Investigating Diversity's Impact on Kings College Hospital Performance

This report presents the results of a study investigating the impact of diversity on organizational performance, using Kings College Hospital as a case study. The research employed both quantitative and qualitative data collection methods, including questionnaires for 100 respondents and open-ended interviews with 10 line managers. The report details descriptive statistics of demographic variables, including age, education, and work experience, illustrating the diversity within the workforce. Key findings reveal employees' perceptions on the impact of educational background on confidence, the positive influence of a diverse workforce on innovation, and the significance of training in fostering awareness about diversity. Inferential analyses, including correlation and regression, were conducted to determine relationships between variables, revealing a positive correlation between organizational performance and diversity. The regression analysis indicated that independent variables explained 95% of the variation in the dependent variable (organizational performance). The report provides valuable insights into the dynamics of diversity within the hospital setting and its influence on various organizational aspects.

Chapter 4: Results and discussions
This main of this research is to find the impact of the diversity on performance of the
organization taking the case of the Kings College Hospital). To examine the same both
qualitative and quantitative data has been collected. Quantitative data was collected among 100
respondents using the close ended questionnaire, whereas for the qualitative analysis data has
was collected from 10 line managers using the open ended questionnaire. Results from the data
analysis have been presented in this chapter. In the first section the results from the quantitative
analysis has been presented. In the second section results from the qualitative analysis has been
shown.
Results from quantitative analysis
Descriptive statistics
Results from the descriptive analysis are shown in table below for the demographic variables.
The descriptive analysis provides the overview of the data and it also helps the researcher to find
whether the sample selected from the population is appropriate for the analysis or not(IMF 2016;
Hubbard 2012).
Statistics
Age Education Work experience
N Valid 100 100 100
Missing 0 0 0
Mean 2.70 2.10 2.60
Minimum 1 1 1
Maximum 4 4 4
Percentiles 25 2.00 1.00 2.00
50 3.00 2.00 2.50
75 3.00 3.00 3.75
Table 1 Descriptive statistic of demographic variables
As shown in the table above the sample size for this study is 100 and there are no missing values
in the data set. Similarly the results for mean and maximum & minimum values are also shown
in the table above. However mean, median, maximum and minimum values are appropriate for
continuous variable. Since the variables in this case are categorical no useful information can be
extracted from these values(Beridze 2016).

20-29 30-39 40-49 above 50
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
50.0
Age
Age
Figure 1 Age of the respondents included in the sample
The bar graph for age is shown in the figure above and the results shows that most of
respondents were in the age group of 40 to 49 years followed by respondents in the age group
30-39. This indicates that most of the employees are in their mid age and the proportion of the
young employees is less. However on the other hand there are employees from all age group
which shows that there is diversity in the workforce in terms of age.
college Diploma Degree master/phd
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Education
Education
Figure 2 Education level of the employees in the data set
In terms of educational qualification most of the employees holds diploma degree. Results also
show that proportion of employees having educational level of college and degree is same. The
proportion of respondents with master/phd degree is very less.

2-5 years 6-10 years 10-15 years above 15 years
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Work experience
Work experience
Figure 3 Work experience of the respondents included in the data set
The next demographic variable included in the current study is work experience and the results
shows that around 35 % of the respondents have work experience of 6 to 10 years. Similarly
proportion of employees having 10 to 15 years of work experience and having more than 15
years of experience is 25 % each. The proportion of employees of having 2-5 years of work
experience is the lowest (15 %).
Objective variables
In this section the results for the objectives variable are discussed and the results from this
section have been used to test the hypothesis proposed in the beginning of the research paper.

Strongly agree Agree Neutral Disagree Strongly Disagree
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
lack of confidence due to my educational
background
lack of confidence due to my educational background
Figure 4 Response from the sample about the confidence and educational background
When asked whether the employees experience lack of confidence because of educational
background most 30 % of the employees agree that their educational background affect their
confidence level. Whereas 30 % of the employees strongly disagree on the fact that confidence
level is affected by the educational a background. The percentages of the employees which are
neutral are only 10 %. Respondents who said that the educational background do not effect
confidence level can be from the higher educational background or the work environment may
be good so that the employees do not experience such feelings(Simons & Rowland 2011).
Strongly agree Agree
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
hospital diverse workforce helps in
increased innovation
hospital diverse workforce helps in increased innovation
Figure 5 Response when asked about hospital diverse workforce in increased innovation

Furthermore the respondents were asked whether the diverse workforce helps in increasing
innovation in the workplace all them agreed. In other words all the employees thinks that diverse
workforce helps to increase innovation as the ideas from different group are different and more
creative ideas are developed with people from diverse background as compared to the employees
from the same background.
Strongly agree Agree Neutral Disagree Strongly
Disagree
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
organization is defined by the diverse
workforce
organization is defined by the diverse workforce
Figure 6 Response related to diversity in the workforce
Similarly when asked whether the structure of the organization is defined by diverse workforce,
40 % of the employees agree and 20 % strongly agree that structure of organization is defined by
diverse workforce. On the other and 10 % of the employees disagree and % strongly disagrees
on the same. However majority of the employees agree so it can be concluded that the diverse
workforce is used do define the structure of the organization.

Strongly agree Agree Neutral
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
50.0
Training that are undertaken by
staffs helps in diversity awareness
training that are undertaken by staffs helps in diversity awareness
Figure 7 Responses related to the training for staff and diversity
During the primary survey one of the questions asked was whether the training undertaken by the
employees in the organization helps in the awareness about diversity. As shown in the figure
above more than 40 % of the employees agree that training helps in improving awareness about
diversity and 40 % of the employees strongly agree. Remaining employees were neutral. It also
shows that none of the employees disagree with the given statement(Bed et al. 2014).
Strongly agree Agree Neutral
0.0
10.0
20.0
30.0
40.0
50.0
60.0
Younger employees benefit from
shared experience
Younger employees benefit from shared experience
Figure 8 Response for benefit for younger employees

Similarly the response for from the employees about the younger employees benefit from shared
experience or not, is shown in the figure above. Results show that around 80 % of the employees
agreed that the younger employees benefits while working with the experienced one as it helps
the younger employee to learn about the work and organization more. None of the employees
disagree with the fact.
Strongly agree Agree Neutral Disagree Strongly
Disagree
0.0
10.0
20.0
30.0
40.0
50.0
60.0
It is very difficult to communicate
with diverse colleagues
It is very difficult to communicate with diverse colleagues
Figure 9 Responses for communication in diverse workforce
When asked whether it is difficult to communication if there are diverse colleagues in the
organization, half of the respondents disagree and 10 % strongly disagree. This shows that
communication is not the problem in organization with diverse colleagues. Only around 30 % of
the employees argued that communication is difficult in diverse workforce.

Strongly agree Agree
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
hospital provides one of the best
frontline services
hospital provides one of the best frontline services
Figure 10 Response for hospital performance
Another question in the questionnaire was related to the performance of the frontline services in
South East London. As the results show in the above figure none of the respondents disagree
which shows that the services provided by the hospital provides quality services. Among the
respondents who agree 60 % strongly agree to the given statement. One of the main reason
behind such results may be because all the respondents are from the same organization so they
do not want to come up against the own organization. Also the quality of the frontline service
may be good which the reason behind such results is.
Strongly agree Agree Neutral Disagree
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
Younger employee assist older
employees on technological changes
Younger employee assist older employees on technological changes
Figure 11 Response for younger employees helping the older for technological changes

Above figure shows the response of the employees when asked whether the older employees
assist the older employees on technological changes. Results show that 40 % of the employees
think that the younger employees do not help the older employees whereas 30 % agree with the
given statement. This shows that the relationship between the older and younger employees in
the organization cannot be defined as good or bad. In some cases the younger ones are helping
the older one whereas in some cased they are not helping(Soni & Ashish 2016; Govitvatana
2001).
9-13 14-18 19-23 24-28
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
Nominal age of young patients
Nominal age of young patients
Figure 12 Nominal age of the young patients in the hospital
Results for the nominal age of the young patients in the hospital show that most of the patients
are in the age group of 24 to 28 years. This is followed by the patients in the age group of 14-18
years. Patients in the age group of 19-23 are 15 %, which is lowest among all the age group.
50-55 55-60 61-65 66-70
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
Mnimum age of old patients
Mnimum age of old
patients

Figure 13 Minimum age of the old patients in the hospitals
Lastly the minimum age of the old patients in the hospital is shown in the figure above . Results
show that most of the patients are in the age group of 66-70 years followed by the patients in 50-
55 years.
Inferential analysis
In the previous section the descriptive results for the variables included in the study has been
shown and this section will be used to discuss the results from the inferential analysis. The
inferential analysis has been performed using correlation and regression.
Reliability Analysis
Reliability Statistics
Cronbach's Alpha N of Items
.939 7
Table 2 Reliability analysis
Since the value of alpha is higher than the minimum required of 0.6 so the variables are reliable ,
so further analysis can be conducted.
Correlation
Correlation analysis is performed to find the relationship between the variables in the study. The
value for correlation between two variables ranges from -1 to +1. The correlation of -1 indicates
that the perfect negative relationship exists between the variables. On the other hand, correlation
value of +1 show that there exist perfect positive relationship(Mukaka 2012).
In this case the correlation between the organization performance and the diversity in the
organization is shown in the table below:
Correlations
increase
d
innovati
on_2
diverse_w
rkfc_3
diverse_aw
rnes_4`
shared_e
xp_5
diverse_coll
eague_6
young_old_
assist_8
increased
innovation_2
Pearso
n
Correl
ation
1 .699** .877** .758** .892** .861**

Sig.
(2-
tailed)
.000 .000 .000 .000 .000
N 100 100 100 100 100 100
diverse_wrkf
c_3
Pearso
n
Correl
ation
.699** 1 .855** .847** .838** .858**
Sig.
(2-
tailed)
.000 .000 .000 .000 .000
N 100 100 100 100 100 100
diverse_awr
nes_4`
Pearso
n
Correl
ation
.877** .855** 1 .870** .864** .839**
Sig.
(2-
tailed)
.000 .000 .000 .000 .000
N 100 100 100 100 100 100
shared_exp_
5
Pearso
n
Correl
ation
.758** .847** .870** 1 .883** .848**
Sig.
(2-
tailed)
.000 .000 .000 .000 .000
N 100 100 100 100 100 100
diverse_colle
ague_6
Pearso
n
Correl
ation
.892** .838** .864** .883** 1 .871**
Sig.
(2-
tailed)
.000 .000 .000 .000 .000
N 100 100 100 100 100 100
young_old_a
ssist_8
Pearso
n
Correl
ation
.861** .858** .839** .848** .871** 1

Sig.
(2-
tailed)
.000 .000 .000 .000 .000
N 100 100 100 100 100 100
**. Correlation is significant at the 0.01 level (2-tailed).
Table 3 Results from the correlation analysis
Correlations
increased
innovation_2
Age Edu_backgrn
d_1
increased
innovation_2
Pearson
Correlation
1 .813** .834**
Sig. (2-tailed) .000 .000
N 100 100 100
Age
Pearson
Correlation
.813** 1 .874**
Sig. (2-tailed) .000 .000
N 100 100 100
Edu_backgrnd_1
Pearson
Correlation
.834** .874** 1
Sig. (2-tailed) .000 .000
N 100 100 100
**. Correlation is significant at the 0.01 level (2-tailed).
Table 4 Correlation results for demographic variable and organizational performance
Results show that most of the correlation coefficients are positive and also statistically
significant. This suggests that the organizational performance and the diversity are positively
correlated, so if diversity in the workplace increases the performance of the organization also
improves. Since the correlation results are significant further analysis can be conducted.
Regression
Regression analysis is conducted to find the impact of the independent variables on the
dependent variables. In this case the dependent variable is the organizational performance which
is measure by the increase in innovation in the organization with increase in diversity in the work
force. Similarly the independent variables include all the factors related to diversity in the study.
Results from the regression analysis are shown in the table below:

Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .976a .952 .949 .111 2.124
a. Predictors: (Constant), young_old_assist_8, diverse_awrnes_4`,
diverse_wrkfc_3, shared_exp_5, diverse_colleague_6
b. Dependent Variable: increased innovation_2
Table 5 Model summary of the regression analysis
Results from the model summary show that the R square is 0.95 which suggests that the
independent variables included in the current research are able to explain 95 % of the variation in
the dependent variable. Remaining variation is explained by some other factors which are not
included in the study. Similarly the results from Durbin-Watson show that the value is close to 2
which indicates that there is no problem of autocorrelation among the variables.
ANOVAa
Model Sum of
Squares
df Mean
Square
F Sig.
1
Regression 22.843 5 4.569 371.124 .000b
Residual 1.157 94 .012
Total 24.000 99
a. Dependent Variable: increased innovation_2
b. Predictors: (Constant), young_old_assist_8, diverse_awrnes_4`,
diverse_wrkfc_3, shared_exp_5, diverse_colleague_6
Table 6 ANOVA results for the regression analysis
Similarly the ANOVA table shows that the F statistic is 371.124 with p value of 0.00. This
shows that the cumulative impact of the independent variable on the dependent variable is
significant (as the p value is less than 0.05).
Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig. Collinearity
Statistics
B Std.
Error
Beta Tolerance VIF
1 (Constant) .619 .033 18.603 .000
diverse_wrkfc_3 -.270 .025 -.553 -
10.647
.000 .190 5.264

diverse_awrnes_4` .484 .038 .690 12.739 .000 .175 5.727
shared_exp_5 -.271 .040 -.387 -6.841 .000 .161 6.226
diverse_colleague_6 .241 .021 .652 11.263 .000 .153 6.526
young_old_assist_8 .197 .021 .516 9.629 .000 .178 5.602
a. Dependent Variable: increased innovation_2
Table 7 Results for the regression coefficients
Results from the regression coefficients show that the diverse workforce shows negative and
significant impact on the organizational performance. In other words increase in the diverse
workforce which is used to define the structure of the organization, the performance of the
organization declines. However the coefficient of diverse colleagues show positive coefficient
which indicates that increase in the diverse workforce increases the organizational performance.
All other coefficients can also be interpreted in similar way.
Qualitative analysis
After the quantitative analysis, in this section the results from the qualitative analysis have been
shown. Data for the qualitative analysis was collected from 10 line managers using the open
ended questionnaire.
Results from the qualitative analysis show that most of the managers think that technology is an
important tool which helps in engaging and promoting diversity in the organization. One of the
manager said that technology helps in the communication process and make is more effective.
While explaining the importance of technology in diversity one of the managers said,
“Technology plays an important role in terms of equality as the trust offer letters and leaflets in
different languages, bearing in mind of the patient and staff population we serve. It ensures
efficiency in communicating, such as translation service, hard of hearing and blind.”
Similarly when the managers were asked whether there are self-development activities
undertaken by the staff related to the diversity awareness, most of the managers said that their
organization follow various strategies to inform employees about the diversity in the workplace
and managers said they use the BAME network for same. (quote). According to one of the
managers “communication e.g. e-mails takes less response time, communicating through our
websites on BAME committee where employees join in the forum. It plays a vital role in
communicating within and with our patients. It’s a good opportunity to train quickly online as
classroom training seems to be outdated.”
All the managers in the Kings College of Hospital said that their organization promote and
implement diversity in the workplace. One of the manager said “It’s one of our core values as an
organization, in accordance with our national obligations; the organization adheres to the
equality guidance such as positive around disability interviews and around equality and

diversity”. This shows that the organization also takes diversity seriously and they are taking
steps to ensure that diversity in the organization do not affect the organizational productivity.
Another question in the questionnaire was related to HR policies and its assistance in dealing
with problems related to diversity in the workforce. Responding to this question, all the manager
said that the HR policies assist in dealing in diversity in the workforce.
When asked about the impact of the educational background on the employee’s performance,
most of the managers argued that higher educational degree helps the employee to learn new
skill and techniques in the workplace, so performance increase with higher educational degree.
One manager argued that “Definitely, as a PHD degree holder, I think educational background
does prepare employees to gain the academic skills needed, that is translated in their career for
organizations success.”
Another important question included in the interview was the impact of age diversity on
improving the employee’s performance and the major challenges. Many managers argued that
the age in the diversity positively affect the employee’s performance. With people from different
age and different work experience, the younger employees can learn from the older employees
whereas the older employees can also learn about new techniques and tools from the younger
employees. Furthermore when asked about the most effective way for managing a diverse
workforce, most of the managers said that the training and awareness are some of the most
effective way. One of the mangers said that, “Awareness programs, clear information, cultural
training. To take an informal approach, team building exercise, adult education learning.”
Hypothesis testing
Hypothesis 1:
Null hypothesis: Diverse colleagues and the organizational performance are not significantly
related.
Alternative hypothesis: Diverse colleagues and the organizational performance are significantly
related.
As the results from the regression results shows that the coefficient is statistically significant so
the null hypothesis can be rejected and the alternative hypothesis can be accepted.
Hypothesis 2:
Null hypothesis: There is no significant relationship between awareness about the diversity in the
workplace and organizational performance.

Alternative hypothesis: There is no significant relationship between awareness about the
diversity in the workplace and organizational performance.
Results from the regression analysis shows that the coefficient of awareness is statistically
significant, so the null hypothesis can be rejected and the alternative hypothesis can be accepted.
Hypothesis 3:
Null hypothesis: There is a no relationship between age diversity and employees performance.
Alternative hypothesis: There is a no relationship between age diversity and employees
performance.
Results from the qualitative analysis shows that age in the diversity has positive impact on the
employees’ performance, so it can be concluded that age diversity and employees performance
are related. So the alternative hypothesis can be accepted.
Hypothesis 4:
Null hypothesis: There is a no relationship between age diversity and organizational
performance.
Alternative hypothesis: There is a relationship between age diversity and organizational
performance.
Since the correlation between age and organizational performance is statistically significant the
null hypothesis can be rejected in favor of the alternative hypothesis.
Hypothesis 5:
Null hypothesis: There is a no relationship between education background and organizational
performance.

Alternative hypothesis: There is relationship between educational background and organizational
performance.
As the results from the correlation analysis show that educational background and organizational
performance are significantly related, the null hypothesis can be rejected and the alternative
hypothesis can be accepted.
References
Bed, P. et al., 2014. Workforce Diversity Management: Biggest Challenge Or Opportunity
For 21st Century Organizations. IOSR Journal of Business and Management, 16(4),
pp.102–107.
Beridze, T., 2016. Boardroom Gender Diversity and Firm Financial Performance:
Evidence from the Banking Sector in Georgia. University of Porto.
Govitvatana, W.V., 2001. GENERATION GAP IN THE WORKPLACE BETWEEN BABY
BOOMERS AND GENERATION X. University of Wisconsin-Stout.
Hubbard, E., 2012. The Diversity Scorecard, Amsterdam: Routledge.
IMF, 2016. Gender Diversity in Senior Positions and Firm Performance: Evidence from
Europe, Washington D.C.
Mukaka, M.M., 2012. Statistics corner: A guide to appropriate use of correlation coefficient
in medical research. Malawi medical journal : the journal of Medical Association of
Malawi, 24(3), pp.69–71.
Simons, S.M. & Rowland, K.N., 2011. Diversity and its Impact on Organizational
Performance: The Influence of Diversity Constructions on Expectations and Outcomes.
Journal of Technology Management & Innovation, 6(3).
Soni, H. & Ashish, A., 2016. Understanding Generation Gap at Work Place. Journal of
Business and Management (IOSR-JBM), 18(8), pp.56–58.

Appendix
Collinearity Diagnosticsa
Mo
del
Dime
nsion
Eigen
value
Cond
ition
Index
Variance Proportions
(Cons
tant)
diverse_w
rkfc_3
diverse_aw
rnes_4`
shared_
exp_5
diverse_coll
eague_6
young_old_
assist_8
1
1 5.794 1.000 .00 .00 .00 .00 .00 .00
2 .121 6.916 .72 .01 .00 .00 .00 .04
3 .027 14.68
1
.21 .02 .24 .05 .00 .77
4 .025 15.12
8
.01 .74 .00 .05 .26 .00
5 .018 18.14
2
.01 .19 .72 .08 .26 .16
6 .015 19.90
1
.04 .03 .04 .83 .48 .03
a. Dependent Variable: increased innovation_2
Correlations
increased
innovation_2
Age Edu_backgrn
d_1

increased
innovation_2
Pearson
Correlation
1 .813** .834**
Sig. (2-tailed) .000 .000
N 100 100 100
Age
Pearson
Correlation
.813** 1 .874**
Sig. (2-tailed) .000 .000
N 100 100 100
Edu_backgrnd_1
Pearson
Correlation
.834** .874** 1
Sig. (2-tailed) .000 .000
N 100 100 100
**. Correlation is significant at the 0.01 level (2-tailed).
diverse_wrkfc_3
Frequency Percent Valid
Percent
Cumulative
Percent
Valid
Strongly agree 20 20.0 20.0 20.0
Agree 40 40.0 40.0 60.0
Neutral 27 27.0 27.0 87.0
Disagree 10 10.0 10.0 97.0
Strongly
Disagree
3 3.0 3.0 100.0
Total 100 100.0 100.0
shared_exp_5
Frequency Percent Valid
Percent
Cumulative
Percent
Valid
Strongly
agree
30 30.0 30.0 30.0
Agree 50 50.0 50.0 80.0
Neutral 20 20.0 20.0 100.0
Total 100 100.0 100.0

diverse_colleague_6
Frequency Percent Valid
Percent
Cumulative
Percent
Valid
Strongly agree 20 20.0 20.0 20.0
Agree 10 10.0 10.0 30.0
Neutral 10 10.0 10.0 40.0
Disagree 50 50.0 50.0 90.0
Strongly
Disagree
10 10.0 10.0 100.0
Total 100 100.0 100.0
diverse_awrnes_4`
Frequency Percent Valid
Percent
Cumulative
Percent
Valid
Strongly
agree
40 40.0 40.0 40.0
Agree 45 45.0 45.0 85.0
Neutral 15 15.0 15.0 100.0
Total 100 100.0 100.0
frnt_service_7
Frequency Percent Valid
Percent
Cumulative
Percent
Valid
Strongly
agree
60 60.0 60.0 60.0
Agree 40 40.0 40.0 100.0
Total 100 100.0 100.0
young_old_assist_8
Frequency Percent Valid
Percent
Cumulative
Percent
Valid Strongly
agree
30 30.0 30.0 30.0

Agree 20 20.0 20.0 50.0
Neutral 10 10.0 10.0 60.0
Disagree 40 40.0 40.0 100.0
Total 100 100.0 100.0
nominal age
Frequency Percent Valid
Percent
Cumulative
Percent
Valid
9-13 23 23.0 23.0 23.0
14-18 30 30.0 30.0 53.0
19-23 16 16.0 16.0 69.0
24-28 31 31.0 31.0 100.0
Total 100 100.0 100.0
minimum age_old
Frequency Percent Valid
Percent
Cumulative
Percent
Valid
50-55 27 27.0 27.0 27.0
55-60 26 26.0 26.0 53.0
61-65 14 14.0 14.0 67.0
66-70 33 33.0 33.0 100.0
Total 100 100.0 100.0