AGE DIVERSITY OF THE WORKFORCE AND
EMPLOYEES' PERFORMANCE -A DESCRIPTIVE
STUDY

K L Gowrishankar, N Kanagaraj, S Gokula Krishnan

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K L Gowrishankar, N Kanagaraj, S Gokula Krishnan. AGE DIVERSITY OF THE WORKFORCE AND EMPLOYEES' PERFORMANCE -A DESCRIPTIVE STUDY. International Journal of Marketing & Financial Management, 2017, 5 (10), pp.1-11. hal-04850319

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**Cite this paper as:** K.L. Gowrishankar, (First Author) - Dr. N. Kanagaraj(Co-Author) & Dr. S. Gokula Krishnan (Co-Author) (2017) "AGE DIVERSITY OF THE WORKFORCE AND EMPLOYEES' PERFORMANCE - A DESCRIPTIVE STUDY" _ International Journal of Marketing & Financial Management, ISSN: 2348 - 3954 (online) ISSN: 2349 - 2546 (print), Volume 5,(Issue 10, Oct -2017), pp 01-11

# AGE DIVERSITY OF THE WORKFORCE AND EMPLOYEES' PERFORMANCE - A DESCRIPTIVE STUDY

K.L. Gowrishankar, (First Author)

Research Scholar, Bharathiyar University,
Coimbatore, Asst. Professor, Faculty of
Management, RVS Technical Campus-
Coimbatore. Tamilnadu. India

Dr. N. Kanagaraj(Co-Author)

Asst. Professor,
RVS Institute of Management Studies and
Research, Coimbatore. Tamilnadu. India

Dr. S. Gokula Krishnan (Co-Author)

Associate Professor,
School of Management, Nehru College of Engineering and Research Centre, Pampady,
Thiruvilwamala, Thrissur- 680 588. Kerala. India

**Abstract:**

**Purpose:** The prime objective of the study is to examine the relationship between age diversity of the workforce and employees' performance.

**Design/Research Methodology:** Descriptive studysurveyed 120 respondents through convenience sampling technique and has been tested with Kaiser-Meyer-Olkin Test's sampling adequacy (0.769) and Bartlett's sphericity test (p = 0.000). Descriptive and Inferential Analysis (Analysis of Variance– One Way, Correlation analysis and Regression Analysis) were deployed.

**Findings:** This study has found that Age Diversity of the workforce has a significant contribution to predict the employees' performance. Further, this study has revealed that Age Diversity of the workforce and employee performance differs across gender, age group, work experience and position of the employees.

**Managerial Implications:** When an organization ensuring the uniqueness among the age diversity of the workforce, they can achieve the reduced conflicts, high utilization of the human at work, can ensure the person-organization fit, person-job fit and person-group fit which will improve the performance of the employees in an organization

**Scope for future work / Limitations:** This contribution mainly focused to measure the relationship between the age diversity of the workforce and employees' performance, and it has not studied any other diversities of the workforce like gender diversity, educational diversity and ethnicity. Further this contribution surveyed 120 respondents in the food processing industry, hence the result may or may not be applicable to the other industries.

**Key Words:** Work Force, Age Diversity, Employee Performance, ANOVA and Correlation.
# Type of Manuscript: A Research Paper

## 1. Introduction

Workforce diversity is a multi-faceted concept that will continue to evolve more industries move toward a global marketplace. It also has proven to have led to a perception of being fundamental for employee performance. In current scenario, employing diversified workforce is a necessity for every organization but to manage such diversified workforce is also a big challenge for management. Workforce diversity is strength for the organization if managed properly, can increase the productivity and thus performance of the organization.

Workforce diversity refers to organizations that are becoming more heterogeneous with the mix of people in terms of gender, age, race, and education background (Robbins, 2009). Frequently, diversity is viewed in a limited fashion, primarily addressing issues of race or gender differences, and linked to the laws providing protected status to certain groups. We have used a very broad definition of diversity, to encompass most characteristics that individuals possess that affect the way they think and do things.

Diversity can be defined as acknowledging, understanding, accepting, and valuing differences among people with respect to age, class, race, ethnicity, gender, disabilities, etc. (Esty et al. 1995). Companies need to embrace diversity and look for ways to become inclusive organizations because diversity has the potential to yield greater work productivity and competitive advantages (SHRM 1995). Managing diversity is a key component of effective people management in the workplace (Black Enterprise 2001).

Demographic changes (women in the workplace, organizational restructuring, and equal opportunity legislation) will require organizations to review their management practices and develop new and creative approaches to managing people. Positive changes will increase work performance and customer service.

The number of dual-income families and single working mothers has changed the dynamics of the workplace. Changes in the family structure means that there are fewer traditional family roles (Zweigenhaft and Domhoff 1998). Significant changes in the workplace have occurred due to downsizing and outsourcing, which has greatly affected human resource management. Globalization and new technologies have changed workplace practices, and there has been a trend toward longer working hours (Losyk 1996). Generally speaking, organizational restructuring usually results in fewer people doing more work.

Companies can succeed at diversity if the initiative to create, manage and value the diverse workforce has the full support of the top management (Hayes, 1999; Jackson et al., 1992). The organization should assign this work to a senior manager (Jackson et al., 1992). The organization should link concerns for diversity to human resource management decisions around recruitment, selection, placement, succession planning, performance management, and rewards (Cascio, 1998). The strategy (diversity or otherwise) must be based on the will of the human resources, strength, and culture of the organization (Hayes, 1999). Managers must understand their firm's culture first and then implement diversity strategies according to that culture (Hayes, 1999).

## 2. Research Objectives and Hypotheses

**H1:** Age Diversity and Employee Performance differs across Gender, Age, Educational Qualification, Work Experience and Position of an employee.

**H2:** Age diversity is positively correlated with the employee performance.

**H3:** Age Diversity has a significant contribution to predict the Employee performance of an organization.
### 3. Review of Literature:

The world's increasing globalization requires more interaction among people from diverse backgrounds. People no longer live and work in an insular environment; they are now part of a worldwide economy competing within a global framework. For this reason, profit and non-profit organizations need to become more diversified to remain competitive. Maximizing and capitalizing on workplace diversity is an important issue for management. Supervisors and managers need to recognize the ways in which the workplace is changing and evolving. Managing diversity is a significant organizational challenge, so managerial skills must adapt to accommodate a multicultural work environment.

#### 3.1. Age

Possible explanations for negative effects of age diversity can be derived from the concept of compositional demography, which draws heavily on theories of social identity and self-categorization. This theory suggests that individuals tend to classify themselves and others into certain groups on the basis of dimensions that are personally relevant for them. These dimensions often include demographic categories such as gender, age, or ethnicity (Kunze et al., 2011; Tajfel and Turner, 1986).

According to social identity theory, social identity and intergroup behavior are guided by the pursuit of evaluative positive social identity; through positive intergroup distinctiveness, which in turn, is motivated by the need for positive self-esteem (Hogg and Terry, 2000; Abrams and Hogg, 1988). In addition to being motivated by self-enhancement, social identity processes are also motivated by a need to reduce subjective uncertainty about one's perceptions, attitudes, feelings, and behaviors and, ultimately, one's self-concept and place within the social world. As according to Al Jishi (2009), the level of performance depends on the level of motivation that stimulates someone to work and carry out the necessary tasks to achieve the goals.

#### 3.2. Employee Performance

Cascio (2000), defined performance as working effective which is the way in which somebody does a job, judged by its effectiveness. It is how well an employee is fulfilling the requirements of a job (Rue &Byars, 1993). Smith (2010), argued that good workforce diversity practices in the area of human resources are believed to enhance employee and organizational performance. According to Cornelius (1999), effective performance can be a key determinant in the achievement of business objectives while maximizing the contribution of employees. Schuler (1992), observed that a performance appraisal system should be objective, relevant to the job and the organization, fair to all employees and offers no special treatment. However, according to Jonathan, David and Aparna (2004), the past research on workplace diversity suggests that diversity can be either detrimental or beneficial for workgroup performance (Williams and O'Reilly, 1998). Good workforce diversity practices in the area of human resources are believed to enhance employee and organizational performance (Adler, 1986).

#### 3.3. Relationship between Age and Employee Performance

According to Winnie (2008), youngsters who are in their learning stage are more willing to learn new things and accept new ideas. Older people who have more life experiences are more mature and possess better problem solving skills. As an addition, the researcher also stated that the western findings suggested that the older and younger employees must come together to form coherent and viable corporate culture. These values possessed by different age groups can complement each other in companies and it tends to achieve better firm performance. In her study result, showed that different age groups provide different values for companies and these values can complement each other which improve companies' performance. As an addition, age heterogeneity on its own has a negative effect on individual productivity. Moreover, in the case of routine tasks, there are no substantial gains from age heterogeneity that could offset the increasing costs resulting from greater age heterogeneity. Thus, in companies with routine types
of work, increasing age heterogeneity overall leads to a decline in productivity (Gellner and Veen, 2009). Similarly, Joshi and Jackson, 2008; found no main effect of age diversity on employee reports of team processes or objectives measure of team performance.

## 4. Methodology

A Descriptive study conducted among the workers (full-time) of food processing companies in Coimbatore, South India, with the sample size 120 through convenience sampling technique. For this, the authors Questionnaire was constructed by adapted 5 items from Age Diversity Scale (ADS) by Abbas, Qaisar, Hameed & Abdul (2010) i.e. This organization provides me with equal opportunities for training and career development (AD1); My team leaders include all members at different ages in problem solving and decision making (AD2); The age differences in work group might cause conflict (AD3); At work, I experience lack of bonding with people of different age group (AD4) and I am positive about age diversity in this workplace (AD5), and 10 items from Employee Performance Scale (EPS) by Giles E.F (2008) i.e. I enjoy my tasks and the division's work approach (EP1); I am committed to the mission and direction of my organization (EP2); I am motivated to complete the task that is assigned to me (EP3); I co-operate well with my colleagues of different ethnicity (EP4); Opposite gender can perform well and I enjoy working with them (EP5); My performance level affects my salary level (EP6); I am satisfied with my current salary level (EP7); I am given the chance to try my own method of doing the job (EP8); By learning more skills through courses/training, I can improve my task performance (EP9) and Good employee performance is important for the future growth of my organization (EP10). Both these scales were surveyed through 5-point scale (i.e.) 1=Strongly Disagree to 5=Strongly Agree. The Cronbach's alpha values of ADS and EPS are 0.831 and 0.856 respectively. KMO test value (0.769) shown the sampling adequacy is very good and the Bartlett's test p value is 0.000 <0.05, indicated that the data is appropriate. Descriptive Statistics, Analysis of Variance (ANOVA), Correlation and Regression test were deployed for the analysis.

## 5. Results, Discussions and Findings

### 5.1. Descriptive Analysis:

#### 5.1.1. Percentage Analysis

<table><caption>The respondents of this study has been distributed as mentioned in the Table No: 5.1.1.</caption><thead><tr><th colspan="2">Variable</th><th>Frequency</th><th>%</th></tr></thead><tbody><tr><td rowspan="2">Gender</td><td>Male</td><td>51</td><td>43</td></tr><tr><td>Female</td><td>69</td><td>57</td></tr><tr><td rowspan="4">Age</td><td>20-29 Years</td><td>24</td><td>20%</td></tr><tr><td>30-39 Years</td><td>41</td><td>34%</td></tr><tr><td>40-49 Years</td><td>37</td><td>31%</td></tr><tr><td>50 Years and Above</td><td>18</td><td>15%</td></tr><tr><td rowspan="5">Educational Qualification</td><td>SSLC</td><td>35</td><td>29%</td></tr><tr><td>Plus Two</td><td>22</td><td>18%</td></tr><tr><td>Graduate</td><td>8</td><td>7%</td></tr><tr><td>ITI / Diploma</td><td>32</td><td>27%</td></tr><tr><td>Others</td><td>23</td><td>19%</td></tr><tr><td rowspan="4">Work Experience</td><td>2-5 Years</td><td>69</td><td>58%</td></tr><tr><td>6-10 Years</td><td>18</td><td>15%</td></tr><tr><td>11-15 Years</td><td>21</td><td>17%</td></tr><tr><td>15 Years</td><td>12</td><td>10%</td></tr><tr><td rowspan="2">Position</td><td>Managerial Level</td><td>9</td><td>7%</td></tr><tr><td>Operational Level</td><td>111</td><td>93%</td></tr></tbody></table>
## 5.1.2. DESCRIPTIVE STATISTICS

### 5.1.2.1. AGE DIVERSITY

The percentage, mean, and standard deviations of responses for each of the items for age diversity are shown in Table 5.1.2.1. There were as much as 65% of the respondents agreed to the first statement of Age Diversity (AD1), while 26% of them neither agreed nor disagreed with that statement. 50% of the respondents are agreed that to the second statement (AD2), while 40% neither agreed nor disagreed. 38% of the respondents are neither agreed nor disagreed, 37% are agreed and 25% are disagreed to question (AD3) and 54% of the respondents are agreed to the fourth statement (AD4), whereas 28% of the respondents are neither agreed nor disagreed. 62% of the respondents agreed and 31% of them neither agreed nor disagreed with the final statement of the age diversity.

<table><caption>Table 5.1.2.1. Descriptive Statistics of Age Diversity</caption><thead><tr><th></th><th>Strongly Disagree</th><th>Disagree</th><th>Neutral</th><th>Strongly Agree</th><th>Agree</th><th>Mean</th><th>S.D.</th></tr></thead><tbody><tr><th>AD1</th><td>0</td><td>8</td><td>26</td><td>51</td><td>15</td><td>3.74167</td><td>0.80436</td></tr><tr><th>AD2</th><td>1</td><td>9</td><td>40</td><td>32</td><td>18</td><td>3.54167</td><td>0.91574</td></tr><tr><th>AD3</th><td>3</td><td>22</td><td>38</td><td>32</td><td>5</td><td>3.10833</td><td>0.91482</td></tr><tr><th>AD4</th><td>3</td><td>15</td><td>28</td><td>42</td><td>12</td><td>3.425</td><td>1.00136</td></tr><tr><th>AD5</th><td>2</td><td>5</td><td>31</td><td>49</td><td>13</td><td>3.675</td><td>0.83175</td></tr></tbody></table>

### 5.1.2.2. EMPLOYEE PERFORMANCE

The percentage, mean, and standard deviations of responses for each of the items for employee performance are shown in Table 5.1.2.2. 75% of the respondents are agreed with the first statement of employee performance -EP1 (Mean = 3.79; SD = 0.83), while 16% are neither agreed nor disagreed. 65% of the respondents are agreed with the second statement of employee performance -EP2 (Mean = 3.77; SD = 0.81), while 29% are neither agreed nor disagreed. 50% of the respondents are agreed with the third statement of employee performance -EP3 (Mean = 3.50; SD = 0.92), while 39% are neither agreed nor disagreed. 68% of the respondents are agreed with the fourth statement of employee performance -EP4 (Mean = 3.8; SD = 0.87), while 24% are neither agreed nor disagreed. 59% of the respondents are agreed with the fifth statement of employee performance -EP5 (Mean = 3.68; SD = 0.98), while 30% are neither agreed nor disagreed. 45% of the respondents are agreed with the sixth statement of employee performance -EP6 (Mean = 3.38; SD = 0.95), while 39% are neither agreed nor disagreed. 41% of the respondents are agreed with the seventh statement of employee performance -EP7 (Mean = 3.16; SD = 1.17), while 33% are neither agreed nor disagreed. 53% of the respondents are agreed with the eighth statement of employee performance -EP8 (Mean = 3.41; SD = 1.01), while 30% are neither agreed nor disagreed. 53% of the respondents are agreed with the ninth statement of employee performance -EP9 (Mean = 3.54; SD = 1.01), while 33% are neither agreed nor disagreed. 49% of the respondents are agreed with the last statement of employee performance -EP10 (Mean = 3.53; SD = 1.07), while 32% are neither agreed nor disagreed.
<table><caption>Table 5.1.2.2. Descriptive Statistics of Employee Performance</caption><thead><tr><th></th><th>Strongly Disagree</th><th>Disagree</th><th>Neutral</th><th>Strongly Agree</th><th>Agree</th><th>Mean</th><th>S.D.</th></tr></thead><tbody><tr><th>EP1</th><td>2</td><td>7</td><td>16</td><td>60</td><td>15</td><td>3.79</td><td>0.82905</td></tr><tr><th>EP2</th><td>2</td><td>4</td><td>29</td><td>49</td><td>16</td><td>3.77</td><td>0.80683</td></tr><tr><th>EP3</th><td>3</td><td>8</td><td>39</td><td>37</td><td>13</td><td>3.5</td><td>0.9167</td></tr><tr><th>EP4</th><td>0</td><td>8</td><td>24</td><td>48</td><td>20</td><td>3.80</td><td>0.86578</td></tr><tr><th>EP5</th><td>3</td><td>8</td><td>30</td><td>38</td><td>21</td><td>3.68</td><td>0.97862</td></tr><tr><th>EP6</th><td>3</td><td>13</td><td>39</td><td>33</td><td>12</td><td>3.38</td><td>0.94543</td></tr><tr><th>EP7</th><td>9</td><td>17</td><td>33</td><td>26</td><td>15</td><td>3.16</td><td>1.16674</td></tr><tr><th>EP8</th><td>6</td><td>11</td><td>30</td><td>43</td><td>10</td><td>3.41</td><td>1.00833</td></tr><tr><th>EP9</th><td>5</td><td>9</td><td>33</td><td>33</td><td>20</td><td>3.54</td><td>1.06823</td></tr><tr><th>EP10</th><td>1</td><td>18</td><td>32</td><td>25</td><td>24</td><td>3.53</td><td>1.06875</td></tr></tbody></table>

## 5.2. Inferential Analysis

### 5.2.1. Analysis of Variance – One Way

H1: Age Diversity and Employee Performance differs across Gender, Age, Educational Qualification, Work Experience and Position of an employee.

Perception on Age Diversity significantly varies across Gender (F = 1124.18 > 2.56; p = 0.00 < 0.05); Age (F = 128.72> 2.56; p = 0.00 < 0.05); Work Experience (F = 259.90> 2.56; p = 0.00 < 0.05) and Position of the employee (F = 484.84> 2.56; p = 0.00 < 0.05) at 0.05 significant level. While Age Diversity does not vary significantly across Educational Qualification (F = 1.46< 2.56; p = 0.23> 0.05) at 0.05 significant level.

Perception on Employee Performance significantly varies across Gender (F = 1199.79 > 2.56; p = 0.00 < 0.05); Age (F = 143.03 > 2.56; p = 0.00 < 0.05); Work Experience (F = 278.79 > 2.56; p = 0.00 < 0.05) and Position of the employee (F = 449.54 > 2.56; p = 0.00 < 0.05) at 0.05 significant level. While Age Diversity does not vary significantly across Educational Qualification (F = 0.9199< 2.56; p = 0.34 > 0.05) at 0.05 significant level. Hence H1 is accepted.
<table><caption>Table 5.2.1. One Way ANOVA of Age Diversity& Employee Performance</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Source of Variation</th><th rowspan="2">SS</th><th rowspan="2">df</th><th rowspan="2">MS</th><th colspan="2">Age Diversity</th><th colspan="2">Employee Performance</th></tr><tr><th>F</th><th>p-value</th><th>F</th><th>p-value</th></tr></thead><tbody><tr><td rowspan="3">Gender</td><td>B.G</td><td>272.43</td><td>1</td><td>272.43</td><td rowspan="3">1124.18</td><td rowspan="3">0.00</td><td rowspan="3">1199.79</td><td rowspan="3">0.00</td></tr><tr><td>W.G</td><td>54.04</td><td>238</td><td>0.23</td></tr><tr><td>T</td><td>326.47</td><td>239</td><td></td></tr><tr><td rowspan="3">Age</td><td>B.G</td><td>81.32</td><td>1</td><td>81.32</td><td rowspan="3">128.72</td><td rowspan="3">0.00</td><td rowspan="3">143.033</td><td rowspan="3">0.00</td></tr><tr><td>W.G</td><td>135.31</td><td>238</td><td>0.57</td></tr><tr><td>T</td><td>216.62</td><td>239</td><td></td></tr><tr><td rowspan="3">Educational Qualification</td><td>B.G</td><td>2.88</td><td>1</td><td>2.88</td><td rowspan="3">1.46</td><td rowspan="3">0.23</td><td rowspan="3">0.91991</td><td rowspan="3">0.34</td></tr><tr><td>W.G</td><td>745.64</td><td>238</td><td>3.13</td></tr><tr><td>T</td><td>748.52</td><td>239</td><td></td></tr><tr><td rowspan="3">Work Experience</td><td>B.G</td><td>184.98</td><td>1</td><td>184.98</td><td rowspan="3">259.90</td><td rowspan="3">0.00</td><td rowspan="3">278.785</td><td rowspan="3">0.00</td></tr><tr><td>W.G</td><td>157.92</td><td>238</td><td>0.66</td></tr><tr><td>T</td><td>342.89</td><td>239</td><td></td></tr><tr><td rowspan="3">Position</td><td>B.G</td><td>103.10</td><td>1</td><td>103.10</td><td rowspan="3">484.84</td><td rowspan="3">0.00</td><td rowspan="3">449.541</td><td rowspan="3">0.00</td></tr><tr><td>W.G</td><td>54.58</td><td>238</td><td>0.23</td></tr><tr><td>T</td><td>157.68</td><td>239</td><td></td></tr></tbody></table>

5.2.2. Correlation Analysis

H2: Age diversity is positively correlated with the employee performance.

<table><caption>Table No: 5.2.2.1. Descriptive Statistics</caption><thead><tr><th></th><th>Mean</th><th>Std. Deviation</th></tr></thead><tbody><tr><td>AD1</td><td>3.74</td><td>.804</td></tr><tr><td>AD2</td><td>3.54</td><td>.916</td></tr><tr><td>AD3</td><td>3.11</td><td>.915</td></tr><tr><td>AD4</td><td>3.43</td><td>1.001</td></tr><tr><td>AD5</td><td>3.68</td><td>.832</td></tr><tr><td>Employee Performance</td><td>3.56</td><td>.456</td></tr></tbody></table>

<footnote>*BG – Between Groups; WG – Within Groups; T- Total</footnote>
<table><caption>Table No: 5.2.2.2. Correlations</caption><thead><tr><th></th><th></th><th>DA1</th><th>DA2</th><th>DA3</th><th>DA4</th><th>DA5</th></tr></thead><tbody><tr><td rowspan="2">AD1</td><td>Correlation</td><td>1</td><td></td><td></td><td></td><td></td></tr><tr><td>Sig.</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="2">AD2</td><td>Correlation</td><td>.077</td><td>1</td><td></td><td></td><td></td></tr><tr><td>Sig.</td><td>.400</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="2">AD3</td><td>Correlation</td><td>.038</td><td>-.031</td><td>1</td><td></td><td></td></tr><tr><td>Sig.</td><td>.677</td><td>.741</td><td></td><td></td><td></td></tr><tr><td rowspan="2">AD4</td><td>Correlation</td><td>.096</td><td>-.042</td><td>.133</td><td>1</td><td></td></tr><tr><td>Sig.</td><td>.298</td><td>.646</td><td>.148</td><td></td><td></td></tr><tr><td rowspan="2">AD5</td><td>Correlation</td><td>.200*</td><td>.288**</td><td>.036</td><td>.056</td><td>1</td></tr><tr><td>Sig.</td><td>.028</td><td>.001</td><td>.699</td><td>.542</td><td></td></tr><tr><td rowspan="2">Employee Performance</td><td>Correlation</td><td>.274**</td><td>.261**</td><td>.221*</td><td>.402**</td><td>.290**</td></tr><tr><td>Sig.</td><td>.003</td><td>.004</td><td>.015</td><td>.000</td><td>.001</td></tr></tbody></table>

* . Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

**Interpretation:** Age Diversity variables, AD1 - This organization provides me with equal opportunities for training and career development (r = 0.274**; p = 0.003 < 0.01); AD2 - My team leaders include all members at different ages in problem solving and decision-making (r = 0.261**; p = 0.004 < 0.01); AD4 - At work, I experience lack of bonding with people of different age group (r = 0.402**; p = 0.000 < 0.01); and AD5 - I am positive about age diversity in this workplace (r = 0.290**; p = 0.001 < 0.01) are positively correlated with employee performance at 0.01 significant level and AD3 - The age differences in work group might cause conflict (r = 0.221*; p = 0.015 < 0.05) at 0.05 significant level. Hence, H2 accepted i.e. Age diversity is positively correlated with the employee performance.

### 5.2.3. Regression Analysis:

**H3:** Age Diversity has a significant contribution to predict the Employee performance of an organization

<table><caption>Table No: 5.2.3.1. Variables Entered/Removed<sup>a</sup></caption><thead><tr><th>Model</th><th>Variables Entered</th><th>Variables Removed</th><th>Method</th></tr></thead><tbody><tr><td>1</td><td>Age<sup>b</sup></td><td>.</td><td>Enter</td></tr></tbody></table>

a. Dependent Variable: Employee Performance

b. All requested variables entered.
<table><caption>Table No: 5.2.3.2. Model Summary<sup>b</sup></caption><thead><tr><th>Model</th><th>R</th><th>R Square</th><th>Adjusted R Square</th><th>Std. Error of the Estimate</th></tr></thead><tbody><tr><td>1</td><td>.567<sup>a</sup></td><td>.321</td><td>.315</td><td>.3771336</td></tr></tbody></table>

a. Predictors: (Constant), Age

b. Dependent Variable: Employee Performance

<table><caption>Table No: 5.2.3.3. ANOVA<sup>a</sup></caption><thead><tr><th>Model</th><th></th><th>Sum of Squares</th><th>df</th><th>Mean Square</th><th>F</th><th>Sig.</th></tr></thead><tbody><tr><td rowspan="3">1</td><td>Regression</td><td>7.933</td><td>1</td><td>7.933</td><td rowspan="3">55.775</td><td rowspan="3">.000<sup>b</sup></td></tr><tr><td>Residual</td><td>16.783</td><td>118</td><td>.142</td></tr><tr><td>Total</td><td>24.716</td><td>119</td><td></td></tr></tbody></table>

a. Dependent Variable: Employee Performance

b. Predictors: (Constant), Age

<table><caption>Table No: 5.2.3.4. Coefficients<sup>a</sup></caption><thead><tr><th rowspan="2">Model</th><th rowspan="2"></th><th colspan="2">Unstandardized Coefficients</th><th>Standardized Coefficients</th><th rowspan="2">t</th><th rowspan="2">Sig.</th></tr><tr><th>B</th><th>Std. Error</th><th>Beta</th></tr></thead><tbody><tr><td rowspan="2">1</td><td>(Constant)</td><td>1.596</td><td>.265</td><td></td><td>6.031</td><td>.000</td></tr><tr><td>Age</td><td>.560</td><td>.075</td><td>.567</td><td>7.468</td><td>.000</td></tr></tbody></table>

a. Dependent Variable: Employee Performance

Age Diversity of the workforce is predicting the employee performance in an organization since (p= 0.000 < 0.01; F= 55.775 > 2.58; β= 0.567) and the model summary table shows that 32% of the employee performance can be predicted by the age diversity of the workforce in the organization. Hence H3 is accepted, i.e. age diversity of the workforce is predicting the employee performance in an organization.

## 6. Major Findings, Suggestions and Implications:

The results of the study have found that Age Diversity of the workforce and Employee Performance are significantly varies across gender of the respondents, age group of the respondents, work experience and position of the employee, while age diversity of the workforce and employee performance does not varies across educational qualification of the respondents. Further, age diversity of the workforce is positively correlated with the employee performance of the organization. Regression analysis revealed that age diversity of the workforce can predict the employees' performance in an organization. When an organization ensuring the uniqueness among the age diversity of the workforce, they can achieve the reduced conflicts, high utilization of the human at work, can ensure the person-organization fit, person-job fit and person-group fit which will improve the performance of the employees in an organization (Gokula Krishnan S et al, 2017). Further studies can be extended to the other industries and sectors in the business world by including other diversities of the workforce.
## 7. Limitations of the Study:

This contribution mainly focused to measure the relationship between the age diversity of the workforce and employees' performance, and it has not studied any other diversities of the workforce like gender diversity, educational diversity and ethnicity. Further this contribution surveyed 120 respondents in the food processing industry, hence the result may or may not be applicable to the other industries.

## 8. Conclusion:

This study set out to examine the area of age diversity of the workforce, with particular reference to the relationship with employees' performance. As a result of research carried out, certain trends emerged in this respect and, as with what was outlined in the literature review, legislation appeared to be the main driving force behind employees' performance is age diversity of the workforce. This research paper has enabled the author to learn from the literature review and there is an evidence to prove that age diversity of the workforce has a positive impact on Employees' performance. This research indicates that there is scope to further develop this concept and further research into the area of employees' performance resulting from other workforce diversities will be required. Finally the authors concluding that age diversity of the workforce is a significant predictor of the employees' performance.

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