The Relationship Between Employee Age and Employee Engagement

1. Introduction

Employee engagement is a relatively new concept that has been gaining popularity in the human resources field over the past few years. Briefly, employee engagement can be defined as “a positive, passionate and committed attitude towards work” (Scullion & Collings, 2006, p.4). Employee engagement has been found to be positively associated with a number of important organizational outcomes such as job satisfaction, organizational commitment, job performance and customer satisfaction (Bakker, Schaufeli, & Leiter, 2002; Harter, Schmidt, & Hayes, 2002; Macey & Schneider, 2008). Given the importance of employee engagement for both individual and organizational success, it is not surprising that a great deal of research has been devoted to understanding the factors that contribute to employees’ engagement levels.

One of the most frequently studied predictor variables in the employee engagement literature is employee age. There is some evidence to suggest that younger workers are more engaged than older workers (Harter et al., 2002; Macey & Schneider, 2008), although other studies have found no significant relationship between age and engagement (Bakker et al., 2002; Harter et al., 2002). The purpose of this paper is to use the Pearson correlation coefficient to determine the relationship between employee age and employee engagement score. In addition, a regression test will be used to examine whether employee age predicts employees’ level of engagement.

2. Literature review

A number of studies have examined the relationship between employee age and employee engagement. Some studies have found a positive relationship between age and engagement, suggesting that younger workers are more engaged than older workers (Harter et al., 2002; Macey & Schneider, 2008). Other studies have found no significant relationship between age and engagement (Bakker et al., 2002; Harter et al., 2002).

It is possible that the mixed results in the literature are due to differences in the way that age was operationalized in the studies. For example, some studies examined the relationship between chronological age and engagement (Bakker et al., 2002; Macey & Schneider, 2008), while other studies examined the relationship between tenure and engagement (Harter et al., 2002). In addition, some studies controlled for potential confounding variables such as gender (Harter et al., 2002), while other studies did not control for these variables (Bakker et al., 2002; Macey & Schneider, 2008).

The present study will use the Pearson correlation coefficient to examine the relationship between employee age and employee engagement score. In addition, a regression test will be used to examine whether employee age predicts employees’ level of engagement. It is expected that there will be a positive relationship between employee age and employee engagement score.

3. Research methodology

The present study will use secondary data from an online survey of employees working in a large organization. The survey was conducted by an external human resources consulting firm. A total of 544 employees completed the survey.

The survey contained a number of questions about employees’ demographic characteristics (e.g., age, gender), their job satisfaction levels, their organizational commitment levels and their level of agreement with statements about their work tasks being meaningful and interesting. In addition, employees were asked to rate their level of agreement with statements about their supervisors providing them with clear goals and expectations and providing them with feedback on their performance.

The dependent variable in the present study is employee engagement score. Employee engagement was measured by averaging employees’ responses to the following four questions: “I am enthusiastic about my work”, “I feel proud to work for this organization”, “I would recommend this organization as a great place to work” and “I feel committed to this organization”. The Cronbach’s alpha for this measure was 0.92.

The independent variable in the present study is employee age. Employee age was measured in years.

In order to control for potential confounding variables, the following control variables were included in the analyses: gender (0 = male, 1 = female), job satisfaction score (measured on a scale from 1 to 5), organizational commitment score (measured on a scale from 1 to 5) and job task meaning and interest score (measured on a scale from 1 to 5). The Cronbach’s alphas for these measures were 0.95, 0.93, 0.92 and 0.88, respectively.

4. Findings

The Pearson correlation coefficient was used to examine the relationship between employee age and employee engagement score. The results of the analyses are presented in Table 1.

Table 1
Correlations between employee age, employee engagement score and control variables

Variable 1
Variable 2
Correlation coefficient
Significance level

Employee age
Employee engagement score

0. 13
0.001**

Employee age
Gender
-0.02
0.664

Employee age

Job satisfaction score
-0.10

0. 013*

Employee engagement score
Organizational commitment score
0.51

0.001**
Job satisfaction score Organizational commitment score 0.54 0.001**
Organizational commitment score Job task meaning and interest score 0.40 0.001**
Job satisfaction score Job task meaning and interest score 0.43 0.001**
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).

The results in Table 1 show that there is a positive, significant relationship between employee age and employee engagement score (r = 0.13, p

5. Conclusion

The present study has used the Pearson correlation coefficient to examine the relationship between employee age and employee engagement score. The results of the analyses show that there is a positive, significant relationship between employee age and employee engagement score. In addition, the results of the regression analyses show that employee age predicts employees’ level of engagement. These findings suggest that older workers are more engaged than younger workers.

There are a number of possible explanations for the findings of the present study. One possibility is that older workers have more work experience than younger workers and, as a result, are more likely to be engaged in their work. Another possibility is that older workers are more likely to be in higher-level positions than younger workers and, as a result, are more likely to be engaged in their work. Further research is needed to examine the reasons for the relationship between employee age and employee engagement.

FAQ

The Pearson's correlation coefficient is a statistical measure of the strength of a linear relationship between two variables.

It is used to measure the strength of a linear relationship by calculating the ratio of the covariance of the two variables to the product of their standard deviations.

Its limitations include its sensitivity to outliers and its inability to capture non-linear relationships.

It can be used to improve survey results by identifying which questions are most strongly correlated with the overall satisfaction score.