factors in Hertzberg‘s two factor theory (Mullins 2005). It is up

to the employer to effectively manage and balance these factors to ensure a

harmonious and productive working relationship. Employees of an enterprise‘ can

organize into labour unions that represent their interest in the organization. Also the

employees through the union utilize their representative power to collectively bargain

with the management of their organizations in order to advance concerns and

demands of their membership (Martins 2003). However an offer of employment or

even the existence of a workers‘ Union does not guarantee employment for whole life

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time. This means that an employment relationship is considered to be at will in which

the employer and employee are both free to terminate the employment at any time and

for any cause or for no cause at all provided the purpose of termination is not deemed

unjust before the law (Boxall, Macky and Rasmussen, 2003).

The termination of employment by an employee or employer reduces the existing

stock of labour force, while an addition by reason of fresh employment increases the

stock of labour force. The process of reducing or adding to the existing stock of

labour of an enterprise is known as turnover (Okunrotifa, 1982). In human resource

management context, turnover can be refers to as staff turnover, employee turnover or

labour turnover which means the rate at which an employer gains or losses employee.

Price (1977) defines turnover as ―the ratio of the number of organizational members

who have left during the period considered, divided by the average number of people

in that organization during the period, while Abassi et al (2000) say employee

turnover is the rotation of workers around the labour market; between firms, job and

occupation and the states of employment and unemployment. Labour turnover is also

seen as the flow of manpower into and out of an organization, in which the inflow is

referred to as accession and the outflow as separation (Fapohunda, 1980). Behrend,

(1953) succinctly sees labour turnover as one of the unorganized forms of industrial

conflict in which employees usually retreat from unsatisfactory situations.

A certain amount of labour turnover is inevitable. Illness: accidents, aging, death and

a variety of personal reasons that bring about separation. Labour turnover is not

always a negative phenomenon as studies have shown that it creates opportunities to

introduce better hands, work practices and procedures, new ideas to an organization as

well as providing career development opportunities for the existing workers (Tziner

and Birati, 1996). High rate of labour turnover however can severely reduce

productivity as workers are perpetual learners, new to the organization all the time,

demoralize incumbents and damage an organization‘s public image thereby adversely

affecting her corporate existence (Olugunde, Asaolu and Elurnulade, 201 1)

Separation arising from job quits has specific adverse effects on both the worker and

the organization. The worker who suddenly disengages from job experience

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disruption on income inflows, and may suffer the need to search, find and learn new

job specifics under new career prospects (OECD Outlook, 1999). The organization

suffers the loss of job- specific skill (Fair, 1992), the loss of investment in terms of

recruitment, induction, training, development and maintenance of the lost employee

(Ongor 2007,). Where a replacement is to be made, the replacement costs include,

search from external labour market for a possible substitute, selection between

competing substitutes and formal and informal training of the substitute until he or

she attains performance level equivalent to the individual who quits (John, 2000). In

addition to these replacement costs, output is affected to some extent as it would

either decline or be maintained at existing level at the cost of overtime payment or

overstretching the existing labour force. The disruptive effects of turnover on

organizations are many that they try at all cost to minimize the turnover rate.

Employee turnover is a much studied phenomenon although there have not been any

precise reasons why people quit jobs. Some of the empirical researches are based on

actual turnover while others on intention to quit. Apart from the practical difficulty in

conducting turnover research among people who have left an organization, some

researchers suggest that there is a strong link between intentions to quit and the actual

turnover (Kirschenbaun and Mano-Ne grin, 1999; Mobley et al, 1979) note that the

relationship between intentions and turnover is consistently and generally strong to

predict satisfactory turnover relationship.

All over the world, small and medium enterprises (‗SMEs) have been looked upon as

the engine of economic growth and for promoting equitable development (Adeyemi,

2011). Small and Medium firms have been praised over time because of the myth that

they have the propensity to employ more labour since most of them have labour

intensive production process than the larger enterprises. In Nigeria, Onah (2003) sees

a vibrant SME sector as a necessary nursery of innovation and entrepreneurship to

jump start the economy. Eneh (2005) has similarly observed that the vibrancy and

growth of Eastern Nigeria economy which was adjudged the fastest growing and

industrializing economy in the world in the early 1 960s was anchored on the

emerging SMEs in some parts of the Region.

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In Nigeria today, SMEs represent on the average between 80-90% of enterprises and

account for 60 to 70% of domestic employment (Aremu and Adeyemi, 2011). For the

Nigerian agrarian economy, SMEs can play significant role in the transition of

agriculture- prone economy to industrial one by furnishing opportunities for

processing activities which can generate sustainable sources of revenue and enhance

the development process of the country (Fida, 2008).

However, findings have shown that SMEs in Nigeria have not done well hence it has

been noted that a good number of them die within the first five years of existence

while smaller percentage go into extinction between the sixth and tenth year with only

about five to ten percent of them surviving, thriving and growing into maturity (Basil,

2005). Ezeh and Onodugo, (2002), Arernu and Adeyemi (2011) have attributed the

early death and poor growth in the SME Sector in Nigeria to factors external to the

sector. Such factors include: poor access to funds, low equity capital from

stakeholders, poor infrastructural facilities, multiplicity of regulating agencies,

overbearing environment, little access to markets and information, corruption and

societal attitudinal processes among others. Internal facts like poor management

practices, poor condition of service and un-conducive work environment are de-

motivators to employees are likely precursors to the unhealthy performance of the

SMEs.

Inadequate motivation (Ologunck, Asaolu and Elumilade, 2011), job related factors

according to Nwadiani and Akpotu, (2002), have been suggested as strong predictors

of labour turnover in Nigerian universities and non-work (personal) factors say Umar

and Karofi (2007) as the major cause of labour turnover among female workers in the

civil service. A series of commissioned studies link job related factors and

organization factors as possible predictors of labour turnover in a range of informal

sectors notably the SMEs in some OECD Countries (Bluedom, 1982; Saks, 1996; and

Zuber, 2001).

However, there is a dearth of researches that have tried to link the seeming poor

survival of SMEs to the rate of labour turnover in Nigeria. This is a lacuna which this

work seeks to fill.

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1.2 Statement of the Problem

The rate at which employer gains and losses employees, thus, it is used to describe it

are how long employees tend to stay or the rate of traffic through the revolving door.

Turnover is measured for individual companies and for their industry as a whole. If an

employer is said to have a high turnover relative to its competitors, it means that

employees of that company have a shorter average tenure than those of other

companies in the same industry. High turnover may be harmful to a company's

productivity if skilled workers are often leaving and the worker population contains a

high percentage of novice workers. Studies in developed economies have shown that

job and organization factors are some major determinants of labour turnover in the

informal sector notably the SMEs. Though these have been historically laid down in

management theories, policy formulation based on studies in developing economies

which do not take into cognizance our individual country peculiarities might be

misleading. The state or condition of yielding a financial profit or gain from the

operations of the organizations determines how long that particular organisation

thrives.

Empirical evidence shows that while younger firms may have a higher propensity to

generate jobs than older SMEs; this is to some extent offset by their lower survival

chances. Since some mature firms also demonstrate a potential to generate jobs.

However, within the context of such a survival of SMEs, young growing firms may

need particular kinds of support which could be offered within the context of policies

designed to encourage and support growing businesses at different stages of

development. SMEs sector plays a pivotal role in the overall industrial economy of

the country. It is estimated that in terms of value, the sector accounts for growth of the

manufacturing output and as well as the total export of the country. Further, in recent

years the MSE sector has consistently registered higher growth rate compared to the

overall industrial sector. The major advantage of the sector is its employment

potential at low capital cost. Therefore when SMEs are not generating enough profit

there is the tendency that they may close which is harmful for the development of the

nation‘s economy. Also SMEs should be encourage with enough incentive to live

longer as well as increase the size which in the long run assist in achieving the desired

goal for which there were set-up.

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1.3 Objectives of the Study

The general objective of the study is to investigate the impact of labour turnover on

the survival of SMEs in Nigeria. The specific objectives are to:

i. Ascertain the impact of labour turnover on the profitability of SMEs in Enugu

State.

ii. Determine the relationship between labour turnover and SMEs age in Enugu

State and

iii. Establish the link between labour turnover and size of SMEs in Enugu state.

1.4 Research Questions

As a result of the above stated objectives, the following are the research questions,

these are:

i. What impact does labour turnover have on the profitability of SMEs in

Enugu State?

ii. What are the relationships between labour turnover and SMEs age in

Enugu State?

iii. What are the relationships between labour turnover and the size of SMEs

in Enugu State?

1.5 Research Hypotheses

In order to achieve the objectives of this study and from the research questions raised

above the following hypotheses are stated, these are:

Ho1: Labour turnover do not have positive significant impact on profitability SMEs

in Enugu State.

Ho2: There is no positive relationship between labour turnover and SMEs age in

Enugu State and

Ho3: There is no positive relationship between labour turnover and SMEs size in

Enugu State

1.6 Scope of the Study

The study will be limited to Enugu state and to the three senatorial zones of the State

precisely. SMEs outside the boundaries of the state will not be included. The study

covers SMEs randomly selected from the three senatorial zones and employees of

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SMEs within the specified zones. In terms of classification of SMEs, the study adopts

The National Council of Industry NCI‘s reclassification of SMEs by size and scale of

operations at its 13th meeting on July 2001 (Eneh 2005), as follows:

Micro/Cottage Industry: An industry with a labour size of not more than 10

workers or total cost of not more than Nl.50 million including working capital

but excluding cost of land.

Small-Scale Industry: An industry with a labour and size of 11- 100 workers

or a total cost of not more than N50 million, including working capital but

excluding cost of land.

Medium Scale Industry: An industry with a labour size of between 101-300

workers or a total cost of over N50 Million but not more than N200 million

including working capital but excluding cost of land.

The SMEs studied are further classified according to their business engagement as

follows:

Agriculture and Agro-allied services industries

Manufacturing/production industries including factories that transform raw

materials into consumer goods or producers of capital goods. extractive and

construction industries

Services industries including financial institutions, recreation providers,

consulting and research and development service providers.

1.7 Significance of the Study

The study is considered significant on the following grounds:

It will contribute to literature in this area as there appear presently scanty researches

on causes of labour turnover and its impact on the performance of the SMEs sector in

Nigeria in general and Enugu State in particular.

The study will provides a guide to the nature and causes of job quits in SMEs in

general and specifically how this turnover occurs along industries, geographical and

gender lines.

20

The findings will help form basis for further studies on the impacts and costs of

labour turnover on the survival of this vital sector of the Nigerian economy and

subsequently how such effects can be mitigated.

The research will benefit employers of labour in the informal sector in their labour

relationship management and the study will provides vital guide on how SMEs can

create sustainable job opportunities towards poverty reduction and economic

development towards the overall achievement of the Millennium Development Goal

in Nigeria.

1.8 Limitations of the Study

The major anticipated limitations of the study will be the lack of, and in most cases

total absence of proper personnel records in the SMEs studies. There is occasional

apathy on the part of staff to disclose information regarding their employment

relation. The most critical will be the non availability of an official list of SMEs in

Enugu State; this will necessitate extensive travels to identify them in their scattered

locations. Thus this adds to the costs, risks and the delay in the final production of the

work.

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REFERENCES

Abassi, S.M. and Holirnan, K.W. (2000), ―Turnover the real bottom line‖ Public

Personnel Management 2 (3) 333-342

Anyaele, J. U. (2003), Comprehensive Economics for Senior Secondary Schools,

Lagos: Johnson Publishers Ltd

Aremu, M.A. and Adeyemi, S. L. (2011), ―Small and Medium Scale Enterprises as a

Survival Strategy for Employment Generation in Nigeria‖ Journal of

Sustainable Development, Vol. 4 No. 1

Basil, A.N.O. (2005), ―Small and Medium Enterprises (SMEs) in Nigeria, Problems

and Prospects‖ PhD Thesis, St Clernents University, St Clernents, Australia

Behrend, J. (1953), ―Absence and Labour Turnover in a Changing Economic

Climate‖ Occupational Psychology, Volume 27

Black‘s law Dictionary, Page 471 (5th edition 1979)

Bluedom, A.C. (1982), ―A Unified model of turnover from organizations‖ Human

Relations Journal, 35; 135-153

Ezeh, J. A and Onodugo, .V.A (2002), Business Policy and Strategic Management-

Issues and Trends, Enugu: Kinsman Publishers Ltd.

Eneh, 0. C. (2005), Small and Medium Enterprises in South East Nigeria: Problems

and Solution, Enugu: WIPRO Publication Ltd

Fair, D. (1992), ―How can managers reduce employee intention to quit?‖ Journal of

Management Psychology, 19(2) 170 -187

Fapohunda, A. M. (1980), ―What is Behind Labour Turnover?‖ Journal of Personnel

Management, Volume 7, No. 2, April — June P. 11

Fida, B.A. (2008), ―The Importance of Sinai! and Medium Enterprises in Economic

Development‖ The free on line library, (Accessed 14/3/2011)

Fox, A. (1974), Beyond Contract: Work Power and Trust Relations, London: Farber

and Farber

John, S. (2000), ―Job-to-job turnover and job to-non-employment movement‖

Personnel Review, 31(6) 710-721

Kirshenbaun, A. and Mano-Negrin, R. (1999), ―Underlying Labour Market

Dimensions of Opportunities: The Case of Employee Turnover‖ Human

Relations Vol. 52(10) pp 1233-1255

Mobley, W. H. et. al. (1979), ―Review and Conceptual Analysis of the Employee

Turnover Process‖ Psychological Bulletin, Vol.86 (3), PP. 493-522

22

Mullins, L. J. (2005), Management and Organizational Behaviours, New York:

Prentice Hall

Nwadiani, M. and Akpotu, N. E. (2002), ―Academic Staff Turnover in Nigerian

Universities‖ Journal of Personnel Management, Vol. 2 (4)

Ologunde, A. O. Asaolu, T.O; and Elumilade, D.O. (2009), ―Labour Turnover among

University Teachers in South- West Nigeria-Issues, Solutions and Lessons‖

Retrieved from http//unpanl.un.org/introdoc/groups/public (Accessed on

23/3/2011)

Onah, J.O. (2004), Introduction to Small and Medium-Scale Enterprises Management

In―Empowering Small and Medium Scale Enterprise in Nigeria by Onah J.O.,

Nwosu I. and Ocheoma. 0. (Edited). Enugu: ECCIMA /MANMARK

Associates Ltd

Ongori, H. (2007), ―A review of literature on employee turnover‖ African Journal of

Business Management, http/www.acadernicjorurnals.org/ajbm, (Accessed on

23/3/2011)

Price, J.L. (1977), The Study of Turnover, Iowa: University Press

Sacks, A. M. (1996), ―The relationship between the amounts of helpfulness of entry

training and work outcomes‖ Hunan Relation Journal, 49; 429-451

Tziner, A. and Birati, B. (1996), ―Assessing employee turnover costs: A revised

approached‖ Human Resource Management Review, Vol. 6 (2) PP1 13

Umar, M. S. and Karofi V.A. (2007), ―Non- Work Factors and Labour Turnover

among Female Employees in Kebbi State Civil Service‖ Journal of Sociology,

Volume 4, No. 2

Zuber, A. (2001), ―A career in food service cons: high turnover‖ Nations Restraunt

News, 35(21): 147-148.

23

CHAPTER TWO

REVIEW OF RELATED LITERATURE

2.1 Overview of Small and Medium Scale Enterprises

Developing countries value small and medium enterprises (SMEs) for the static and

dynamic gains that these firms bring. From the static point of view, Small and

medium enterprises, on average, are believed to generate relatively large amounts of

employment while also achieving decent levels of productivity. From the dynamic

point of view, the sector is viewed as being populated by firms most of which have

considerable growth potential, a contrast with micro enterprises that tend not to

graduate from that size category (Leidholm and Mead 1999). Many Small and

medium enterprises will grow significantly without exiting that size category while

others will eventually become large, that is, the ―seed-bed for large firms‖ function of

small and medium enterprises. Another aspect of the dynamics of small and medium

enterprises that distinguishes them from larger enterprises is their high entry and exit

rates. The process of rapid turnover raises a set of issues about possible impacts on the

economic efficiency of the sector and about policies that may curtail such efficiency

losses as are associated with it. Finally, it is often argued that one advantage of small

and medium enterprises is their flexibility, relative at least to larger firms. This is

construed by some as a plus in industries and economies that, for whatever reason,

face rapidly changing market conditions, including sharp macroeconomic downturns

such as those that have bedeviled most of the countries of Africa over the last few

years.

In general, small and medium enterprises are an integral element of the informal

sector in most developing countries. In the majority of cases, these enterprises are

initially informal but gradually some of them survive and become formal businesses,

thereby providing the foundation of modern private companies (Mkandawire, 1999;

Cook and Nixson, 2005). Hence, the growth of these enterprises is part and parcel of a

dynamic growth process in the corporate sector, as argued by Liedholm and Mead

(1994) and Prasad et al. (2005).

As noted by Cook and Nixson (2005), although a number of measures have been used

to identify and describe small and medium enterprises, there is no consensus on any

24

one measure and it is customary to use several metrics, including the value of fixed

assets of the enterprise, enterprise turnover and the number of employees. Ryan

(2005) has pointed out that the term may be used to cover a wide range of economic

activities for an indicative number of employees; for example survival activities (<1

employees), household activities (1þ), micro enterprise sector (<5), small emergent

enterprises (<25) and growth businesses (<100 employees).

In the poorest countries, on average almost two thirds of workers are employed in

enterprises with less than 5 employees while the majority work for enterprises with

less than 100 employees (Cull et al., 2004). During the last 50 years, considerable

insight into the characteristics of small and medium enterprises has been gained. Early

literature, particularly Staley and Morse (1965), enhanced the conceptualization of the

main characteristics of small and medium enterprises and the pattern of growth of

these enterprises.

However, Anderson (1982) notes that there was lack of basic data on the management

and characteristics of small and medium enterprises. Industrial censuses tended to

concentrate on large enterprises; censuses of small and medium enterprises were often

non-existent or quite infrequent and published after a long delay. The lack of data

hampered any attempts to undertake serious empirical work on measuring the

characteristics of small and medium enterprises and explaining the behaviour of these

enterprises (Cook and Nixson, 2005). However, during the 1980s, some efforts were

made to collect baseline data on small and medium enterprises by, among other tasks,

identifying universes, constructing samples and devising methods to deal with

incomplete entries. However, due to poor book-keeping by small and medium

enterprises, the data were often incomplete, unreliable and not repeated across

samples. Hence, while the baseline data could be used for measuring the

characteristics of small and medium enterprises, it was not adequate for testing

theoretical propositions about the expected behaviour of the small and medium

enterprises.

Gradual improvements were achieved over the years such that by the early 1990s,

some basic databases were available for empirical studies aimed at identifying the

constraints facing the growth and development of small and medium enterprises in

25

developing countries (Levy, 1993). One of the main findings from these studies was

that the growth and development of small and medium enterprises in developing

countries were mainly inhibited by access to finance, poor managerial skills, lack of

training opportunities and high cost of inputs (Cook and Nixson, 2005). Importantly,

further studies especially those conduced in the late 1990s and thereafter suggest that

finance is the most important constraint for the MSE sector (Green et al., 2002).

Each country tends to derive its own definition based on the role of small-scale

industries are expected to play in the economy and the programme of assistance

designed to achieve that goal. Varying definitions among countries may arise from

differences in industrial organization at different levels of economic development in

parts of the same country (Anamekwe, 2001). For instance, Sule (1986) suggested

that a firm that can be regarded as micro or small in an economically advanced

country like United States of America, Great Britain or Japan, given their high level

of capital intensity and advanced technology, may be classified as medium or even

large in a developing country like Nigeria. Definitions also change over time, owing

to changes in price levels, advances in technology or other considerations.

In the United States of America, the Small Business Administration (SBA, 2003) has

various definitions for small businesses depending on the type of industry.

Manufacturing and mining businesses with fewer than 500 employees are considered

small businesses while businesses in wholesale trade industries must have fewer than

100 employees. For other industries, such as retail and construction, businesses are

classified based on annual revenue. Also, in Ghana, the Ministry of Industries uses a

definition involving multiple criteria of turnover, fixed assets and the number of

employees. However, the criteria such as turnover and volume of output are strongly

influenced by management effectiveness and efficiency, which vary from one

industry to another (Ajayi, 2002).

The definition of small-scale enterprises (SSEs) in Nigeria has changed over the years

not only in consonance with the changing fortune of the country but also in

accordance with the diversity of the Small and Medium Enterprises (SMEs)

supporting institutions in the country. Prior to 1992, different institutions in Nigeria

adopted varying definitions of small enterprises. The institutions include the Central

26

Bank of Nigeria (CBN), Nigerian Bank of Commerce and Industry (NBCI), Centre

for Industrial Research and Development (CIRD), Nigerian Association of Small-

Scale Industrialists (NASSI), Federal Ministry of Industry (FMI) and the National

Economic Reconstruction and Fund (NERFUND).

2.2 Developments in the Theory on Small and Medium Enterprises

The last 50 years have witnessed important developments in the conceptualisation of

the main issues relating to the small and medium enterprises sector and subsequent

theoretical work. The main theory, which goes back to the seminal work by Lewis

(1955), is the labour surplus theory. It is argued that the driving force behind small

and medium enterprises development is excess labour supply, which cannot be

absorbed in the public sector or large private enterprises and is forced into small and

medium enterprises in spite of poor pay and low productivity. Arguably, the small and

medium enterprises sector develops in response to the growth in unemployment,

functioning as a place of last resort for people who are unable to find employment in

the formal sector. Small and medium enterprises are expected to grow in periods of

economic crisis, when the formal sector contracts or grows too slowly to absorb the

labour force.

However, when formal employment grows, the small and medium enterprises sector

is assumed to contract again and thus develops an anti-cyclical relationship with the

formal economy. Particular attention has been paid to the behaviour of the small and

medium enterprises sector before and after the introduction of structural adjustment

policies; examples include Daniels (1994) and Brand et al. (1995) for Zimbabwe and

Meagher and Yunusa (1996) for Nigeria.

One re-interpretation of the labour surplus theory is the new literature on

deagrarianisation, which relates the development of rural non-agricultural activities to

the rural surplus labour, which, in turn, either supplements agricultural production

with nonagricultural activities or migrants to the urban areas (Bryceson, 1996;

Bryceson and Jamal, 1997). The effect of such a theory would be similar to that of the

theory of commercialisation of the rural areas, namely, a continuous growth in the

informal small and medium enterprises sector.

27

However, there are some empirical problems with the unemployment theory of the

growth and development of small and medium enterprises. First, there is lack of

reliable and adequate data for researchers to test the hypothesis that small and

medium enterprises absorb surplus labour from the public sector or large private

enterprises and the hypothesis that increases in labour demand by small and medium

enterprises has taken place before or after structural adjustment. Second, for the small

and medium enterprises sector to function as a place of last resort, it must be easily

accessible. However, many studies have shown that this is only the case for a handful

of small and medium enterprises activities. It is also sometimes argued that small and

medium enterprises concentrate on trade because this requires less capital and

knowledge than production.

While it may be true that production requires more investment capital than trade,

small scale trade is likely to require more working capital than small-scale production

in order to secure a certain income. This is partly because value added is lower for the

trader than for the producer, and partly because, in small-scale production, the

customer will often be required to pay for the materials in advance, while the small-

scale trader will have to give credit (probably more often than large formal retailers).

Therefore, there are severe limitations to the extent to which the small and medium

enterprises sector can function as a place of last resort during crises.

The second theory for explaining the development of the small and medium

enterprises sector in developing countries is the output-demand theory. The theory

postulates that a prerequisite for the development of small and medium enterprises is

that there is a market for their products and services. Therefore, the small and medium

enterprises sector will tend to develop a cyclical relationship with the economy as a

whole. However, small and medium enterprises will also develop in competition with

large enterprises in the formal sector, and their development will be constrained by

formal sector monopolies. Structural adjustment and other policies that limit such

monopolies, and attempt to create more competition, will therefore be advantageous

to the small and medium enterprises, because this may allow them to capture market

shares from the large enterprises. Proponents of structural adjustment and stabilisation

policies tend to base their arguments on this theory. Empirical studies based on the

output-demand theory tend to focus on the upper end of the small and medium

28

enterprises sector, particularly the manufacturing enterprises and the larger, more

resourceful and successful small and medium enterprises, which have a potential to

grow into the formal economy. These studies propose strengthening of the small and

medium enterprises through networks or via the creation of forward linkages with the

formal economy, for example franchising and sub-contracting. This approach has not

had much success in Africa due to problems of poor infrastructure and lack of trust

between both parties. This creates an unstable environment and reduces the efficiency

of the formal sector and access to factor markets for small and medium enterprises

(see, for example Liedholm and Mead, 1993; Grierson and Mead, 1995).

In addition, a modified strand of the output-demand theory links small and medium

enterprises and the long-run development of the rural agrarian economy in an anti-

cyclical relationship, to the detriment of agricultural production (Bryceson and Jamal,

1997). As a result of monetisation, commercialisation and urbanisation, the rural

population turns to nonagricultural activities and the money economy. This creates a

growing market for small and medium enterprises‘ goods and services.

The third theory, known as the firm growth theory, contends that, as a result of

industrialisation and economic growth, small and medium enterprises are likely to

disappear and be replaced by modern large-scale industry. This theory has, however,

been shown to be inaccurate in the sense that small and medium enterprises do not

normally compete directly with large enterprises; rather, they often tend to remain

micro and small, co-existing with large multi-national companies, which phenomenon

the World Bank (1989) has identified as the ‗missing middle‘ (Ryan, 2005). For

example in a study of Botswana, Kenya, Malawi, Swaziland and Zimbabwe, Mead

(1994) found that most small and medium enterprises started with one to four

employees and never expanded; less than 1% grew to exceed 10 employees. In

addition, the small and medium enterprises tend to find niches in the factor and input

markets where scale economies cannot be exploited by large enterprises.

The most obvious activity where these niches exist is in distribution to areas or

income groups where their costs would be prohibitively high for large enterprises.

However, in a literature survey on macro analyses of micro enterprises in developing

countries, Liedholm and Mead (1993) came to the conclusion that macro-level

29

empirical evidence indicates that, as aggregate per capita income increases, there is a

systematic pattern of evolution of MSEs towards larger firms based in larger

localities, producing more modern products.

Nevertheless, critics of this view argue that analyses on MSE development must take

account of differences in their efficiency, the type of influence MSEs exercise in

society, linkages between small and large enterprises, the changing roles of women

entrepreneurs, differences in the level of education in the labour force and other socio-

economic differences. In all, each of the three theories has been modified into some

variants; however, one of the important elements common to all the theories and

variants is the proposition that the growth of MSEs can contribute to poverty

reduction.

2.3 Socio-Economic Factors Affecting SMEs

Nigeria since independence has been undergoing some economic strangulation that

has impoverished the nation and its citizenry over the years. The Centre for Gender

and Social Policy Studies (CGSPS), in a communiqué early in the year 1999 observed

that the general socio-economic situation in Nigeria over the years had deteriorated

and consequently, poverty has increased. It was agreed that Nigeria has descended to

join the group of low-income countries and poverty is pervasive and deep-seated in

the country. It also pointed out that there a lot of unrecognized poor in Nigeria today

especially in the rural areas (which of course included the several riverine fishing

communities), which have not benefited economically from government agricultural

development policies (Aworemi, Abdul-Azeez and Opoola, 2010).

The Vanguard (1997) depicts the situation by reporting that many Nigerian families

can no longer provide enough food, adequate shelter, comfortable accommodation,

decent clothing and proper Medicare for family members. In some cases, the

breadwinner, father or mother is out of job. In several other cases both father and

mother and even the children have jobs but their incomes fall flat in the face of

inflation and high cost of living. People die of hunger and starvation for lack of

money to buy foods and drugs. Individuals in the rural communities (especially in the

riverine areas) live in shacks and houses with leaky roofs because of their inabilities

30

to pay house rents. The same report has it that poverty level in Nigerian family rose to

about 75% in 1997. Polygamous marriage was prevalent in these rural areas as well as

the high numbers of children per family contribute to family poverty.

Nigeria‘s demographic profile in 1995 indicated a population of 111.7 million with an

average household size of 5.0, population growth rate of 2.83%, rural population of

64% compared to 36% urban population and a 6.2% urban growth rate. It estimated

that the mean age of marriage is 16.9 years (a common situation of the in the rural

areas among the young girls and adolescent women as a result of their lack of

adequate educational background and/or education training institutions. The total

fertility rate (National average) is 6.0%, 15-49 year female population is 25.2 million

and 15-49 year male population is 22.9 million. Children 6-11 year population is

estimated to be about 19.3 million, under five population is 17.1 million and under

one population is 2.5 million and doubling time with the quoted growth rate (2.83%)

is 25 years, hence, the socio-economic potentials of individuals (for example the

women in the riverine) in the small-scale enterprises is significant. Some

characteristics like age, gender, and individual background such as education and

former work experience have an impact on entrepreneurial intention and endeavour

(Kristiansen, et al, 2003) found that human capital or human resource such as age,

gender, education and experience is a further influence on the decision to become

self-employed (Aworemi, Abdul-Azeez and Opoola, 2010).

2.4 Small and medium scale enterprises: A conceptual Discourse

Small and medium scale enterprises have been long recognized as an instrument of

economic growth and development. This growing recognition has led to the

commitment of World Bank group on SMEs sector as core element in its strategy to

foster economic growth, employment and poverty alleviation. In the year 2004the

World Bank group has approved roughly $2.4 billion in support of micro small and

medium enterprises (World Bank, 2001, Ayyagari et al 2007) While the importance

of small and medium scale enterprises has not been in doubt, unfortunately classifying

businesses into large and medium scale is subjective and premised on different value

judgment. Such classification has followed different criteria such as employment,

sales or investment for defining small and medium scale enterprises. According to

extant literature the definition vary in different economies but the underlying concept

31

is the same. Ayaggari et al (2003) Buckley (1989) contends that the ―definition of

small and medium scale enterprises varies according to context, author and

countries‖. In country such as USA, Britain and Canada small scale business is

defined in terms of annual turnover and the number of paid employees. (Ekpeyong

and Nyang, 1992) In Britain for example small scale business is conceive as that

industry with annual turnover of 2 million pound or less with fewer than 200 paid

employees (Ekpeyong and Nyang, 1992). In the case of Japan it is conceptualized as

type of industry, paid up capital and number of employee.

Consequently small and medium scale enterprises are defined as those manufacturing

with 100million yen paid up capital and 300 employees. Those in wholesale trade

with 300million paid up capital with 100 employees while those in retail trade with

100million paid up capital with 50 employees (Ekpeyong and Nyang, 1992). In the

case of Nigeria hardly do you see a clear-cut definition that distinguishes between

small and medium scale enterprises. However, the Central Bank of Nigeria in its

monetary policies circular No. 22 of 1988 view small scale industry are those

enterprises which has annual turnover not exceeding 500,000 naira.(CBN; 1988)

Similarly in 1990 the Federal Government of Nigeria defined small scale enterprises

for the purpose of commercial bank loans as those enterprises whose annual turnover

does not exceed 500,000 thousand naira and for merchant bank loan those enterprises

with capital investment not exceeding 2 million naira (excluding the cost of land) or a

minimum of 5 million naira.

Ogechukwu (2006) contends that in the wake of SFEM, and SAP era in 1993, this

value has now been reviewed and subsequently, increased to five million naira. Since

this happened, there may be a need to classify the small scale industry into micro and

super-micro business, with a view to providing adequate incentives and protection for

the former. In that context, any business or enterprise below the upper limit of N250,

000 and whose annual turnover exceeds that of a cottage industry currently put at N5,

000 per annum is a small scale industry. (Ibid; 5) The National Directorate of

Employment (NDE) concept of a small scale industry has been fixed to a maximum of

N35, 000. (Ibid; 5). In other words a business unit of not less than $240 dollar is

characterized as a small scale business in Nigeria. That may not be the same in other

32

countries, but that classification may be useful in developing countries, because of the

low capacity of its small scale industry.

That is why Kozak, (2007) argues that we cannot explain SME other than to say they

are companies with metric (usually no of employees or annual turnover that fall

bellow certain threshold. It is these indicators, number of employees and or rate of

turn over that tend to define the context within which different countries and

economies situate their understanding of small and medium scale enterprises. This is

to say that, even though SMEs is definable with much or less the same indicator (No

of employees, rate of turnover .etc) the indicators are not the same in all countries all

the time. In other words while number of employee and rate of turnover are the

indicator, the number of employee and total amount of turn over for defining SMEs in

different countries are certainly not the same. For instance, the employee

requirements in Britain is 200, with 2million pound turnover, the same cannot be said

of Japan with 100million Japanese yen as paid up capital and 300 paid employees.

While in Nigeria, the paid employees are usually not considered important, but more

importantly is the turnover of 500,000 especially for the purpose of Commercial and

Mortgage bank loans. Balunywa (2010) however affirmed that the number of

employee may not be a good indicator, especially where the company is labour

intensive. This is true in country like India, where labour intensive is a policy

approach to industrialization. However, that is not to say that in some cases, trading

organization cannot transact big business, but yet employed few employees. In that

case, capital employed may be used as indicator for defining small and medium scale

enterprises.

In countries where the number of employees is an indicator, the number of employee

required differs from country to another. In Uganda the figure of employees for SMEs

is between 5-50, (Ngobo, 1995) in India it is 30-100, while in the US, is less than 500.

(Stoner et.al, 1996) In Kenya, 10 or fewer people are called micro business, while 11-

50 are referred to small enterprises and 51-100 are called medium enterprises. (Kibera

and Kibera, 1997). That is why in the United State of America, small business

administration is defined as one that is independently owned and operated, is not

dominant in its field and meet up employment or sales standard developed by the

33

agency (Stoner et.al 1996). This shows the same trend with other countries like

Nigeria and Japan except that the exchange value differs in the financial criteria.

In a more general and comprehensive term Ogechukwu (2005) chronicled a general

criteria for defining small and medium scale enterprises in different countries. These

includes number of employees, annual turnover, local operations, sales volumes,

financial strength, managers and owners autonomy, relatively small markets

compared to their industries and capital usually supplied by individual or shareholders

etc. There are so many small scale business units in Nigeria which qualifies within

this context most of them are in the commercial sector. However a common trend in

Nigeria today is the gradual classification of service provider, hotels, fast food and

restaurants as small and medium scale enterprises.

As a result of this definitional differences and lack of universal definition, the

European Union in 2003 adopted a universally accepted definition of small and

medium scale enterprises and micro business as companies with less than 250

employees, with respect to financial criteria, revenues must not exceed 50 million

Euro (measure as turn over) or 43million euro(measure as balance sheet) In addition,

the European Commission specifies term of ownership stating SMEs must be

independent with less than 25% being owned by outside interest (European

Commission; 2007).

In a report of enterprises association, Macqueen (2004) conceive of SMEs as

enterprises employing 10-99 full time employees or with a fixed capital investment of

US$1000-500,000. Small and medium scale enterprises are certainly not transnational

company, multinational cooperation, publicly owned enterprises or large facility of

any kind. However they can depend on business and ownership structure to become a

large business unit (Macqueen 2006) while it can be argued that 80% of the financing

of SMEs come from owners, friends and families, business form can take different

form including private ownership, limited partnership, contract and sub-contracts,

cooperatives or associations. (Kozak, 2007) Small and medium scale enterprises have

a narrow context within which its operation is carried out. However, where it is

effectively operated it has capacity to sprout the economic growth and national

development.

34

2.5 Small and medium scale enterprises in Nigeria: Revisiting government

intervention

In every economies small and medium scale enterprises has been seen has a pivotal

instrument of economic growth and development either in developed or developing

economies. Several studies have confirmed this. (Ogujiuba; et al 2004, Onugu; 2005,

Ihua; 2009) Data from the federal office of statistics in Nigeria affirmed this

importance when it reveal that about 97percent of the entire enterprises in the country

are SMEs and they employed an average of 50% of the working population as well as

contributing to50 percent of the country industrial output. As Ariyo (1999) and Ihua

(2009) averred, SMEs in Nigeria are not only catalyst of economic growth and

development, but are also the bedrock of the nation.

Although small business activities had existed since the period of independence in

Nigeria, however, conscious effort on small and medium scale enterprise as

instrument of economic and national development started in 1970-1979 when Nigeria

adopted the policy of indigenization through its national development plan

programme. The development plan articulated the need for the Nigerian economy to

be self reliant through industrialization, entrepreneurial development employment

generation and development through increasing export trade. (NDP, 1970)

The federal government singled out small and medium scale enterprises as the key

area of intervention. This was premised on the government desire of giving support to

small scale industries in the country as a measure of meeting up with its commitment

to the development plan and the indigenization policy. The intention was that it would

be a reaction against the dominance of the economy by the international capitalist

entrepreneur and on the account that revitalizing small and medium scale enterprise

would enhance the capacity of the indigenous capitalist class, as a potential player in

economic growth and national development.

In its intervention effort, government promulgates different regulation for the basis of

protecting the small scale industries. Some of the regulations include Nigeria

Enterprises Promotion No. 3 of 1977, Patent Right and Design Act No 60 of 1979

Custom Duties (dumped and subsided goods Act No. 9 of 1959, Industrial Promotions

act No. 40 of 1979, Industrial development Tax Act No. 2 of 1971 among others

35

(Alawe, 2004). Apart from the promulgated act government supported SMEs through

favorable investment policies, institutional and fiscal policies, protective business law

and financial incentives to encourage the national development and indigenization

policy which small and medium scale are very central to. Several micro lending

institutions were established to enhance the capacity and development of small and

medium scale enterprises. Such microcredit institutions include Nigeria Bank for

commerce and industry (NBCI) National Economic Reconstruction Funds (NERF)

People`s Bank of Nigeria (PBN) Community Bank (CB) National Export and Import

Bank (NEIB) and the liberalization of the banking sector to enhance the banking

institutions for effective participation in the growth and capacity building of small and

medium scale enterprises (Ogujiuba; et al, 2004).

Government also established Raw Materials and Research Development Council

(RMRDC) of finance and research institutions in 2001, the research report of this

institution is useful to SMEs and business organization in their product choice

decision, product development delivery strategies to increase SMEs business

effectiveness and efficiency. To complement this effort, government also created

some polytechnics and university to provide manpower scheme and also set up some

manpower training institutions. Such as Centre for Management Studies, (CMD)

Administrative Staff College of Nigeria (ASCON) Industrial Training Institute (ITI)

etc. (Ogechukwu, 2006) A number of recommendations and findings of these

institutes and centre were geared towards developing small and medium scale

enterprises

In addition to this, the government through the bankers‘ forum at the initiative of

CBN as an interventionist strategy also established small and medium industry equity

investment scheme (SMIEIS) in 2001. This scheme requires bank to set aside 10

percent of their profit before tax to fund SME in an equity participation framework. In

2002, government further intervened to enhance the capacity of SMEs through direct

policy as consisting of direct investment and the establishment of more SMEs,

promotion institution agencies (technological development institutions, credit lending

institutions, technical and management institutions and the provisioning of

infrastructures such as industrial estate, nationalization of foreign firms and provision

36

of incentives and subsidies for the promotion of small and medium scale companies.

(Alawe 2004)

The establishment of anti-corruption bodies such as Economic and Financial Crime

Commission (EFCC) and Independent Corrupt Practices Commission (ICPC),

investment in power generation, road maintenance and construction and enactment of

pension funds were addition effort geared towards improving the SMEs sector

(Onugu, 2005). In spite of the participation and effort of the government in

developing SMEs, the contribution index of manufacturing to GDP was 7% in 1970-

1979 (Odedokun, 1981). In 2004, a survey conducted by manufacturer association of

Nigeria revealed that only about 10percent of industries run by its members are fully

operational. Similarly Joshua (2008) contends that about 70percent of the small and

medium scale enterprises in Nigeria are between operational or on the verge of

folding-up, while the remaining 30 percent operate on low level capacity and are

vulnerable to folding up in the nearest future.

In 2009, the constraint was further compounded by a sharp drop of manufacturing to

GDP of 4.19 percent while industrial capacity utilization dropped to 48.8percent

(National Bureau of Statistics, 2009). This portends danger for the Nigeria economy

given the fact that manufacturing industries are critical agent of real growth and

development for the country (Abiodun, 2010).

2.6 Impact of Socio-Economic Factors on the Performance of Small-Scale

Enterprises

Among others, Nigeria say Aworemi, Abdul-Azeez and Opoola (2010) one of the

major oil producing countries in the world was recently classified to be one of the

poorest countries. World Bank (2000) stated that the poverty has increased

dramatically with 65% of the population living below the poverty line as against 43%

in 1992. It has been observed that there is no country in Africa whose deterioration in

socio-economic status has been as severe as that of Nigeria, to the extent that within

the last five years, half of the population is living below the poverty line (World

Bank, 2000). The socio-economic status of the country has considerably affected the

development and improvement of certain sectors. Recent times have witnessed a

number of strategies, and activities like sharply expanded programmes, techniques

37

and innovations in agricultural programmes in Nigeria in order to address the

deteriorating socio-economic situation.

Universities, research institutes and private sector organizations are the most

important institutions involved in the technical entrepreneurship, which is one of the

major sources of wealth, power and employment in developed countries.

Unfortunately, the absence of viable industrial and private sector, the deficiencies of

existing infrastructure and dominance of foreign-based multinational companies tend

to have a limiting effect on the capacity to create, foster and nurture indigenous

enterprises in Nigeria. Identifying and supporting the activities of potential and

existing entrepreneurs has become a major concern for an increasing number of

governments in developed and developing countries. Public policies are designed in

developing countries to increase the pool of entrepreneurs and to promote the

formation of certain types of business at the micro and small-scale levels which foster

technological activities (Litvak, 2002).

The governments in most developing countries such as Nigeria were criticized for

paying inadequate attention to the need for accelerated economic growth and for not

harnessing the abilities of their own citizens for technological innovations and

entrepreneurship (Anamekwe, 2001). Critic concluded that these developing countries

depend on exogenous technologies that are inappropriate for their environment. This

has been responsible for Nigeria‘s exports which have largely been based on raw

materials and semi-manufactured goods with the petroleum sector as the most

important. Less than 5% of these exports are on the average attached to knowledge

intensive goods and services (Akeredolu-Ale, 1975). These problems became acute in

the 1980‘s and early 1990‘s, when Nigeria experienced stagnating industrial output

and decreasing crude oil prices while industrialization through the production of

indigenous technological development became central topics in the industrial policy

debates. This view was subsequently enunciated in the various development plans,

national budgets, and rolling plans and in the current reform programmes elaborated

in the National Economic Empowerment and Development Strategy (NEEDS) (Sule,

1986). The central theme of the policy has been that small industries should spearhead

the nations drive towards economic recovery. Studies have shown that small-scale

industries in many countries provide the mechanism for promoting indigenous

entrepreneurship, enhancing greater opportunities per unit of capital invested and

38

aiding the development of local technology (Nils-Henrik and Morch, 1995). Recent

work summarized in the background paper on small-scale industries has shown that

small-scale forest-based processing enterprises form a very large part of the overall

forest products processing total in employment terms (FAO, 1995).

In Nigeria, small-scale businesses represent about 90% of the industrial sector in

terms of the number of enterprises. They also account for 70% of national industrial

employment if the threshold is set at 10-50 employees, contribute 10% of

manufacturing output and a meager 1% of gross domestic product (GDP) in 2001

(Ajayi, 2002). Similarly, they have also contributed significantly to economic

development through employment, job creation and sustainable livelihood (Nigeria

Investment Promotion Commission, 2003).

In spite of the major role, the significance and contributions of the small-scale

enterprises to the national economy, this set of enterprises are still battling with many

problems and certain constraints that exist in promoting their development and

growth. For instance, (International Labour Organization, 1994) study shows that

inadequate entrepreneurial talent affects the development of small-scale

manufacturing and processing industries. While large-scale industries are established

with expatriate capital, small-scale industries need to have a domestic entrepreneurial

and industrial base. Other problems that hinder the advancement of small-scale

enterprises are the persistent low level of technology, the shortage inadequate

entrepreneurial skills of operators and the absence of an effective management

technique. Discussion of a change in the level of technology and its impact on the

Nigerian industries has focused on large firms (i.e capital-intensive, high technology

sectors). Focus on this change in the small-scale firms is relatively little. Small-scale

enterprises tend to concentrate on traditional industries where low entry barriers, low

minimum production scales, and relatively large labour force are the potential

advantages.

However, the traditional industries have not been immune to the recent technological

revolution taking place in the field (Adubifa, 1990). Hanshom (1992) and McCormick

(1998) stated that African small enterprises are found to be unorganized in production

activities. Low capital investment on capital goods and lack of division of labour in

39

production makes these enterprises remained week. It is a clear fact that many micro,

small and medium-scale enterprises are dying out owing to lack of financial support

from the government and other citizens. Mills (1990) stated that the major pre-

occupation of all developing countries these days is simply how to improve social,

economic and political status of the people. According to Uma (1974), it involves the

improvement of the living standards of the mass of the low income population and

making the process self-sustaining. Improving the living standard of the people

involves the setting of priorities in the mobilization and the use of resources available.

In some rural areas, the working and living conditions of women for instance, have

not been able to be ameliorated by many recent programmes designed to improve

their economic status. Many writers have pointed out the detrimental effects on

women of technological and socio-economic changes in the process of development

(Dey, 1975; Zeidenstein, 1975; Palmer, 1978; Whitehead 1985; Stevens 1985). There

has not been a total consideration and enough provisions for some rural left out in the

provisions of the government toward the advancement of their enterprises.

The recent economic crisis in Nigeria has brought about an ironic change – an

increased demand for locally produced goods. For example, aso oke (a type of

traditional dress woven in the cottage industry) is now popular at social gatherings

and in the fashion houses. Because refrigerators have become unaffordable, rural

dwellers are stuck with locally produced ―water pots‖ which are noted for their

cooling effects on drinking water. Also, many Nigerians have now resorted to using

locally produced soap (ose dudu, i.e black soap). Yet, the people producing these

goods are constrained by their lack of access to critical resources (capital, labour,

land, infrastructures, and improved technology (Aworemi, Abdul-Azeez and Opoola,

2010).

2.7 Constrain against the Survival and Growth of SMEs

Guzman and Santos (2001) developed a conceptual model showing that

socioeconomic and institutional factors, such as macroeconomic policies, in an

entrepreneur‘s external environment, and personal characteristics of the entrepreneur,

directly affect enterprise success and economic development. Extending work by

Shane (2004), they propose that these socioeconomic and institutional factors also

influence the types of, and information about, such opportunities that are available to

40

the entrepreneur. According to Mintzberg (1989), barriers to SMME survival and

growth are likely to be faced in all four functional areas of business operation -

management, marketing, operations and finance – and may be directly related to the

size and start-up conditions of an SMME. This implies that analysis of constraints to

enterprise success and economic development must also consider firm level barriers.

2.7.1 Socioeconomic constraints

Constraints such as a lack of public infrastructure services and reduced access to

profitable markets may result from an SMME‘s spatial distance from urbanized areas.

These boundaries are demarcated by local authorities. Areas situated far from

urbanized centers within municipal boundaries can be classified as ‗rural‘ (Smit,

1997, cited by Rogerson, 1999). Rogerson (1998) found that the availability of

infrastructure services is often directly linked to the location of business. The SMMEs

located closer to urban centers often have better access to services compared to those

in poorer rural areas (Naude, 1998; Berry et al, 2002; Klitgaard and Fitschen, 1997;

Matangul et al, 2001). Necessary services for business survival and growth include

access to water, electricity, serviceable roads, telecommunications, postal services and

protection from crime.

These rural communities have been spatially isolated in areas that typically have a

sparse resource base, limited cash circulation, and negligible information about

product opportunities outside survivalist trading, services or production activities.

Consequently, rural entrepreneurs often compete within a small, location specific with

relatively low-income clients, where fewer customers may afford their product.

Larger, more developed markets may be situated at prohibitive distances from the

entrepreneur‘s home, and the entrepreneur‘s proximity to both buyers and suppliers

constrains business performance. Lack of own transport markedly increases the

transaction costs for enterprises based in remote rural areas or at large distances from

main roads (Rogerson, 1998). Moser (1997) found that rural SMMEs, as a result of

their greater distance from developed markets, place a high value on social capital or

contact networks. A lack, or absence, of such networks potentially places a major

constraint on agribusiness SMME survival and growth (Fenwick and Lyne, 1999).

41

2.7.2 Institutional constraints

Institutional constraints may arise directly or indirectly from a perceived lack of either

government or private sector support for SMMEs.

2.7.2.1 Lack of government support for SMMEs

Entrepreneurs may interpret the administrative and financial burdens placed on their

enterprise by having to comply with a range of government legislated procedures and

laws as a lack of government support for the agribusiness SMME sector. Lack of

investment, or start-up, capital and difficulty in accessing investment capital have

been identified by SMME owners as a major constraint to their business survival and

growth. Inadequate property rights and an absence of title deeds in many developing

countries results in a lack of collateral necessary to access to investment capital, and

creates a lack of incentive to make fixed improvements to land, which compounds the

problem of low collateral. Difficulties in accessing investment capital may also arise

from SMME owners‘ lack of understanding of loan application procedures, or a

private lending institution‘s bias against SMMEs due to the relatively high costs of

administering relatively small loans (Bannock, 2002).

2.7.2.2 Lack of private sector support for SMMEs

Once a business has started up, access to expansion or working capital may be

restricted by an entrepreneur‘s difficulties in understanding private sector loan

financing schemes, weak organizational arrangements, overly complexapplication

procedures, and private lending institutions‘ bias against financing SMMEs (Naude,

1998). Access to markets may also be a constraint if appropriate intermediary and

private institutions do not interface with SMMEs to link entrepreneurs with potential

buyers and suppliers of inputs.

Subcontracting linkages between large enterprises and emerging SMMEs are an

important element in facilitating SMME sector growth (Naude, 1998). Private

intermediaries and parastatal organizations like development financiers can provide

SMME support through training activities, business counseling, advice on contract

tenders, and help in securing loans (Mead, 1998).

42

2.7.3 Firm level barriers

An SMME owner‘s lack of knowledge or management skills, or inability to multi-

task, and not competing products, may cause business failure (El Namaki, 1990; Hoad

and Rosko, 1964). Young small firms may also face severe under-capitilisation and

liquidity problems. Knight (1981) states that most enterprises are started with a small

equity base that only grows when the firm generates retained earnings from

operations. Owners and managers frequently lack the ability to present a convincing

business plan to lending institutions, and lending institutions are often biased against

financing small business. The issue of loan collateral is important for small

businesses, as they seldom own sufficient fixed assets to qualify for bank loans. Cash

flow problems can be exaggerated when entrepreneurs invest heavily in start-up

equipment (Bhide, 2000).

Escalante (1996) cites low quality, and high turnover, of labour as common obstacles

encountered by newly established firms. Smaller firms can seldom afford the wage

rates necessary to attract highly qualified or skilled labour and employees rarely

remain in small firms as they accept more lucrative employment opportunities from

larger, more established firms. The physical facilities and business premises used by

many small businesses are often inadequate to provide any long-run competitive

threat to larger established enterprises, and many small businesses can seldom afford

sufficient technology at start-up (Karlson, 1994 cited by Escalante, 1996).

The biggest threat to new SMMEs in the early part of their business operations is

often the well-entrenched, secure position of strong competitors who have already

captured a portion of the existing market (Porter, 1979). Combined with the firm level

barriers described above, this makes them particularly vulnerable to rivalry from

competing sellers, the bargaining power of buyers and input suppliers, the threat of

new entrants to their product markets, and the threat from substitute products in other

industries (Porter, 1980). A comprehensive review of 98 articles on factors

responsible for the success of SMMEs around the world by Nieuwenhuizen and

Kroon (2003) identifies business knowledge, market orientation, financial knowledge

and management, and creativity and innovation, as key firm-level factors affecting

successful business performance.

43

The above review shows that the constraints to survival and growth faced by SMMEs

may result from one, or a combination of, dimensions such as lack of access to public

infrastructure, a lack of public sector support, restrictive government policies, the

nature of an emerging SMME, an entrepreneur‘s lack of management and/or

innovation skills, or a lack of private sector intermediary support.

2.8 Finance, MSEs and Poverty Reduction

One important innovation in development research and policy has been the refocusing

of the goals of development strategy from an exclusive concern with economic

growth to ‗growth with poverty reduction‘. The prioritisation of poverty reduction has

also increased interest in the contribution that financial development can make to

poverty reduction. For example the profound argument made by Stiglitz (1998) is that

market failure is a fundamental cause of poverty, and financial market failures, which

mainly arise from market imperfections, asymmetric information and the high fixed

costs of small-scale lending, limit the access of the poor to formal finance, thus

pushing the poor to the informal financial sector or to the extreme case of financial

exclusion. In addition, it is argued that improving the access of the poor to financial

services enables these agents to build up productive assets and enhance their

productivity and potential for sustainable livelihoods (World Bank, 2001b). Hence,

the bottom-line argument is that improving the supply of financial services to the poor

can directly contribute to poverty reduction. It is in this context that researchers and

policy analysts have shown a renewed interest in the contribution of finance to

development and poverty reduction, in order to obtain empirical grounds for

formulating financial sector policies that can contribute to poverty reduction.

It has also been argued that financial development can have an indirect effect on

poverty outcomes through its direct impact on economic growth. Dollar and Kraay

(2002) argue that growth has been beneficial to the poor, although it should be noted

that economic growth can generate different poverty outcomes (McKay, 2002).

Growth may reduce poverty through improving the position of some on the lower

scale of the distribution; in some cases, growth may benefit the non-poor but may

improve income distribution overall.

44

Jalilian and Kirkpatrick (2002, 2005) model the interaction among financial

development, economic growth and poverty reduction, where ‗financial development

potentially has two poverty impacts, first indirectly through its impact on the rate of

mean income growth, and second, directly through improved supply of, and access to,

financial services to the poor‘ (Jalilian and Kirkpatrick, 2002). The model was tested

on panel data covering 26 countries including 18 developing countries, allowing for

various measures of financial development and poverty, including both income and

headcount data for the poor as well as the Gini coefficient for inequality and the Theil

inequality index. One important finding of the study is that a unit change in financial

development improves the growth prospects of income of the poor by almost 0.4%.

Overall, the results are consistent with the argument that financial development does

contribute to poverty reduction.

A crucial link between financial development and poverty reduction is through the

growth of MSEs. Inadequate access to credit and other financial services from formal

financial institutions has long been recognised as a constraint on the expansion of the

MSE sector. In response to what is seen as a failure of the market to provide small

firms with adequate access to external finance, significant resources continue to be

channelled into the financing of the MSE sector in developing countries. For example

Beck et al. (2005) estimate that the World Bank Group has approved more than $10

billion in MSE support programmes in the last 5 years, of which some 80% involves

direct financial assistance. In addition, a recent survey of funding sources for

businesses, conducted by the Investment Climate Surveys in 2002–2003 in 40

developing countries in Europe, Asia, Africa and Latin America, has found that larger

firms generally have more access to bank credit than small firms, whereas the latter

rely heavily on internal funds and retained earnings (Cull et al., 2004). Specifically,

the conclusion reached by Cull et al. (2004) is that dependence on informal sources of

funds decreases with size.

Views about the way in which financial services should be provided to poor people

have been changing in the last 50 years. Until recently, the dominant approach has

been based on the view that poor people lack the financial capital that will enable

them to invest and engage in productive activity, in particular making use of their

labour. In general, this view identifies capital constraints to growth as a key cause of

45

slow development. For about four decades since the early 1950s, efforts to provide

credit to poor people focused on the direct provision of credit through government

agricultural credit schemes and NGO initiatives.

Although initially such credit was usually targeted at the agricultural sector, often in

the context of the introduction of new agricultural technologies, the approach started

to take root in the informal enterprise sector in the mid-1970s. At this time, research

started to demonstrate the importance of the informal sector as a source of

employment and potential economic growth (Cook and Nixson, 2005). Subsequently,

development interventions by donors and governments started to target credit to the

informal sector. However, as shown by Murinde and Kariisa-Kasa (1997), the

performance of the credit programmes was generally found to be poor, in agriculture,

state enterprises and NGOs.

The intellectual consensus after World War II, especially in the 1960s and 1970s, was

that governments would intervene to provide directed credit to MSEs. However, it

was shown that government intervention in the financial sector led to financial

repression and the attendant distortions in the credit markets (Murinde, 1996). The

remedial policy, which came into force in the 1980s was financial liberalisation,

which saw the lifting of state intervention in the financial sector. Subsequently, the

literature in the early 1990s started to examine the implications of financial

liberalisation for MSEs (Aryeetey and Nissanke, 1998; Ryan, 2005). According to

mainstream finance theory, it was expected that financial liberalisation would

facilitate access to finance and thus reduce the transactions costs facing MSEs.

However, the assumption that financial liberalisation improves access to credit for

MSEs does not stand up well to the experience of developing countries, which face

market imperfections and asymmetric information. For example Steel (1994) and

Steel et al. (1997) have challenged this assumption for developing countries, while

Dawson (1993) has found that formal sector credit was out of reach for smaller

enterprises in Ghana and Tanzania. Moreover, Kariuki (1995) has shown that access

to credit by Kenyan firms declined after liberalisation, due to higher nominal interest

rates and increases in other transactions costs. Further evidence shows that the small

size of MSEs is a serious impediment and enterprises have to grow in order to gain

further access; in this context, Meier and Pilgrim (1994) have found that in

46

Bangladesh, Nepal and the Philippines, only enterprises towards the upper end of the

size distribution had viable access to formal sector finance.

Since the late 1990s there has been a further shift in analysis and understanding of

poor people‘s financial needs. Livelihoods approaches suggest that poor people use

the resources they have to construct livelihood strategies in response to the risks and

opportunities that they face (Johnson et al., 2005). This perspective converges with

growing insights into the operation of informal financial systems to offer a more

holistic perspective on the financial service requirements of poor people. The

approach suggests the need to shift emphasis from the provision of credit for specific

productive purposes to the provision of financial services, which allow poor people to

more effectively manage the financing of their livelihood strategies.

2.9 Labour Turnover and Firm Performance

Labour turnover is an important and pervasive feature of the labour market. In OECD

countries, approximately 10-15% of workers quit their jobs every year; 15% in the

United States alone (OECD Employment Outlook, 1999, 2005). Labour turnover

affects both workers and firms. Workers experience disruption, the need to learn new

job-specific skills and find different career prospects (see, Chow et al. (1999), Tran

and Perloff (2002), Roy (2002), Theodossiou (2002), Gautier et al. (2002), Taplin et

al. (2003), Clark (2004) and Leuven (2005).

Firms, on the other hand, lose job-

specific skills, suffer disruption in production and incur the costs of hiring and

training new workers. Incoming workers, however, may be better educated, more

skilled and have greater initiative and enthusiasm than those who leave. The focus of

the economics literature on labour turnover has been on the impact of turnover on

workers rather than on firms. This may be due to limited availability of data, which

has allowed only sporadic study of these issues. Turnover and hiring costs have been

studied, for example, by Burgess and Dolado, 1989, Hammermesh, 1995 and

Hammermesh and Pfann, 1996, while Hutchinson et al, 1997, and Kersley and

Martin, 1997, have analysed the impact of turnover on productivity.

The theory used to explain the impact of turnover on firms is mostly based on the well

known efficiency wage model of Salop (1979),

in which firms choose wages so as to

minimise the marginal cost of labour, balancing the marginal effect of higher wages

47

against the marginal reduction in training costs induced by higher wages. In an earlier,

similar setting Schlicht (1978) shows that natural unemployment is induced by

excessive labour mobility in the face of high turnover costs. More recently, in the

context of a dynamic search model where a continuum of firms choose permanent

wage offers and workers sequentially sample from those, Burdett and Mortensen

(1998) show that firms paying high wages and making low profits per worker

experience low turnover, while firms paying low wages and making high profits have

high turnover.

Brown, Garino and Martin (2007), explore the theoretical predictions of an extension

to the model of Salop (1979) developed by Garino and Martin (2007), which

distinguishes between newly hired and incumbent workers, since the latter have more

job-specific human capital but may have less general human capital. A higher

turnover rate implies that the proportion of new hires in the workforce is larger.

If this

causes a sufficiently large increase in productivity then an increase in turnover can

increase profits. Garino and Martin (2007) show that this effect is possible, but only

when firms do not unilaterally choose the wage – for example when the wage is

negotiated with a union or set nationally. When the firm chooses the wage

unilaterally, as in Salop‘s original model, the impact of turnover on profits is negative.

In order to test the predictions from this theoretical framework, we analyse cross-

section, establishment-level data from the 2004 Workplace and Employee Relations

Survey (WERS) in order to ascertain the nature of the relationship between turnover

and measures of firm performance. Our findings support the inverse relationship

predicted by Salop (1979) if firms are able to choose wages unilaterally, which

confirms our theoretical priors. Furthermore, where firms do not set wages

unilaterally, our empirical analysis generally supports a positive relationship between

the quit rate and firm performance, again in line with the theory.

Thus, after exploring the theoretical predictions from an extension to the efficiency

wage model of Salop (1979), where the rate of turnover is an exogenous function of

the wage and of other factors including the general market wage, by distinguishing

between incumbent and newly hired workers in the production function, they find that

if firms can choose wages unilaterally, the effect of turnover on profits is negative,

since, for a given turnover function, profit maximising firms adjust the wage to

48

minimise the cost of labour. Also in the case where firms cannot choose the wage

unilaterally, the impact of an exogenous increase in turnover on the maximun profit

function can be positive as well as negative. Thir empirical findings generally accord

with the theoretical predictions supporting a standard inverse relationship between

quit rate and firm performance where workplaces choose wages unilaterally; and

indicate a positive relationship if workplaces cannot choose wages unilaterally

(Brown, Garino and Martin, 2007).

2.10 Labour Scheduling with Employee Turnover and Absenteeism

Easton and Goodale (2002) say a host of direct and indirect costs arise from the wake

of each employee who voluntarily leaves an organization. Obvious expenses include

the employer's recruiting, hiring, and training costs for a replacement employee. Until

the vacancy is filled, employers may also face additional overtime costs, reduced

productivity, increased customer queue times, lost sales and business opportunities,

and the likelihood of additional turnover due to the extra work shouldered by

coworkers of the departing employees (Herman, 1997; McConnel, 1999; Richardson,

1999).

Turnover is not just expensive; it is pervasive, arising in virtually all professions.

Twenty percent of all new school-teachers and forty-four percent of all new lawyers

quit within three years (Cooper, 2000; Flaherty, 1999). The average annual turnover

rate (the number of annual resignations divided by the average workforce size) among

call center employees is 31 percent (Karr, 1999), although larger operations (500 or

more agents) average 61 percent/year. Zuber (2001), citing declining turnover rates

for limited-service restaurant workers, reported that 1999 turnover averaged 123

percent in this industry.

Voluntary turnover problems also tend to be persistent and difficult to eliminate.

Leonard's (1998) survey of human resource professionals found that 55 percent took

measures to improve turnover, but only 10 percent reported noticeable improvements.

Furthermore, many firms report that it takes 75 - 90 days to fill a vacant position

(Fitz-enz, 1997; Matson, 1999), followed by weeks or months of training before a

newly-hired employee becomes proficient. While turnover results in permanent losses

of human capital, unexpected absences due to illness or personal matters consume 2.5

49

percent of all scheduled work hours in the U.S. service sector (Bureau of Labor

Statistics, 2001). Some industries, however, suffer much higher absenteeism rates.

Call center managers, for example, report losing 12 - 16 percent of all scheduled work

hours to absenteeism (Call Center Ops, 2001).

The need to protect service delivery systems from turnover and absenteeism is well

established. Turnover planning models have been developed for many industries and

professions, including banking (Jones et al, 1973), engineering (Lapp and Thompson,

1974), law enforcement (Leeson, 1981), and the armed services (Charnes et al., 1972;

Collins, et al, 1983; Eiger et al., 1988). Typically, these models anticipate the effects

of turnover on existing staff and estimate the number of new employees that should be

recruited into the organization each year at each grade to satisfy projected future

staffing needs (Bartholomew, Forbes and McClean, 1991).

Easton and Goodale (2002) explore the day-to-day operational impact of turnover and

absenteeism, and developing techniques that mitigate their impact through short-term

staffing and scheduling decisions. Their premise is that both service demand and

employee availability are random variables. Easton and Goodale (2002) model the

day-to-day flux of employee resignations and new hires as a Markov process, then

derive estimates for the probabilities of realizing different incumbency levels. From

the underlying employee survivor function they predict workforce experience levels

and proficiencies. Modeling the service delivery system as a multi-server queue, they

also estimate revenue losses due to reneging when customer patience decays

exponentially with waiting time. Finally they devise a labor staffing and scheduling

model that integrates workforce incumbency probabilities, experience levels, and

random employee absenteeism with the object of maximizing expected profit under

stochastic demand and impatient customers. The model determines the nominal

workforce size, and how those employees should be deployed over time, to

compensate for anticipated turnover and absenteeism.

Easton and Goodale (2002) preliminary tests indicate that firms with low turnover,

low absenteeism, short average vacancy times, comparatively high unit revenues, and

multiple daily demand peaks benefit least from the SLS/DL model. In contrast, firms

with comparatively long transaction times, high customer arrival rates, relatively tight

50

profit margins, more patient customers, and greater task complexity (training time)

should experience significant benefits from this approach. These results suggest a

number of directions for future research. For example, we assumed interchangeable

employees with common skill sets, scheduling preferences, availability and reliability.

In future research, we hope to apply this methodology to systems with extant,

heterogeneous employees. Easton and Goodale (2002) also assumed single stage

processes in fairly large-scale systems. For smaller, lower volume operations or

systems with a sequence of operations, it may be more difficult to realize performance

advantages of the magnitude reported here. Finally, SLS/DL considers only one

strategy for coping with turnover -- overstaffing. Using other coping strategies, such

as temporary workers, overtime, reassigning cross-trained employees, etc., may

provide additional benefits.

2.11 Labour Turnover and Motivation for Workers’ Behaviour

Labour turnover is the flow of manpower into and out of an organization (Fapohunda,

1980). The inflow of manpower is referred to as accession and the outflow as

separation (leaving). Separation may be in the form of quits, discharges, lay-offs,

retirement, leaves of absence and even death. Accession on the other hand has to do

with replacements and new hires. Labour turnover is one of the unorganized forms of

industrial conflict. It is a retreat by employees usually from unsatisfactory situations.

Satisfaction is however only a part of the answer to the problem of labour turnover.

Other factors influencing include: the conditions of the labour market (Behrend,

1953), age of the worker, chances of obtaining another job and financial

responsibilities of workers, among other things. The incidence of labour turnover can

at times be seen as a reflection of the quality of management skill in securing

contentment among the people employed.

A certain amount of labour turnover is inevitable. Illness, accidents, aging, death and

a variety of personal reasons bring about separation. Too much of labour turnover

however can severely reduce productivity, as workers are perpetual learners, new to

the organization all the time; demoralize incumbents and damage an organization‘s

public image thereby adversely affecting her corporate existence. It implies therefore

51

that management should be concerned about the level of labour turnover in their

organization, determine the degree of it that is healthy or unhealthy for the

organization.

High labour turnover is dangerous as it affects the growth and productivity of an

establishment. Scholars believe that a core of experienced workers is necessary for the

success of an organization. For experience on the job and in the organization, workers

must be stable (Hackett, 1979). Organizations are highly concerned about employee‘s

leaving because it is generally very costly to select and train new employees to

replace those who left. There is a general situation of discontent pervading the entire

labour scene in Nigeria.

Studies on the influence of motivation on workers behaviour and productivity dates

back to 1911 when Fredrick W. Taylor the father of scientific management theory

presented his ideas on ―Pierce-rate system‖; (Taylor, 1911). Since then, a large

number of experiments including the famous Hawthorne studies have been done in

Industrial Psychology to determine the factors that influence workers‘ behaviour.

Several motivation theories have since been postulated in an attempt to predict

workers‘ behaviour in organizations. These include Abraham Maslow‘s theory; on the

hierarchy of needs which stated that an unsatisfied need is a motivating force. They

suggested that motivation to produce stemmed from a present or anticipated state of

discontent and a perception of direct connection between individual‘s production and

a state of satisfaction.

Other theories that have contributed in this direction include: Skinner‘s(1953)

Reinforcement theory, Herzberg‘s Two-factor theory; which tried to relate motivation

and need satisfaction to employee performance and productivity, and concluded that

positive job attitudes are favourable to increased productivity; McGregor‘s(1960)

Theory X and Theory Y, McClelland‘s (1961) Learned needs theory, Vroom‘s(1964)

Expectancy theory, Porter and Lawler‘s(1968) Integrative motivational model, and

Alderfer‘s (1972) ERG theory of work motivation. Some theories attempted to predict

performance behaviour. Locke‘s (1968, 1978) Goal-Setting theory and Adam‘s

(1963) Equity theory emphasized the role of social comparisons as an important

52

motivator of behaviour. Likert (1969) was of the opinion that the quality of

supervision could have a direct correlation with work satisfaction and productivity.

Mullins, (1999), and, Nwachukwu, (1994) says that the present day managers are of

the opinion that reward is a very strong motivating factor for workers and they make

use of both intrinsic and extrinsic factors. Oloko (1977) discovered that Nigerian

workers were more committed and motivated to work in organizations managed by

fellow Nigerians in which they foresee opportunity for advancement as limitless, than

in organizations managed by foreigners where management and supervisors‘ positions

were regarded as belonging to a special class. However, performance and productivity

was still low in these Nigerian organizations. According to Oloko in his 1991 study,

the low level was due to some other factors such as reluctance of supervisors to

delegate responsibilities to subordinates, reluctance of subordinates to accept

responsibilities, which is rational reaction to the fixed sum view of power held by

their superior, absence of cooperative relationship between and within grades of

employees, and treatment of members and time with careless abandon by

management.

Akerele, cited in Aluko (1998) stressed that in Nigeria, managers fail to effectively

manage their human resources. He gave the following as reasons for the

ineffectiveness:

1. Failure of management to provide good quality of work life and failure to

carry employees along with them, and this result in absenteeism, punctuality

problem, accidents, low morale, high-labour turnover and other forms of man-

day losses.

2. Management‘s inability to provide fair working conditions, which often lead

to industrial unrest, strikes, protracted negotiations all with serious effects on

productivity and labour turnover.

3. Poor remuneration in relation to profits made by organizations, unjustifiable

wage differential between high and low income earners in different sectors in

the economy also contribute to low morale, lack of commitment, low

productivity and high labour turnover.

53

It is obvious therefore that management‘s long standing concern with motivation

stems from the fact that low worker motivation are thought to be reflected in such

circumstance as low productivity, strikes, personal conflicts between supervisors and

their subordinates, absenteeism and high labour turnover (Ajila, 1996). Jobs,

according to Argyris (1970) have a stable set of identifiable characteristics that are

relevant to individual needs, wants and aspirations. Where the job characteristics are

compatible with a person‘s needs, the individual will be satisfied. Where the opposite

is the case, dissatisfaction sets in and this will be manifested in terms of leaving the

organization.

2.12 Employee Turnover and Employee Compensation in Small Business

Economists have long recognized that large firms on average pay higher wages than

small firms for the same type of work. This has been confirmed in study after study

beginning with Moore (1911) and continuing through King (1923), Mellow (1982),

Oi (1983), and Brown and Medoff (1989) among others. In companies with more than

500 employees, workers earn an average of 35 percent higher wages compared to

small companies (Brown et al., 1990) which is in the same range as the gender-wage

gap, the race gap, and union/non-union membership gap.

The size-wage gap increases with the size differential; Davis et al. (1991) found a 79

percent wage premium at plants with more than 5,000 employees as compared to

plants with 20 to 49 employees between 1963 and 1986. Their study also found that

33 percent of the wage gap increase among U.S. manufacturing production workers

between 1975 and 1986 was attributable to the size-wage premium. In spite of the

large and growing importance of the employer size wage premium, previous attempts

to account for this premium in terms of observable worker or employer characteristics

have met with limited success (Brown and Medoff, 1989; Davis et al., 1991; Oi,

1983, 1990; Hamermesh, 1980, 1993; Barron et al., 1987; Dunne and Schmitz, 1992).

Empirical evidence shows that the shorter duration of most small firm employment is

due to higher failure rates and greater turnover (Brown et al., 1990; Davis et al.,

1996). According to the theory of equalizing differences, this should result in higher

wages at small firms to compensate for the increase in the unemployment risk (Rosen,

1986).

54

There are also several possible explanations for the size-wage premium based in

economic theory. One explanation hypothesizes that size is related to market power

(Weiss, 1966; Mellow, 1982; Akerlof and Yellen, 1990). Large employers are more

likely to be monopolists and earn rents; thus, they must share some of these rents with

their employees to obtain optimal effort. The wage premium observed is the result of

the market power of a worker's firm.

A second explanation assumes that employers care about the mix of workers in the

plant and find it more profitable to match high-skilled workers with other high-skilled

workers, and low-skilled workers with low-skilled workers (Kremer, 1993; Kremer

and Maskin, 1995). If there are fixed costs involved in hiring more-skilled workers,

then large firms will be more likely than small firms to match workers by skill level

(Barron et al., 1987). The premium results from the overall skill mix of the workforce.

Another theory that posits firm size can proxy for worker ability is the capital-skill

complementarity hypothesis (Hamermesh, 1980, 1993; Griliches, 1970). Based on

Lucas‘s (1978) model, it posits that the most-skilled managers will manage the largest

firms in terms of employees and capital. If skill and capital are complements, then the

firm will also use the most-skilled workers. The premium here results from the

capital-labor ratio. Another explanation using the Lucas model theorizes that the

most-skilled managers are working for the largest firms. However, in Oi's (1983)

model, managers divide their time between monitoring workers and other

management tasks. All managers can monitor, but only the more-skilled managers can

perform the other functions. More-skilled managers employ more highly skilled and

highly paid workers because they require less monitoring. It is not clear why more-

skilled managers are not also better monitors or why more-skilled workers necessarily

require less monitoring. The premium results from the skill of managers.

Some explanations do not rely on the assumption that worker quality is positively

correlated with firm size. In Bulow and Summers (1986) the workers engage in

shirking and employers must choose between monitoring employees or paying high

wages under the threat of termination if they are caught shirking. If the cost of

detection rises with size, large employers will choose to pay higher wages and reduce

monitoring. The premium results from the amount of monitoring.

55

Another explanation holds that there is a positive correlation between high wages and

the growth and survival of firms (Brown and Medoff, 1989). This implies that the

firm‘s age should be included in the regressions to account for the premium. Some

studies theorize that larger firms have not only more skilled workers but also more

advanced technology, because they have more output to enable easier amortization of

the fixed costs (Dunne and Schmitz, 1992; Reilly, 1995). If capital and worker skill

are complements, then the larger the firm the more likely it will employ more-skilled

workers. The premium results from the firm‘s access to technology.

2.13 The importance of managing human resources in SMEs

Running a successful organization requires finding, retaining and motivating the right

employees. Current changes in the economic and demographic structure of Western

societies, such as the increased role of knowledge, the ageing of the workforce and a

decreasing inflow of entrants into the workforce, further increase the importance of

the management of the (internally and externally) available human resources. This

holds for all organisations, irrespective of their size. Recent years have witnessed an

increased flow of scientific papers on the relationship between various firm (and

employee) performance measures, and how these firms manage their human

resources. The general consensus of these studies is that HRM matters: employing the

right HRM policies and practices is likely to increase organizational performance.

Whereas early research on human resource management (HRM) and performance

tended to focus on the impact of separate HR practices on firm performance, the more

recent work looks at the combined effect of integrated sets of practices. These studies

relate certain types of ‗bundles‘, ‗systems‘ or ‗configurations‘ of HRM practices to

different indicators of organizational performance. Some of these integrated systems

of HRM practices have been labelled high involvement work systems or high

performance work systems (HPWS). Such systems are thought to increase employees‘

abilities, commitment and motivation, which in turn enhances their and ultimately the

firm‘s performance.

Several studies suggest that such HPWS can indeed positively affect firm

performance (Huselid, 1995). Although the results of studies on HPWS yield

promising results as to their effectiveness, many questions remain unanswered

56

(Delery, 1998). For example, exactly when and how do such HPWS affect

performance and what is their impact on other processes in the organization? In this

study we focus on several such questions. The main question we address here is

whether the relationship between HPWS and firm performance also holds in a small

business context.

Generally speaking, HRM research tends to ignore small and medium-sized

enterprises. This also holds for research on HPWS and firm performance. Only very

few studies so far have focused on HPWS and their effectiveness in small and

medium-sized enterprises (Way, 2002). Multi-industry HPWS research has tended to

exclude firms with fewer than 100 employees, and this exclusion ―has created a lack

of understanding of the impact of HPWS within the US small business sector‖ (Way,

2002). Other studies confirm that we know very little about the science and practice

of HR in small organizations (Huselid, 2003). This lack of knowledge on the

effectiveness of HPWS in the small business sector is not limited to the USA. In

Europe, such knowledge is also lacking.

Yet, even more so than in the USA, a large percentage of the workforce in EU

countries works in the small business sector and the contribution of SMEs to the

economy tends to be substantial. Thus, increasing our understanding of the role of

HPWS in SMEs in different countries is both scientifically and practically relevant.

2.14 High performance work systems

Recently, various studies have related certain types of ‗bundles‘, ‗systems‘ or

‗configurations‘ of HRM practices to different indicators of organizational

performance. Examples of such studies can be found in Arthur (1992, 1994), Batt

(2002), Becker and Gerhart (1996), Delery and Doty (1996), Den Hartog and Verburg

(2004), Guthrie (2001), Huselid (1995), Ichniowski and Shaw (1999) and MacDuffie

(1995). Some of these integrated systems of HRM practices have been labelled high

involvement work systems or high performance work systems (HPWS). A high

performance work system (HPWS) can be defined as a set of distinct but interrelated

HRM practices that together ―select, develop, retain, and motivate a workforce (1)

that possesses superior abilities (i.e., superior (a broad repertoire of) skills and

behavior scripts); (2) that applies their abilities in their work-related activities; (3)

57

whose work-related activities (i.e., actual employee behaviors/ output) result in these

firms achieving superior intermediate indicators of firm performance (i.e., those

indicators over which the workforce has direct control) and sustainable competitive

advantage‖ (Way, 2002).

2.15 Human Resources Management and Firm size

Firm size is positively related to the adoption of many HR instruments (Compeer et

al, 2005). Generally speaking, smaller firms are less likely to use formal HRM

practices than larger firms are (De Kok et al., 2003). Nevertheless, it seems intuitively

likely that HRM will also matter in small firms, even though the exact HRM practices

that larger and smaller firms benefit from, as well as the specific benefits yielded (e.g.

performance, innovativeness, growth), may differ.

Several studies amongst smaller firms suggest that HRM is indeed relevant in the

small firm context. For example, De Kok (2001) examines the impact of training on

production, for a panel of Dutch manufacturing firms with 40 – 5.000 employees. He

examines the impact that training may have on gross production and value added. He

presents a model where training is measured by the number of training days per

employee. The impact of training can be moderated by the amount of training support

per employee (the time spent in setting up and managing the training programme) and

by firm size. His results support the presence of a moderating effect of training

support per employee, but find no support for a moderating effect of firm size.

Instead, there is an indirect effect of firm size: smaller firms tend to provide less

training support per employee than larger firms, which reduces the impact of training

on gross output and value added. Even though training has a positive effect on

performance, for smaller firms this positive effect may not be enough to outweigh the

costs of training.

Cardon (2003) suggests that small and/or new firms are likely to have more problems

in recruiting employees, because they lack both the resources and the legitimacy.

Likewise,

Williamson concludes that ―without applicants having knowledge of a firm, its

practices or its members, small firms find it harder to establish their legitimacy as a

prospective employer‖ (Williamson, 2000). She concludes that contingent labour will

be especially beneficial for small firms in pursuit of growth. In a study among 120

58

German enterprises with 1 – 50 employees, Rauch et al. (2005) find a significantly

positive impact of HR development and utilization on employment growth. Thus,

effective management of Human Resources in small firms may yield beneficial

outcomes for small firms.

Other studies also suggest that HRM is likely to have an impact on firm performance

in small firms. However, often, these studies control for size rather than focus on it.

For example, Hayton (2003) finds a positive effect of HRM on entrepreneurial

performance in a sample of 99 US firms with 100 – 500 employees. He gathered

information on 25 HR practices. Factor analysis revealed two factors, labelled

‗traditional HRM practices‘ (practices that tell employees what to do, and when, e.g.

formal job descriptions and a structured salary system) and ‗discretionary HRM

practices‘ (practices that promote discretionary behaviour of employees). The

dependent variable in his study is entrepreneurial performance, which reflects the

extent to which a firm is able to accept risk and be innovative or competitively

aggressive. He finds a significantly positive effect of the ‗discretionary HRM

practices‘ scale on entrepreneurial performance, while traditional HRM practices do

not have such an impact. Firms with fewer than 100 employees were removed from

the sample since formal HRM practices were expected to be limited for these

enterprises. However, this assumption is not tested, and smaller firms may well have

and/or benefit from such practices.

Batt (2002) examines the impact of several HRM practices (combined in a high

involvement work system) on quit rates and sales growth for U.S. call-centres with 10

or more employees (establishment level). Although this is one of the few empirical

studies on the effect of HPWS on performance that includes small firms,

establishment size is not treated as a relevant variable in this study. The sample is

stratified in two size classes (10-99 and >= 100 employees), but no information is

provided on the number of call centres in each size class. Average total firm size is

not reported, nor is it used as a control variable in the reported analyses. She does

report, however, that ―I considered factors such as size, age, (…). These measures,

however, are highly correlated with those already in the study and did not produce

any significant differences in the results‖. On the one hand, this suggests that firm size

didn‘t have a significant impact as a control variable. On the other hand, it suggests

59

that firm size is strongly related to other variables (although, unfortunately, we do not

know which ones). Her results partially support the existence of both positive indirect

and positive direct effect of HPWS on sales growth in the call-centres (some of which

are small businesses).

Several articles on the relationship between HRM and organizational life cycle (both

empirical and theoretical) also address the role of HRM in small businesses. For

example,

Leung (2003) focuses on strategies for recruiting core personnel (management) during

the start-up and growth phase of young (and usually small) enterprises. Baird and

Meshoulam (1988) suggest that HRM systems may depend on the specific life cycle

of SMEs: During the start-up phase, HRM activities are loose and informal, most

likely performed by the owner/founder. Activities are focused on a narrow range of

HR issues related to hiring and firing. Next, during the high growth phase a

formalization of the organization occurs, additional managers are introduced,

including HR specialists; a shift may take place from emphasizing recruitment and

selection to focusing on training and development as well as the design of

compensation policies. Finally, in the mature phase, there is more attention for

performance appraisal, labour relations, affirmative actions and a broader role for the

HR function (Baird and Meshoulam, 1988; Rutherford et al., 2003). Similarly,

Ciavarella (2003) proposes prescriptive arguments for how the HRM system of an

organization should be matched with its stage in the organizational life cycle.

Rutherford et al. (2003) identify various problems that owners or managers of SMEs

may have with the management of their human resources, in particular regarding

hiring, retention and development (training). They examine whether the main

problems encountered by these firms are related to the organizational life cycle and

find that this is indeed the case. In particular, firms exhibiting no growth often have

problems with recruiting employees, whereas high-growth firms often have problems

with training. These studies indeed suggest that attention to HRM in a broad sense can

benefit small firms. Here we focus on high performance work systems and address the

role these may play in small enterprises.

60

2.16 High performance work systems and performance in small businesses

High performance work systems are thought to increase performance. Some support

for the existence and effectiveness of HPWS has been found. However, research on

HPWS was mostly done in large firms. Even in the available research in larger firms

both the choice of which specific practices should be included in the HPWS and the

operationalisation of the chosen practices that make up the proposed system vary

widely. HPWS researchers tend to stress practices in the area of employee

development, autonomy and participation, as well as having a motivating reward

system and incentive structure that ensures that employees hard work ‗pays off‘, both

in terms of financial compensation and career opportunities. Strict selection, work

designed so that employees have discretion and opportunity to use their skills in

collaboration with other workers may also be seen as part of such systems (Verburg

and Den Hartog, 2006). For example, Batt (2002) states that such systems generally

include ‗relatively high skill requirements; work designed so that employees have

discretion and opportunity to use their skills in collaboration with other workers; and

an incentive structure that enhances motivation and commitment‘ (p.587). Similarly,

Delaney and Huselid (1996) mention employee participation and empowerment, job

redesign including team based systems, extensive employee training, and

performance-contingent incentive compensation as practices that are jointly likely to

improve organizational performance.

In his study of HPWS in the US small business sector Way (2002) focused on the

HRM practices extensiveness of staffing, performance based pay, pay level, job

rotation, training, participation and self-directed work teams as practices that

combined would be able to enhance the ability of small firms to select, develop,

retain, and motivate a workforce that produces superior employee output. As

hypothesized, he found that the HPWS comprised of these elements was associated

with lower workforce turnover and higher perceived productivity. However, he found

no significant relationship with labour productivity (measured as the ratio between

sales and labour costs). Here, we use Way‘s measures as our starting point, as this will

allow for a comparison of the findings of our research with those of Way, as stated

Way focused on a HPWS comprised of extensiveness of staffing, performance based

pay, pay level, job rotation, training, participation and self-directed work teams. Such

a system is likely to enhance labour productivity and lead to reduced voluntary labour

61

turnover (in chapter three we discuss this relationship in more detail; we also refer the

reader to Way (2002) for an extensive description).

2.17 High performance work systems and innovativeness in small businesses

As described above, we expect that HPWS in SMEs can increase firm performance.

Besides performance, we suggest HPWS is relevant to productivity but could also

affect innovativeness of small firms. The innovation literature mentions many

organization level influences that are likely to play a role in the innovation process

within firms.

Anderson, De Dreu and Nijstad (2004), for example, mention elements such as

structure, strategy, size, resources, culture and leadership. HPWS may also form an

important organizational level influence on innovativeness. To enhance innovation,

HRM practices need to ensure that creativity can thrive and new knowledge and skills

can be created in the firms. Firms also need to maintain an environment that supports

the implementation of these new ideas in the workplace. For example, Shipton et al.

(2004) suggest that innovation will be promoted and sustained where HRM practices

are in place to manage the creation, transfer and implementation of knowledge.

Most of the practices in high performance work systems are likely to stimulate

innovation. For example, research on innovation and creativity shows that domain

relevant knowledge is an important aspect of creativity (Amabile et al., 1996). Thus,

organizations need to ensure that such knowledge is present. This is done through

strict selection of new employees, focusing on breadth and depth of expertise

(Mumford, 2000) as well as through training and development of employees that are

already in the firm to keep knowledge and skills up to date (Shipton et al., 2004).

Job design also has the potential to enhance creativity and innovation. Mumford

(2000) stresses the need to define jobs in terms of broad core duties that allow

employees to pursue emerging opportunities and creative production activities, rather

than defining jobs narrowly in terms of administrative requirements or financial

objectives. HRM practices such as involvement and participation have been stressed

in the HR literature as well as ways to promote employees‘ commitment to the

organization and its goals (including innovation). Having more influence and

62

autonomy is proposed to lead to broader ownership of problems and a more flexible

and proactive view of performance of employees. Similarly, Mumford (2000)

mentions the importance of having sufficient employee autonomy and influence to

stimulate creativity, for example, allowing for discretion in structuring of work

activities and allocating time to core duties. Research supports this importance of

autonomy and participation for innovative behavior (Amabile et al., 1996).

There is also a potential role of reward systems in stimulating innovativeness. Firms

could use skill or knowledge-based pay to increase employees‘ acquisition of

knowledge outside their immediate jobs, which may promote creativity (Guthrie,

2001). Mumford (2000) also suggests that firms should provide incentives for on-

going development of knowledge and expertise to stimulate creativity. He further

suggests tailoring performance objectives to the creative elements of the work and

providing a mix of rewards based on progress towards objectives (rather than solely

based on outcomes). On the other hand, extrinsic rewards may under certain

conditions decrease the intrinsic motivation for performing creative tasks that are seen

as crucial for creative performance

(Amabile, 1996).

Finally, research on innovation suggests that new ideas and knowledge need to be

communicated (transferred) through the organization so that they can be implemented

(see Damanpour, 1991). Thus, knowledge transfer is a fundamental pre-requisite for

innovation implementation (Shipton et al., 2004). Transferring and then implementing

knowledge involves developing shared understanding between individuals and work

groups. Shipton et al (2004) suggest that the frequency of contact and reciprocal

interdependence of employees working together in teams is one way to promote

effective co-ordination and knowledge dissemination. In sum, the elements of the

HPWS used in this study (extensiveness of staffing, performance based pay, pay

level, job rotation, training and participation) may enhance both small firm

productivity and innovativeness.

2.18 The Microfinance Revolution and SMEs

The microfinance revolution was introduced into the development economics arena

slightly more than two decades ago (Morduch, 1999). However, the widespread

63

adoption of the microfinance model did not occur until the early 1990s. Since the mid

1990s, microfinance programmes and institutions have become an increasingly

important component of strategies to promote MSE development in developing

countries, and specifically to reduce poverty.

Existing literature indicates that microfinance programmes and institutions have been

subjected to rigorous statistical analyses based on sample surveys (Hulme, 2005). In

addition, and quite recently, microfinance activities have also been subjected to

considerable impact assessment studies, focusing on multi-method impact

assessments as well as participatory approaches. Specifically, almost all microfinance

programmes assume that intervention will change human behaviours and practices in

ways that lead to the achievement of desired outcomes (Sebstad and Chen, 1996). For

example the provision of a microfinance package of technical assistance and a loan is

intended to increase household income which in turn may lead to greater household

economic security and thus lead to positive changes in the morbidity and mortality of

household members, in educational and skill levels and in future economic and social

opportunities.

In general, however, knowledge about the achievements of microfinance initiatives

remains not only partial but also highly contested (Hulme, 2005). On the one hand,

some studies argue that microfinance has very beneficial economic and social

impacts; see, for example Holcombe (1995) and Hashemi and Schuler (1997). On the

other hand, some studies tend to caution against such optimism and argue that

microfinancing is associated with some negative impacts; see, in particular,

Montgomery (1996); Buckley (1997); Wood and Sharrif (1997). Between the polar

sides of the dichotomy are some studies which clearly point out the beneficial impacts

but also argue that microfinance does not assist the poorest see Hulme and Mosley

(1996) and Mosley and Hulme (1998).

Notwithstanding the application of these diverse methods and increased research

activity in this area, it is still not very clear that microfinance is a panacea for poverty

(Wood and Sharrif, 1997). To shed light on these issues, the microfinance literature

has recently focussed on measuring the impact of credit on household welfare

(Hulme, 2005). It is argued that credit contributes positively to household welfare

64

through improving household production or smoothing consumption over time.

Specifically, it is shown that although most credit programmes may not serve the

poorest of the poor, all categories of the poor may be able to benefit through increased

income and reduced vulnerability to ‗shocks‘, as noted in Khandker (1998, 2003).

The theoretical literature on microfinance has been dominated by two strands. In the

first strand, a generic theoretical model of microfinance activities tends to feature

three sets of agents: households (potential borrowers), formal lenders and informal

lenders (such as money lenders, relatives, friends and ROSCAs). These markets are

characterised by high lending transaction costs and lack of collateral when farmers do

not own their own land, as indicated in Meyer and Nagarajan (2000). As a

consequence, borrowers are charged high interest rates. Households consist of

borrowing and non-borrowing households; they may borrow from formal lenders,

informal lenders or both in order to finance their economic activities. The demand for

credit depends on household attributes and the village characteristics in which

households live. As the interest rate is fixed, there is some rudimentary credit

rationing, in which lenders screen the applications and decide to whom to offer loans

and how much to offer. Some applicants receive loans, others are rejected, and yet

others receive smaller loans than they applied for. Hence, in this strand of the

literature, the generic model tends to pose three most important issues, namely, to:

identify the determinants of the credit supply to households; specify the determinants

of credit rationing; and determine the channels through which credit may contribute to

household welfare.

The second strand of the theoretical literature focuses on the unconventional methods

that microfinance institutions use to improve borrowers‘ payback behaviour (see, for

example Morduch, 1999). In particular, the literature deals with the implications of

group lending practices with jointly liable borrowers, as suggested in Ghatak (2000).

A jointliability contract specifies that the entire group is liable for loans that are given

to individual group members. A well-known example is the Grameen Bank‘s group

lending program. It has been emphasised that group lending with joint liability may

lead to peer-monitoring or peer-pressure among group members which reduces

problems of moral hazard and enforcement (Stiglitz, 1990; Besley and Coate, 1995).

This may be because a high joint liability component in the debt contract provides

65

incentives to borrowers to choose a safe investment project. In addition, some recent

theoretical papers have noted that joint liability lending induces group members to

self-select each other (Ghatak, 2000). It is argued that the optimal outcome is one in

which all borrowers with the same probability of success match together

(homogeneous matching). It has also been argued that the optimality of homogeneous

matching only holds in a frictionless world (Green et al., 2005). However, the real

world is characterised by frictions due to imperfect information, the unavailability of

partners with the same risk characteristics, the inability to enforce contracts and the

inability to fully screen and monitor group members.

66

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80

CHAPTER THREE

RESEARCH METHODOLOGY

3.3 Nature and Sources of Data

The nature of data for this research will be of secondary nature. Secondary data are

data which have been processed, collated and existed in published form (Onwumere,

2005). The secondary data sources that will be used in this study will be extracted

from selected SMEs in Enugu State. The relevant data include; Net profit; age size of

employees, size (share capital), and the Number of staff (labour turnover) for the

period under study.

3.4 Population and Sample Size/Techniques

The idea of sampling or determining sample size is to obtain a part of the population

from which some information about the entire population can be inferred. In line with

the nature of this type of research, the population of the study is the SMEs in Enugu.

This will also constitute the total sample size for this research. The sample size will

consist of selected SMES, from the Senatorial district in Enugu State that are relevant

to this study. Therefore the sampling Techniques is the Non Probability Convenience

sampling method.

3.3 Description of Research Variables

The variables for the study will be made of dependent and independent variables.

Below is a breakdown of the respective variables.

3.3.1 Independent Variable:

Labour Turnover: The rate at which an employer gains and loses employees. Simple

ways to describe it are "how long employees tend to stay" or "the rate of traffic

through the revolving door." Turnover is measured for individual companies and for

their industry as a whole. If an employer is said to have a high turnover relative to its

competitors, it means that employees of that company have a shorter average tenure

than those of other companies in the same industry. High turnover may be harmful to

a company's productivity if skilled workers are often leaving and the worker

population contains a high percentage of novice workers (Zuber, 2001), it will be

represented as;

81

Labour Turnover = No of Employees that had left the firm

No of Employee that had stayed over the same period

3.3.2 Dependent Variables

The dependent variables include Profitability, Age and Size

Profitability: The state or condition of yielding a financial profit or gain, In this

research the profitability of SMEs will be measured by the reported Profit After Tax

(Naude, 1998)

Age: The empirical evidence have shown that while younger firms may have a higher

propensity to generate jobs than older SMEs, this is to some extent offset by their

lower survival chances. Since some mature firms also demonstrate a potential to

generate jobs. However, within the context of such a survival of SMEs, young

growing firms may need particular kinds of support which could be offered within the

context of policies designed to encourage and support growing businesses at different

stages of development (David and David, 1998) Thus in this research, age will be

represented by the no of years the business have been in existence.

Size: The SMEs sector plays a pivotal role in the overall industrial economy of the

country. It is estimated that in terms of value, the sector accounts for about 39% of the

manufacturing output and around 33% of the total export of the country. Further, in

recent years the MSE sector has consistently registered higher growth rate compared

to the overall industrial sector. The major advantage of the sector is its employment

potential at low capital cost. In this research the size will be represented by the Total

Assets of each SME (Steel, 1994)

3.4 Model Specification

The simple regression equation is stated thus;

Y = B1 + B2X2 + u ........................................................................................... (1)

Where, Y =dependent variable; X =explanatory variable; B1 =intercept of Y; B2

=slope coefficients; U =stochastic variables (Gujarati, 1995).

Therefore, in writing the model equation, the following proxies and symbols will be

used in this research.

82

Labour Turnover = LT

Profitability = PAT

Age = AG

Size = Total Assets (TA)

a = Regression equation intercept

b = Regression equation coefficient

μ = error term

Equation (1) will be re-written to suit the study along the four hypotheses.

Thus, for hypothesis one which states that Labour turnover do not have positive

significant impact on profitability SMEs in Enugu State, it is represented as:

NP = a + b LT + μ …………............................................................

(2)

For hypothesis two, which states that there is no positive relationship between labour

turnover and SMEs age in Enugu State, it is represented as;

AG = a + b LT + μ ………................................................................

(3)

For hypothesis three, which states that there is no positive relationship between labour

turnover and SMEs size in Enugu State it is represented as;

SZ = a + b LT + μ..............................................................................

(4)

3.5 Technique for Analysis

The hypotheses stated in chapter one will be tested using the Ordinary Least Square

Regression model. The justification for adopting this analytical technique is based on

the following premise; the ordinary least square is assumed to be the best linear

unbiased estimator (Gujarati, 1995); it has minimum variance (Onwumere, 2005), and

similar works in other jurisdiction adopted this technique in their study.

83

REFERENCES

David, S and David, N. (1998), ―Targeting Established SMEs: Does Their Age

Matter?‖ The Journal of the Local Economy Policy Unit May 1, 1998 13: 64-71

Gujarati, D.N. (1995), Basic Econometrics, Singapore: Mcgraw- Hill Book Co

Kerlinger, F.N. (1973), Foundations of Behavioural Research Techniques In Business

and Economics Eleventh Edition, Boston; McGraw Hill Irwin

Naude, W (1998), ―SMMEs and economic development in South Africa‖ Africa

Insight 28(3/4): pp 133–145

Onwumere, J.U.J (2005), Business and Economic Research Method, Lagos; Don-

Vinton Limited

Steel, W. (1994), ―Changing the institutional and policy environment for small

enterprise development in Africa‖ Small Enterprise Development 5(2): pp 4–9

Zuber, A. (2001), ―A career in foodservice--cons: High turnover‖ Nation's Restaurant

News; 35(21), pp 147-148

84

CHAPTER FOUR

PRESENTATION AND ANALYSES OF DATA

4.1 Presentation of Data

The relevant data that was used to test the hypotheses are presented below. Fifty (50)

SMEs was sampled in Enugu State and the proxies extracted. The proxies are the

profit after tax, age of the SMEs, size which was represented by total assets of the

SMEs and the labour Turnover which was derived by Number of Employees that had

left the firm divided by Number of Employee that had stayed over the same period.

Below is the extract of the relevant data.

From the questionnaires distributed to employees and employers of the fifty (50)

SMEs in Enugu. The table below shows the response from the structured questions as

contained in the questionnaire.

Table 4.1: Responses on sexes of respondents

Alternatives Employee Employer Total Percent (%)

Male 173 45 218 70

Female 88 5 93 30

Total 261 50 311 100

Source: Field Survey, 2011

From the above table, it was revealed that two hundred and eighteen (218)

respondents representing seventy (70) percent are male; a breakdown shows one

hundred and seventy-three (173) respondents were employees of the SMEs sampled

and forty-five (45) respondents are male employers. It was revealed from the table

also that ninety-three respondents representing thirty (30) percent were female; a

breakdown shows that eighty-eight (88) respondents were employees of the SMEs

sampled and five (5) respondents are employers.

85

Table 4.2: Responses on age of Employees respondents

Alternatives Employee Percent (%)

20-30year 103 39

30-40years 86 33

40 and above 52 20

others 20 8

Total 261 100

Source: Field Survey, 2011

From the above table, it was revealed that one hundred and three (103) respondents

representing thirty-nine (39) percent of the employees are aged 20-30 years, eighty-

six (86) representing thirty-three (33) percent of the employees are aged 30-40 years

while fifty-two representing twenty (20) percent of the employees are aged 40years

and above and twenty (20) employees years were not captured from the questionnaire,

this represented eight (8) percent of the SMEs sampled.

Table 4.3: Responses on age of Employers respondents

Alternatives Employee Percent (%)

20-30year 2 4

30-40years 23 46

40 and above 25 50

Others 0 0

Total 50 100

Source: Field Survey, 2011

From the above table, it was revealed that two (2) respondents representing four (4)

percent of the employers are aged 20-30 years, twenty-three (23) representing forty-

six (46) percent of the employers are aged 30-40 years while twenty-five (25)

representing fifty (50) percent of the employers are aged 40years and above of the

SMEs sampled.

86

Table 4.4: Responses on Marital status of Employees respondents

Alternatives Employee Percent (%)

Single 96 37

Married 106 41

Widow 37 14

Widower 22 8

Total 261 100

Source: Field Survey, 2011

From the above table, it was revealed that ninety (96) respondents representing thirty-

seven (37) percent of the employees are single, one hundred and six (106)

representing forty-one (33) percent of the employees are married while thirty-seven

(37) representing fourteen (14) percent of the employees are widow and above and

twenty-two (22) employees were widower of the SMEs sampled.

Table 4.5: Responses on Marital status of Employers respondents

Alternatives Employee Percent (%)

Single 15 30

Married 21 42

Widow 3 6

Widower 11 22

Total 50 100

Source: Field Survey, 2011

From the above table, it was revealed that fifteen (15) respondents representing thirty

(30) percent of the employers are single; twenty-one (21) representing forty-two (42)

percent of the employers are married while three (3) representing six (6) percent of

the employers are widow and eleven (11) representing twenty-two (22) percent of

respondents are widower of the SMEs sampled.

87

Table 4.6 Summary of Proxies from Sampled SMEs

SMEs Profit After Tax

(N)m (A)

Age (B) Size (Total Assets) (C)

(N)m

Labour Turnover

SME 1 1,207,400 10 1,877,283 0.333

SME 2 139,794 10 1,299,268 0.410

SME 3 395,731 5 1,319,907 0.313

SME 4 701,307 9 969,334 0.267

SME 5 664,895 20 1,026,553 0.410

SME 6 802,910 17 2,845,143 0.089

SME 7 589,950 12 1,847,671 0.709

SME 8 434,117 2 1,692,370 0.348

SME 9 317,728 18 1,525,837 0.524

SME 10 74,488 16 707,595 1.097

SME 11 628,017 15 8,737,949 0.571

SME 12 609,943 5 6,594,540 0.333

SME 13 531,776 3 4,233,325 0.323

SME 14 199,687 8 2,811,063 0.442

SME 15 155,445 9 2,452,274 0.720

SME 16 29,721 10 622,215 0.611

SME 17 22,013 11 512,867 0.469

SME 18 22,754 5 524,641 0.018

SME 19 14,237 11 478,393 0.293

SME 20 14,355 8 344,608 0.344

SME 21 195,683 9 669,882 0.145

SME 22 118,484 14 474,084 0.419

SME 23 231,382 13 386,920 0.136

SME 24 242,807 5 301,683 0.297

SME 25 218,913 6 179,563 0.073

SME 26 2,596,533 20 14,436,466 0.550

SME 27 1,077,496 21 11,711,961 0.286

SME 28 1,617,263 20 10,850,004 1.538

SME 29 1,616,457 19 16,818,583 1.750

SME 30 2,167,249 11 9,452,494 1.097

SME 31 2,452,427 13 109,855,351 1.186

SME 32 1,763,706 14 58,869,455 0.717

SME 33 1,119,047 12 42,041,615 0.238

SME 34 626,865 11 40,985,814 2.200

SME 35 387,430 12 31,090,399 2.25

SME 36 8,331,599 9 15,342,204 0.403

SME 37 5,441,899 4 10,816,368 0.391

SME 38 5,660,329 6 11,572,200 0.125

SME 39 5,303,128 15 10,531,760 1.882

SME 40 3,835,493 18 9,079,343 0.425

SME 41 417,962 12 3,429,738 0.618

SME 42 208,318 11 2,676,969 0.750

SME 43 211,470 9 2,300,418 0.842

SME 44 101,759 7 986,923 0.136

SME 45 91,139 5 933,016 0.157

SME 46 872,532 8 4,310,442 0.591

SME 47 697,751 4 4,273,495 0.519

SME 48 525,944 8 9,318,660 0.875

SME 49 434,132 9 6,006,343 0.688

SME 50 220,737 7 9,917,170 0.686

Source: Field Survey 2011

It could be observed from the above table that SMEs 36 had the highest Profit after

tax, it recorded a PAT of N8,331,599, this was followed by SMEs 38 which had a

PAT of N5,660,329 while SMEs 19 and 20 had the lowest PAT, it was N14,237 and

N14,355 respectively. It was also revealed from the table that SMEs 27 has been in

88

existence for 21years, this was followed by SMEs 5, 26 and 28. The SME that had the

shortest year of existence was SME 8. For size that depended on the total assets of the

SMEs, SMEs 31 had the highest Total Assets while SMEs 24 had the least Total

Assets.

4.2 Test of Hypotheses

The hypotheses stated in Chapter One and mathematically represented in chapter

three was tested using three steps, Step one is the restatement of the hypotheses in null

and alternate forms, step two is the analyses of the result and step three is the

decision.

4.2.1 Test of Hypothesis One

Ho1: Labour turnover do not have positive significant impact on profitability SMEs in

Enugu State

From the appendix 4, it was revealed that, there is a positive non-significant impact of

labour turnover on the profitability of small and medium scales enterprises in Enugu

state as labour turnover coefficient is 371721.86, and t–value of 0.782. The

correlation coefficient is 0.112 which is positive as indicated by a positive beta. Thus,

there was positive correlation between labour turnover and profitability of small and

medium scales enterprises in Enugu state. The d–test statistic value is 0.771.

However, the variation in profitability of small and medium scales enterprises

explained in this model is 1.3%, which indicates that there are other variables which

must have impacted on profitability of small and medium scales enterprises other than

labour turnover. Based on the result as revealed the null hypothesis is rejected while

the alternate hypothesis accepted which states that Labour turnover have positive

significant impact on profitability SMEs in Enugu State though the impact was not

significant as revealed from the result.

4.2.2 Test of Hypothesis Two

Ho2: There is no positive relationship between labour turnover and SMEs age in

Enugu State

It was revealed from appendix 5, that the correlation coefficient is 0.340 which is

positive as indicated by a positive beta. Thus, there was positive correlation between

labour turnover and age of small and medium scales enterprises in Enugu state. To

89

further support the correlation results, there is positive significant impact of labour

turnover on the age of small and medium scales enterprises in Enugu state as labour

turnover coefficient is 3.218, and a t–value of 2.509. The d–test statistic value is

1.219. However, the variation in age of small and medium scales enterprises

explained in this model is 11.6% as indicated by the coefficient of determination; this

is low which indicates that there are other variables which must have impacted on age

of small and medium scales enterprises other than labour turnover. Based on the result

as revealed, the null hypothesis is rejected while the alternate hypothesis accepted

which states that there is a positive relationship between Labour turnover and age of

SMEs in Enugu State

4.2.3 Test of Hypothesis Three

Ho3: There is no positive relationship between labour turnover and SMEs size in

Enugu State

It was also revealed from appendix 6, that there was positive correlation between

labour turnover and size of small and medium scales enterprises in Enugu state, the

correlation coefficient is 0.340 which is positive as indicated by a positive beta. To

further buttress the correlation results, there is positive significant impact of labour

turnover on the size of small and medium scales enterprises in Enugu state as labour

turnover coefficient is 14537668, and having a t–value of 3.080. The d–test statistic

value is 1.080. However, the variation in size of small and medium scales enterprises

explained in this model is 16.5% as indicated by the coefficient of determination (R2),

this is low which indicates that there are other variables which must have impacted on

size of small and medium scales enterprises other than labour turnover. Based on the

result, the null hypothesis is rejected while the alternate hypothesis accepted which

states that there is positive relationship between labour turnover and SMEs size in

Enugu State.

90

CHAPTER FIVE

DISCUSSION OF FINDINGS

From the hypothesis tested for objective one, there was positive non-significant

impact of labour turnover on the profitability of small and medium scales enterprises

in Enugu state as indicated by the labour turnover coefficient is 371721.86, and t–

value of 0.782. The correlation coefficient is 0.112 which is positive as indicated by a

positive beta. Thus, there was positive correlation between labour turnover and

profitability of small and medium scales enterprises in Enugu state. The d–test

statistic value is 0.771. However, the variation in profitability of small and medium

scales enterprises explained in this model is 1.3%, which indicates that there are other

variables which have impacted on profitability of small and medium scales enterprises

than labour turnover. The implication of this findings reveals that an increase in

labour turnover holding all else constant increases profitability of SMEs. As stated by

Ologunde, Asaolu and Elumilade (2009), the termination of employment by an

employee or employer reduces the existing stock of labour force, while an addition by

reason of fresh employment increases the stock of labour force. The process of

reducing or adding to the existing stock of labour of an enterprise increases the

chances of SMEs in attracting capable hands that improves the productivity of these

SMEs, hence profitability is enhanced. This view is consistent with work of

Ologunde, Asaolu and Elumilade (2009).

As revealed from the hypothesis tested for this objective, there was positive

correlation between labour turnover and age of small and medium scales enterprises

in Enugu state as indicated by the correlation coefficient of 0.340 which is positive as

indicated by a positive beta. To further support the correlation results, there is positive

significant impact of labour turnover on the age of small and medium scales

enterprises in Enugu state as labour turnover coefficient is 3.218, and a t–value of

2.509. The d–test statistic value is 1.219. However, the variation in age of small and

medium scales enterprises explained in this model is 11.6% as indicated by the

coefficient of determination; this is low which indicates that there are other variables

which must have impacted on age of small and medium scales enterprises other than

labour turnover. Labour turnover is also seen as the flow of manpower into and out of

an organization, in which the inflow is referred to as accession and the outflow as

91

separation (Fapohunda, 1980). Behrend, (1953) posits that labour turnover as one of

the unorganized forms of industrial conflict in which employees usually retreat from

unsatisfactory situations. However when there is high turnover which indicates that

more persons enters the organisation, hence sustainability is enhanced, therefore there

is a relationship between age of SMEs and labour turnover as the longer the lives of

the SME, the higher the labour turnover. This is consistent with the works of

Fapohunda (1980) and Behrend (1953).

Lastly, there was positive correlation between labour turnover and size of small and

medium scales enterprises in Enugu state, the correlation coefficient is 0.340 which is

positive as indicated by a positive beta. To further buttress the correlation results,

there is positive significant impact of labour turnover on the size of small and medium

scales enterprises in Enugu state as labour turnover coefficient is 14537668, and

having a t–value of 3.080. The d–test statistic value is 1.080. However, the variation

in size of small and medium scales enterprises explained in this model is 16.5% as

indicated by the coefficient of determination (R2), this is low which indicates that

there are other variables which must have impacted on size of small and medium

scales enterprises other than labour turnover. This indicates that a high labour

turnover increases the size of SMEs in Enugu State. This relationship between SMEs

size and labour turnover is consistent with the results obtained by Kirschenbaun and

Mano-Ne grin (1999) and Mobley et al, (1979).

92

REFERENCES

Behrend, J. (1953). ―Absence and Labour Turnover in a Changing Economic

Climate‖ Occupational Psychology, Vol. 27

Fapohunda, A.M. (1980). ‗What is behind labour Turnover?‘ Journal of Personnel

Management Vol. 7, No. 2, April-June, pp 11

Kirshenbaun, A. and Mano-Negrin, R. (1999), ―Underlying Labour Market

Dimensions of Opportunities: The Case of Employee Turnover‖ Human

Relations Vol. 52(10) pp 1233-1255

Mobley, W. H. et. al. (1979), ―Review and Conceptual Analysis of the Employee

Turnover Process‖ Psychological Bulletin, Vol.86 (3), PP. 493-522

Ologunde, A. O. Asaolu, T.O; and Elumilade, D.O. (2009), ―Labour Turnover among

University Teachers in South- West Nigeria-Issues, Solutions and Lessons‖

Retrieved from http//unpanl.un.org/introdoc/groups/public (Accessed on

23/3/2011)

93

CHAPTER SIX

SUMMARY, CONCLUSION AND RECOMMENDATION

6.1 Summary of Findings

As revealed from the findings in this research, below is a summary of findings;

i. Labour turnover have positive significant impact on profitability SMEs in

Enugu State though the impact was not significant thus an increase in labour

turnover increases the profitability of SMEs in Enugu state.

ii. There was positive relationship between Labour turnover and age of SMEs in

Enugu State. Thus whenever there is correlation between the labour turnover

and the lont-term growth of SMEs IN Enugu state.

iii. Once again there was positive relationship between labour turnover and SMEs

size in Enugu State. This indicates that an increase in labour turnover, assist in

expanding the size of SMEs in Enugu State.

6.2 Conclusions

Developing countries value small and medium enterprises (SMEs) for the

static and dynamic gains that these firms bring. From the static point of view, Small

and medium enterprises, on average, are believed to generate relatively large amounts

of employment while also achieving decent levels of productivity. From the dynamic

point of view, the sector is viewed as being populated by firms most of which have

considerable growth potential, a contrast with micro enterprises that tend not to

graduate from that size category. Many Small and medium enterprises will grow

significantly without exiting that size category while others will eventually become

large, that is, the seed-bed for large firms function of small and medium enterprises.

Another aspect of the dynamics of small and medium enterprises that distinguishes

them from larger enterprises is their high entry and exit rates. The process of rapid

turnover raises a set of issues about possible impacts on the economic efficiency of

the sector and about policies that may curtail such efficiency losses as are associated

with it. it is also often argued that one advantage of small and medium enterprises is

their flexibility, relative at least to larger firms. This is construed by some as a plus in

industries and economies that, for whatever reason, face rapidly changing market

conditions, including sharp macroeconomic downturns such as those that have

bedeviled most of the countries of Africa over the last few years.

94

It is observed that SMEs have high labour and this was justified by the results of this

research. Labour turnover is an important and pervasive feature of the labour market.

In many countries, workers quit their jobs every year. Labour turnover affects both

workers and firms as well SMEs. Workers experience disruption, the need to learn

new job-specific skills and find different career prospects.

Firms, on the other hand,

lose job-specific skills, suffer disruption in production and incur the costs of hiring

and training new workers. Incoming workers, however, may be better educated, more

skilled and have greater initiative and enthusiasm than those who leave. While the

focus of the economics literature on labour turnover has been on the impact of

turnover on workers rather than on firms, this may be due to limited availability of

data, which has allowed only sporadic study of these issues. Turnover and hiring costs

have impact on productivity from several studies; this was observed from the findings

of this research that labour turnover have an impact on profitability of SMEs in Enugu

State and also it had a positive relationship with age and sizes of this SMEs.

6.3 Recommendations

Labour turnover is often seen as the flow of manpower into and out of an

organization, in which the inflow is referred to as accession and the outflow as

separation. Also some see labour turnover as one of the unorganized forms of

industrial conflict in which employees usually retreat from unsatisfactory situations.

No doubt, a certain amount of labour turnover is inevitable. Illness: accidents, aging,

death and a variety of personal reasons that bring about separation. Labour turnover is

not always a negative phenomenon as studies have shown that it creates opportunities

to introduce better hands, work practices and procedures, new ideas to an organization

as well as providing career development opportunities for the existing workers.

However high rate of labour turnover as could be observed fro the findings of this

study that it impacts on profitability as well as severely reduce productivity as

workers are perpetual learners, new to the organization all the time, demoralize

incumbents and damage an organization‘s public image thereby adversely affecting

her corporate existence. It is therefore in line with the research findings that the

following recommendations are suggested especially as it affects small and medium

scale enterprises in Nigeria, these are;

95

First, all over the world, small and medium enterprises have been looked upon as the

engine of economic growth and for promoting equitable development. Small and

Medium firms have been praised over time because of the myth that they have the

propensity to employ more labour since most of them have labour intensive

production process than the larger enterprises. However when studies show high

turnover rates, its impact can be detrimental to the survival of these small and medium

scale enterprises, thus, SMEs should be encouraged to imbibe the culture of

maintaining and existing workforce instead of laying off workers indiscriminately.

This will ensure consistency and continuity which enhances growth and survival.

Secondly, findings have shown that most SMEs in Nigeria have not done well, and it

has been noted that a good number of them die within the first five years of existence

while smaller percentage goes into extinction between the sixth and tenth year with

only about five to ten percent of them surviving, thriving and growing into maturity.

Consistent with the findings of this research, there is positive relationship between

age and labour turnover, the implication is the more number of years of existences of

these small and medium scale enterprises, the higher the labour turnover rate. This is

quite worrisome for these firms, thus growth and survival of small and medium scale

enterprises and impeded. Factors that have often attributed to the impact observed

from this study are poor access to funds, low equity capital from stakeholders, poor

infrastructural facilities, multiplicity of regulating agencies, overbearing environment,

little access to markets and information, corruption and societal attitudinal processes

among others. Internal facts like poor management practices, poor condition of

service and un-conducive work environment are de-motivators to employees are

likely precursors to the unhealthy performance of the SMEs. Therefore, this study

recommends increased government participation in that sector through the provision

of basic amenities such as good roads, electricity and power etc and such other factors

that will encourage continual existences of these firms.

Lastly, the study also recommends better motivational schemes should be put ion

place to encourage employees to remain in these SMEs. A well motivated workforce

contributes positively to productivity and this in turn enhances survival Therefore

efforts should be made by employers to formulate good welfare schemes for the work.

96

APPENDIX 1

QUESTIONNAIRE LETTER

Institute for Development Studies,

University of Nigeria, Enugu Campus

Enugu.

Dear Respondent,

The Impact of Labour Turnover on Survival of SMEs in Enugu State

I am a student of the above named Department, undertaking a research on the above

topic. The objective of this study is to assess the Impact of Labour Turnover on

Survival of SMEs in Enugu State. This questionnaire is designed to enable me collect

information for the research.

Your kind assistance is hereby requested in filling this form.

All information you provide will be treated with strict confidence and shall be used

strictly for academic purpose.

Thanks for your co-operation.

Yours Faithfully

Nwachukwu, Ogbonnaya

PG/M.Sc/09/54154

97

APPENDIX 2

QUESTIONNAIRE

Please, tick the one you think is most appropriate

SECTION A: BIOATA

1. Sex: (a) Male [ ] b. Female [ ]

2. Age group : (a) 20 – 30 years [ ] (b) 30 – 40 years[ ] (c) 40 years and

above [ ] Others [ ]

3. Marital Status (a) Single [ ] (b) Married [ ]

4. Highest of Education (a) Primary education [ ] (c) Secondary education [ ]

(b) Tertiary education [ ] (d) No formal education [ ] (e) others [ ]

5. Occupation (a) Farmer [ ] (b) Trader [ ] (c) Students [ ] (d) Civil

servant [ ] (e) Others [ ]

SECTION B

6. Do you have knowledge of Labour turnover

Yes [ ] (b) No [ ]

7. How long have you worked with your company?

(a) Less than One year [ ] (b) One year [ ] (c) Two years[ ] (d)

Three Years[ ] (e) Four years [ ] (d) Five years and above [ ]

8. Does your employer recruit workforce regularly?

(a) Yes [ ] (b) No [ ]

9. To what extent do you think your employer changes your companies‘

workforce?

Very high extent [ ] (b) high extend [ ] (c) very low extent [ ]

(d) Low extent [ ] (e) moderate

10. What is the total number of staff in your company?

(a) 0-5 [ ] (b) 6-15 [ ] (c) 16-30 [ ] (d) 31-50 [ ] (e) 51 and above [ ]

11. How long have your company be in existence?

(a) 0-5 [ ] (b) 6-15 [ ] (c) 16-30 [ ] (d) 31-50 [ ] (e) 51 and above [ ]

98

12. To what extent do you agree your company can still be in existences for the

next ten yrs?

(a) Very high extent [ ] (b) high extent [ ] (c) very low extent (d) low

extent [ ](e) moderate [ ]

13. To extent you think your company is making profit?

(a) Very high extent [ ] (b) high extend [ ] (c) very low extent [

]

(d) Low extent [ ] (e) moderate

14. Do your company reports the profit after tax to employees?

(a) Yes [ ] (b) No [ ]

15. To what extent do you think that size of your company can play in enhancing

profitability?

(a) Very high extent [ ] (b) high extent [ ] (c) very low extent [ ]

(d) low extent [ ] (e) moderate

16. To what extent do you think that the profitability of your company can play in

enhancing growth?

(a) Very high extent [ ] (b) high extent [ ] (c) very low extent [ ]

(d) Low extent [ ] (e) moderate

99

Appendix 3

SMEs Profit After

Tax

(N)m (A)

Age

(B)

Size (Total

Assets) (C)

(N)m

No Employees

that had Left

the Firm (D)

No Employees

that had Left

the Firm (E)

Labour

Turnover

F = (D/E)

SME 1 1,207,400 10 1,877,283 40 120 0.333

SME 2 139,794 10 1,299,268 32 78 0.410

SME 3 395,731 5 1,319,907 15 48 0.313

SME 4 701,307 9 969,334 12 45 0.267

SME 5 664,895 20 1,026,553 50 122 0.410

SME 6 802,910 17 2,845,143 12 135 0.089

SME 7 589,950 12 1,847,671 61 86 0.709

SME 8 434,117 2 1,692,370 8 23 0.348

SME 9 317,728 18 1,525,837 22 42 0.524

SME 10 74,488 16 707,595 34 31 1.097

SME 11 628,017 15 8,737,949 16 28 0.571

SME 12 609,943 5 6,594,540 10 30 0.333

SME 13 531,776 3 4,233,325 10 31 0.323

SME 14 199,687 8 2,811,063 23 52 0.442

SME 15 155,445 9 2,452,274 72 100 0.720

SME 16 29,721 10 622,215 11 18 0.611

SME 17 22,013 11 512,867 15 32 0.469

SME 18 22,754 5 524,641 1 57 0.018

SME 19 14,237 11 478,393 24 82 0.293

SME 20 14,355 8 344,608 21 61 0.344

SME 21 195,683 9 669,882 8 55 0.145

SME 22 118,484 14 474,084 18 43 0.419

SME 23 231,382 13 386,920 15 110 0.136

SME 24 242,807 5 301,683 11 37 0.297

SME 25 218,913 6 179,563 6 82 0.073

SME 26 2,596,533 20 14,436,466 11 20 0.550

SME 27 1,077,496 21 11,711,961 16 56 0.286

SME 28 1,617,263 20 10,850,004 20 13 1.538

SME 29 1,616,457 19 16,818,583 21 12 1.750

SME 30 2,167,249 11 9,452,494 34 31 1.097

SME 31 2,452,427 13 109,855,351 51 43 1.186

SME 32 1,763,706 14 58,869,455 89 124 0.717

SME 33 1,119,047 12 42,041,615 10 42 0.238

SME 34 626,865 11 40,985,814 11 5 2.200

SME 35 387,430 12 31,090,399 27 12 2.25

SME 36 8,331,599 9 15,342,204 48 119 0.403

SME 37 5,441,899 4 10,816,368 9 23 0.391

SME 38 5,660,329 6 11,572,200 4 32 0.125

SME 39 5,303,128 15 10,531,760 32 17 1.882

SME 40 3,835,493 18 9,079,343 34 80 0.425

SME 41 417,962 12 3,429,738 21 34 0.618

SME 42 208,318 11 2,676,969 9 12 0.750

SME 43 211,470 9 2,300,418 16 19 0.842

SME 44 101,759 7 986,923 3 22 0.136

SME 45 91,139 5 933,016 8 51 0.157

SME 46 872,532 8 4,310,442 13 22 0.591

SME 47 697,751 4 4,273,495 14 27 0.519

SME 48 525,944 8 9,318,660 21 24 0.875

SME 49 434,132 9 6,006,343 22 32 0.688

SME 50 220,737 7 9,917,170 24 35 0.686

Source: Field Survey 2011

100

APPENDIX 4

HYPOTHESIS ONE

Descriptive Statistics

Mean Std. Deviation N

PAT 1126844.04 1728456.472 50

LAB .61188 .521796 50

Correlations

PAT LAB

Pearson Correlation PAT 1.000 .112

LAB .112 1.000

Sig. (1-tailed) PAT . .219

LAB .219 .

N PAT 50 50

LAB 50 50

Variables Entered/Removed(b)

Model Variables Entered Variables Removed Method

1 LAB(a) . Enter

a All requested variables entered.

b Dependent Variable: PAT

Model Summary

Model R R

square

R square

Adjusted

Std Error of

the Estimate

R square

Change

Sig. F

change

Durbin

Watson

1 0.112a 0.013 -0.008 1735773.722 0.013 0.438 0.761

a Predictors: (Constant), LAB

b Dependent Variable: PAT

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.

1 Regression 1843462298377.348 1 1843462298377.348 .612 .438(a)

Residual 144547064720372.600 48 3011397181674.429

Total 146390527018749.900 49

a Predictors: (Constant), LAB

b Dependent Variable: PAT

101

Coefficients(a)

Model Unstandardized Coefficients Standardized Coefficients t Sig.

B Std. Error Beta

1 (Constant) 899394.870 380442.969 2.364 .022

LAB 371721.858 475099.955 .112 .782 .438

a Dependent Variable: PAT

Coefficient Correlations(a)

Model LAB

1 Correlations LAB 1.000

Covariances LAB 225719966992.178

a Dependent Variable: PAT

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation N

Predicted Value 906085.88 1735769.00 1126844.04 193963.088 50

Residual -1348339.000 7282400.000 .000 1717538.965 50

Std. Predicted Value -1.138 3.139 .000 1.000 50

Std. Residual -.777 4.197 .000 .990 50

a Dependent Variable: PAT

102

APPENDIX 5

HYPOTHESIS TWO

Descriptive Statistics

Mean Std. Deviation N

AGE 10.72 4.932 50

LAB .61188 .521796 50

Correlations

AGE LAB

Pearson Correlation AGE 1.000 .340

LAB .340 1.000

Sig. (1-tailed) AGE . .008

LAB .008 .

N AGE 50 50

LAB 50 50

Variables Entered/Removed(b)

Model Variables Entered Variables Removed Method

1 LAB(a) . Enter

a All requested variables entered. b Dependent Variable: AGE

Model Summary

Model R R

square

R square

Adjusted

Std Error of

the Estimate

R square

Change

Sig. F

change

Durbin

Watson

1 0.340 0.116 0.098 4.686 0.116 0.016 1.219

a Predictors: (Constant), LAB b Dependent Variable: AGE

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.

1 Regression 138.188 1 138.188 6.294 .016(a)

Residual 1053.892 48 21.956

Total 1192.080 49

a Predictors: (Constant), LAB b Dependent Variable: AGE

103

Coefficients(a)

Model Unstandardized Coefficients Standardized Coefficients

T Sig. B Std. Error Beta

1 (Constant) 8.751 1.027 8.518 .000

LAB 3.218 1.283 .340 2.509 .016

a Dependent Variable: AGE Coefficient Correlations(a)

Model LAB

1 Correlations LAB 1.000

Covariances LAB 1.646

a Dependent Variable: AGE

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation N

Predicted Value 8.81 15.99 10.72 1.679 50

Residual -7.871 11.329 .000 4.638 50

Std. Predicted Value -1.138 3.139 .000 1.000 50

Std. Residual -1.680 2.418 .000 .990 50

a Dependent Variable: AGE

104

APPENDIX 6

HYPOTHESIS 3

Descriptive Statistics

Mean Std. Deviation N

SIZE 9840843.18 18672816.666 50

LAB .61188 .521796 50

Correlations

SIZE LAB

Pearson Correlation SIZE 1.000 .406

LAB .406 1.000

Sig. (1-tailed) SIZE . .002

LAB .002 .

N SIZE 50 50

LAB 50 50

Variables Entered/Removed(b)

Model Variables Entered Variables Removed Method

1 LAB(a) . Enter

a All requested variables entered. b Dependent Variable: SIZE

Model Summary

Model R R

square

R square

Adjusted

Std Error of

the Estimate

R square

Change

Sig. F

change

Durbin

Watson

1 0.406a 0.165 0.148 17239386.6 0.165 0.003 1.080

a All requested variables entered. b Dependent Variable: SIZE

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.

1 Regression 2819600388854908.000 1 2819600388854908.000 9.487 .003(a)

Residual 14265429640338400.000 48 297196450840383.300

Total 17085030029193300.000 49

a Predictors: (Constant), LAB b Dependent Variable: SIZE

105

Coefficients(a)

Model Unstandardized Coefficients Standardized Coefficients

t Sig. B Std. Error Beta

1 (Constant) 945534.811 3779439.098 .250 .804

LAB 14537668.120 4719791.117 .406 3.080 .003

a Dependent Variable: SIZE

Coefficient Correlations(a)

Model LAB

1 Correlations LAB 1.000

Covariances LAB 22276428191575.630

a Dependent Variable: SIZE

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation N

Predicted Value 1207212.88 33655288.00 9840843.18 7585701.357 50

Residual -17773666.000 91668144.000 .000 17062567.719 50

Std. Predicted Value -1.138 3.139 .000 1.000 50

Std. Residual -1.031 5.317 .000 .990 50

a Dependent Variable: SIZE

106

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