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Demographic Diversity in the Workplace
and Its Effect on Employee Performance: A
Case of IBM Kenya
Anne Onsarigo1 and Thomas Katua Ngui
2
1(The Catholic University of Eastern Africa, Kenya)
2(Senior Lecturer, The Management University of Africa, Kenya)
Abstract: The need for this study stemmed from the desire by organizations to embrace workforce diversity in a
bid to enhance employee performance. The main purpose was to establish the effects of workforce diversity on
employee performance in Kenya with focus on the technology industry. The objective of the study was to identify
the diversity attributes that exist at IBM Kenya, and establish their effect on employee performance. This study’s
theoretical background was based on three theories, namely reinforcement theory, equity theory, and
organizational citizenship behavior (OCB) theory. The study adopted a descriptive research design. The study
targeted employees of IBM Kenya with focus on employees working at the IBM headquarter offices in Nairobi.
The sample size was 105 employees. Primary data was collected using structured questionnaires. The
researcher used drop and pick method in administering the questionnaire. Data analysis was done using
computer analysis software, SPSS version 23.0. Both descriptive and inferential statistics were carried out and
the findings were provided using distribution tables. From the findings, employees of IBM Kenya strongly
agreed that there was gender balance in the organization, which motivated them to remain committed at work,
they also agreed that the policies that existed in the organization, giving equal opportunities for growth and
development regardless of gender, age or educational background improved employee performance over time.
Further findings revealed that having different age groups in senior positions encourages and motivates
employees; good working relationships between employees of different age groups improved employee
performance, and involvement of members of different age groups in solving problems and in decision making
enhanced employee performance. Additionally, working with employees with different educational levels or
backgrounds has improved their performance. The study concluded that workforce diversity practiced by
technology companies highly influenced performance of employees leading to overall organizational
performance. The study then recommended that the government in collaboration with other stakeholders in the
technology industry should ensure that there are effective workforce diversity policy guidelines in a bid to
enhance employee performance which highly contributes to organizational performance and growth.
Keywords: Workforce Diversity and Employee Performance
I. INTRODUCTION
Workforce diversity
According to Abdel (2012) workforce diversity is a multi-faceted concept that will continue to evolve
as more industries move towards both working in and recruiting employees from a global market place.
Workforce diversity means creating an inclusive environment in the workplace that accepts each individual's
differences, embraces their strengths and provides opportunities for all staff to achieve their full potential.
Diversity is really all the attributes that define a person, these include but are not limited to: age, ethnicity,
ancestry, gender, physical abilities/qualities, race, sexual orientation, educational background, geographic
location, income, marital status, military experience, religious beliefs, parental status, and work experience. A
common misconception about diversity is that only certain persons or groups are included under its umbrella,
when in fact, exactly the opposite is true. Workforce diversity is a multi-faceted concept that will continue to
evolve as more industries move towards both working in and recruiting employees from a global market place
(Abdel, 2012). Organizations that promote and achieve a diverse workplace will attract and retain quality
employees and increase customer loyalty (Al Gore, 2000). For public organizations, diversity also translates
into effective delivery of essential services to communities with diverse needs. Leaders and managers within
organizations are primarily responsible for the success of diversity policies because they must ensure that the
policies are effective. The leaders and managers within organizations must incorporate diversity policies into
every aspect of the organization’s functions and purpose (Al Gore, 2000).
Employee performance is a means of carrying out actions efficiently and effectively by the employees
to achieve the predetermined objectives of an organization (Baldwin, 2008). It is normally looked at in terms of
outcomes or employee’s output against the set individual objectives populated from the company objectives
(Armstrong, 2010). However, it can also be looked at in terms of behavior (Armstrong, 2007).
Anne Onsarigo and Thomas Katna Ngni, International Journal of Research in Engineering, IT and Social
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According to Bates and Horton (1995) performance is a multi-dimensional contrast, the measurement
of which varies, depending on a variety of factors. They also state that it is important to determine whether the
measurement objective is to assess performance outcome or behavior. A more comprehensive view of
performance is achieved if it is defined as embracing both behavior and outcomes. Brumbrach (1988) argued
that performance means both behavior and results. Behaviors emanate from the performer and transforms
performance from abstraction to action. This therefore means that when one is managing performance of teams
and individuals, both input (behavior) and output (results) should be considered. It has become increasingly
evident that organization’s must incorporate diversity into their business, in order for them to create better
innovations and achieves better financial outcomes.
International Business Machines, Kenya
The International Business Machines Corporation is an American multinational technology company
headquartered in Armonk, New York, United States, with operations in over 170 countries. The company began
in 1911 as the Computing-Tabulating-Recording Company (CTR) and was renamed "International Business
Machines" in 1924. IBM manufactures and markets computer hardware, middleware and software, and provides
hosting and consulting services in areas ranging from mainframe computers to nanotechnology. IBM is also a
major research organization, holding the record for most U.S. patents generated by a business (as of 2018) for
25 consecutive years.
Nicknamed Big Blue, IBM is one of 30 companies included in the Dow Jones Industrial Average and
one of the world's largest employers, with (as of 2016) nearly 380,000 employees. Known as "IBMers" (IBM,
2018). IBM began operating directly in East Africa since 1958 and has recently transformed into a Cognitive
solutions company powered by Cloud. For over sixty years, IBM Kenya has been highly involved in
encouraging growth and development within East Africa. The Nairobi office is the operations headquarters for
IBM in the region overseeing eight countries including Tanzania, Uganda, Burundi, Rwanda, Ethiopia, South
Sudan and Djibouti. Long term partnerships within the industries such as telecommunications, government, oil
and gas sectors has allowed them to focus on providing innovative solutions which speak to the needs of local
citizens (IBM, 2015)
In 2010 under the leadership of the Chief Executive Officer (CEO),Ginni Rometty, IBM Kenya began
an expansion strategy which saw the number of employees grow from 20 in 2010 to about 300 employees in
2018 (IBM, 2018). The growth in number of employees also saw an increasingly diverse workforce been
brought on board.
According to IBM CEO, Ginni Rometty (2018), IBM thinks about diversity the way they think about
innovation — both are essential to the success of their business. When they innovate, technology becomes
smarter for clients and creates new opportunities for growth. When they incorporate diversity into their
business, they create better innovations and outcomes. IBM has embraced diversity, and it gives opportunities
for IBMers and their clients to achieve their full potential.
However, no tranformation comes without challenges. From 2013 IBM Kenya has not been meeting its
yearly targets in most of the business brands due to the ongoing transformation (IBM, 2015). During a strategy
session held in 2015, IBM Kenya committed to adopting best diversity practices in the workplace including
hiring employees of different ages, increasing the number of female employees, employing and assigning duties
based on educational qualifications, having a career development guide for all employees, rewarding ideas and
innovations of the employees regardless of their backgrounds (IBM, 2015). However, a study on the effect of
the adopted workforce diversity initiatives on employee performance in IBM Kenya has not been conducted.
Therefore this study sought to establish the existence of workforce diversity at IBM Kenya and its effect on
employee performance. This study focused on primary dimensions of diversity in the workplace specifically
three types; gender, age, and educational background.
Problem statement
Understanding the effect of workforce diversity in the workplace is key to organizational sustainability.
According to Williams and O’Reilly (1998) and Passos and Caetano (2005), it is imperatively evident from
previous studies that workplace diversity can be either detrimental or beneficial for employee performance.
According to studies that have been conducted in relation to the issue of workplace diversity, it’s become visible
that gender, age, educational background and ethnicity are the main differences that can affect employee
performance within an organization. However, there is limited research that specifically focuses on diversity in
the workplace and its effect on employee performance. This is supported by Hambrick and Mason (2012) who
noted that lack of sufficient pieces of evidence that can help organizations to link the existing relationships
between workforce diversity and employee performance is seemingly proving to be one of the most complex
issues than what is implied in most research discussions. Thus, this study sought to bridge the research by
focusing on the effect of workforce diversity on employee performance. With a focus was on gender, age, and
educational background diversity in IBM Kenya.
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Research Objectives
The purpose of this study was to establish how diversity in the workplace can influence performance of
employees with focus on IBM Kenya. Specifically, the study tends to;
i) Identify the diversity attributes or practices that exist at IBM Kenya
ii) Establish the effect of gender diversity on employee performance at IBM Kenya
iii) Establish the effect of age diversity on employee performance at IBM Kenya
iv) Determine the effect of educational background diversity on employee performance at IBM Kenya.
Scope and delimitations of the study
This study focuses on the technology industry with focus on IBM Kenya, sampling its respondents
from the IBM Kenya headquarters at Hurlingham, Nairobi which is representative of IBM East Africa. The
study only focuses on diversity and employee performance. The study focused only on gender, age and
educational background of employees.
II. LITERATURE REVIEW Theoretical Review
Equity theory
Equity theory was first developed in 1963 by John Stacey Adams who was a workplace and behavioral
psychologist. The theory was regarded as one of the many theories of justice. Adams (1963) argues that
employees seek to maintain equity between what they put into a job and what they receive from it against the
perceived inputs and outcomes of others. The theory concentrates on the concept of fairness in the workplace.
Employees may thus, compare the inputs they devote to the work with the outputs they receive from the
organization. The theory further emphasizes on the need for a balance of employee inputs and outputs as
compared to others (Drafke & Kossen, 2002). Once employees feel that their inputs do not commensurate to the
treatment they receive from the organization, which means it lacks the element of fairness, they are demotivated
resulting in poor employee performance.
Equity theory suggests that employee perceptions of what they contribute to the organization, what
they get in return, and how their return-contribution ratio compares to others inside and outside the organization
determine how fair they perceive their employment relationship in terms age, gender and educational
background (Adams, 1963). External equity exists when an employer gives equal opportunities to candidates
regardless of gender, age and educational background. Internal equity exists when an employer treats all
employees equal despite their age, gender, and educational background. Equity theory brought to the attention
of the researchers that both external equity and internal equity are very important for employee performance
hence the need to determine whether IBM Kenya’s workforce diversity practices incorporated external equity.
Empirical Review
Internationally, industry practitioners as well as an increasing number of scholars, argue that diversity
is a positive factor that leads to competitive advantages for firms (Farley, 2003; Richard, 2006). Wentling and
Rivas (2013) did a study on status of diversity initiatives in selected multinational corporations in the United
States. The purpose of the study was to provide information on the status of diversity initiatives in selected
multinational corporations, to report on the dimensions of the diversity initiatives, and to interpret the dynamics
of the corporate response to workforce diversity. Eight multinational corporations headquartered in the United
States were selected for the study. Two methods of data collection were used: semi-structured face‐to‐face
interviews and document analysis. Diversity managerdirectors were asked to provide information on their
diversity initiatives; on the planning, implementation, and evaluation of diversity initiatives; and on plans for
future diversity initiatives. The study revealed that multinational corporations are planning, implementing, and
evaluating a large number and variety of diversity initiatives not only in the United States but also
internationally. Further findings of the study revealed that youngsters who are in their learning ages are always
willing to learn as many things and ideas as possible. In contrast, older people who have vast work experiences
are more mature and thus have more problem-solving skills.
However, another study ran by Mwatumwa (2015) on the effect of workforce diversity on employee
work performance with particular focus on the County Government of Mombasa (CGM). With a target
population comprised of employees of the CGM working in the County Assembly. Where data was collected
through self-administered questionnaires and was descriptively analyzed. Found that workforce diversity is a
well-accepted phenomenon at the CGM and that there was no discrimination detected resulting from ethnic,
gender or educational background. The workforce was harmonious but without expectations of high or low
performance based on an employee`s demographic background. Further findings indicated that an employee`s
ethnic, gender and educational background did not have any contributory effect on performance. From
Mwatumwa’s (2015) findings, workforce diversity does not influence employee work performance at the
County Government of Mombasa.
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Conceptual framework
Figure 1. Conceptual Framework
Source: Author (2018)
Theoretical Framework
Study was guided by various theories, these include: Reinforcement Theory.
III. RESEARCH DESIGN AND METHODOLOGY Research design
This study adopted descriptive research design which, according to Chandran (2004) and Kothari
(2008), is the most appropriate for studying social phenomena due to its ability to describe a situation and
portray an event, or situation as it exists. The use of descriptive research design in this study enabled the
researcher to establish the status of IBM Kenya’s workforce diversity and describe its effect on employee
performance as it currently exists.
There are three basic types of descriptive research methods: observational, case-study, and survey
methods (Jackson, 2009). The researchers found it appropriate to apply both the case-study method and the
survey method. According to Jackson (2009), case study research involves an in-depth study of an individual or
group of individuals while in survey method participants answer questions administered through interviews or
questionnaires. In this study, the researchers used IBM Kenya as the case study and a survey was conducted
whereby participants of this research answered questions administered through questionnaires. The researchers
used the quantitative approach through closed-ended questions to acquire specific, accurate and relevant
information that ensured the objectives of this study were achieved.
Population of Study
The population of this study comprised of all employees of IBM Kenya. According to the IBM Kenya
Database (2018), the total number of employees of IBM Kenya is 320. This number was the study population of
this research. However, the researchers targeted employees working at the headquarters of IBM Kenya in
Hurlingham, Nairobi. Therefore, the target population for this study was 105 employees working at IBM
headquarters in Nairobi, Kenya.
Sample size
According to Sekaran and Bougie (2010), a sample size larger than 30 and less than 500 are
appropriate for most empirical research. In a descriptive research, 10% of the target population is adequate for a
sample size (Mugenda 2008). However, if the target population is less than 200, then census is applied
(Mugenda, 2008). A census is a complete enumeration of all the items in the target population (Kothari, 2004).
Since the target population for this study was 105, which was less than 200, the researchers applied the census
technique during data collection. Therefore, the sample size for this study was the same as the target population
– all the 105 employees working at IBM headquarters in Nairobi, Kenya as shown in Table 3.1.
Table 3.1: Target Population and Sample Size
Type of employees Target Population Sample Size
Managers 40 40
Technicians 25 25
Data Analysts 10 10
Engineers and Designers 5 5
Procurement officers 5 5
Human resource officers 5 5
Administrators 5 5
Legal Advisor 5 5
Tax Leaders 5 5
Total 105 105
Source: IBM Kenya Database (2018)
Data collection instruments
For this study, the researcher chose to use a structured questionnaire to collect primary data. This is a
questionnaire that contains closed-ended questions. Closed-ended questions are short and specific (Yang, 2008),
and in most cases they are a pre-coded set of questions to which respondents recorded their answers within
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closely delineated alternatives (Upgrade & Shende, 2012). The closed-ended questions enabled the researcher to
obtain precise and specific information on diversity attributes at IBM Kenya and its effect on employee
performance. In addition, closed-ended questions eased data analysis since the responses were pre-coded.
Data collection procedures
After obtaining all the legal documents for data collection, the researchers recruited and trained three
research assistants to help in data collection. The research assistants together with the researchers made a prior
visit to the headquarters of IBM in Nairobi. They introduced themselves and explained the purpose of the study
and consulted with the administration of IBM Kenya for the possibility and appropriate time to distribute the
questionnaires to the employees and even booked appointments with those that agreed to participate in the
study. The questionnaires were self-administered hence the research assistants employed ‘drop and pick’
method of collecting data. All employees working at the headquarters of IBM in Nairobi were issued with
questionnaires to fill.
Validity and reliability
The accuracy of data to be collected largely depends on the data collection instruments in terms of their
validity and reliability. Similarly, validity is the degree to which results obtained from the analysis of the data
represent the phenomenon under study (Mugenda, 2008). Validity checks whether a questionnaire is measuring
what it purports to measure (Bryman & Cramer, 1997). The study made use of both construct validity and
content validity.
Construct validity aimed at dividing the questionnaire into several sections by ensuring that each
section assessed a specific objective and ensured that the questions asked closely tied to the conceptual
framework of the study. For content validity, the questionnaire was examined by human resource scholars to
check for relevance of the statements, objectivity, meaning and clarity. From the evaluation, the questionnaire
was adjusted accordingly before the pilot study and data collection exercise.
In this study, Cronbach's alpha coefficients (α) were used to determine the average internal consistent
(reliability) of items that were on multiple Likert scale. The higher the (α) coefficient the more reliable was the
construct. As a rule of the thumb, the acceptable range of Cronbach alpha coefficient is between 0.70 and 0.90
or higher depending on the type of research. For exploratory or descriptive research, 0.70 or more is acceptable
while 0.80 and 0.90 are acceptable for basic research and applied sciences respectively. Therefore, the
researcher conducted Cronbach alpha test using questionnaires obtained from the pilot study exercise. The
findings were as shown in Table 2.
Table 2: Cronbach’s Alpha Coefficients for Multiple Likert Scale Items
Category of multiple Likert scale items Cronbach's
Alpha
Cronbach's Alpha Based
on Standardized Items
No. of
Items
Gender diversity attributes .880 .881 7
Age diversity attributes .713 .787 8
Educational background diversity attributes .807 .858 8
Effect of gender diversity in work place on
employee performance
.757 .768 6
Effect of age diversity in workplace on employee
performance
.775 .790 5
Effect of educational background diversity on
employee performance
.676 .689 8
Indicators of employee performance .957 .948 9
From Table 3, Cronbach's alpha coefficients for all variables with multiple Likert scale items was
approximately 0.7 or more, which indicates that the level of internal consistency for the items that were used in
each variable was acceptable hence the items were reliable to measure the variables of this study. This implies
that the questionnaire that was used in this study was reliable hence the findings were accurate and relevant.
Data Analysis Plan
Quantitative data that was obtained during data collection was first cleaned to remove incomplete
questionnaires and irrelevant answers. Only duly filled questionnaires were analyzed. First, the pre-coded
responses in the questionnaires were keyed into the Statistical Package for Social Science (SPSS) version 23.0.
Then the researcher analyzed the data using both descriptive and inferential statistics.
According to Kothari (2008) descriptive statistics provides for important distribution of scores by use
of statistical measures of dispersion, distribution and central tendencies. Descriptive statistics describe the basic
features of the data that was obtained from the field. It did not provide the relationship between the independent
variables (Diversity at IBM Kenya) and the dependent variable (employee performance at IBM Kenya). It only
summarized and described the study findings. Frequencies, standard deviations, percentages and means were
used in this study for descriptive statistics.
For inferential statistics, multiple regressions were carried out to determine the relationship between
each of the three independent variables and employee performance. It predicted the existence of relationships
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and or influence of predictor variable on dependent variables. Essentially, multiple regression analysis is an
extension of bivariate regression analysis that allows for simultaneous investigation of the effects of two or
more independent variables to the underlying single-scaled dependent variable (Abbas, Qasar & Hameed, 2010).
The analysis was significant because it enabled the researcher to find out which independent variable had great
effect on the underlying dependent variable. In addition to that, the researchers could also assess the regression
coefficients for each independent variable to understand the relationship that exists between single dependent
variable and multiple independent variables (Zikmund, 2003). The regression formula that was used in this
study is:
Y = β0 + β1x1 + β2x2 + β3x3+ β4x4+ ε
Where: Y is the employee performance as result of workforce diversity adopted by the technology industry in
Kenya.
B0 is a constant
β1 to β4 are the coefficient of the independent variables
x1 to x4 are the independent variables where
ε is the error term
Response Rate
The study targeted a sample of 105 respondents who included employees of IBM Kenya working at the
headquarters in Nairobi. However, out of a total of 105 questionnaires that were administered, only 80 were
duly filled and returned, thus making the response rate of this study to be 76% (80) as shown in Table1.
Mugenda (2008) and Neuman (1997) noted that in a descriptive study, a response rate of 50% is adequate for
analysis and reporting, 60% is good, and 70% and above is excellent. Therefore, this study’s response rate of
76% (80) was excellent hence satisfactory enough for analysis, reporting and drawing conclusions. The response
rate was a true representative of the study population.
Table 1: Response rate
Category of respondents Target
sample size
Actual
respondents
Response rate
Managers 40 36 90%
Technicians 25 22 88%
Data Analysts 10 7 70%
Engineers and Designers 5 2 40%
Procurement Officers 5 2 40%
Human Resource Officers 5 2 40%
Administrators 5 3 60%
Legal Advisors 5 3 60%
Tax Leaders 5 3 60
Total 105 80 76%
Descriptive Analysis
During data collection, the researcher listed several items/statements corresponding to diversity at the
workplace and its influence on performance of employees in the technology industry in Kenya. The respondents
(employees) were asked to rate the statements on a Likert scale of 1–5 whereby 1=Strongly Disagree,
2=Disagree, 3=Not sure, 4=Agree and 5=Strongly Agree. The “Means” and “Standard Deviation” for each
statement were established to provide a generalized feeling of the respondents on their perception on the
influence of diversity on their performance.
For generalization purposes, an outcome with a mean of 1 and less than 1.5 implied that the employees
strongly disagreed with the item/statement that the researcher used to rate their level of agreement hence the
attribute would be deemed to have no influence on employee performance. Means greater than 1.5 and less than
2.5 implied that the employees were disagreed with the item/statement that the researcher used to rate their
perception; hence the attribute had influence on employee performance to little extent. Means greater than 2.5
and less than 3.5 implied that the employees were not sure with the item/statement that the researcher used to
rate their perception; hence the attribute had influence on employee performance to some extent. Means greater
than 3.5 and less than 4.5 implied that the employees agreed with the item/statement that the researcher used to
rate their perception, hence the attribute would be deemed to have influence on employee performance to a great
extent. Means that are more than 4.5 implied that the employees strongly agreed with the item/statement that the
researcher used to rate their perception hence the activity had influence on employee performance to a very
great extent.
On the other hand, Standard Deviation describes distribution of the respondents’ feedback in relation to
the Mean. It provides an indication of how far the individual responses to each statement deviate from the Mean.
A Standard Deviation of more than 1 shows that there is no consensus on the respondents’ feedback, while a
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standard deviation of greater than 0.5 but less than 1 shows that the responses are moderately distributed. When
the Standard Deviation is less than 0.5, it is an indication that the responses are concentrated around the Mean.
Information of the respondents
Information of the respondents helped the researcher to know the factors that could have influenced the
respondent’s answers, interests and opinions. In addition, it helped the researcher to compare responses and how
they varied between subgroups of the respondents. The researcher concentrated on gender, age, education level,
position respondents held at work, and period respondents had worked in their organization.
Gender diversity
Study findings on gender of the employees of IBM Kenya indicated that close to half (56.3) of the
employees of IBM Kenya who participated in this study were male while 43. 7% were female which indicates
that the gender ratio of the respondents of this study was approximately 1:1; an indication that there was gender
balance in this study thus information obtained was reliable. Based on these findings, it is concluded that there
is gender diversity in IBM Kenya.
Age diversity
The study’s findings on the age bracket of the respondents showed that most (62.5%) of the
respondents were 26-35 years, followed by 20.0% who were 36-45 years, then 18-25 years at 16.3%, and only
one respondent who was 46-55 years at 1.2%. Cumulatively, majority (78.8%) of the respondents were the
youth (18-35 years) while a few (21.2%) were adult (more than 35 years). These findings show that there is age
diversity among employees of IBM Kenya.
Level of education of the respondent
Study findings on the level of education of the respondents shows that most (48.7%) of the employees of
IBM Kenya had a bachelor’s degree, followed by 38.8% who had a Masters’ degree, 2.5% had a PhD, while
very few (1.2%) had only a secondary education. These findings show that there is diversity in educational
background at IBM Kenya.
Position held by employees at IBM Kenya
Respondents were required to indicate the position they held in their organization (IBM Kenya).
Findings presented show that most (27.5%) of the respondents were technicians and this could be attributed to
the fact that IBM is a technology company which requires more technicians in its operations. Following the
technicians are project managers at 18.8%, operational managers at 10.0%, business and data analyst at 8.8%,
marketing and sales managers at 7.5%, ICT managers at 5.0% among others. These findings show that most
participants of this study held different positions hence the findings truly represented all categories of
employees in the technology industry.
Period respondents had worked at IBM Kenya To establish the respondents’ experience with technology companies, respondents were asked to
indicate the number of years they had worked with their organization. Their responses show that slightly more
than half (57.5%) of the respondents had worked at IBM Kenya for a period of 1 – 5 years, 27.5% had worked
for a period of 6 – 10 years, 11% had worked for 11-20 years, while a few (5.0%) had worked with IBM Kenya
for less than a year. The findings show that participants of this study had varied experience within the
technology industry with majority having experience of at least one year. With at least one year experience in
the technology industry, majority of the respondents of this study were probably aware of diversity practices in
the technology industry and its effect on employee performance hence the information they provided was
reliable.
Diversity attributes at the workplace
The first objective of this study was to identify the diversity attributes or practices that exist at IBM
Kenya. There were three types of diversity that the study focused on, namely gender, age, and educational
background diversities.
Gender diversity attributes
The study sought to establish the existence of gender diversity attributes at IBM Kenya. First,
employees of IBM Kenya were asked to indicate whether there is gender diversity in their organization.
Findings were as shown in Table 2.
Table 2: Whether there is gender diversity at IBM Kenya
Whether there is gender diversity at IBM Kenya Frequency Percentage (%)
Yes 72 90.0
No 8 10.0
Total 80 100.0
From the findings in Table 2 above, close to all respondents at 90% agreed that there is gender
diversity at IBM Kenya. This implies that there are various attributes of gender diversity that are being
implemented by IBM Kenya. Therefore, various attributes of gender diversity were listed and respondents were
asked to indicate the extent to which they agreed or disagreed to the attributes. The findings were as shown in
Table 3
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Table 3: Gender diversity attributes at IBM Kenya
Gender diversity attributes N Mean Std. Deviation
There is gender balance among employees of IBM Kenya 80 3.8375 1.08434
During hiring and recruitment of employees, IBM Kenya gives
equal opportunities to both male and female
80 3.9875 0.96119
There is equal opportunities for growth and development for
both male and female employees
80 3.9125 0.99612
Our organization has a career development for both male and
female employees
80 3.9125 1.06965
Our organization’s leadership comprise of both male and female 80 3.9125 1.06965
Our organization’s training and development program is
developed to meet the criteria/requirement of the male and
female gender.
80 3.8625 1.17725
Our organization involves both male and female in decision-
making
80 3.8750 1.14045
From the findings in Table 3, employees of IBM generally agreed (3.5≤ Mean> 4.5) that: there is
gender balance among employees of IBM Kenya, IBM Kenya gives equal opportunities to both male and female
during hiring and recruitment of employees, there is equal opportunities for growth and development for both
male and female employees, IBM Kenya has a career development plan for both male and female employees,
the leadership of IBM Kenya comprise of both male and female, training and development program of IBM
Kenya is developed to meet the criteria/requirement of both genders, and that IBM Kenya involves both male
and female in decision-making.
These findings on gender diversity attributes clearly show that IBM Kenya highly values gender
diversity among its employees. According to Burns and Bush (2016), unlike men, women do not have an upper
hand during hiring. As if not enough, women are also discriminated against when it comes to receiving equal
salaries for equal work and even job promotions. As a matter of fact, most females who replace their male
counterparts always receive lower salaries. In addition to that, other researchers have also shown that gender
discrimination is amongst the most challenging issues at the organizational levels that affects productivity
(Francisco et al., 2005).
Age diversity attributes
First, respondents were asked whether there is age diversity among employee at IBM Kenya. From the
findings in Table 4, majority of the respondents at 88.8% agreed that there is age diversity at IBM Kenya while
11.2% disagreed that there is age diversity.
Table 4: Whether there is age diversity among employees in IBM Kenya
Age diversity among employee of IBM Kenya Frequency Percentage (%)
Yes 71 88.8
No 9 11.2
Total 80 100.0
From the findings in Table 4, it is evident that there is age diversity at IBM Kenya. The researcher
went further to identify the attributes of age diversity that exists at IBM Kenya. Study findings were as shown in
Table 5.
Table 5: Age diversity attributes
Age diversity attributes
N Mean Std.
Deviation
I am positive about age diversity in this workplace 80 3.8375 0.86337
Our organization hire employees without discrimination of their
age
80 3.8750 0.80150
Our organization’s current leadership comprise of people in
different age groups
80 3.6875 0.97557
There is no age biasness in the current employees of IBM
Kenya
80 3.7625 0.98397
Our organization provides equal opportunities for training and
career development despite the age of the employee
80 3.8375 0.87791
My team leaders include members of different age groups in
solving problems and in decision making.
80 3.9125 0.85970
The age differences in work group do not cause conflict 80 3.9000 0.89443
At work, there is good bonding with people of different age
group.
80 3.8250 0.88267
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From the findings in Table 5, employees of IBM Kenya generally agreed (3.5≤ Mean> 4.5) that: they
were positive about age diversity in their workplace, IBM Kenya hire’s employees without discrimination of
their age, current leadership of IBM Kenya comprise of people in different age groups, and there was no age
biasness in the current employees of IBM Kenya. The employee also agreed (3.5≤ Mean> 4.5) that: IBM Kenya
provides equal opportunities for training and career development despite the age of the employee, team leaders
in IBM Kenya include members of different age groups in decision making and solving problems, they also
agreed that the age differences in teams do not cause conflict, and that there is teaming with people of different
age groups in their workplace.
These findings demonstrate that indeed there is age diversity at IBM Kenya. According to Gellner and
Veen (2013), company performance can be improved by complementing values brought by different age groups.
Having employees of the same age group on its own can have a negative effect on productivity.
Attributes of Educational diversity in workplaces Employees of IBM Kenya were asked whether there is educational background diversity among them.
Findings in Table 6, indicate that majority of employees of IBM Kenya at 82.5% agreed that there is educational
background diversity at IBM Kenya while 17.5% denied that there is educational background diversity among
them.
Table 6: Whether there is education background diversity at IBM Kenya
Whether there is education background diversity at IBM
Kenya
Frequency Percentage (%)
Yes 61 82.5
No 14 17.5
Total 80 100.0
With majority of employees of IBM Kenya agreeing that there is educational background diversity
among them, the researcher further asked them to indicate the extent to which they agreed to various attributes
of educational background in workplaces. Their responses were as shown in Table 7.
Table 7: Educational background diversity attributes
Findings shown in Table 7, indicate that employees of IBM generally agreed (3.5≤ Mean> 4.5) that:
the recruitment plan of IBM Kenya is based on the education background of the employees, the leadership
comprise of people with higher academic qualifications, educational qualification of employees correspond to
the position they held at IBM Kenya, and that IBM Kenya rewards specialized education and skills. Further,
employees of IBM generally agreed (3.5≤ Mean> 4.5) that: IBM Kenya provides paid study leave to employees
who go for further studies to enhance their performance, opportunities for educational growth and advancement
exist for employees who have lower qualification in education, that team leaders of IBM Kenya includes all
members at different education level in problem solving and decision making, and that IBM Kenya gives equal
treatment when it comes to the diversity of education background.
These findings imply that indeed there is educational background diversity at IBM Kenya. Gwendolyn,
(2012) found that various organizations did implement education diversity initiatives to get employees to work
effectively together toward achieving organizational goals. Employee’s education background can be a
showcase of one’s knowledge, skills, and capability. Holland (1997) thought that the choice of a specific major
in school may reflect one’s cognitive strength and personality.
Educational background diversity attributes
N Mean Std.
Deviation
The recruitment plan of the organization is based on the education
background of the employees
80 3.7500 0.89301
The organization’s leadership comprise of people with higher academic
qualifications
80 3.6750 0.91090
Educational qualification of employees correspond to the position they hold
at IBM Kenya
80 3.6250 0.97273
Our organization rewards specialized education and skills 80 3.6500 1.09197
The organization provides paid study leave to employees who further their
education that will enhance their performance.
80 3.7125 1.06965
Opportunities for educational growth and advancement exist for employees
who have lower qualification in education.
80 3.7750 1.10207
The team leader includes all members at different education level in
problem solving and decision making.
80 3.5750 1.21983
The organization gives equal treatment when it comes to the diversity of
education background.
80 3.6750 1.06468
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Effect of diversity on employee performance
The purpose or general objective of this study was to establish how diversity in the workplace has
influenced performance of employees in the technology industry with focus on IBM Kenya. Therefore, this
section provides the effect of diversity in workplace on employee performance.
Effect of gender diversity on employee performance
The second objective of this study was to establish the effect of gender diversity on employee
performance in IBM Kenya. To achieve this, six common effects of gender diversity on employee performance
were listed and respondents were asked to indicate the extent to which they agreed or disagreed to the effects.
Their responses were as summarized in Table 8 below.
Table 8: Effect of gender diversity on employee performance
Effect of gender diversity on employee performance N Mean Std.
Deviation
Gender balance among employees of IBM Kenya has motivated me to
remain committed hence improved performance at work
80 3.8000 0.95996
The organization’s policy of giving equal opportunities for growth and
development for both gender has improved my performance over time
80 3.8500 1.00757
Availability of a career development for both gender has improved
performance of employees
80 4.7875 6.40943
Gender balance in leadership of IBM Kenya has motivated employees
hence improving their performance
80 3.9000 1.00127
The organization’s training and development program that meet the
requirement has improved employee performance
80 3.7875 1.00245
Involvement of both male and female in decision-making gives
employees freedom to express themselves hence motivating them to
perform better at work.
80 3.6625 1.04268
From the findings in Table 8, employees of IBM Kenya strongly agreed (Mean score of 4.7875) that
availability of a career development for both gender has improved performance of employees at IBM Kenya.
Further, the employees generally agreed (3.5≤ Mean> 4.5) that: gender balance among employees motivate
them to remain committed at work, organizational policy of giving equal opportunities for growth and
development for both gender improve employee performance over time, gender balance in organizational
leadership improve employee performance through motivation, organizational training and development
program that meet the requirement improve employee performance, and involvement of both gender in
decision-making gives employees freedom to express themselves hence motivating them to perform better at
work. These findings imply that gender diversity at workplace is very influential in enhancing employee
performance hence enhancing organizational growth.
In line with this study’s findings on the effect gender diversity on employee performance;
Organizations typically benchmark against companies that are gender inclusive in employee relations to chart
their success in fostering diverse and gender inclusive work environments (Daniels, 2004). It is also worth
noting that we live in a world where women are constantly stereotyped against certain characteristics like
ability, aggression, and ambitious, which are presumed to be the characteristic that make an employee
successful as they climb the corporate ladder, with most cultures around the globe adhering to that notion.
Because of these assumptions, many organizations obviously prefer to hire men compared to women as they are
perceived to be better performers. The challenge is to first overcome the thought that women are not capable of
performing certain types of work.
Effect of age diversity on employee performance
The third objective of this study was to determine effect of age diversity on employee performance.
Therefore, the researcher sought to achieve this objective by listing five common effects of age diversity on
employee performance and asking respondents to indicate the extent to which they agreed or disagreed to the
age diversity effects. Their responses were as summarized in Table 9 below.
Table 9: Effect of age diversity on employee performance
Effect of age diversity on employee performance
N Mean Std.
Deviation
Having different age groups in senior positions encourage and motivate
employees to perform in their work
80 3.7375 0.85305
Provision of equal opportunities for training and career development all age
groups has improved performance of employees
80 3.8125 0.82820
Involvement of members of different age groups in solving problems and in
decision making has enhanced employee performance
80 3.7375 0.97752
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Lack of employee conflicts due to age differences in work group has improved
employee performance
80 3.7375 1.01562
Good bonding with employees of different age groups has improved my
performance
80 3.7375 1.01562
As shown in Table 9, the employees of IBM Kenya generally agreed (3.5≤ Mean> 4.5) that having
different age groups in senior positions encourage and motivate employees to perform in their work, good
bonding with employees of different age groups improved their performance, and that involvement of members
of different age groups in solving problems and in decision making enhanced employee performance.
Additionally, the employees agreed (Mean score of 3.7375) that lack of employee conflicts due to age
differences in work group improved employee performance. The employees also agreed (Mean score of 3.7375)
that provision of equal opportunities for training and career development of all age groups improved
performance of employees. These findings have demonstrated that age diversity at workplaces in technology
industry plays major role on employee performance.
The effects of age diversity on employee performance are consistent with organizational behaviour.
Research on age-group relations at workplaces shows that conflict is a common outcome when employees of
different age groups encounter each other. By definition, diverse work teams include members who can be
identified as belonging to distinct age groups. When findings from research on age group relations is applied to
understanding dynamics within diverse teams, the natural prediction is that age diversity in work teams leads to
negative outcomes such as disruptive conflict that must be avoided (Turner & Haslam, 2001).
The method adopted for managing a diverse workforce in terms of age can either be detrimental to the
employee performance and productivity or can bring out the full potential in them depending on how effective it
is. Employees who feel more valued work hard while the age group of employees that consider themselves as
minority group feel less valued leading to lower performance. This can be because of stereotyping, and
prejudice within an organization (Goetz, 2001). Therefore, when an organization ignores the existence and
importance of age diversity, conflicts can emerge and neither the corporation nor its employees will realize their
potential. The main undoing of age diversity in the workplace is increase in conflicts. These conflicts arise
largely due to ignorance, prejudice feelings or derogatory comments that cause lack of acceptance. These lead to
negative dynamics such as ethnocentrism, stereotyping, cultural or age clashes with the feeling of being superior
to others. If management ignores such conflicts; the employee performance may suffer (Otike, Messa &
Mwalekwa, 2005).
Age diversity has become an unavoidable fact of life in many organizations (Kunze et al., 2013).
According to the social identity and self-categorization theories; people will classify themselves into age groups
based on characteristics that they identify with and as a result, they will tend to favour these groups at the
expense of other groups different from theirs (Kunze et al., 2013). Gelner and Stephen (2009) both show us that
conflicts can be frequent where there is a generational gap.
Effect of educational background diversity on employee performance
The fourth and last objective of this study was to establish the effect of educational background
diversity in workplaces on employee performance. Nine effects of educational background diversity on
employee performance were designed and respondents were asked to indicate the extent to which they agreed or
disagreed to those effects. Study findings were as shown in Table 10 below.
Table 10: Effect of educational background diversity in the workplace on employee performance
Effect of educational background diversity in the workplace on employee
performance
N Mean Std.
Deviation
Working with employees with different educational levels or background
has improved my performance at work.
80 3.9500 1.04215
Due to educational background diversity at IBM Kenya, employees are
very innovative
80 4.0000 0.96784
I get committed and motivated to complete my tasks because the
organization rewards my educational advancements
80 3.9250 0.96489
Specialized skills and trainings offered by our organization has improved
my performance at work
80 3.9125 0.98333
The organization’s career development guide and rewards on educational
achievements has improved my performance at work
78 3.9103 0.90001
I enjoy and remain committed to my work because the organization
provides equal treatment to its employees despite their educational
background
80 3.8875 1.00623
The organization’s principle of involving all members at different
education level in problem solving and decision making has improved my
performance
80 3.8625 1.07614
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I am confident at my work due to my education background 80 3.9125 1.02121
Table 10 reveals that employees of IBM Kenya generally agreed (3.5≤ Mean> 4.5) that
working with employees with different educational levels or background has improved their performance,
educational background enhance employee performance through innovation and employees get committed and
motivated to complete their tasks because the organization rewards their educational advancements. Also, the
employees agreed (3.5≤ Mean> 4.5) that: they were confident at their work due to their education background,
IBM Kenya’s career development guide and rewards on educational achievements improved employee
performance, and they enjoyed and remained committed to their work because IBM Kenya provides equal
treatment to its employees despite their educational background. Finally, the employees agreed (3.5≤ Mean>
4.5) that IBM Kenya’s principle of involving all members at different education level in problem solving and
decision making improved their performance and specialized skills and trainings offered by IBM Kenya
improved employee performance.
Based on these findings, it is probable to conclude that educational background diversity in workplaces
is very influential on employee performance hence the need to adopt best practices of educational background
workforce diversity. According to Dutton and Duncan (1987), educational background diversity is assumed to
be associated with cognitive diversity, which expands a team’s informational resources and enhances its
problem-solving capacity. Thus, within the context of top management teams, educational background diversity
broadens the range of cognitive perspectives needed to recognize strategic opportunities and consider various
strategic alternatives, which enhances a team’s ability to identify and deal with environmental conditions.
The relationship between educational background diversity and employee performance may be more complex
than has been articulated in the past. However, the current study established that IBM Kenya’s team comprised
of employees with varying academic qualifications across the organization. Based on literature and this study’s
findings, it is logical to conclude that organizations with highly diverse employees in terms of educational
background may have a broader range of perspectives and skills, which may enhance strategic problem-solving
and decision-making capabilities. Consequently, such organizations may experience higher employee
performance hence high growth rate.
Attributes of employee performance
The researcher sought to measure employee performance using various attributes as shown in Table 11
below.
Table 11: Indicators of employee performance
Indicators of employee performance
N Mean Std.
Deviation
I enjoy my tasks and the division’s work approach 80 5.0075 8.09781
I am committed to the mission and direction of my organization 80 3.9000 0.90847
I am comfortable working with IBM Kenya and am proud to be
associated with the organization
80 4.0125 0.92084
I am motivated to complete the task that is assigned to me 80 5.0005 6.33494
I am able to perform in all key areas of my role 80 4.0125 0.90699
I co-operate and work well with my colleagues. 80 3.9500 0.88447
I maintain consistency in my work 80 3.9875 0.83429
I always meet deadlines on tasks assigned to me 80 3.9125 0.91671
I am always responsible for my work 80 3.9625 0.99929
I have good relationship with my leaders and fellow employees
From the findings in Table 11, employees of IBM Kenya who participated in this study strongly agreed
that they enjoyed their tasks and the division’s work approach (Mean score of 5.0075) and they were motivated
to complete the task that was assigned to them (Mean score of 5.0005. This is a clear indication the employees’
performance at IBM Kenya was excellent. In addition, the employees generally agreed (3.5≤ Mean> 4.5) that:
they were committed to the mission and direction of IBM Kenya, they were comfortable working with IBM
Kenya and proud to be associated with the organization, they were able to perform in all key areas of their role,
they co-operated and worked well with each other colleagues, they always met deadlines on tasks assigned to
them, and that they maintained consistency in their work.
These findings on the attributes of employee performance assert that employees in the technology
industry who participated in this study performed well. According to Baldwin (2008), employee performance is
a means of carrying out actions efficiently and effectively by the employees in order to achieve the
predetermined objectives of an organization. Armstrong and Baron (2010) noted that employee performance is
normally looked at in terms of outcomes or employee’s output against the set individual objectives populated
from the company objectives. Additionally, employee performance can be viewed in terms of behavior. It is
how well an employee is fulfilling the requirements of the job and it is determined by a combination of three
main factors namely: efforts, ability and direction.
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According to Bates and Horton (1995), performance is a multi-dimensional contrast, the measurement
of which varies, depending on a variety of factors. They also state that it is important to determine whether the
measurement objective is to assess performance outcome or behavior. A more comprehensive view of
performance is achieved if it is defined as embracing both behavior and outcomes. Brumbrach (1988) argues
that performance means both behavior and results. Behaviors emanate from the performer and transform
performance from abstraction to action. This therefore means that when one is managing performance of teams
and individuals, both input (behavior) and output (results) should be considered.
Inferential Statistics
The researcher used inferential statistics techniques to allow this study to use the population sample to
generalize about the entire population from which the sample was drawn. The study applied the regression
analysis, the Summary Model, Analysis of Variance, and regression correlation coefficient of determination to
determine the predictive power of the influence of diversity attributes on employee performance in technology
industry Kenya using IBM Kenya as a case study.
Regression aanalyses
Using the statistical package for social sciences (SPSS) version 23.0, the researcher used multiple
regression analysis to test relationship between diversity at IBM Kenya (gender diversity, age diversity, and
education background diversity) which were the independent variables and employee performance in IBM
Kenya which was the dependent variable. The regression analysis coefficients were used in the determination of
the relationship between the dependent variable (employee performance in IBM Kenya) and the independent
variables (gender diversity, age diversity, and background education diversity). The coefficients explain the
extent to which changes in the dependent variable can be explained by the change in the independent variables
or the percentage of variation in the dependent variable that is explained by all the three independent variables.
IV. MODEL SUMMARY Table 12 shows the Model Summary of the regression analysis that was conducted.
Table12: Model Summary of the regression analysis
Model R R
Square
Adjusted
R Square
Std. Error
of the
Estimate
Change Statistics
R Square
Change
F
Change
df1 df2 Sig. F
Change
1 .899a .808 .091 .46603 .008 0.829 79 1 .007
From Table 12 above, findings indicate the three independent variables (gender diversity, age diversity,
and education background diversity) that were studied explain only 80.8% on the effect on employee
performance in IBM Kenya as represented by the R Square (R2). This therefore means that other factors not
studied in this research contribute 19.2% of the influence on employee performance. Therefore, further research
should be conducted to investigate the other factors (19.2%) that influence performance of employees in the
technology industry in Kenya.
ANOVA Results
Table 13 is a summary of the ANOVA statistics obtained from the mean of variables within workforce
diversity that influence employee performance in the technology industry in Kenya. ANOVA cross tabulated
results were obtained based on the consideration of average values of respondents’ views and opinions on the
influence of workforce diversity on employee performance. Estimates were made based on the respondents’
perception on the influence of gender diversity, age diversity, and background education diversity on employee
performance.
Table 13: ANOVA of the Regression
ANOVAb
Model Sum of Squares Df Mean Square F Sig.
Regression 3.517 79 0.330 1.029 .007a
Residual 1.043 1 0.320
Total 4.550 35 b. Predictors: (Constant): gender diversity, age diversity, and background education diversity
a. Dependent variable: employee performance in technology industry in Kenya
The significance value obtained in the regression model is used to measure whether the relationship
between the independent variables and the dependent variable is statistically significant. From the table above,
the significance value (p) for the relationship between the workforce diversity adopted by technology industry in
Kenya and employee performance is 0.007. Since the significance value (p) for this relationship is less than the
statistically acceptable significant value of 0.05 i.e. p ≤ 0.05, it is then concluded that the relationship between
the workforce diversity adopted by the technology industry in Kenya and employee performance is statistically
significant in predicting how diversity influence’s performance of employees. The F critical at 5% level of
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significance was 0.320. Since F calculated is greater than the F critical (value = 1.029), this shows that the
overall model was significant.
Coefficient of Correlation
The researcher conducted multiple correlation analysis to determine the relationship between
workforce diversity and employee performance in technology industry in Kenya. The tested variables included:
gender diversity, age diversity, and background education diversity. The results were as presented Table 14
below.
Table 14: Coefficient of correlation compensation strategies-employee performance
Model Un-standardized Coefficients Standardized
Coefficients
t statistics Sig.
Level
B Std. Error Beta
(Constant) 1.767 0.489 3.615 .007
1 Gender diversity attributes in
workplace
0.128 .139 .190 .916 .006
2 Age diversity attributes in
workplace
0.143 .100 .211 1.434 .011
3 Educational background
attributes in workplace
0.253 .105 .310 2.396 .006
Dependent variable: Employee performance in technology industry in Kenya
As per the SPSS generated table above, regression equation
Y = β0 + β1x1 + β2x2 + β3x3+ β4x4+ ε
Where: Y is the employee performance as result of workforce diversity adopted by technology industry
in Kenya.
B0 is a constant
β1 to β4 are the coefficient of the independent variables
x1 to x4 are the independent variables where
ε is the error term.
Therefore,
(Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + ε) becomes:
(Y= 1.767+ 0.128X1+ 0.143X2+ 0.253X3) + ε
From the established equation, it implies that if workforce diversity in the technology industry in
Kenya (gender diversity, age diversity, and educational background diversity) is considered and kept constant at
zero, employee performance in the technology industry in Kenya will be effective at 1.767. However, the data
findings analyzed indicate that taking all other independent variables (workforce diversity) at zero: a unit
increase in gender diversity attributes in workplace will lead to a 0.128 effectiveness in performance of
employees in the technology industry in Kenya; a unit increase in age diversity attributes in workplaces will
lead to a 0.143 effectiveness in performance of employees in the technology industry in Kenya; while a unit
increase in educational background diversity attributes in the workplace will lead to a 0.253 effectiveness in
performance of employees in the technology industry in Kenya. From these findings, it can be concluded that,
diversity adopted by the technology industry in Kenya has great influence on performance of employees.
At 5% level of significance and 95% level of confidence, the relationships between workforce diversity (gender
diversity, age diversity, and educational background diversity) adopted by the technology industry and the
employee performance were all significant. This is because the statistical significant value (p) of each diversity
type was less than 0.05 implying that the relationship of each diversity type with employee performance was
statistically significant.
V. CONCLUSION In today’s competitive environment in the corporate world, employees’ performance continues to make
a significance impact on the success or failure of any organization with regards to achieving organizational
goals and objectives. This means that an organization must get the employees’ priorities right to continue to
remain relevant in today’s competitive corporate environment. Among the priorities of the employees is the
organizations’ workforce diversity practice. Workforce diversity practices motivate employees leading to
enhanced performance. As a result, organizations gain a competitive advantage in the market place due to
improved employee performance that provide a platform for growth in terms of market share and profitability.
In this regard, study findings show; that gender balance among employees motivates them to remain committed
at work, organizational policies that provide equal opportunities for growth and development for both gender
improve employee performance over time have ascertained that workforce diversity has a great influence on
employee performance, that having different age groups in senior positions encourage and motivate employees
to perform in their work, and that involvement of members of different age groups in solving problems and in
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decision making enhanced employee performance, and that involving all members at different education levels
in problem solving and decision making improves their performance. The study findings revealed that providing
equal opportunities of growth and development without discrimination based on gender, age, or educational
background is very important in influencing employee performance in the technology industry. Therefore, it is
reasonable to conclude that workforce diversity practiced by technology companies highly influence’s
performance of employees leading to overall organizational performance. This could be the factor that
contributes to growth and dominance of IBM Kenya in the technology industry not only in Kenya but
internationally.
Recommendations
Based on the study’s findings, the following are the recommendations of this study:
The government in collaboration with other stakeholders in the technology industry should ensure that
there are effective policy guidelines on workforce diversity to enhance employee performance. This
will lead to improved organizational performance hence improved economic growth.
All technology companies should adopt best practices of workforce diversity to enhance employee
performance thus leading to improved organizational performance. The best practices of workforce
diversity should correspond to employers’ priorities for better performance.
Areas for further research
The study recommends a further research to be conducted to compare the influence of workforce
diversity and other factors that influence employee performance like good set of skills, productive work
environment, leadership style, organizational culture, trainings, motivation, renumerations among others. This
will provide a basis to conclude that workforce diversity in the technology industry influence’s employee
performance more or less than other factors.
A further study should be conducted on the workforce diversity in public technology companies and its
effect on employee performance. This due to the fact this study concentrated on a private technology
organization, i.e. IBM Kenya.
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About the Authors
Anne Onsarigo is a Master Degree Student of Catholic University of Eastern Africa Kenya, She holds
Bachelor's degree from Spicer Memorial College, India. Majoring in Computer Science. She is a HR
Practitioner.
Dr. Thomas Katua Ngui is a Senior Lecturer at The Management University of Africa, Kenya. He
previously served as Head of Department of Marketing and Management and also as Director Graduate
Business School at The Catholic University of Eastern Africa for the last 8 years. Dr. Ngui has published widely
in the areas of Human Resources Management, Entrepreneurship, Strategic Management and Corporate
Governance. He is also a Certified Management Consultant, Full Member of the Institute of Human resources
management (Kenya) and Full Member of The Kenya Institute of Management. Dr. Ngui is also a Member and
Chairman of the Finance and General Purpose Committee of the Board of Directors of Machakos Water and
Sewerage Company Ltd.
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