Research on reward preferences remains inconclusive. Total reward theories often do not take the role of intrinsic psychological rewards into consideration. Further to this, there are not only limited instruments available to measure reward preferences but also ease of access to psychometrically sound measures is further challenging.
The aim of this study was to develop and validate an instrument to measure reward preferences in the working environment.
Organisations require tools to enhance waning motivational levels in the workplace. The measurement of reward preferences appears essential to determine what employees ultimately want from their work to improve levels of motivation. Major limitations exist regarding current reward preference instruments.
Quantitative scale development procedures were employed to construct the 32-item instrument. Data were collected from South African employees (
The factor analysis revealed a 3-factor structure (Non-financial rewards, Financial rewards and Benefits and growth opportunities). Items evidenced good factor loadings and dimensions demonstrated high internal consistency. The dimensions and overall scale performed mostly well in accordance with Rasch Model expectations. Based on the overall results, one can confirm that the new instrument has satisfactory psychometric properties.
The instrument can help employers and scholars to measure, understand and explore what employees value and seek from the working environment.
The study expands on limited pre-existing theory and empirical research pertaining to the measurement of rewards preferences. A unique and psychometrically sound reward preference instrument is provided for use by scholars and employers.
Organisations seek to know what motivates employees’ and what they ultimately value from the employment relationship. Total rewards – financial and non-financial rewards that organisations offer to workers – motivate and drive employees to put forth their best efforts (Riaz, Akhtar, & Aslam,
Despite the influx of total reward research, there are still pitfalls in the total rewards domain. Brown (
An overlooked way of rewarding employees is by focussing on the psychological façade of designing work to be more intrinsically motivating and satisfying (Renard & Snelgar,
To measure preferences towards rewards and achieve the goals of this study, human resource practitioners as well as scholars require readily available instruments. Despite growing interest in reward preferences locally (e.g. Bussin & Thabethe,
The aforementioned highlights that there is a need to develop a psychometrically sound measuring instrument to explore reward preferences. To this end, the primary objective of this study was to develop and validate a rewards preference measure based on financial, non-financial and intrinsic psychological rewards. The motive for the development of this instrument is that there are no current and psychometrically sound scales readily available to measure such preferences.
Reward is conceptualised as returns employees receive for carrying out tasks and responsibilities in the workplace (Jiang, Xiao, Qi, & Xiao,
Rewards are important as they play an integral role in the field of talent management. Adequately designed reward systems are highly effective tools in enhancing employee motivation and boosting job satisfaction (Noor & Zainordin,
Financial rewards are economic and monetary in nature. They are controlled directly by an organisation (Kshirsagar & Waghale,
Non-financial rewards consist of non-monetary returns. These rewards are deemed intangible (Joshi,
Intrinsic rewards are those positive feelings (such as happiness) which derive from the working context (Obicci,
Meaningful work can be defined as one’s experience and personal significance of work (Michaelson,
Felt responsibility can be defined as situations in which one feels obliged to perform, take action or deliver on something (Avey, Avolio, Crossley, & Luthans,
Challenging work encapsulates tasks which are difficult yet energising (Preenen, Van Vianen, & De Pater,
A sense of competence is conceptualised as the positive feelings that one gets when they are able to cope with tasks, exceed expectations and produce matter-worthy work. Basic psychological need satisfaction in self-determination theory (Ryan & Deci,
Task interest and enjoyment occur when employees find their work tasks fun or enjoyable to engage with (Crane,
Preferences have been defined as an individual’s liking, desire or favouring towards phenomenon (Scherer,
Reward preferences are significant in talent attraction and retention (Victor & Hoole,
The Reward Preference Questionnaire (RPQ; Nienaber et al.,
In light of the above, the intrinsic psychological façade of rewards remains precluded from these instruments. Moreover, despite limited attempts to develop, refine and validate these reward preferences measures, many reward surveys administered to employees are not based on empirical research (Nicholls,
To develop the reward preferences instrument, an exploratory sequential research design was employed. This article constitutes the second phase and was established on findings from the initial qualitative phase. The qualitative phase was used to define the construct, ensure content and face validity and inform the items. During the first phase, data were collected using focus group discussions and analysed using a deductive and constructionist thematic analysis. Findings revealed that
Non-probability convenience sampling was used to collect data from the final sample (
A detailed breakdown of the samples demographics is presented (
Frequency distribution of sample participants.
Item | Category | Frequency ( |
Percentage (%) |
---|---|---|---|
Gender | Male | 302 | 47.30 |
Female | 337 | 52.70 | |
Race | Black | 392 | 61.30 |
Coloured | 73 | 11.40 | |
Indian | 16 | 2.50 | |
Asian | 3 | 0.50 | |
White | 150 | 23.50 | |
Other | 5 | 0.80 | |
Home language | English | 175 | 27.40 |
Afrikaans | 90 | 14.10 | |
isiXhosa | 54 | 8.50 | |
isiZulu | 120 | 18.80 | |
Sesotho | 47 | 7.40 | |
SiSwati | 35 | 5.50 | |
Xitsonga | 15 | 2.30 | |
Sepedi | 61 | 9.50 | |
Other | 42 | 6.50 | |
Educational qualification | Grade 12 or lower | 177 | 27.70 |
Diploma or certificate | 140 | 21.90 | |
Certified Professional Qualification | 52 | 8.10 | |
BTech | 17 | 2.70 | |
Bachelor’s degree | 69 | 10.80 | |
Honours degree | 78 | 12.20 | |
Master’s degree | 71 | 11.10 | |
Doctoral degree | 21 | 3.30 | |
Other | 12 | 1.90 | |
Missing | 2 | 0.30 | |
Industry | Banking or Insurance or Finance | 77 | 12.10 |
Construction | 62 | 9.70 | |
Education | 52 | 8.10 | |
Transportation | 13 | 2.00 | |
Service | 37 | 5.80 | |
Healthcare | 52 | 8.10 | |
Sports | 12 | 1.90 | |
Beauty | 17 | 2.70 | |
Legal | 36 | 5.60 | |
Events or Hospitality | 16 | 2.50 | |
Mining | 8 | 1.30 | |
Retail | 61 | 9.50 | |
Agriculture | 11 | 1.70 | |
Aviation | 2 | 0.30 | |
Automotive | 15 | 2.40 | |
Other | 159 | 24.90 | |
Missing | 9 | 1.40 | |
Work experience (years) | 1 to 6 | 209 | 32.70 |
6 to 10 | 135 | 21.10 | |
11 to 20 | 127 | 19.90 | |
21+ | 162 | 25.30 | |
Other | 1 | 0.20 | |
Missing | 5 | 0.80 |
A biographical questionnaire required participants to indicate their age, gender, race, home language and occupational category. The Rewards Desirability Inventory (RDI) was developed to measure preferences towards different types of rewards by asking participants to indicate how important each type is to them. Based on a literature review and the qualitative findings from phase 1 (Victor & Hoole,
Data were collected using both paper-based and online questionnaires. The researcher initiated contact with companies via email. Company representatives either forwarded the email with an electronic survey link to participants or requested paper-based questionnaires to be delivered. Paper-based questionnaires were handed back to the company representative within 2 weeks. Electronic questionnaires were completed at the leisure of participants within a month of the email request. The remaining participants were recruited via social media platforms including LinkedIn and Facebook. Electronic links to the survey were open for 2 months and reminder adverts to participate in the study were carried out at weekly intervals.
Approval was granted from the relevant institution to conduct research. Participants were informed of (1) the nature and purpose of the study, (2) option to voluntarily participate and withdraw, (3) an indication that responses will remain confidential and anonymous and (4) contact details of the research team. All data collected were stored electronically via a password protected system.
Data were screened for input errors, unengaged and/or unexpected response cases. Missing cases were replaced using the ‘mice’ (multivariate imputation by chained equations) package in R (Version 3.6.2.). An exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were carried out. Data suitability to verify factorability was explored by scrutinising the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO; Kaiser,
A CFA was used to verify the factor structure using the ‘lavaan’ package in R. Using a robust ML estimation method, the estimated factor structure was tested. To analyse model fit, goodness-of-fit indices were calculated. The following fit statistics were analysed: Chi-square (X²; where the
Item response theory was used to further test and assess underlying psychometric properties of the RDI using Winsteps (Version 4.4.8). Firstly, the researcher explored functioning of rating scales. The category probability, category frequencies and chi-square fit statistics were evaluated. Fit statistics were acceptable at between 0.50 and 1.5 (Linacre,
The KMO test produced an index of 0.95 whilst Bartlett’s test of sphericity was significant at
Pattern matrix for the three-factor solution.
Items and factor labels | Factors |
|||
---|---|---|---|---|
Α | 1 | 2 | 3 | |
0.95 | - | - | - | |
Item 28: Am confident in my abilities to do my job | - | 0.81 | - | - |
Item 47: Am able to see results for work that I have started and completed | - | 0.76 | - | - |
Item 44: Feel proud about the work that I produce | - | 0.74 | - | - |
Item 39: Do work that I am passionate about | - | 0.73 | - | - |
Item 21: Am able to gain relevant working experience from my job | - | 0.71 | - | - |
Item 27: Am kept well informed about important information at work | - | 0.70 | - | - |
Item 5: Have the skills and abilities to do my work | - | 0.69 | - | - |
Item 12: Know that I am good at my job | - | 0.69 | - | - |
Item 37: Do work that gives me a sense of achievement | - | 0.69 | - | - |
Item 43: Work for a company that encourages good communication | - | 0.67 | - | - |
Item 32: Fully complete work task from start to finish | - | 0.66 | - | - |
Item 50: Do work that requires me to put in the extra effort | - | 0.66 | - | - |
Item 9: Do work that challenges my skills and abilities | - | 0.65 | - | - |
Item 49: Do work that I enjoy | - | 0.65 | - | - |
Item 54: Feel part of my company’s successes | - | 0.65 | - | - |
Item 24: Do work that I find interesting | - | 0.64 | - | - |
Item 40: Do work that has a positive impact on other people | - | 0.63 | - | - |
Item 26: Am a good fit for my company’s culture | - | 0.57 | - | - |
Item 15: Do work that challenges me | - | 0.56 | - | - |
Item 18: Have a supervisor or manager who trusts me | - | 0.54 | - | - |
Item 36: Work in an organised (structured) environment | - | 0.53 | - | - |
Item 22: Will keep my job regardless of my company’s economic problems | - | 0.49 | - | - |
Item 4: Have freedom in choosing how I should go about completing my work tasks | - | 0.46 | - | - |
Item 19: Am able to complete work tasks according to my liking | 0.38 | - | - | |
0.85 | - | - | - | |
Item 17: Regularly receive a pay cheque | - | - | 0.74 | - |
Item 41: Get paid on a regular basis | - | - | 0.73 | - |
Item 55: Receive higher pay for a higher job level | - | - | 0.64 | - |
Item 51: Receive higher pay for more years of working experience | - | - | 0.63 | - |
Item 60: Receive a salary, wage or hourly rate of pay for the work that I do | - | - | 0.49 | - |
0.80 | - | - | - | |
Item 14: Work for a company that pays money towards my medical aid | - | - | - | 0.84 |
Item 52: Work for a company that pays money towards my pension or retirement fund | - | - | - | 0.62 |
Item 11: Work for a company that offers training relevant to my needs | - | - | - | 0.45 |
Item 30: Have opportunities to be promoted | - | - | - | 0.39 |
With regard to the CFA, although a perfect fit was not obtained (
Goodness-of-fit indices.
Model | χ² | TLI | CFI | RMSEA | SRMR | AIC | BIC | |
---|---|---|---|---|---|---|---|---|
Model 1 | 1422.632 | 492 | 0.821 | 0.833 | 0.078 | 0.056 | 25321.615 | 25580.103 |
AIC, Akaike’s Information Criteria; BIC, Bayesian Information Criteria; CFI, Comparative Fit Index; Df, Degrees of freedom; RMSEA, Root Means Square Error of Approximation; SRMR, Standardised Root Mean Residual; TLI, Tucker Lewis Index.
With regard to the Rasch analysis, good functioning of ratings was apparent in that each category featured as a unique point in the dataset and no disorder in the category thresholds was detected. The category probability curves were distributed from -7 to 7 logits. Proper ordering of categories was evident and each category measured a unique part of the underlying trait (see
Category probability curves for the 5-point rating scale.
As demonstrated, more than 75% of responses were captured by Categories 4 and 5 (
Category frequencies for the Rewards Desirability Inventory.
Response category | Observed | % | Infit MNSQ | Outfit MNSQ | Andrich threshold | Category measure |
---|---|---|---|---|---|---|
1 | 604 | 3 | 1.66 | 2.16 | NONE | (-2.38) |
2 | 1222 | 6 | 0.88 | 1.01 | −0.93 | −1.00 |
3 | 3251 | 16 | 0.93 | 1.03 | −0.55 | −0.07 |
4 | 6446 | 31 | 0.84 | 0.75 | 0.23 | 0.96 |
5 | 9331 | 45 | 0.96 | 0.97 | 1.24 | (2.56) |
MNSQ, mean of the squared residuals.
The Wright Map ranged from low (-2 logits) to high (5 logits). The higher a person scored on the latent construct, the more probable it was that the person would select a higher category (i.e. 4 or 5). In addition, item 14 was the most difficult to endorse, whereas item 5 was the easiest.
The average measures for both persons and items (indicated by the letter
Wright Map (Item or person locations).
With regard to unidimensionality, eigenvalues produced coefficients of < 2 upon inspection of the first contrast for all three dimensions (Linacre,
With regard to Factor 1, Items 9, 19 and 22 appeared to display some misfit. Specifically, the ICC for these items showed that individuals who scored low on Factor 1 were scoring higher than expected, and vice versa. The summary fit statistics are presented (
Summary item fit statistics.
Factor | Item | Measure | SE | Infit MNSQ | Outfit MNSQ | ||
---|---|---|---|---|---|---|---|
1 | RDI 19 | 0.66 | 0.05 | 1.39 | 6.12 | 1.49 | 6.87 |
RDI 22 | 0.63 | 0.05 | 1.52 | 7.87 | 1.80 | 9.90 | |
RDI 50 | 0.54 | 0.05 | 1.00 | 0.05 | 1.11 | 1.75 | |
RDI 26 | 0.39 | 0.05 | 0.98 | −0.25 | 1.04 | 0.68 | |
RDI 36 | 0.37 | 0.05 | 1.25 | 3.95 | 1.46 | 6.11 | |
RDI 4 | 0.26 | 0.05 | 1.19 | 3.01 | 1.37 | 4.92 | |
RDI 24 | 0.16 | 0.05 | 1.16 | 2.52 | 1.29 | 3.86 | |
RDI 27 | 0.16 | 0.05 | 0.97 | −0.47 | 1.09 | 1.31 | |
RDI 54 | 0.13 | 0.05 | 0.95 | −0.80 | 1.02 | 0.34 | |
RDI 9 | 0.07 | 0.05 | 0.95 | −0.81 | 1.14 | 1.87 | |
RDI 15 | 0.04 | 0.05 | 0.91 | −1.47 | 0.89 | −1.64 | |
RDI 43 | −0.07 | 0.06 | 0.88 | −2.04 | 0.86 | −2.02 | |
RDI 40 | −0.10 | 0.06 | 1.11 | 1.78 | 1.17 | 2.17 | |
RDI 47 | −0.11 | 0.06 | 0.74 | −4.49 | 0.73 | −3.99 | |
RDI 21 | −0.18 | 0.06 | 0.83 | −2.77 | 0.84 | −2.22 | |
RDI 37 | −0.18 | 0.06 | 0.77 | −3.85 | 0.71 | −4.18 | |
RDI 39 | −0.20 | 0.06 | 0.93 | −1.14 | 0.92 | −1.05 | |
RDI 32 | −0.21 | 0.06 | 1.02 | 0.32 | 0.93 | −0.92 | |
RDI 49 | −0.22 | 0.06 | 0.85 | −2.43 | 0.90 | −1.32 | |
RDI 18 | −0.30 | 0.06 | 1.03 | 0.42 | 1.12 | 1.52 | |
RDI 12 | −0.36 | 0.06 | 0.98 | 0.34 | 1.00 | 0.00 | |
RDI 28 | −0.40 | 0.06 | 0.83 | −2.81 | 0.75 | −3.32 | |
RDI 44 | −0.52 | 0.06 | 0.78 | −3.57 | 0.67 | −4.40 | |
RDI 5 | −0.57 | 0.06 | 0.95 | −0.80 | 0.93 | −0.82 | |
RDI 51 | 0.46 | 0.06 | 1.01 | 0.23 | 1.02 | 0.29 | |
2 | RDI 55 | 0.11 | 0.06 | 0.88 | −1.76 | 0.90 | −1.53 |
RDI 17 | −0.05 | 0.06 | 1.17 | 2.29 | 1.14 | 1.86 | |
RDI 60 | −0.10 | 0.06 | 0.99 | −0.06 | 0.98 | −0.22 | |
RDI 41 | −0.42 | 0.06 | 0.99 | −0.05 | 0.90 | −1.25 | |
3 | RDI 14 | 0.44 | 0.05 | 0.87 | −0.28 | 0.84 | −2.75 |
RDI 52 | −0.01 | 0.05 | 0.98 | −0.30 | 0.93 | −1.02 | |
RDI 11 | −0.21 | 0.06 | 0.97 | −0.43 | 1.02 | 0.26 | |
RDI 30 | −0.22 | 0.06 | 1.13 | 1.95 | 1.10 | 1.41 |
RDI, Rewards Desirability Inventory; MNSQ, mean of the squared residuals.
With regard to Factor 2, item 60 appeared to display misfit. The ICC for this item showed that individuals who scored low on Factor 2 were scoring higher than expected, and vice versa. A plausible explanation for this may be that individuals displayed extreme behaviour towards these items. The minor misfit of this item was taken into consideration, and further analysis was approached with caution. The mean infit and outfit MNSQ for persons were both 0.99 (SD = −0.10). In terms of the items, the mean infit and outfit MNSQ were 0.81 (SD = 0.13) and 0.82 (SD = 0.13), respectively. Item 51 was the hardest item to endorse (
With regard to Factor 3, inspection of the ICCs evidenced that no items appeared to display misfit. The mean infit and outfit MNSQ for persons were 0.96 (SD = −0.2) and 0.97 (SD = −0.10). In terms of items, the mean infit and outfit MNSQ were 0.99 (SD = −0.30) and 0.97 (SD = −0.50), respectively. Item 14 was the hardest item to endorse (
For Factor 1, the person reliability was 0.87, with a person separation index of 2.59. The item reliability was 0.97, with an item separation index of 5.83. Cronbach’s alpha was 0.95. For Factor 2, the person reliability was 0.62, with a person separation index of 1.27. The item reliability was 0.95, with an item separation index of 4.61. Cronbach’s alpha was 0.86. For Factor 3, the person reliability was 0.64, with a person separation index of 1.33. The item reliability was 0.96, with an item separation index of 4.76. Cronbach’s alpha was 0.81.
The aim of this study was to develop and validate the RDI to assess the extent to which individuals show preferences towards different types of rewards. The final measure consisted of 32 items. The dimensions were labelled as non-financial rewards, financial rewards and benefit and growth opportunities. These findings are partially consistent with the results from Khan, Shahid, Nawab and Wali (
This scale was developed in response to a need for a reward desirability scale that takes into account, not only financial rewards and non-financial but intrinsic psychological rewards as well. Although the hypothesised model was only partially supported, it is important to note that the non-financial rewards category consisted of both non-financial and intrinsic psychological rewards. The financial rewards category conformed as hypothesised whilst the benefits and growth opportunity category was unexpected. As such, it is important to review each dimension in relation to prior research. The first dimension was labelled non-financial rewards and consisted of both non-financial and intrinsic psychological rewards. A potential explanation of why these items may have loaded onto the same dimension is because both types of rewards were defined as intangible in nature (e.g. Jacobs et al.,
Through the application of a Rasch analysis, the researcher was able to further investigate the psychometric properties of the instrument. In accordance with the fit statistics, measures and thresholds for the categories, it was evident that the response categories performed adequately in accordance with Rasch Model expectations. The majority of the sample endorsed Categories 4 (‘very important to me’) and 5 (‘extremely important to me’) when specifying their preferences towards rewards. The item-person map confirmed these findings.
A potential reason as to why the majority of the sample felt that rewards were important to them is best explained by Herzberg’s two-factor theory (Herzberg et al.,
Findings of the Rasch analysis confirmed a three-factor structure (as supported by the factor analyses), with each subscale displaying unidimensionality. In accordance with the individual items for Factor 1 (non-financial rewards), Item 22 (‘Will keep my job regardless of my company’s economic problems’) displayed some misfit in the form of underfit. It was also the second hardest item to endorse. Bond and Fox (
In line with the reliability of the factors, internal consistency was acceptable for all dimensions. In addition, all factors evidenced adequate item reliability and item separation index coefficients, indicating that the sample size was adequate. For Factors 2 and 3, the person reliability and person separation coefficients were below the desired values as recommended by Linacre (
This article offers researchers and managers a tool to explore reward preferences more holistically and intricately. Specifically, those who are interested in exploring what employees ultimately value from their job can use this tool to detect which specific types of rewards employees seek from their working engagements. Moreover, this study offers a credible tool for data collection and analyses for the broader purpose of making sound reward-related decisions. This may be useful in business contexts pertaining to career development, attraction and retention, recruitment and selection and reward and remuneration.
It is particularly noted that this tool can be used to enhance talent management strategies in that managers will have improved insight into how rewards can be better implemented and distributed to suit individual preferences and needs. This article provides managers with awareness that the provision of intrinsic psychological rewards is as equally important as extrinsic reward offerings. Therefore, this study provides insight into why job tasks can be better structured to elicit positive emotional experiences felt by employees when engaging in their actual work. As previously alluded to, the combination of extrinsic and intrinsic psychological rewards can assist employees in delivering their finest performance and satisfying their needs. Having said this, managers could use this tool to identify suitable levers for non-financial and intrinsic psychological rewards, for example, identifying gaps in training and development or identifying how jobs could be redesigned to enhance employee work motivation and job satisfaction.
Firstly, participants were required to complete a self-report measure. Participants may have answered inaccurately as a result of social desirability bias. An alternative explanation for giving inaccurate answers may be attributed to participants misinterpreting item statements (item ambiguity or difficulty). It must be noted that this study serves as the first version of the RDI, thereby allowing for further development and refinement in future studies. Secondly, the sample of this study consisted solely of working South Africans. Generalising these findings to other countries should be carried out with caution. For future research purposes, it is recommended that the research method and sample be extended to international contexts. Thirdly, the three-factor solution was selected as suggested by theory. However, it was evident that the subscales partially supported the hypothesised dimensions. It is, therefore, recommended that future studies replicate the research results to determine whether three-factors do indeed underlie reward preferences.
This study reinforces the idea that there are multiple rewards which employees seek and value from their work. Therefore, total reward packages should be updated to focus more on non-financial rewards and particularly, on the inclusion of intrinsic psychological rewards. This study formed part of the second phase of a broader exploratory sequential mixed methods study to develop and validate the RDI. Underlying total rewards, and therefore, reward preferences are three dimensions: non-financial rewards, financial rewards and benefit and growth opportunities. After completing and interpreting scores from the instrument, managers can develop a better understanding of what employees seek from their work. In turn, managers can devise remuneration packages to suit individual employees’ needs so that employees are more motivated and satisfied in their jobs. Although the instrument should be subject to further scrutiny and refinement, the preliminary results of this instrument reveal satisfactory psychometric properties in the South African context.
The authors have declared that no competing interests exist.
The study was conducted by J.A.V. as part of her PhD in Industrial Psychology at the University of Johannesburg in 2020. C.H. was J.A.V.’s supervisor and edited the work for publication. Both authors contributed significantly to the conceptualisation and review of the study.
Ethical clearance was obtained from the research committee of the primary research institution. IPPM-2017-162 (D).
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
The data that support the findings of this study are available from the corresponding author (C.H.) upon reasonable request.
The views and opinions expressed in the article are those of the authors and do not represent the views of any affiliated institution.