Work engagement is critical for both employees and employers. With the reported downward spiral of engagement levels worldwide, organisations are recognising that in order to address this, attract best talent and keep employees motivated, they need to shift their attention to total reward strategies.
The overall purpose of this study was to explore the relationship between total rewards and work engagement in a South African context and to determine which reward categories predict work engagement. The study further endeavoured to determine whether gender and age had a moderating effect on the relationship between total rewards and engagement.
Statistics report that less than 30% of all working people are optimally engaged in their work. Considering that individuals spend more than a third of their lives at work committing themselves emotionally, physically and psychologically – research indicates that employees are no longer satisfied with traditional reward systems and want to feel valued and appreciated.
In this quantitative, cross-sectional research design using a non-probability convenience and purposive sampling strategy, 318 questionnaires were collected and analysed from financial institutions in Gauteng in which opinions were sought on the importance of different types of rewards structures and preferences, and how engaged they are in their workplace. The 17-item UWES and Nienaber total reward preference model were the chosen measuring instruments.
A small statistically significant correlation (
Although small, the significant correlation between total rewards and work engagement implies that total rewards are important motivators for employees in the workplace. Of the total rewards scales tested, only performance and career management significantly predicted work engagement, suggesting that more research is needed. Organisations seeking to implement total reward strategies should pay specific attention to which strategies have an impact on work engagement.
Organisations must take cognisance that factors such as performance and career management significantly predicted work engagement and should be considered as part of their total reward offerings.
Work engagement has become a critical aspect of study not only for individuals in the academic field but also for research practitioners and top management within organisations (Hewitt,
The positive relationship between engagement and organisational outcomes such as increased performance, organisational effectiveness, customer satisfaction, employee satisfaction, productivity and reduced staff turnover has been widely reported (Evenson,
Research has shown that engagement levels worldwide are at critical levels (Hewitt,
In the current economic context, it is therefore of utmost importance for organisations to find ways to motivate employees and boost their levels of engagement. In recent years, organisations have shifted their attention to total reward packages as a means of motivating employees and raising engagement levels (Giancola,
Total rewards can be described as the sum of the values of each element of an employee’s reward package and may include everything that employees view as important and of value within their jobs (Bussin & Van Rooy,
a firm’s entire employee value proposition, including direct and indirect financial rewards, positive characteristics of the work itself, career opportunities in the firm, social activities associated with the workplace, and a variety of other conveniences and services provided by the employer. (p. 4)
Work engagement is influenced by various types of rewards (Hewitt,
In recent years, a number of different total rewards models have been developed. For the purpose of this study, Nienaber’s (
Therefore, given the current challenges many organisations face with declining engagement levels, the primary purpose of this study was to investigate the relationship between work engagement and total rewards.
Some studies have also found evidence that gender differences exist in relation to reward structure (Murao,
Various aspects of age have been reported. Previous research found that women are discriminated against in the workplace on the grounds of age (Duncan & Loretto,
Age and gender were therefore investigated as potential moderators for the relationship between total rewards and work engagement.
Lastly, reward packages are mostly offered as a one-size-fits-all solution to employees without much regard to which rewards are more effective for a particular organisation setting. A better understanding of which rewards are preferred by workers will lead to better informed and customised reward strategies, which, in turn, will lead to improved engagement.
There is scarcity of research investigating specifically the relationship between total rewards and work engagement internationally as well as nationally. The main objective of this study was to explore the relationship between total rewards and work engagement in a South African context. The Nienaber’s (
Research Question 1: What is the relationship between work engagement and total rewards?
Research Question 2: Which reward category has the most influence and/or biggest impact on work engagement?
Research Question 3: Do gender and age have a moderating effect on the relationship between total rewards and engagement?
As early as in the nineties, Kahn (
The engaged life is an important concept as individuals spend more than a third of their lives engaged in their work (Van Zyl, Deacon & Rothmann,
Furthermore, Kahn (
Engaged employees experience a psychological presence in the workplace which helps them develop a sense of identity (Rothmann & Rothmann,
It is important to understand that organisations need to encourage and foster work engagement amongst employees in order to flourish and prosper during constant environmental changes (Shimazu & Schaufeli,
Work engagement is a complex and multidimensional construct. Although there are some similarities, it should not be confused with other constructs such as job satisfaction, involvement and commitment (Maslach, Schaufeli & Leiter,
One of the key aspects seen as impacting employee engagement is rewards. According to Eric (
According to Gross and O’Malley (
Over the years, the reward systems have changed within organisations from merely financially remunerating individuals to motivating them in the workplace as well (Hankin,
Intrinsic and extrinsic rewards differ to a large extent. Intrinsic rewards focus on the job and work itself, whereas extrinsic rewards are external to the job and the work that surrounds the job. Intrinsic rewards include growth opportunities, a sense of accomplishment, status, acknowledgement, satisfaction, self-esteem, challenge, autonomy and responsibility (Mahaney & Lederer,
According to Bussin (
Long and Shields (
The question is therefore proposed as to which rewards are the real motivators of work engagement. From a strategic perspective, it is crucial that an effective total reward system is designed to ensure greater employee and organisational outcomes.
Total rewards are seen as the combination of various different rewards, including financial and non-financial rewards and intrinsic and extrinsic rewards, which are made accessible to working individuals in exchange for their value-add in the workplace (Armstrong,
Various total rewards models and frameworks have been developed in recent years, offering different reward structures. Many of these programmes offer similar rewards and benefits. The WorldatWork model (
Monthly salary and remuneration: The pay that is provided by an employer to an employee for services incurred, including both fixed and variable pay, based on the individual’s level of performance.
Variable pay: This is also referred to as contingency pay. Variable pay is offered in different forms, including short-and long-term incentives. Short-term incentives are linked to the performance of the individual, the team or the organisation. Long-term incentive plans may include share option schemes, premium-priced share option schemes, share purchase plans, share appreciation rights and deferred annual bonus share plans.
Benefits: Packages or programmes provided by an employer to an employee in order to supplement cash remuneration. Benefits may include income protection benefits, savings, health benefits, job security benefits and retirement programmes.
Performance: The orientation of organisational, group and individual efforts, as well as the creation of employee expectations in order to move towards the achievement of organisational goals.
Career management: Combined learning experiences with the aim of enhancing employees’ skills, knowledge and competencies. Providing employees with the opportunity to grow and develop and advance in their careers. This type of reward encourages employees to become productive and engaged in their work.
Quality work environment: Lawler, Nadler and Cammann (
Work–home integration: The implementation of organisational policies and practices supporting employees towards their achievement of success and balance between work and home lives.
Nienaber’s total reward preference model is presented in
Nienaber’s total reward preference model.
Many researchers have emphasised the idea that there are certain demographic variables that have an impact on and are essential to the understanding of the relationship between total rewards and work engagement (Antoniou et al.,
In terms of the relationship between total rewards and gender, previous research indicated that gender differences existed in relation to reward structure, seen against the significant gender differences in wages that persist even though individual and job characteristics have been controlled for (Murao,
A quantitative, descriptive, cross-sectional research design using a non-probability convenience and purposive sampling strategy was carried out in order to reach a large sample of participants in various financial institutions in Gauteng. Data were collected through the distribution of paper-and-pencil questionnaires.
The participants of this study consisted of a random sample of 318 employees from various financial organisations based in Johannesburg, South Africa (
Demographic and biographical characteristics of participants (
Item | Category | Participants |
|
---|---|---|---|
Frequency | % | ||
Gender | Men | 110 | 34.6 |
Women | 208 | 65.4 | |
Missing values | - | - | |
Age | 18–27 | 81 | 25.4 |
28–38 | 111 | 34.8 | |
39–48 | 70 | 21.9 | |
49–59 | 41 | 12.9 | |
60+ | 14 | 4.4 | |
Missing values | 1 | 0.6 | |
Racial group | African | 74 | 23.2 |
Mixed race | 23 | 7.2 | |
White | 175 | 54.9 | |
Indian | 36 | 11.3 | |
Asian | 9 | 2.8 | |
Other | 1 | 0.3 | |
Missing values | 1 | 0.3 | |
Current position | Trainee/intern | 36 | 11.3 |
Junior manager | 67 | 21.0 | |
Middle manager | 56 | 17.6 | |
Senior manager | 33 | 10.3 | |
Executive | 17 | 5.3 | |
Other | 99 | 31.0 | |
Missing values | 10 | 3.5 | |
Level of education | Grades 8–11 | 13 | 4.1 |
Grade 12 | 92 | 28.9 | |
Degree and/or diploma | 140 | 44.0 | |
Postgraduate | 65 | 20.4 | |
Other | 8 | 2.6 | |
Missing values | - | - | |
Job family | Human resources | 39 | 12.2 |
Administrative | 77 | 24.1 | |
Sales and service | 52 | 16.3 | |
IT | 18 | 5.6 | |
Process and project management | 16 | 5.0 | |
Marketing | 19 | 6.0 | |
Finance | 42 | 13.2 | |
Consulting | 20 | 6.3 | |
Other | 32 | 10.9 | |
Missing values | 3 | 0.4 |
IT, information technology.
The data showed that white people represented 55% of the sample, 65% was female and the majority of respondents fell into the age groups of 28–38 (35%), 18–27 (25%) and 39–48 years (22%). The most prominent position was made up of junior managers (21%). In terms of level of education, the biggest group had either a degree or diploma (44%).
The questionnaire consisted of three sections, namely, Part A to Part C. Part A included a number of questions about respondents’ demographic composition. Part B included the 17-item UWES developed by Schaufeli et al. (
Part C included the total rewards preferences questionnaire developed by Nienaber (
Participation in the study was voluntary. Participants were selected on the basis of their availability and willingness to partake in the study. Various financial institutions in Gauteng were approached to obtain permission to conduct the research within their organisations. Questionnaires were distributed through human resource managers in the organisations and participants were requested to seal their questionnaires in a clearly marked envelope (with the researcher’s detail), but anonymously. The questionnaires were collected from the organisations after 2 weeks. Each questionnaire contained a cover letter which explained the purpose of the research, included a confidentiality clause and provided the assurance that participants can withdraw at any stage of the research and instructions on how to complete the questionnaire.
Statistical analysis was carried out using the SPSS program (SPSS Inc.,
The skewness and kurtosis were examined to evaluate the distribution of the data and items that did not meet the cut-off points were discarded from further analysis. The cut-off scores for skewness and kurtosis are both < 2 and < 4, respectively (Finch & West,
Multiple regression analysis was conducted to determine the relationship between the chosen demographic variables, total rewards and work engagement. Both homoscedasticity and multicollinearity were accounted for when conducting multiple regression. Homoscedasticity refers to the variance around the regression line remaining the same for all predictor (independent) variables (Tabachnick & Fidell,
A moderated regression analysis was conducted with age and gender as separate moderators in order to determine whether gender and age acted as moderators in the relationship between reward preferences and work engagement.
The following results will be presented: descriptive statistics, EFA, correlation, internal reliability, regression analysis and moderated regression analysis.
Descriptive statistics of the reward preference questionnaire.
Scales | Mean | SD | Skewness | Kurtosis | |
---|---|---|---|---|---|
Performance and career management | 98.44 | 11.84 | 0.88 | −1.19 | 2.52 |
Conducive working environment | 84.16 | 19.13 | 0.89 | −0.35 | −0.19 |
Total rewards scale | 178.17 | 25.42 | 0.91 | −0.52 | 0.12 |
Work engagement | 84.34 | 17.37 | 0.95 | −0.70 | 1.43 |
SD, standard deviation;
The Nienaber’s reward scale was originally based on a theoretical framework of six factors identified from the literature and previous studies. After being subjected to exploratory and second-order factor analysis, a newly formed two-factor reward structure emerged which replaced the original six factors proposed. The two factors were named conducive working environment and remunerations and benefits, and achieved Cronbach’s alphas of 0.88 and 0.86, respectively. The 46 items of the total reward scale were subjected to EFA. Principal component analysis with direct Oblimin rotation was selected. Items were only considered to be maintained when they met the criteria of factor loadings > 0.30, not cross-loading. To assist the decision on which items were to be included, the corrected item total correlations were scrutinised (DeVellis,
Two-factor structure for total reward preference scale.
Variable | Component |
|
---|---|---|
1 | 2 | |
My employer should provide me with an allowance or subsidy to care for my financially dependant parents | 0.86 | - |
My employer should provide holiday programmes for my children | 0.85 | - |
An on-site convenience store is… | 0.80 | - |
On-site or subsidised childcare facilities is… | 0.75 | - |
An on-site staff restaurant is… | 0.76 | - |
An on-site fitness centre is… | 0.72 | - |
An on-site medical centre is… | 0.69 | - |
My employer should provide me with financial assistance to buy a house | 0.65 | - |
Subsidised tuition for my children is… | 0.64 | - |
I think employers should provide phased in return to work after maternity/paternity leave | 0.57 | - |
A dedicated parking bay in the building where I work is… | 0.54 | - |
Formal recognition for a job well done (e.g. a fully paid overseas trip) is… | 0.52 | - |
The opportunity to take sabbatical leave is… | 0.49 | - |
I need a laptop 3G card to perform optimally | 0.46 | - |
Increases should be linked to inflation and not to personal performance | 0.46 | - |
Bonus allocations should be linked to my team’s performance | 0.44 | - |
I would like to go on an international secondment | 0.40 | - |
I need to log into the employer’s network from home | 0.40 | - |
Annual allocations of shares and or share options are… | 0.37 | - |
Constructive and honest feedback on my performance is… | - | 0.75 |
My job should be challenging and test my abilities | - | 0.72 |
Having a good working relationship with colleagues is… | - | 0.72 |
The quality of co-workers in my team is… | - | 0.71 |
Growth opportunities, learning and development are… | - | 0.69 |
I should be held accountable for my personal job outputs | - | 0.65 |
Management should encourage team performance | - | 0.61 |
My career path planning should align with my personal interests and goals | - | 0.58 |
A comfortable work environment (décor, equipment) is… | - | 0.57 |
I think coaching and mentoring are… | - | 0.57 |
Bonus allocations should be linked to my personal performance | - | 0.56 |
Personal safety and security in the workplace is… | - | 0.55 |
Retirement and disability benefits are… | - | 0.55 |
Merit increases should be linked to personal performance | - | 0.48 |
Informal recognition for a job well done (e.g. a thank you note) is… | - | 0.46 |
Medical aid benefits through medical aid schemes are… | - | 0.43 |
My annual performance bonus and/or incentive is… | - | 0.35 |
Extraction method: Principal Component Analy-sis; Rotation method: Promax with Kaiser Normalisa-tion.
Note: Rotation converged in 3 iterations.
In order to answer the first research question to determine the relationship between total rewards and work engagement, the relationship between total rewards and work engagement was first analysed and thereafter between the work engagement and the various reward subscales. As can be seen in
Correlations between total rewards and work engagement.
Variable | Mean | SD | Work engagement | Total rewards |
---|---|---|---|---|
Work engagement | 84.33 | 17.37 | - | 0.25 |
Total rewards | 178.17 | 25.42 | 0.25 |
- |
Correlation is significant at the 0.01 level (2-tailed).
The correlation results between the reward subgroups and work engagement are presented in
Correlations between reward subscales and work engagement
Subscales | Mean | SD | 1 | 2 | 3 |
---|---|---|---|---|---|
Work engagement | 84.35 | 17.56 | - | - | - |
Conducive working environment | 84.63 | 18.91 | 0.12 |
- | - |
Performance and career management | 98.44 | 11.84 | 0.35 |
0.39 |
- |
Correlation is significant at the 0.05 level (2-tailed).
Correlation is significant at the 0.01 level (2-tailed).
To answer this research question, multiple regression was used to explore the prediction of work engagement from the subcategories of total rewards. From the original six subscales, only two subscales, conducive working environment and performance and career management, remained that met all the criteria and could be reasonably interpreted. The results, as shown in
Moderated regression analysis with reward subscales as predictors of work engagement.
Model | Coefficient |
Δ |
|||||||
---|---|---|---|---|---|---|---|---|---|
Unstandardised | Standardised | ||||||||
B | Standard error | Beta | |||||||
Contstant | 34.28 | 8.11 | - | 4.23 | 0.00 |
20.05 | 0.35 | 0.12 | 0.12 |
Conducive working environment | −0.01 | 0.05 | −0.02 | −0.24 | 0.81 | - | - | - | - |
Performance and career management | 0.52 | 0.09 | 0.36 | 5.92 | 0.00 |
- | - | - | - |
Statistically significant
To determine whether gender and age influenced the relationship between total rewards and work engagement, moderated regression analyses as explained by Field (
From
Moderated regression analysis with age as moderator between work engagement and total rewards.
Model | Coefficients |
Δ |
|||||||
---|---|---|---|---|---|---|---|---|---|
Unstandardised |
Standardised | ||||||||
B | SE | Beta | |||||||
Constant | 54.26 | 6.63 | - | 8.18 | 7.07 | 14.86 | 0.29 |
0.09 | 0.08 |
Total rewards | 0.17 | 0.04 | 0.25 | 4.58 | 6.71 | - | - | - | - |
Age | 2.45 | 0.83 | 0.16 | 2.94 | 0.00 | - | - | - | - |
Dependent variable: Work engagement.
Moderated regression analysis with gender as moderator between work engagement and total rewards.
Model | Coefficients |
Δ |
|||||||
---|---|---|---|---|---|---|---|---|---|
Unstandardised |
Standardised | ||||||||
B | SE | Beta | |||||||
Constant | 54.77 | 7.40 | - | 7.40 | 1.23 | 10.30 | 0.25 |
0.06 | 0.06 |
Total rewards | 0.17 | 0.04 | 0.25 | 4.50 | 9.70 | - | - | - | - |
Gender | 0.64 | 3.53 | 0.01 | 0.18 | 0.86 | - | - | - | - |
Dependent variable: Work engagement.
Performance and career management (0.88), conducive working environment (0.89), as well as the total reward scale (0.91) met the criterion of reliability in satisfactory manner. The results of this study only partially supported the factor structure found by Nienaber (
Another reason could be the rigour of the development of the instrument as such. Although relatively satisfactory scores were obtained for the two reward subscales, further scale refinement is recommended, as a large number of items have still been retained. In new scale development, one needs to take care to not merely discard items without investigating the instrument on item level. It is suggested that this instrument be further analysed through techniques such as Rasch analysis to further refine the scales. Rasch analysis is a more sophisticated technique utilised for the process of new scale development where more stringent measures are applied to assist with the decision to include or exclude items (Beninato & Ludlow,
On a theoretical level, one would expect to have found a different factor structure as many studies found support for a wider mixture of both intrinsic and extrinsic rewards (Kaplan,
The statistically small-to-moderate significant correlation between total rewards and work engagement, although not as high as in previous studies, corresponded with results reported by previous research (Hewitt,
The results post an encouraging sign for organisations that total reward structures are important tools in their strategies to boost engagement levels. Lastly, although the relationship between work engagement and total rewards is positive, it is not as high as one would hope for. This can be attributed to the total rewards scale still being in its development phase. It is believed that with further item refinement these relationships will also improve.
The second research question addressed which reward category had the most influence on work engagement. It was found that only performance and career management significantly predicted work engagement and explained 12% of the variance. This implies that there exist a number of other factors and constructs that contribute towards predicting work engagement. This study has not looked at factors such as the influence of generational cohorts, personality characteristics and tenure which could also help explain the variance (Shaul,
This research question addressed whether age and gender moderated the relationship between total rewards and work engagement. For this sample, only age had a moderating effect. This is in support with other research done in South Africa where age did seem to have an influence on reward preferences (Bussin & Van Rooy,
South African organisations will gain insight from this study on how to improve an individual’s levels of work engagement through designing a total rewards framework that matches the needs of employees and the business. The small-to-moderate relationship between total rewards and engagement provides support for organisations to focus their energy on utilising total rewards as part of their engagement strategies. The results, however, also warrant some caution. According to popular belief, monetary rewards play an important part in reward strategies. This however can differ from one organisation to another. Each organisation needs to have a thorough understanding of its own workforce and their particular needs.
The results indicated that total rewards could explain only 12% of the variance in work engagement. Organisations must take cognisance that both total rewards and work engagement are complex and multidimensional constructs that need to be closely studied and understood on organisational and individual levels if the desired effects are to be achieved. The type of rewards chosen provides useful information in themselves as they provide insight regarding where their motivational potential lies. Results from the Nienaber (
What is perhaps evident from this study and the Nienaber study is that more attention should be given to the development of the actual reward scale. Careful attention must be given to the theoretical framework that will provide foundation for the questionnaire to follow. The specific items will need to be relevant for a specific context and workforce. If science and practice collaborate together, much better results can be achieved.
Some limitations must be noted. The findings of this study cannot be generalised to other demographic categories and cultures because of the non-representativeness of the sample. For example, there were far more women and white people in the sample than what are seen as representative of South African society. The reason for the unequal distribution of gender and race could be attributed to the sample being selected from organisations whose employees were predominately female. This was purely by chance. In addition, as the sample was drawn only from organisations within Gauteng, the participants cannot accurately represent other provinces and organisations within South Africa. Furthermore, the study used a cross-sectional design and was unable to determine the relationship between total rewards and work engagement over time. Through the use of a longitudinal study, deeper insight could be provided into the causal relationships between the different reward categories and work engagement. Common method bias could also have influenced the results. In addition, another limitation can be inferred by keeping in mind that the total reward instrument is still in the development phase and being tested.
This research has provided useful insights that can assist organisations in designing their total rewards models as part of their engagement strategies. As this investigation has been conducted during an economically volatile time which could have influenced the results, it is recommended that it be repeated in the form of a longitudinal study in order to determine the impact of different reward preferences on work engagement over time. Furthermore, the results have indicated that it would be beneficial for organisations to pay attention to the type of benefits they offer to their employees, as there are certain preferences which in turn influence their levels of work engagement such as constructive and honest feedback, challenging job, growth opportunities, informal recognition, career path planning and mentoring (Bussin & Van Rooy,
If organisations want to include total rewards as part of their engagement strategies, it is imperative that they understand the complex nature in the reward–engagement relationship and how best to use reward systems to meet the needs and goals of both the organisation and employees. Certain rewards are better predictors of work engagement than others, implying that companies should steer away from one-size-fits-all reward strategies.
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in conducting this study or writing this article.
The study was conducted at the University of Johannesburg. C.H. was the supervisor of the study. She contributed to its conceptual design, revision and update of the literature review, conducted some of the statistical analysis and was responsible for the writing of the article. G.H. was responsible for participating in the conceptual design, was the main contributor of the literature review and the sole data collector capturer and also conducted a substantial portion of the statistical analysis.