PRODUCTIVITY OF DIRECT SALES PERSONNEL IN COMMERCIAL BANKS IN

KENYA- SURVEY OF SELECTED BANKS

NAME

REG NO.

AN APPLIED RESEARCH PROJECT PROPOSAL SUBMITTED IN PARTIAL

FULFILLMENT OF THE OF ……..

KENYATTA UNIVERSITY

SEPTEMBER, 2014

DECLARATION

DEDICATION

ACKNOWLEDGEMENT

I first and fore most thank God Almighty for giving me the opportunity and strength to pursue a

Masters Degree in Business Administration. I also extend my gratitude to Dr. Walter, my

supervisor who has been there throughout this whole process sharing his expertise and offering

his guidance and support. I am exceptionally grateful for his assistance.

ABSTRACT Every Organization’s profitability and survival is determined by the performance and productivity of its employees. Sales productivity is usually at the centre of every service organization’s profitability, hence the need to understand those factors that are likely to affect productivity of sales personnel. The objectives of this study were founded in the Maslow’s Hierarchy of Needs Theory whereby the researcher investigated how certain motivational factors affect productivity of Direct Sales Personnel in Commercial Banks in Kenya. The study answered the questions; what was the influence of employee morale on productivity?, To what extent does employee satisfaction improve productivity?, How does employee engagement affect organizational productivity?, And what was the impact of employee morale, satisfaction and engagement on productivity?.The target population included all Direct sales personnel employed by the four leading commercial banks located in Thika town namely; Kenya Commercial bank, Barclays bank, Standard Chartered bank and Cooperative bank. The study conducted a census survey including all the 263 direct sales personnel from these banks as the number was not too big to necessitate sampling. Judgement sampling was used to determine the banks that will fairly represent the banking industry in Kenya. Data was collected using structured questionnaires, which were administered through a “drop and pick later” method where the response rate was 81%. The collected data was analysed using descriptive statistics and multiple regression analysis. This included means, percentages and proportions. The statistical package for the social sciences (SPSS) was used as a software tool for data entry and management, statistical analysis and presentation. The study found that satisfaction, engagement and morale were found to influence motivation of direct sales personnel by a greater percentage (86%) than productivity of direct sales personnel where 72% of productivity was attributed to these factors. The study also revealed 72% of productivity was attributed to motivation. It was also found that direct sales personnel had a high turnover rate where 51% worked for less than 1 year. The regression results of this study were significant and had the correct sign concurring with theory, previous studies and expectation of the researcher. The study recommended that the Kenyan Commercial Banks should ensure they pay better salaries and give resources and rewards to direct sales personnel to improve the performance of the direct sales personnel where the companies will reduce the high direct sales personnel turnover hence increase motivation and productivity.

LIST OF TABLES

Table 3.1 Sample Framework

LIST OF ABBREVIATIONS

BBK - Barclays Bank of Kenya

CBK - Central Bank of Kenya

CO-OP. BANK- Cooperative bank

DSE- Da-re-Salaam Stock Exchange

DSP- Direct Sales Personnel

I.T- Information Technology

KCB- Kenya Commercial Bank

NBFI- Non-bank Financial Institution

NSE- Nairobi Stock Exchange

NYSE- New York Stock Exchange

RSE- Rwanda Stock Exchange

SCBK- Standard Chartered Bank of Kenya

STANCHART- Standard chartered

USE- Uganda Securities Exchange

DEFINITION OF TERMS

Attitude: Noe, (2002) defines attitudes as a combination of beliefs and feelings that predispose

a person to behave a certain way.

Direct Selling: Michael, J. et al., (2006) defined direct selling as a direct personal presentation,

demonstration and sale of products and services to consumers usually in their homes or at their

jobs.

Employee Engagement: Truss, C. et al, (2006) define employee engagement as simply,

“passion for work”.

Employee Morale: Haddock, (2010) defined employee morale as an intangible wave that

depicts how optimistic and supportive one feels towards the organization they belong to.

Employee Satisfaction: Armstrong, (2006) defined employee satisfaction as the attitude and

feelings people have about their work. Positive and favorable attitudes towards the job indicate

job satisfaction and vice versa.

Motivation: Collins, (1995) defined motivation as incentive for action

Productivity: Dorgan, (1994) defined productivity as the increased functional and

organizational performance including quality. It is a ratio to measure how well an organization,

individual, industry or country converts input resources (labor, materials, machines etc) into

goods and services.

Strategy: Thompson, J. et al, (2007) defined strategy as a long term plan of action designed to

achieve a particular goal, most often “winning”.

CHAPTER ONE: INTRODUCTION AND BACKGROUND OF THE STUDY

1.1 Introduction

The profitability and survival of every organization is determined by its performance which to a

large extent depends on the productivity of its workforce, therefore it is very important to know

the factors that affect employees’ productivity so as to be able to improve performance.

A global productivity study conducted by Proud Foot Consulting Company (2008) concluded

that there are six critical barriers to improved global productivity. Managers around the world

were asked to rank the factors they perceived as being critical in affecting productivity. The

results were as follows; Staff shortages and insufficient labour pool (27.1%), internal

communication problems (25.1%), Legislation and regulation (21.9%), Low employee

motivation and morale (21.2%), high staff turnover rate (19.9%) and quality of supervisors

(19.6%). The study concluded that there are four levers that can help improve productivity for

example, effective management, development of the workforce, clearer communication and

targeted training.

In Africa, the factors that influence productivity are as follows; Staff shortages and insufficient

labour pool (37%), Legislation and regulation (33%) and Quality of supervisors (31%).

Managers in Africa suggested possible solutions or strategies to help improve productivity and

91% of them felt that organizations should invest in workforce skills, development and training

in order to improve productivity (Proud Foot Consulting Company, 2008). Productivity is of

fundamental importance to the individual worker of whatever status, to an organization whether

commercial or not and to every national economy at large and most of all to the uplifting of the

welfare of the citizen (Yesufu, 2000). According to Akinyele (2007) Conducive work

environment ensures the wellbeing of employees which enables them to exert themselves to their

roles with all vigor that may translate to higher productivity. Productivity is measured by

considering performance increase as when there is less absenteeism, fewer employees leaving

early, less breaks or less employee turnover (Cecunc, 2004).

This section will begin with a brief background of this research study followed by a brief

description of the global trends in banking. An overview of the banking industry in Africa will

be given and thereafter a highlight of the banking industry in Kenya. What follows is a brief

highlight of the status of Thika town followed by a brief history of four commercial banks

namely; Kenya Commercial Bank, Barclays Bank, Standard Chartered Bank and Cooperative

Bank of Kenya. These are the banks from where the population of the study will be sampled. The

problem statement will then be discussed followed by the purpose of the study, research

objectives and research questions and finally the significance of the study, scope of the study,

limitations and delimitations of the study. The chapter will end with the theoretical review and

conceptual framework of the study.

1.2 Background of the Study

Increased competition in the banking industry in Kenya has made it necessary for banks to

come up with numerous strategies for competitive advantage with direct selling as the most

popular strategy among all the others. Direct selling stands out among all other strategies for

competitive advantage (Pfeffer, 1994). Brown (2009) identified sales productivity as a primary

element to the success of every institution. It is therefore very important to know the factors that

affect or influence productivity. Studies carried out by Armstrong (2006), Clawson (2005) and

Hankin (2004) suggested that productivity is affected by some specific factors like employee

engagement and morale along with employee satisfaction.

The direct selling strategy was adopted less than ten years by Commercial banks in Kenya

therefore very few studies have looked at how productivity of DSP’s is influenced by

satisfaction, morale and engagement. Direct sales strategy is widely applicable among

Commercial banks in Kenya today, hence the reason for this study to determine the factors

affecting productivity of Direct Sales Personnel in commercial banks in Kenya.

1.3 Global trends in banking

The banking industry has experienced mixed results in the post-crisis period from 2008 to

2010. Industry growth has slowed considerably; the growth rate of assets of the top 1000 banks

globally in the post-crisis period remained 2.7%, compared to the double digit growth rates

witnessed during the pre-crisis years of 2006 to 2007. On the other hand, when looking at risk

management and profitability, there has been significant recovery. Profits have returned to pre-

crisis levels and the solvency of the industry has witnessed significant improvement with growth

of 3.8% registered in capital adequacy ratio during 2007 to 2010

(www.thebankerdatabase.com.n.d.). The banking industry in the emerging markets remained

profitable even during the worst phase of the crisis. This contrasts with the performance of banks

from developed markets which registered huge losses during the same period. Banks from the

emerging markets are expected to drive the growth of the global banking industry (Barth &

Levine, 2000).

The global banking industry has also entered a period of enhanced regulation. More stringent

capital adequacy and risk management standards are now being imposed upon banks. Certain

key priorities have emerged for the banking industry for example restoration of customer

confidence, addressing issues such as low efficiency of existing channels, ageing technology,

high operating costs and the existence of complex processes. Technology, including the

development of consumer-centric solutions is being seen as a key to meeting these priorities. As

a result, certain major trends are emerging in the banking industry. Remote banking solutions are

being adapted and used as tools for providing greater convenience to customers as well as

driving operational efficiency. Business intelligence and customer relationship management

(CRM) are emerging as vehicles for delivering customized offerings and driving greater

consumer-centricity (The banker, 2009).

The global forces for change include technological innovation, deregulation of financial services

at the national level and opening-up to international competition and changes in corporate

behavior, such as increased emphasis on shareholder value (Barth & Levine, 2000). All the

above changes have made it necessary for banks worldwide to re-evaluate their strategies

periodically in order to remain competitive.

1.4 Banking trends in Africa

The banking sector in countries across Africa is undergoing a transformation for example;

African banks are now assessing and managing operations more diligently as they are forced to

comply with international regulatory frameworks on a national and international level (The

banker, 2009). African Banks face a number of business challenges for example growing

pressure to maintain margins, manage portfolio risks more effectively and meet evolving

customer needs. To this end, banks are focusing on improving operations across key business

areas e.g., trade, treasury, and core banking). They are initiating efficiency improvements to

optimize balance sheet performance, with technology deployments considered a key enabler in

the transformation of related banking operations (Central Bank of Kenya, 2005)

A trend is emerging in which traditional corporate banks are expanding into retail banking as

a means of increasing the funding base, since retail banking is viewed as an easy source of

funding. Diversification into related product and service offerings is also taking place in the

corporate banking subsector. Certain products and financial instruments (e.g., structured lending

products and derivatives) are expected to grow in popularity in the coming years. Mergers and

acquisitions are a growing trend in the African banking sector. Larger African banks continue to

acquire smaller domestic market players as they look to expand into new markets. Furthermore,

larger African and international banks are actively seeking to drive pan-African strategies and

are striving for a greater share in mature markets and profitability in less developed markets(The

Banker, 2009).

Generally, the above changes have led to banks developing various strategies among them the

direct selling strategy to enable them compete and survive in this competitive business

environment. Banks that do not compete effectively have become victims of acquisitions by the

major players.

1.5 Status of the Banking industry in Kenya

The Companies Act, the Central Bank of Kenya (CBK) Act and the Banking Act are the

main regulators and governors of banking Industry in Kenya. These Acts are used together with

the prudential guidelines which Central bank of Kenya issues from time to time. Central Bank of

Kenya is tasked with formulating and implementation of monetary and fiscal policies. It is the

lender of last resort in Kenya and is the banker to all other banks. The Central Bank of Kenya

ensures the proper functioning of the Kenyan financial system, the liquidity in the county and the

solvency of the Kenya shilling. The Ministry of finance is where Central Bank of Kenya falls. To

address issues that affect the Banking industry in Kenya, banks have come together and formed a

forum under the Kenya Bankers Association (Mars group Kenya, 2009).

Central Bank of Kenya requires financial institutions to build up their minimum core capital

requirement to Kenya shillings 1 Billion. The Terrorist attacks on the twin towers in United

States of America emphasized and led to the mandating Acts like Anti-money laundering.

Nations are working closely to ensure that proceeds of crime do not get into the financial systems

of the world. The Global crisis experienced affected banking industry in Kenya and more so the

mobilization of deposits and trade reduction (Kenya Commercial Bank, 2011).

Kenyan Banks have realized tremendous growth in the last five years and have expanded to

the east African region. The banking industry in Kenya has also involved itself in automation,

moving from the traditional banking to better meet the growing complex needs of their customer

and globalization challenges. There has been increased competition from local banks as well as

international banks, some of which are new players in the country. This has served the Kenyan

economy well as the customers and shareholders are the ones who have benefited the most

(Central Bank of Kenya, 2005). The competition in the banking industry in Kenya has forced

banks to adopt various strategies to help acquire market share and compete effectively. Direct

selling strategy has become a very popular strategy among the commercial banks in Kenya in the

last ten years.

1.6 Thika Town

Thika is a town in Kiambu County with a population of approximately 139,853 people. It is

situated 40km north east of Nairobi. Thika town is home to various tourist attractions for

example Chania Falls, Fourteen Falls, Thika Falls, Ol-Donyo Sbuk National Park. It is the

biggest pineapple growing region in Kenya which helps to sustain “Delmonte”a world leader in

marketing and distributing fresh fruits and vegetables.

Thika has a vast banking network which comprises of local Banks, International Banks and small

upcoming micro-finance institutions. More than ten registered Commercial Banks in Kenya have

opened have opened branches in Thika town. All the largest and leading banks in Kenya are

represented in Thika town for example Barclays Bank, Kenya Commercial Bank, Standard

Chartered Bank, Equity Bank and Cooperative Bank. These banks have had to come up with

strategies to compete against one another and direct selling has become a very popular strategy

among all the banks.

1.7 Kenya Commercial Bank (KCB)

KCB is a commercial bank licensed by the central bank of Kenya which is the national

banking regulator. According to the KCB website, KCB Group, the parent company of KCB

Kenya, had the largest branch network in Kenya out of all 43 licensed commercial banks in the

country by the end of the year 2010. Shares of the stock of Kenya Commercial Bank Group

(KCB Group) are listed on the Nairobi Stock Exchange (NSE), under the symbol (KCB). The

Group's stock is also cross listed on the Uganda Securities Exchange (USE), the Rwanda Stock

Exchange (RSE) and the Dar es Salaam Stock Exchange (DSE). As of December 2010, KCB

Group was the largest financial services group in Kenya, with an asset base valued at over KES:

251 billion (Kenya Commercial Bank, 2011).

1.8 Barclays Bank of Kenya (BBK)

Barclays Bank of Kenya, a subsidiary of Barclays PLC has operated in Kenya for more than

90 years and has an extensive network of over 107 branches and 193 ATMs across the country.

Key services offered are Corporate Banking, Retail Banking, Credit Card Business and Treasury

Services. It has an extensive network, supported by a staff complement of over 6,900 and a

variety of newly developed tailor-made products and services which has ensured a solid and

growing customer base spread across the country. One of the key strategic goals for Barclays

bank by the year 2007 was to widen the bank’s reach by expanding its distribution channels and

enhancing sales capability. Another key hallmark for 2007 was the revolution in the bank’s sales

capability. During the year the bank recruited 4,358 direct sales staff making it possible to take

products to wherever existing or potential retail customers are. This unrivalled sales force was

instrumental in fuelling growth of customer numbers and assets. As of march 2011 the bank

maintained a network of one hundred and fifteen branches in Kenya (Barclays Bank of Kenya,

2007).

1. 9 Cooperative bank of Kenya Limited

The Bank was initially registered under the Co-operative Societies Act at the point of

founding in 1965. This status was retained up to and until June 27th 2008 when the Bank's

Special General Meeting resolved to incorporate under the Companies Act with a view to

complying with the requirements for listing on the Nairobi Stock Exchange (NSE). The Bank

went public and was listed on December 22 2008. Shares previously held by the 3,805 co-

operatives societies and unions were ring-fenced under Coop Holdings Co-operative Society

Limited which became the strategic investor in the Bank with a 64.56% stake. The Bank runs

three subsidiary companies, namely: Kingdom Securities Limited, a stock broking firm with the

bank holding a controlling 60% stake; Co-op-Trust Investment Services Limited, the fund

management subsidiary wholly-owned by the bank; and Co-op Consultancy & Insurance Agency

Limited (CCIA), the corporate finance, financial advisory and capacity-building subsidiary

wholly-owned by the bank. As of December 2011, it was the third-largest financial services

provider in Kenya, by asset value, behind Kenya Commercial Bank and Barclays Bank Kenya.

At that time its total assets were valued at approximately KES: 168.3 billion. The bank is well

known for its focus on the needs of cooperative societies in Kenya (Cooperative Bank of Kenya,

2007).

1.10 Standard Chartered Bank of Kenya Limited

Standard Chartered Bank (Kenya) Limited, is a commercial bank in Kenya. It is a subsidiary

of the British multinational financial conglomerate known as Standard Chartered. According to

CBK, (2005), Standard Chartered bank of Kenya is one of the licensed commercial banks in

Kenya. Standard Chartered bank was the fourth largest commercial banks in Kenya, by assets, as

of December 2011 with total assets valued in excess of KES: 164 billion. The stock of the bank

is listed on the Nairobi Stock Exchange where it trades under the symbol: SCBK. In 2011,

Standard Chartered Bank celebrated 100 years of presence in Kenya since they opened their first

two branches, Treasury Square in Mombasa and Kenyatta Avenue in Nairobi, in January

1911(Standard Charted Bank, 2011).

1.11 Statement of the Problem

Increased productivity can be attributed to various factors like employee satisfaction,

employee participation and employee morale. According to Armstrong (2006), satisfied

employees tend to be more productive, creative and committed to their employers. Akinyele

(2007) however, proposed that productivity in an organization is as a result of Conducive work

environment that ensures the wellbeing of employees enabling them to exert themselves to their

roles with all vigour that may translate to higher productivity. Research done by Haddock (2010)

proposed that organizations can improve their productivity further if they improved employee

morale because morale influences staff productivity, performance and creativity. On the contrary

Roeloelofsen (2002) proposed that engaged employees have a passion for their work and

therefore engaged employees are the most productive.

The researcher, an employee of one of the leading commercial banks in Kenya has witnessed

the dilemma faced by commercial banks in Kenya in their attempt to maintain and retain their

direct sales workforce. Employees are generally aware of the specific factors that affect their

productivity. These insights have influenced the decision to carry out this study to determine

from the Direct Sales Personnel themselves, those factors that affect their productivity. The

identification of the particular or specific factors that limit productivity among the direct sales

workforce in commercial banks in Kenya will lead to significant productivity gains in the

banking industry.

1.12 Purpose of the Study

The purpose of this study was to determine the factors that affect productivity of direct sales

workforce in commercial banks in Kenya. Increased competition in the banking industry and the

fact that direct sales strategy is one of the most popular competitive strategy used by majority of

the banks, calls for approaches that will help improve productivity of the sales workforce. This

study therefore determined the factors that employees perceive as mostly affecting their

productivity.

1.13 General Objective

The General objective of this study was to determine the factors that affect productivity of direct

sales personnel in Commercial Banks in Kenya.

1.13.1 Specific Objectives

i. To determine the influence of employee morale on productivity.

ii. To establish the extent to which employee satisfaction improves productivity.

iii. To find out how engagement of employee affects organizational productivity.

iv. To assess the impact of employee morale, satisfaction and engagement on motivation

hence productivity.

1.14 Research Questions

i. What was the influence of employee morale on productivity?

ii. To what extent does employee satisfaction improve productivity?

iii. How does employee engagement affect organizational productivity?

iv. What was the impact of employee morale, satisfaction and engagement on motivation?

1.15 Significance of the Study

This study is of great significance because it was aimed at assisting strategic managers and

also the direct sales personnel in the banking industry to optimize sales productivity. The finding

give the strategic managers an insight into issues that affect the sales workforce so that they can

adopt approaches suitable to both the management and the workers in a way that will make

workers feel part of the bigger picture. This will help to harmonize direct selling with the rest of

the functions in the bank. The findings of this study are also of immediate benefit to other

business administrators intending to adopt the direct sales strategy so that they can adopt the best

approach of managing their strategy so as to gain competitive advantage. The study forms a basis

upon which other researchers can develop their studies.

1.16 Scope of the Study

The researcher colleced data from DSP’s working in four of the leading commercial banks in

Thika town namely; Kenya Commercial bank, Barclays bank of Kenya, Standard Chartered

Bank and Cooperative bank of Kenya. Thika town was chosen because of its close proximity to

the researcher.

1.17 Limitations of the Study

This study was limited by the failure of respondents to answer questions candidly hence

results may not reflect the opinion of all members of the included population. The researcher

attempted to solve this by instructing respondents not to put their names on the questionnaires to

help assure them that the information they give will be treated with confidence and that they

remained anonymous. Another challenge the researcher faced was trying to distribute the

questionnaires to the respondents who are field workers and are not stationed in their offices like

the other employees. The researcher attempted to solve this problem by seeking help from the

branch managers of the respondent banks who helped to schedule appointments between the

DSPs and the researcher.

1.18 Delimitations of the Study

The study was delimited to only four commercial banks out of the 43 Licensed commercial

banks in Kenya because they were among the first commercial banks to adopt the direct sales

strategy and they have employed at least more than five direct sales personnel in each of their

branches therefore they offer a sufficient sample population to represent all commercial banks in

Kenya.

1.19 Theoretical Framework

1.19.1 Maslow’s Hierarchy of Needs Theory

This study was founded on the theory of employee as proposed by Abraham Maslow in 1943.

Motivation can be defined as the drive that leads people towards action and without this drive

people cannot act. This implies that people act because they hope to achieve or gain something in

return. Maslow’s hierarchy of Needs theory will explain in different ways how motivation is

acquired and the effects it has on employee satisfaction, morale and engagement which in turn

affects productivity. According to Greenberg and Baron (2003) Maslow’s theory is of great value

because it gives practical implications to every management of organizations. It suggests to

managers how they can make their employees become self-actualized because self-actualized

employees are able to optimize their full potential. It is therefore important to enable them reach

this stage by helping meet their needs (Hersey & Blanchard 1993). Managers must develop

different types of incentives for different employees based on the stages of their lives.

According to Porter and Bigley (2003) the stages follow a hierarchy that begins with

psychological (relating to survival), safety and security (for example job security), belongingness

(for instance a desire for acceptance) which in turn leads to esteem and ego (for example greater

concern for the job) and finally peaks with self-actualization (realization of the person’s full

potential). Maslow refers to the state of being happy and psychologically stable as self-

actualization. The five stages can be grouped into two categories starting with the basic needs

and then moving upwards to the higher order needs. The most basic human needs which are

represented by food, water, shelter and safety are considered essential for human survival or

existence. Higher order needs are concerned with social activities, esteem building and self-

actualization or constant self-improvement. Each of these needs operate all the time although one

set which is said to be deficient dominates the individual at any one time and circumstance

(Greenberg & Baron 2003)). Motivation to fulfill these needs originates from internal and

external factors. Internally motivated factors lead to a sense of accomplishment and pleasure

while people that are externally motivated are said to be influenced by elements controlled by

others for example money and praise (Ryan &Deci, 2000). Maslow’s hierarchy is displayed in a

pyramid model with the basic needs at the bottom and the higher needs at the top. The needs

were presented in this way to show the importance of each need on the others with the most

important and broadest category being the physiological needs at the bottom (Redmond, 2010).

Figure 1.1 Maslow’s Hierarchy of Needs Model (Christensen, 2002)

1.19.2 Basic Order Needs (Psychological and Safety Needs)

This category of needs is made up of two levels of needs; the first level is concerned with

physical or physiological needs which include food, water, air, shelter, warmth and sleep.

Employees who are at this level of needs require wages to meet these needs so managers can use

wages as a motivator so as to give them job satisfaction, high morale and engagement which will

result to high productivity. The second level of needs in this category is the Safety needs which

is concerned with employees’ desire to feel secure and to have an assurance that the

physiological needs will continue to be met. This is the level at which an employee wants

pension so they will favour jobs that are on permanent and pensionable terms. There is also the

need to feel protected from dangers for example a safe working environment or issues

concerning their health and job security. Managers can motivate these employees by providing

Self

actualization

Needs

Esteem Needs

Social Needs

Safety Needs

Physiological Needs

them with benefits like health benefits, equitable and fair work practices and a safe working

environment.

1.19.3 Higher order Needs (Social, Esteem and Self Actualization Needs)

The higher order needs category comprises of three levels; the social needs level, esteem

needs level and at the top most is the self-actualization needs level. The social needs level has to

do with an employee’s desire to belong or to be accepted and to be in an environment where

there is trust. Managers can motivate employees who are in this level by allowing them to

participate in decision making (listen to their input) for example by conducting employee

surveys. This level of needs also requires teamwork, performance evaluations because this will

make them feel appreciated. The esteem needs level employees are concerned with rank,

position or repute. They need self-assurance; they want to feel that they are needed by others.

Employees at this level can be motivated through job tittles or spacious offices. The highest level

is known as self-actualization which is concerned with success and enlargement. They are

seeking fulfilment because they have already contented with all the lower levels of need so they

want to accomplish their possible self-development. Employees at this level can be motivated by

workplace independence or autonomy and also status on the job.

1.20 Conceptual Framework

This model (figure 1.1) explains the relationship between the independent variables, the

intervening and the dependent variable. The independent variables of the study (Employee

satisfaction, Morale and Engagement) affect the intervening variable (Motivation) which then

affects the dependent variable (Productivity of Direct Sales Personnel). The absence or lack of

Employee Satisfaction, Morale and Engagement leads to lack of or absence of Motivation which

results to low productivity of DSPs and the presence of Employee Satisfaction, Morale and

Engagement results to presence of motivation which leads to high productivity.

Independent Variables

Dependent VariableIntervening

Variable

Employee Satisfaction

Employee Morale

Productivity of DSPs

Motivation

Figure 1.2 Conceptual Framework

According to Shauffeli & Bakkar (2004) engaged employees are likely to have a greater

attachment to their organization and a lower tendency to quit. Employee satisfaction is a result of

favorable and positive attitudes towards the job (Armstrong, 2006). Haddock (2010) defines

morale as a feeling of trust, self-worth, purpose and pride in one’s contribution towards their

organization while Truss, C. et al (2006) defines employee engagement as simply passion for

work. Neeley (1999) associated job satisfaction with the feeling of pride which builds in to group

feeling of spirit de corps thus paving way for high morale.

It can be thus concluded that there is significant association between satisfaction, morale and

engagement. Employee satisfaction and morale lead to employee engagement which according to

Konrad (2006) generates the kind of discretionary effort that leads to enhanced performance and

productivity. Motivated employees will have high morale and job satisfaction which will lead to

high productivity. Lack of motivation will result to low morale and lack of job satisfaction which

creates disengaged employees and the result is low productivity.

CHAPTER TWO: LITERATURE REVIEW

2.1 Introduction

This chapter reviewed literature of the motivational factors that affect productivity of

employees which have been used in this study. It helped the researcher to determine the

influence of employee morale on productivity, establish the extent to which employee

satisfaction improves productivity and how engagement of employees affects organizational

productivity.

2.2 Theoretical Review

2.3 Employee Morale

Morale is recognized in management literatures as an important factor in governing the

efforts of workers and in determining the overall company performance (Hyman & Mason,

1995). Haddock (2010) defines morale as an intangible wave that depicts how optimistic and

supportive one feels towards the organization they belong to. Morale denotes a feeling of trust,

self-worth, purpose and pride in one’s contribution towards their organization. According to

Moorhead and Griffin (2004) morale is a result of top down rather than bottom up

communication. The benefit of high morale is seen in the form of improved communication, low

attrition, high retention and an innovative organization which creates a positive working

environment and increases productivity. Millet (2010) stated that low morale leads to problems

like decrease in productivity and low performance.

Employee morale is very difficult to quantify because it is a feeling and not an action or

outcome and studies conducted have not been able to establish whether it is best evaluated as a

group or an individual experience (Hyman & Mason, 1995). There are some measures that have

attempted to capture the positive effects employee morale for example it is identified with energy

and persistence, enthusiasm, cooperation and cohesion (Kartzell & Yanalorich, 2000). Other

measures try to assess an individual’s mental health or how they feel at a particular point in time

for example considering elements like depression or anxiety (Davis, 1985). There are two

approaches that attempt to measure morale; the first approach uses job satisfaction and

organizational commitment to measure employee morale (Robbins, 2001). The second approach

uses employee turnover rates, grievances and strikes (Robinson, 2006).

When an organization ensures that their employees are motivated they will be able to retain

them but demoralized employees will leave the organization to join the competition every chance

they get.

2.4 Employee Engagement

Khan (1990) defined employee engagement as the harnessing of organization members’

selves to their work roles. Engagement is the state of being psychologically present when

occupying and performing an organizational role. Truss, C et al. (2006) defines employee

engagement as simply “passion for work”. It covers the common theme running through all other

definitions. Sweney (2005) proposed that employee engagement can be achieved through the

creation of an organizational environment where positive emotions such as involvement and

pride are encouraged, resulting in improved organizational performance, lower employee

turnover and better health. Vanderberg and Lance (1992) found that the most important driver of

engagement was senior management’s interest in employee wellbeing. According to Konrad

(2006) employee engagement has been found to be closely linked to feelings and perceptions

around being valued and involved, which in turn generates the kinds of discretionary effort that

leads to enhanced performance and productivity. This implies that managers must share control

and involve employees in important decision making or they risk having a disengaged

workforce.

Schaufeli & Bakker (2004) proposed that engaged employees are likely to have a greater

attachment to their organization and a lower tendency to quit. Sonnentag (2003) concluded that

these positive experiences and emotions are likely to result in positive work outcomes and hence

increased productivity. Employees choose to engage themselves based on amounts or types of

resources they collect from their organization (Mashonganyike 2004). According to Nel and

Werner (2003) employees exchange their engagement for organizational resources. One way to

measure employee engagement is by assessing their business outcomes including the quality of

work (Carrell & Grobler 1998). Employee engagement can also be inferred from their individual

attitudes, behavior or intentions towards their work or the organization (Ireland & Hitt).

According to Buchanan and Huczynski (2004), organizations can engage their employees by

providing an environment that encourages positive emotions and pride which then leads to high

performance and lower employee turnover. Positive employees think more flexibly, they are self-

controlled and less defensive at the workplace (Sweney & McFarlin, 2005).

Engaged employees will always speak highly of the organization and they will go out of their

way to help out even if they do not get anything in return for helping out.

2.5 Employee Satisfaction

Armstrong (2006) defines employee satisfaction as the attitude and feelings people have

about their work. Mullins (2005) defined it as a positive emotional reaction towards the job,

feelings of happiness which one finds while doing the job. According to George and Jones

(2008) employee satisfaction is a state of mind which is influenced by various factors like

welfare measures, autonomy, communication, equity etc. Job satisfaction represents a feeling

that appears as a result of the perception that the job enables the material and psychological

needs (Armstrong, 2006). According to Mowday, R. et al. (1982) satisfied employees tend to be

more productive, creative and committed to their employers.

Employee satisfaction is the result of high morale and engagement because employees with a

high morale are engaged and they will be satisfied with their jobs.

2.6 Productivity of Direct Sales Personnel

Wilson (2004) defines productivity as the increased functional and organizational

performance including quality. According to Spector (1997) the work environment includes

some factors which either contributes positively or negatively to achieving maximum employee

productivity. Christen (2006) determined that attitudes and management styles influence

employee productivity and that one of the tasks of managers is to motivate people in the

organization to perform at high levels. According to Lambert (2005) Productivity is rarely

measured but is inferred from changes in employees’ attitudes. However, Davis and Nestrom

(1985) proposed that productivity is measured considering performance increase as when there is

less absenteeism, fewer employees leaving early, less breaks or less employee turnover.

We can therefore conclude that the attitudes that employees form toward their job affects their

performance and hence their productivity for example employees with a low attitude will be

absent from the office often and they will most likely leave employment as soon as a better offer

presents itself.

2.7 Empirical Evidence

Studies by Ryan and Deci (2000) revealed that although compensation package is one of the

extrinsic motivation tools, it has a limited short term effect on employees’ performance and

productivity. Weiss (1999) concluded that levels of job satisfaction and perception of fairness of

pay affect employee commitment and intention to stay with the organization. Research by

Roelofsen (2002) indicated that improving working environment results in a reduction of

complaints and absenteeism and an increase in productivity. Kartzell and Yanalorich (2000)

provided evidence that the more satisfied workers are with their jobs, the better the company is

likely to perform in terms of subsequent profitability and particularly productivity. Sekar (2011)

revealed that there is a relationship between work, the work place and the tools of work and that

the workplace becomes an integral part of the work itself. Haynes (2008) found that interaction is

perceived to be the component with the most positive effect on productivity. According to Sekar

(2011) people are the most valuable resource of an organization and management of people

makes a difference to company performance. Davis and Nestrom (1985) concluded that

mentoring and coaching is crucial for employees because it encourages positive relations and

increases their self-confidence helping them perform better in their roles.

Leonard (2000) concluded that less organizational bureaucracy a greater sense of purpose,

clear goals, and being able to see results were essential to productivity. Gryna et al. (2007)

showed that improvement in quality results directly to an increase in productivity. Cooper and

Schindler (2007) proposed that fear impacts productivity because it leads to traits like lack of

extra efforts, making and hiding mistakes, missing deadlines and loss of creativity, motivation

and risk taking. Longenecker and Leffakis (2002) revealed that leadership is the single most

influential factor affecting productivity in today’s workplace. Research by Peters and Waterman

(1982) revealed that poor leadership in demonstrating and leading change is one of the greatest

obstacles to productivity in corporations. Taylor (1998) proposed four key principles that can be

applied to dramatically improve productivity in the workplace. These principles advised

managers to systematically design each job, scientifically, select and train the workers, cooperate

closely with the workers and divide the work and responsibility equally between the worker and

management.

2.8 Knowledge Gap.

Studies have been carried out touching on factors that affect employee productivity in

general as described above. Commercial banks in Kenya adopted the direct selling strategy not

more than ten years ago therefore not very many studies have been carried out to address the

factors that affect the direct sales personnel in commercial banks in Kenya. The researcher found

it necessary to address the issue of productivity from the perspective of direct sales personnel

themselves in order to shed some light in that area. This study therefore seeked to determine the

factors that DSP’s in commercial banks in Kenya perceive as most affecting their productivity, a

fact that has not been extensively investigated.

CHAPTER THREE: RESEARCH DESIGN AND METHODOLOGY

3.1 Introduction

This chapter explains the methodology that was used in executing the research in a way that

ensured its success. The chapter describes the research design, research site, target population,

sampling design, data collection tools and procedures, data analysis and presentation.

3.2 Research Design

A descriptive survey research design was be adopted for this study because of its ability to

describe the current status of DSPs in commercial banks in Kenya and thus help bring out the

factors that affect their productivity. The use of this design was justified due to its uniqueness of

enabling the researcher to gather primary information which was not available from other

sources. Further, it allowed for the same information to be collected from each and every

respondent (Cooper & Schindler, 2007).

3.3 Research Site

This study was conducted in Thika town and targeted DSPs currently working for four

commercial banks namely; KCB, BBK, Standard Chartered and Cooperative Bank. Thika town

is a highly industrialized town and all the banks that have fully adopted the direct selling strategy

have branches there. Its close proximity to the researcher also makes it an ideal site for the study.

3.4 Target Population

The target population for this study included DSP’s from four commercial banks located in

Thika town namely; KCB, BBK, Standard Chartered Bank and Cooperative Bank of Kenya. The

researcher targeted these four banks because they have adopted the direct sales strategy on a full

scale and have employed at least five or more DSP‘s in their branches unlike some banks who

have either one or two direct sales staff in the branches. According to the branch managers of the

individual respondent banks the four banks have a total population of 263 DSP’s in their Thika

branches from which a census survey will be conducted.

3.5 Sampling Technique

The researcher used Judgment sampling to select target banks for the study. This technique

was chosen because not all banks have adopted the direct sales strategy; some have adopted it on

a trial basis, others have not adopted it at all therefore have no direct sales staff and then there are

those that have fully adopted and embraced it. The researcher selected four of those banks that

have fully adopted the direct sales strategy and have employed at least more than five direct sales

staff in their branch. A census was conducted of all the direct sales staff employed in the four

target banks. A census is a complete account of all items in a population (Kumar, 2011).

3.6 Sample Size

The sample size included all the direct sales staff from the four target banks because they had

the information required for the study. Information gathered from the branch managers of the

four respondents banks confirmed that there are 263direct sales personnel employed by the four

target banks. The feelings of the respondents from the target population represented the feelings

of all DSP’s in commercial banks in Kenya. The sample size will consist of 100% from each

respondent bank as shown in the table below;

Table 3.1 Sample Framework

Respondent Bank Population Size Sample Ratio Sample Size

Kenya Commercial bank 35 100% 35

Barclays Bank of Kenya 119 100% 119

Standard Chartered Bank 67 100% 67

Cooperative Bank 42 100% 42

TOTALS 263 100% 263

3.7 Research instruments

The main tool for data collection was a structured questionnaire, which was self-administered

and will have both closed ended and open ended questions. The questionnaire items were

developed in a way to elicit responses in line with the problem statement and research questions.

Since the questionnaires were easy to administer, they captured huge quantities of information

and took a short time for the respondents to fill. The researcher selected this instrument because

the information gathered can be stored for further references, and the cost of administering

questionnaires is lower than other research instruments.

3.8 Validity, Reliability and Piloting of Research instruments

It is very important for the researcher to ascertain whether the instruments used to collect

data obtained the desired results. According to Kimberlin and Winterstein (2008) validity refers

to the extent to which a research instrument measures what it is expected to measure. The

researcher consulted experts in order to ensure validity of the questionnaires.

A Reliable research instrument is considered one that is uniform and stable thereby producing

precise and predictable results every time (Kumar, 2011). The researcher did a pretest or trial test

of the questionnaires which involved a small number of respondents to test whether the questions

were clear and appropriate. The feedback from the small number of respondents gave evidence

of the reliability of the questionnaire.

3.9 Data collection procedure

The structured questionnaires was administered through a “drop and pick later” procedure.

The researcher first seek authority from the management of the respondent banks after which

arrangements were made on how and when the research instruments will be delivered to and

collected from the respondents.

3.10 Data Analysis

The collected data was analyzed using descriptive statistics and multiple regression analysis.

The statistical package for the social sciences (SPSS) was used as a software tool for data entry

and management, statistical analysis and presentation. Data collected was also scanned to ensure

it was complete and that all instructions had been followed by the respondents. Descriptive

statistics included mean scores, percentages and proportions which were used to establish the

importance of variables under study. A multiple regression analysis was conducted to test the

relationship between the independent variables (employee satisfaction, employee morale,

employee engagement) and the dependent variable (productivity of DSPSs). Results of data

analysis were presented in the form of tables and figures to help establish how the factors in

question affect productivity of DSPs in commercial banks in Kenya.

3.11 Ethical Considerations

The researcher ensured that the respondents’ participation was voluntary and that their

responses were treated with absolute confidentiality to avoid any negative consequences to

themselves or the target banks. The researcher dropped and picked the questionnaires personally

to ensure high levels of confidentiality. All these made the respondents feel secure as they

provided the appropriate information.

CHAPTER FOUR: DATA ANALYSIS AND PRESENTATION

4.1 Introduction

This chapter presents the empirical results including descriptive statistics, the multiple regression

analysis and key findings of the investigation. The study established the factors that influence

productivity of direct sales personnel in selected commercial banks in Kenya and also the

relationship between their motivation and productivity.

Table 4.1 Response Rate Return

Respondent Bank Target No. of

questionnaires

No. of

questionnaires

returned

Response rate

Kenya Commercial bank 35 23 65.7%

Barclays Bank of Kenya 119 110 92.4%

Standard Chartered Bank 67 51 76.1%

Cooperative Bank 42 29 69%

TOTALS 263 213 81%

The study was able to get a response from 213 respondents out of 263 questionnaires distributed

that is a response rate of 81%. The reasons cited in the case of non response were lack of

cooperation especially from male direct sales employees. This section contains the presentation

and interpretation of findings arising from data analysis and presents findings according to the

study objectives.

4.2 Descriptive Analysis.

This section presents findings in respect to the demographic characteristics of the respondents

and other general characteristics.

Gender of the respondents

The study established the gender of the respondents and the results is given in table 4.2 below

Table 4.2 GenderFrequency Percent Valid

PercentCumulative

Percent

ValidFemale 127 59.6 59.6 59.6Male 86 40.4 40.4 100.0Total 213 100.0 100.0

The study findings showed that majority of the respondents were female representing 59.6% of

the total respondents with male composed of 40.4% of the total respondents. The representation

of gender of the DSP suggested that the occupation of DSP attracted more female than male.

Age Range of the respondents

The study established the age of the respondents from three categories and the results were

presented in table 4.3

Table 4.3 Age Range of the respondents

Frequency Percent Valid Percent

Cumulative Percent

Valid 20 - 25 57 26.8 26.8 26.8

26 -35 145 68.1 68.1 94.9

36 -45 11 5.1 5.1 100.0

Total 213 100.0 100.0

Form Table 4.3 it was found that the majority of the respondents were of the ages of 26-35 years

represented by 68.1% with 145 respondents. The range of 20-25 years had 57 respondents

accounting for 28.2% and 5.2 percent of the respondents had their age lie on the range of 36-45

years with only 11 respondents. This shows that very few individuals work past the age of 35

years as DSP.

Academic qualification of the respondents

The respondents were asked to state their current attained education qualification and the result is given in Table 4.4

Table 4.4 Respondents Academic qualification

Qualifications Percentage%

Diploma 19

Bachelors 48

Post Graduate Diploma 32

Masters 1

Form Table 4.4 the study found majority of the direct sales personnel had a qualification of

degree (48 percent), diploma and postgraduate diploma personnel were 51 percent of the total

personnel with only 1 percent of the direct sale personnel with a Masters degree. This

information suggested that direct sales personnel did not attract or require very high

qualifications of education as shown on Table 4.4.

Work experience of the respondents

The respondents were asked to state for how long they have worked as direct sales personnel

and the responses are recorded in Table 4.5

Table 4.5 Work experience duration

Duration Range Percentage of respondents

Less than 1 year 51

1-3 years 40

3-5 years 9

From Table 4.5 it was found that the majority of direct sales personnel worked for an average of

one year, these personnel were represented by 51 percent. Those who worked for 1 - 3 years

were 40% with 9 percent of the personnel working for 3 - 5 years. The study therefore concluded

that there was a high turnover of direct sales personnel.

The direct sales personnel were required to state what they liked about their jobs and the results

were recorded in table 4.6.

Table 4.6 what direct sales personnel liked about their job

Attribute Liked Percentage of respondents

Commissions 10

Experience 23

Good Pay 2

Networking 3

Time Flexibility 1

Travelling 29

None 32

The study required the respondents to state what they liked most about their job and travelling

experience was most liked by 29% of the respondents. The least liked was time flexibility with

only 1% of the respondents appreciating it.

4.3 Comparative statistics

This section analyzed comparative Means of the data collected on scale basis. Table 4.7 reported

the first two comparative statistics from the data.

Table 4.7 comparative statistics on Satisfaction and challenges of the job

In what scale would you rate your Job satisfaction based on working conditions?

How challenging is your job?

N 213 213Minimum 2 1Maximum 9 5Mean 5.57 4.06Std. Deviation 2.033 1.421Median 7.00 4.00% of Total Sum 100.0% 100.0%

From Table 4.7 direct sales personnel on average rated their job satisfaction based on the

working condition on scale of 5.57/10. The personnel implied from their average scale of

4.06/5 that their job was challenging. Therefore the direct sales personnel did not have

satisfaction in their job which could affect their productivity negatively as Roelofsen

(2002) found reduced challenges improved satisfaction hence productivity.

Table 4.8 recorded the comparative statistics on career development, satisfaction of

training opportunities, pride of work and if work for direct sales personnel was fairly

distributed.

Table 4.8 comparative statistics on career development, training opportunities, pride and distribution of work

I am getting enough career development

prospects

I am satisfied with the

opportunities for training

I am Satisfied with the

company's employee welfare

programssuch as rewards,

incentives, food coupons, insurance and health care.

How would you rate your

pride in working for

this organization?

Work is fairly distributed in

my Organization

N 213 213 213 213 213Minimum 1 1 1 1 1Maximum 5 5 5 5 5Mean 1.87 2.50 1.87 1.65 2.42Std. Deviation .931 1.239 1.010 .901 1.367Median 2.00 3.00 2.00 3.00 4.00% of Total Sum 100.0% 100.0% 100.0% 100.0% 100.0%

From table 4.8 the direct sales personnel on average rated their career development

prospects and satisfaction with welfare programs on a scale of 1.87/5. This implied that

the majority of the direct sales personnel felt that their career development prospects

were not guaranteed and their welfare was not good enough. The direct sales personnel

on average rated their satisfaction with opportunities for training at a scale of 2.5/5. The

average for pride of their work was 1.65/5 with a majority of the direct sales personnel

rating work distribution on scale of 2.42/5. This implied that the majority of the direct

sales personnel did not take pride in their work. These low scales of career development,

training opportunities and pride of direct sales personnel could lead to decreased

motivation hence productivity of an organization. Therefore it is essential that individual

motivation is practiced by an organization to improve productivity (Gryna et.al, 2007)

Table 4.9 reported the comparative statistics on resources, recognition, and involvement

in decision making of the direct sales personnel.

Table 4.9 comparative statistics on resources, recognition and decision making

I have the resources I need

to do my job well

My manager recognizes and acknowledges

my good performance

what percentage of all the

decision making process in your

organization that relates to sales do they involve

you?

My manager holds regular meetings with

my workgroups

My manager establishes plans

and work objectives with

me.

N 213 213 213 213 213Minimum 1 1 0 1 1Maximum 5 5 80 5 5Mean 2.08 3.59 2.15 2.30 2.27Std. Deviation 1.047 .994 7.400 1.142 1.124Median 3.00 3.00 2.00 3.00 3.00% of Total Sum 100.0% 100.0% 100.0% 100.0% 100.0%

Form the comparative statistics recorded in Table 4.9, it was found that direct sales personnel on

average rated the resources provided for their job on scale of 2/5. This implied that the direct

sales personnel felt that they had inadequate resources. The direct sales personnel also

acknowledged that their managers recognize their good performance by rating recognition by

3.59/5. Direct sales personnel on average rated 2.15/5 when they are involved in decision making

and average of 2.3/5 when they hold meetings. From the comparative statistics DSP were pleased

that their managers recognized their performance however they did not feel that they were

included in decision making. These indicated that the direct sales were not engaged in the

organization decision however as found by Buchanan and Huczynski, (2004) employee

engagement encouraged high performance which influenced productivity.

Table 4.10 recorded the comparative statistics on rate of company’s performance and motivation.

Table 4.10 comparative statistics on productivity and motivationHow well do you rate sales

performance?How motivated do you feel

when working for your Organization as a DSP?

N 213 213Minimum 4 4Maximum 9 10Mean 5.32 5.57Std. Deviation 1.133 1.421Median 6.00 6.00

% of Total Sum 100.0% 100.0%

Form Table 4.8 the direct sales personnel rated the sales performance on a scale of 5.32/10 and

motivation on a scale of 5.57/10. This implied that a lot needed to be done to improve the

motivation of direct sales personnel hence sales performance. Investigations on influence of

motivation to productivity of an organization found that motivation played a major role in

improving productivity (Cooper and Schindler, 2007).

4.4 Correlation Analysis

In testing linear relationship between the explanatory variables, correlation matrix is used as a

very important indicator in determining the strengths of variables in the model. A correlation

statistics greater than 0.8, reflects a high correlation among variables.

The study’s was guided by the research questions on the influence of employee morale,

satisfaction and engagement on motivation and productivity. Hyman & Mason (1995),

established that resources could be used to show morale of employees and therefore the study’s

question on whether direct sales personnel had resources they need for their job was used as a

proxy for morale. The question on whether managers established work plans and objectives with

the direct sales personnel was used to show engagement. The correlation of the variables was

recorded in Table 4.11

Table 4.11 Correlation Matrix

in what scale would you rate

your Job satisfaction

based on working

conditions?

I have the resources I need to do

my job well

My manager establishes plans and

work objectives with me.

How motivated do you feel

when working for your

Organization as a DSP?

How well do you rate sales performance?

In what scale 1

would you rate your Job

satisfaction based on working conditions?I have the

resources I need to do my job well

.284** 1

My manager establishes plans

and work objectives with

me.

.691** .228** 1

How motivated do you feel when

working for your Organization as a

DSP?

.409** .478** .412** 1

How well do you rate sales

performance?

.517** .478** .447** .780** 1

Form Table 4.11, the correlation results indicated that the variables in this study (Performance,

motivation, employee morale, satisfaction and engagement) are not strongly correlated thus the

variables can be regressed.

4.5 Regression Analysis

The variables having passed all the statistical tests, regression analysis was conducted. The study

estimated three regression models. The first regression was on the influence of employee morale,

satisfaction and engagement on productivity, the regression output were recorded in Table 4.12

and Table 4.13

Table 4.12 Model Summary Productivity

Model R R Square Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change df1

1 .846a .715 .717 .609 .715 175.199 3

a. Predictors: (Constant), I have the resources I need to do my job well, My manager establishes plans and work objectives with me., in what scale would you rate your Job satisfaction based on working conditions?

Table4.13 Coefficientsa

Model Unstandardized Coefficients

Standardized Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.043 .238 8.574 .000

in what scale would you rate your Job satisfaction based on working conditions?

.314 .029 .564 10.865 .000

My manager establishes plans and work objectives with me.

.216 .052 .214 4.198 .000

I have the resources I need to do my job well

.743 .042 .687 17.833 .000

a. Dependent Variable: How well do you rate your company's sales performance?

Form Table 4.12 The overall regression fit as estimated by Adjusted R-squared indicates a good

fit. The Adjusted R2- for motivation is reported to be approximately 72% implying that 72% of

productivity has been explained by the independent variables (satisfaction, morale and

engagement). From Table 4.13 the sign of the coefficients are as expected and significant.

The second regression was on the impact of employee morale, satisfaction and engagement on

motivation, the regression output were recorded in Table 4.14 and Table 4.15

Table 4.14 Model Summary Motivation

Model R R Square Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change df1

1 .938a .880 .863 .912 .880 101.886 3

a. Predictors: (Constant), I have the resources I need to do my job well, My manager establishes plans and work objectives with me., in what scale would you rate your Job satisfaction based on working conditions?

Form Table 4.14 The overall regression fit as estimated by Adjusted R-squared indicates a good

fit. The Adjusted R2- for motivation is reported to be approximately 86% implying that 86% of

motivation has been explained by the independent variables (satisfaction, morale and

engagement).

Table 4.15 recorded the motivation regression coefficients output from the second regression

analysis on the impact of employee morale, satisfaction and engagement on motivation.

Table 4.15 Motivation regression-Coefficientsa

Model Unstandardized Coefficients

Standardized Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.568 .357 4.394 .000

in what scale would you rate your Job satisfaction based on working conditions?

.278 .043 .398 6.423 .000

My manager establishes plans and work objectives with me.

.362 .077 .286 4.685 .000

I have the resources I need to do my job well

.890 .062 .656 14.251 .000

From Table 4.15 the sign of the coefficients are as expected and significant. Employee morale,

satisfaction and engagement are all significant (P<0.01) and positively impacting motivation.

The third regression was on the influence of motivation on productivity. The regression output

are recorded on table 4.16 and 4.17

Table 4.16 Model Summary Motivation to productivity

Model R R Square Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

1 .850a .722 .720 .599 .722 547.143 1

a. Predictors: (Constant), How motivated do you feel when working for your Organization as a DSP?

Table 4.17 Coefficientsa

Model Unstandardized Coefficients

Standardized Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.189 .223 9.808 .000

How motivated do you feel when working for your Organization as a DSP?

.677 .029 .850 23.391 .000

a. Dependent Variable: How well do you rate your company's sales performance?

Form Table 4.16 The overall regression fit as estimated by Adjusted R-squared indicates a good

fit. The Adjusted R2- for productivity is reported to be approximately 72% implying that 72%

sales productivity is explained by motivation. From Table 4.17 the sign of motivation coefficient

is as expected and significant

4.6 The influence of employee morale on productivity

To achieve the first objective, productivity was regressed against morale, satisfaction and

engagement. The coefficients for all independent variables were significant at 1% confidence

level as shown in Table 4.13. It was found that 72% of direct sales personnel productivity was

explained by satisfaction, morale and engagement as shown in Table 4.12. For a unit change in

morale, sales productivity improved by 0.743 as shown in Table 4.13. According to Moorhead

and Griffin (2004) morale is a result of top down rather than bottom up communication. The

benefit of high morale is seen in the form of improved communication, low attrition, high

retention and an innovative organization which creates a positive working environment and

increases productivity. Millet (2010) stated that low morale leads to problems like decrease in

productivity and low performance. As presented in Table 4.10 the direct sales personnel rated

their performance on a scale of 5.32/10. This could be attributed to the low rate of rewards

(1.87/5) as shown in Table 4.8 and the low rate of resources to direct sales personnel of (2/5) as

shown in table 4.9.

4.7 The extent to which employee satisfaction improves productivity

To achieve the second objective, productivity was regressed against morale, satisfaction and

engagement and the regression output was recorded on Table 4.13. From Table 4.13 it was found

that a unit change in satisfaction, direct sales productivity improved by 0.314. This result was

significant as at 1% level of signification as P < 0.01 and the coefficient had a positive sign as

expected which meant it improved productivity. This result was consistent with Research by

Roelofsen (2002) that indicated, improving working environment resulted to reduction of

complaints and absenteeism hence improved satisfaction and an increase in productivity. This

was found to be true for the direct sales personnel as revealed in the regression output in Table

4.13.

4.8 The influence of employee engagement on productivity

The influence of employee engagement on productivity was the third objective of the study.

From the regression output presented in Table 4.13 it was found that for a unit change in direct

sales employee engagement, sales productivity improved by 0.216. This result was as expected

and agreed with the study of Konrad (2006) that revealed that employee engagement has been

found to be closely linked to feelings and perceptions around being valued and involved, which

in turn generates the kinds of discretionary effort that leads to enhanced performance and

productivity. According to Buchanan and Huczynski (2004), organizations can engage their

employees by providing an environment that encourages positive emotions and pride which then

leads to high performance and lower employee turnover. This study found that the turnover for

direct sales employee was very high with 51% of the employee working for less than 1 year as

indicated in Table 4.5.

4.9 Impact of employee morale, satisfaction and engagement on motivation

To achieve the fourth objective, direct sales personnel motivation was regressed against the

independent variables (morale, satisfaction and engagement) and the results were presented in

Table 4.15. It was found that 86% of direct sales personnel motivation was explained by

satisfaction, morale and engagement as shown in Table 4.14. The coefficients for all independent

variables were significant at 1% confidence level as shown in Table 4.15. For a unit change in

satisfaction, motivation increased by 0.278. This result concurred with a study by Weiss (1999)

that concluded the levels of job satisfaction and perception of fairness of pay affect employee

commitment and intention to stay with the organization.

Form the regression output presented in Table 4.15 it was also found that for a unit change in

direct sales employee engagement, motivation increased by 0.362. This result agreed with the

studies of Schaufeli & Bakker (2004) who proposed that engaged employees are likely to have a

greater attachment to their organization and a lower tendency to quit and Sonnentag (2003) who

concluded that these positive experiences and emotions are likely to result in positive work

outcomes and hence increased motivation.

The regression output presented in Table 4.15 revealed that a unit in morale, motivation

increased by 0.890. Investigations by Mashonganyike (2004) had the same conclusion that

employee allocation of adequate resources was important for improving employee motivation.

Therefore the results presented in Table 4.15 conclude that morale of direct sales personnel will

increase motivation

All this results were significant and had the expected signs for direct sales personnel as indicated

in Table 4.14 and Table 4.15. The results show that as other studies expect satisfaction,

engagement and morale to increase motivation for employee was the same for direct sales

personnel. These results therefore lead the study to conclude that satisfaction, engagement and

morale were important to improve the motivation hence reduce the high turnover of direct sales

employees as recorded in Table 4.5 where 51% of the direct sales employee work for less than

one year.

Konrad (2006) revealed that employee satisfaction, engagement and morale lead to motivation of

employees which in turn leads to high productivity of an organization. Employee satisfaction,

engagement and morale were found to influence motivation hence improving productivity as

recorded in Table 4.17. The results established that 72% sales productivity is explained by

motivation as shown in Table 4.17. The coefficient for motivation was also found to be

significant at 1% confidence level as shown in Table 4.16. For a unit change in motivation sales

productivity would improve by 0.677 as shown in Table 4.17. Cooper and Schindler (2007)

revealed that company’s traits of motivation could not be ignored to improving productivity.

Form this study this is confirmed by finding that 72% of the company’s sales performance was

attributed to motivation. Gryna et al. (2007) in their study showed that organizational motivation

lead to improvement in quality results that directly improved employee productivity.

4.10 conclusions

It can be concluded that motivation for direct sales personnel is very important to improving

company’s sales performance and productivity as 72% of productivity is attributed to motivation.

The study concluded that satisfaction, engagement and morale were significant to improving

motivation and productivity. Satisfaction, engagement and morale were found to influence

motivation of direct sales personnel by a greater percentage (86%) than productivity of direct

sales personnel where 72% of productivity was attributed to these factors.

With other studies investigating the influence of employees in general to productivity, this study

investigated specifically the influence of direct sales employees in company’s productivity. The

study found that direct sales personnel Satisfaction, engagement and morale had a positive

influence on a company’s productivity.

CHAPTER FIVE: SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

5.1 Introduction

This chapter presents the summary of the collected findings, the conclusions drawn from these

findings and the recommendations the study makes.

5.2 Summary of findings

This study investigated the productivity of direct sales personnel In Kenya. The objectives of this

study were founded in the Maslow’s Hierarchy of Needs Theory whereby certain motivational

factors affect productivity of Direct Sales Personnel in Commercial Banks in Kenya. Three

models were regressed with application of SPSS, with the first regression on productivity against

satisfaction, engagement and morale. The variables were found to impact productivity positively.

The second regression was on motivation against satisfaction, engagement and morale. The

variables were found to influence motivation positively. The third regression was on productivity

against motivation where motivation was found to positively impact productivity.

The study answered the questions; what was the influence of employee morale on productivity?

To what extent does employee satisfaction improved productivity? How employee engagement

affected productivity? And what was the impact of employee morale, satisfaction and

engagement on motivation? The target population included all Direct sales personnel employed

by the four leading commercial banks located in Thika town namely; Kenya Commercial bank,

Barclays bank, Standard Chartered bank and Cooperative bank. The study conducted a census

survey including all the 263 direct sales personnel from these banks as the number was not too

big to necessitate sampling. Judgement sampling was used to determine the banks that will fairly

represent the banking industry in Kenya. Data was collected using structured questionnaires,

which were administered through a “drop and pick later” method where the response rate was

81%.

The study also revealed that the majority of the direct sales personnel represented by

approximately 60% were female, with male being 40% of the total direct sales personnel. It was

also revealed that majority of the direct sales personnel were aged 26-35 years representing

approximately 68% of the total direct sales employees. It was also found that majority (48%) of

the direct sales personnel had a bachelor’s qualification, with 51% having a diploma or

postgraduate qualification and only 1% percent had a Masters qualification. There was found to

be high (51%) turnover of direct sales personnel who only worked for less than 1 year. Most

(29%) of the direct sales personnel indicated that they liked the aspect of travelling in their work,

with least (1%) liking the time flexibility of their work.

5.3 conclusions

With having researched on the influence of employees in general to productivity, this study

investigated specifically the influence of direct sales employees in company’s productivity. The

study found that direct sales personnel Satisfaction, engagement and morale had a positive

influence on a company’s productivity.

Form the findings, the sign of the independent variables (satisfaction, engagement and morale)

were consistent with theory and majority of the past studies reviewed in literature. However this

study was specific to direct sales personnel with the other studies investigating employee in

general. The study revealed that satisfaction, engagement and morale influenced motivation of

direct sales personnel by a greater percentage (86%) than productivity of direct sales personnel

where 72% of productivity was attributed to these factors. The coefficients of the independent

variable were found to significant at 1% confidence level and this implied that the variables were

justified to be included in the regression model after they were found not to be highly correlated.

5.4 Recommendations

Based on the study finding, the Kenyan commercial banks should focus on improving motivation

to increase the productivity of the direct sales personnel. It is evident from the finding that

morale was more influential than satisfaction and engagement in improving motivation hence

productivity. Factors that contributed to morale were better pay and employee rewards which

included commissions, health insurance and bonuses. Factors that contributed to satisfaction and

engagement will also be important in increasing motivation hence productivity.

Banks should ensure that they pay better salaries and give resources and rewards to direct sales

personnel to improve their performance where the companies will reduce the high direct sales

personnel turnover hence increase motivation and productivity.

5.5 Suggestions for further research

This study investigated the productivity of direct sales personnel In Kenya. Lack of motivation

can be stumbling block to a company’s direct sales productivity. Satisfaction, engagement and

morale are crucial to motivate employees and in turn increase direct sales productivity. Further

studies on specific employees of a specific department in company will help companies identify

factors that may increase the productivity of these companies.

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APPENDICES

APPENDIX ONE: LETTER OF INTRODUCTION

Catherine Njoki Chege

P.O.Box 253 Gatundu- 01030

Dear Respondent,

RE: REQUEST FOR RESEARH DATA.

I am a post graduate student undertaking research in partial fulfillment of the requirement for the master

of business administration degree in the department of business administration of Africa Nazarene

University. The study is on “Factors affecting productivity of direct sales Personnel in commercial

banks in Kenya”. You have been selected to take part in this study. The questionnaire provided is meant

to collect information that will be of much importance to the above mentioned study. The information

you provide will be used solely for academic purposes and will be treated with utmost confidentiality.

Please fill it with honesty.

Your cooperation will be highly appreciated.

Best Regards,

Catherine Njoki Chege

APPENDIX 2: QUESTIONNAIRE

This survey is aimed at providing an opportunity to communicate your opinion about your

company and your job. We assure you that your responses will be held in confidence.

SECTION ONE: (General Information)

1) Gender (Tick one)

a. Male

b. Female

2) Age (Tick one)

a. 20-25

b. 26-35

c. 36-45

d. Above 45

3) Are you a Direct Sales personnel (Tick as appropriate)

a. Yes

b. No

4) Select your Academic qualifications 

a. Certificate

b. Diploma

c. Bachelors

d. Post Graduate

5) How long have you worked for the organization as a DSP? (Tick one)

a) Less than one year

b) 1-3 years

c) 3-5 Years

d) More than 5 years

SECTION TWO: (Questions related to Employee Satisfaction)

6) Are you satisfied with your working conditions? (Tick One)

a. Yes

b. No

7) Is your job challenging and interesting? (Tick One)

a. Yes

b. No

8) On a scale of 1(Not Challenging) to 5(Very Challenging), How challenging is your job?

___________________________

9) Are the work deadlines realistic? (Tick One)

a. Yes

b. No

10) I am getting enough career development prospects (Tick One)

a) Strongly Dis-Agree

b) Dis-Agree

c) Neither Agree nor Dis-Agree

d) Agree

e) Strongly Agree

11) I am satisfied with the opportunities for training (Tick One)

a) Strongly Dis-Agree

b) Dis-Agree

c) Neither Agree nor Dis-Agree

d) Agree

e) Strongly Agree

12) I am satisfied with the company’s employee welfare programs such as rewards,

incentives, food coupons, insurance and health care (Tick One)

a) Strongly Dis-Agree

b) Dis-Agree

c) Neither Agree nor Dis-Agree

d) Agree

e) Strongly Agree

13) On a scale of 0(Not Satisfactory) to 10(Very Satisfactory), how would you rate your Job

satisfaction based on ALL working conditions?

_________________________________

14) Give at least three suggestions on how to improve the work environment in your

organization. (Comment in your own words)

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15) In as few words as possible describe what you love most about your job

___________________________________

16) Are you actively looking for a job outside this organization? (Tick One)

a) Yes

b) No

SECTION THREE: (Questions related to Employee Morale)

17) Are the physical working conditions safe and comfortable? (Tick One)

a) Yes

b) No

18) Are you highly committed to your Organization? (Tick One)

a) Yes

b) No

19) Are you proud to tell people that you work for this company? (Tick One)

a) Yes

b) No

20) Do you feel good about coming to work every morning? (Tick One)

a) Yes

b) No

21) On a scale of 1(Not Proud) to 5(Very Proud), how would you rate your pride in working for this organization?

_____________________________

22) Work is fairly distributed in my Organization? (Tick One)

a) Strongly Dis-Agree

b) Dis-Agree

c) Neither Agree nor Dis-Agree

d) Agree

e) Strongly Agree

23) I have the resources I need to do my job well (Tick One)

a) Strongly Dis-Agree

b) Dis-Agree

c) Neither Agree nor Dis-Agree

d) Agree

e) Strongly Agree

24) My manager recognizes and acknowledges my good performance (Tick One)

a) Strongly Dis-Agree

b) Dis-Agree

c) Neither Agree nor Dis-Agree

d) Agree

e) Strongly Agree

25) Briefly comment on some of the issues that affect your sales productivity

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26) Among the above issues, which one seems to NEGATIVELY affect your performance

MOST?

________________________________________

27) Among the above issues, which one seems to POSITIVELY affect your performance

MOST?

________________________________________

SECTION FOUR: (Questions related to Employee Engagement)

28) Are you given enough feedback on performance? (Tick One)

a) Yes

b) No

29) My manager allows me to participate in making decisions (Tick One)

a) Strongly Dis-Agree

b) Dis-Agree

c) Neither Agree nor Dis-Agree

d) Agree

e) Strongly Agree

30) My manager holds regular meetings with my work groups (Tick One)

a) Strongly Dis-Agree

b) Dis-Agree

c) Neither Agree nor Dis-Agree

d) Agree

e) Strongly Agree

31) In what percentage of all the decision making process in your organization that relates to

sales do they involve you?

_____________%

32) My manager establishes plans and work objectives with me (Tick One)

a) Strongly Dis-Agree

b) Dis-Agree

c) Neither Agree nor Dis-Agree

d) Agree

e) Strongly Agree

33) : On a scale of 1(Very Unmotivated) to 5(Highly Motivated), how motivated do you feel

when working for your Organization as a DSP?

_______________________

34) What changes would you recommend to your Organization concerning the role of a DSP?

(Comment in your own words).

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35) On a scale of 1(Poor Overall Performance) to 10(Excellent Overall Performance), how well do

you rate your company's sales performance?

__________________________________

THANK YOU FOR YOUR COOPERATION