Original Research

A total rewards framework for the attraction of Generation Y employees born 1981–2000 in South Africa

Mark H.R. Bussin, Keshia Mohamed-Padayachee, Philip Serumaga-Zake

Received: 14 Apr. 2018; Accepted: 11 Feb. 2019; Published: 11 July 2019

Copyright: © 2019. The Author(s). Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Orientation: The workforce is changing, as employers aim to attract qualified individuals from Generation Y, born 1981–2000, but strategies for attraction require adaption, as the ‘one-size-fits-all’ model no longer works for today’s multigenerational workforce.

Research purpose: Determining what changes and priorities organisations need to consider for their total rewards frameworks to attract youth employees.

Motivation for the study: Companies offer employees historical benefits that they do not want or value. This is important when one considers the attraction of Generation Y to organisations, as they are increasingly becoming a formidable factor in an organisations’ success and sustainability. The motivation for this study was understanding what rewards are aligned with the aspirations of this skilled generation, to attract them.

Research approach/design and method: A sequential mixed-method approach was followed, where data were collected, using quantitative and qualitative methods. A questionnaire was distributed and a response rate of 276 participants from seven of the nine provinces in South Africa achieved. Interviews were conducted where 11 participants validated the quantitative findings.

Main findings: Seven reward categories were found to affect Generation Y’s attraction to organisations, (1) leadership and environment (2) benefits (3) performance incentives (4) individual development (5) safe, secure working environment (6) work–life balance and resources and (7) performance recognition.

Practical/managerial implications: A different approach is required for the attraction of Generation Y.

Contribution/value-add: No empirical study exists that authenticates total rewards models for Generation Y, identifying the most important reward preferences and developing a new, more effective total rewards framework.

Keywords: generational theories; youth attraction; Generation Y; total rewards model; remuneration and benefits.

Introduction

Organisational environments are characterised by increasing shortages of skilled labour, and it has become imperative to design employment systems that prioritise human resources to create a competitive advantage (Holland, Sheenan, & De Cieri, 2007).

Human resource practice initiatives can help to attract skilled labour to gain and retain competitive advantage (Pahuja & Dalal, 2012). Rewards drive employee morale; therefore, employee rewards distribution has always loomed large in organisations (Appelbaum, Serena, & Shapiro, 2005). With labour costs sometimes accounting for more than 50% of the total costs of doing business, strategic management of human capital assets is of primary importance. For employees, an equitable rewards distribution system signals management’s emphasis on valuing employees (Datta, 2012).

Incentives play an important role in attracting, motivating, rewarding, energising and retaining employees, and a ‘one-size-fits-all’ plan is not appropriate for today’s multigenerational workplace (Nelson, 1999). Flexible work arrangements and other initiatives aimed at enhancing quality of life have universal appeal (Nelson, 1999).

The focus and purpose of the present study was to identify what rewards for attraction are important to skilled and qualified youth, Generation Y employees born in the years 1981–2000, regarding the reward categories of identified total rewards models.

Background to the study

The idea of total rewards emerged in the 1990s, and in 2000 WorldatWork introduced its first total rewards model. The WorldatWork total rewards model was intended to advance the concept of rewards and help practitioners think about and execute remuneration in new ways. From 2000 to 2005, the body of knowledge associated with total rewards became more robust as practitioners experienced the power of integrated strategies. During the past two decades, various total rewards models were published. Each approach presents a unique point of view, but all recognise the importance of leveraging multiple programmes, practices and cultural dynamics to satisfy and engage the best employees, contributing to improved business performance and results (Wang, 2012). It has become clear that the battle for talent involves much more than highly effective, strategically designed compensation and benefits programmes. While these programmes remain critical, the most successful companies have realised that they must take a much broader look at the factors involved in attraction, motivation, and retention. They must employ all the factors – including compensation, benefits, work–life, performance recognition, development and career opportunities – to their strategic advantage (Wang, 2012).

Understanding the external and internal rewards that incentivise skilled and qualified youths is important to determine what changes and priorities organisations need to consider for their total rewards strategies to attract youths entering the workforce. This study will inform organisations regarding the total rewards they can incorporate into their total reward strategies.

Trends from the research literature

Employers apply total rewards models without considering the differing needs of employees (Bussin & Toerien, 2015). Employers need to design reward practices that will support the achievement of business goals and motivate employees to perform at uninterruptedly high levels (Armstrong, 2010). Creating a combination of transactional and relational rewards is required to attract high-performance employees (WorldatWork, 2015). Further, while attraction has been closely related to transactional rewards, such as pay and benefits, more is required to attract this future workforce (Bussin & Toerien, 2015), which this study addresses.

Research objective

This study was intended to determine the reward priorities of Generation Y, representing youth employees born between 1981 and 2000, to develop a more relevant total rewards framework, compared to other generations, for their attraction to private and public organisations in South Africa. An objective of the study was to determine the reward priorities of youth employees to develop a more relevant total rewards framework for attraction.

In view of this, the study aimed to answer the following research questions:

• Which rewards factors attract Generation Y to organisations?
• How can a total rewards framework for the attraction of Generation Y be best conceptualised?

This study was aimed at developing a total rewards framework for the attraction of the youth by attempting to answer the aforementioned research questions.

Value-add of the study

The research results will aid the understanding of Generation Y reward preferences through an appropriate reward framework. The study further proposes a total rewards framework for the attraction of Generation Y, making a positive contribution to managing rewards in a challenging work environment, thereby contributing to existing literature. The study, thus, contributes to the body of knowledge and is beneficial to academics, practitioners and students in the field of human resource management.

What will follow

In the subsequent section the article provides a critical evaluation of the literature and summary of the themes emerging from the research findings, setting the context, highlighting the dynamics of the problem and demonstrating the importance of the research question.

Synthesis and critical evaluation of the literature

Generational theory

Today’s workplace consists of three generations – Baby Boomers (born 1946–1964), Generation X (born 1965–1980) and Generation Y (born 1981–2000) – who have each been influenced by the events of their time, therein creating new challenges for employers (Kapoor & Solomon, 2011). The research reviewed all three of these generations, with a specific emphasis on Generation Y as representing youth employees. While the outgoing generation of Baby Boomers and the existing workforce of Generation X have shaped the working environment of today, the emerging Generation Y will contribute to shaping the workforce over the years to come.

The South African National Youth Policy (2009, p. 39) defines ‘youths’ as persons between the ages of 14 and 35 years. This wide scope of youths includes those who have been exposed to different socio political and historical experiences and spans a 20-year life cycle.

Howe and Strauss (1991, p. 14) define a ‘generation’ as a unique cohort born within a period of about 20 years, whose boundaries are fixed by peer personality. The group encounters key historical events and social trends while occupying the same phase of life. Bell and Narz (2007) describe generations as defined by demographics and key life events that shape, at least to some degree, distinctive generational characteristics.

Based on these definitions, the researcher identified the parallel between the South African National Youth Policy (2009) and Howe and Strauss’s (1991) generational theories to describe today’s youth employee as opposed to those of the past. The study is focused on youths born from 1981 to 2000, aligned with the definition of the South African National Youth Policy (2009, p. 39) and the description of Generation Y of Howe and Strauss (1991, p. 14).

For a reward strategy to be effective, it is necessary to collect data on the preferences of employees, so that an organisation can devise appropriate rewards strategies and assess the influence thereof on employees’ attraction and retention.

This study used generation theory and selected total rewards models, with an emphasis on the WorldatWork (2015) total rewards model, to identify the potential rewards factors that attract the youth to organisations. The WorldatWork (2015) total rewards model provides a comprehensive list of monetary and non-monetary rewards to employees in exchange for their time, talents, efforts and results. These include the categories of remuneration, benefits, work–life balance, performance and recognition, and development and career opportunities, which are considered by organisations to be the preferences desired by older generations but not necessarily those of the youth. In addition, the model, unlike some of the other models reviewed, such as the Hay Group model (2008), does not consider work culture and climate, leadership and direction, work environment, a compelling future, and career (Dalton, Thompson, & Price, 1977; Hardigree, 2008; Lawrence, Arthur, & Hall, 1995) and environmental awards (see also Zingheim & Schuster, 2000).

Each generation’s priorities or preferences vary, as well as their views regarding work (Bussin & Toerien, 2015). It is increasingly important that organisations offer more of what future generations of employees prefer, rather than what organisations perceive they need (Angeline, 2011). The ideal, therefore, is to ask the youth what their preferences are. This study was therefore aimed at filling this gap by attempting to answer the aforementioned research questions and test the research hypothesis described later.

Total rewards systems

A total rewards system encompasses the reward framework for an organisation and the strategy to attract and retain talent (Armstrong, 2010; Hay Group, 2008; Towers Watson, 2012b; WorldatWork, 2015; Zingheim & Schuster, 2000). As the war for talent intensifies and competition between organisations increases, it is vital that companies create a competitive advantage in attracting and retaining talent (Holland et al., 2007). Per Tsede and Kutin (2013) and WorldatWork (2015), total reward is an integral element of reward management and is the combination of financial and non-financial rewards given to employees in exchange for their efforts.

Over the last decade, as the external environment has become more turbulent, organisations have sought initiatives to ensure the recruitment of a high-quality workforce (Bussin & Toerien, 2015). Many organisations have attempted to remedy this problem by simply offering increased pay (WorldatWork, 2015). While this may provide some respite in the form of a short-term solution, this approach may not deliver the best results (Angeline, 2011). Realising the shortcomings of this approach, some organisations have turned to wider reward mechanisms, but up to now none has managed to improve on the existing total rewards models (Silverman & Reily, 2003); this study was intended to close this gap.

There is no total rewards framework that has been developed based on the preferences of this generation. The objective of this study was therefore to develop a more comprehensive and effective total rewards framework for the attraction of youth to organisations. Some of the most popular total rewards frameworks were considered, namely, those of Armstrong (2010), Hay Group (2008), Towers Watson (2012b), WorldatWork (2015) and Zingheim and Schuster (2000). Table 1 provides a summary of the components of the selected total rewards models considered in the measuring instruments of this study.

The categories and associated elements as depicted in Table 1 were used to compile the survey questionnaire that was used to collect quantitative data during Phase I of the research and the interview questions that were posed to collect qualitative data during Phase II.

It was hypothesised that the youth of Generation Y are different from previous generations, as found by Angeline (2011), Bussin and Toerien (2015), Bell and Narz (2007), Holland et al. (2007) and Howe and Strauss (1991), and understanding what they prefer is critical to an organisation’s success; it is equal to understanding customers’ needs and wants. It is increasingly important that organisations offer more of what future generations of employees prefer, rather than what organisations perceive they need (Angeline, 2011). The ideal, therefore, is to ask the youth what their preferences are. This study was aimed at filling this gap by attempting to answer the first research question: ‘How can a total rewards framework for the youth be conceptualised best?’

The hypotheses derived from this research question were as follows: ‘There is an association between the reward categories (e.g. remuneration, benefits, performance recognition, etc.) that attract employees to organisations and the generation to which they belong’.

The key to attracting the youth in the workplace is understanding what they prefer and providing it in a way that they find meaningful. According to the literature, the youth are different from previous generations, and understanding what they prefer is significant to an organisation’s success (Bussin & Toerien, 2015).

The next section discusses the research design and approach adopted in this study and how the researcher went about answering the research question.

Research approach and design

The philosophies regarding research approaches that the researcher applied in this research study were ontology and epistemology. Both aspects of ontology, namely subjectivism and objectivism, were applied in this study. The researcher used a deductive approach and hypothesis testing to study phenomena and interpret the data. The epistemological position the present study took was to investigate what intrinsic and extrinsic rewards the youth value – what attracts them to organisations.

The pragmatic paradigm was applied in this study. Under this paradigm, researchers focus on the research question (Polit & Beck, 2012); to derive knowledge about the problem (Creswell, 2014; Polit & Beck, 2012). The researcher utilised a sequential mixed-methods approach to explore and guide the evaluation of the reward categories and elements of a total rewards model. Subsequently, it was determined what changes needed to be made on the existing WorldatWork (2015) total rewards model to develop a more effective total rewards framework for attraction of the youth to organisations.

Combining the quantitative and the qualitative methodologies was necessary. The qualitative results were used to explain and interpret the findings of the quantitative phase of the study (Creswell, 2014). In this study, the mixing of the two methodologies provided the ability to statistically analyse the scientific data, while recognising the environmental factors that influence the youth’s decision-making. Qualitative methods were used in the first phase of the study to explore the phenomenon and come up with the hypothesis to be tested using quantitative methods in the second phase. Then factor analysis was completed to categorise the key concepts into rewards categories that comprised the building blocks of the framework.

Research methodology

Data were firstly collected through questionnaires. A survey questionnaire was used to collect quantitative data from professional and organisational databases and face-to-face distribution, and it reached participants from seven of the nine provinces in South Africa. Other responses, 0.39%, came from Swaziland and the Ivory Coast. Respondents from the other generations came from the population of employees in organisations where the questionnaire was distributed and professional databases and from colleges and universities. Thereafter, abstract and descriptive research, in the form of semi-structured interviews, was conducted.

Phase II entailed a qualitative study in which interviews were conducted to collect detailed qualitative data to explain and interpret the results of Phase I. A semi-structured interview guide was used. Rich and in-depth information aided validation of the preliminary conclusions drawn from the quantitative data collected in Phase I, by adding explanations and interpretations of the identified significant relationships between the key variables and the factors that are considered to affect the attraction of the youth in organisations. The qualitative results filled the gaps in the explanations and interpretations of the results of the quantitative research.

Target population and sample

The target population for the quantitative phase of the study comprised undergraduate and postgraduate students from colleges and universities in Gauteng, Cape Town and KwaZulu-Natal, as well as qualified and skilled employees including youth working in both private and public organisations. In addition, the researcher distributed the questionnaire to organisation and professional databases.

The target population for the qualitative phase of the study included youth respondents, managers and human resource (HR) professionals residing in Gauteng Province, one of the most densely populated provinces in South Africa based on the population data of South Africa Central Statistic Services (2013), representing both the public and private sectors while ensuring representation from the other provinces through electronic distribution of the questionnaire.

Sampling methods

Non-probability methods (i.e. convenient, snowball and purposive sampling methods) were applied. Convenient sampling as applied ensured that inputs were received from qualified youths and industry experts. Snowball sampling was applied to locate potential key informants. Purposive sampling was used with specific characteristics such as age and skilled employees, ensuring that the right decisions were made about which interviewees were best suited to the study and could provide the required information (Burns & Grove, 1993; De Vaus & De Vaus, 2001), using a selection criterion that was based on the researcher’s expert opinion (Tongco, 2007).

Quantitative methods

Draft questionnaires were distributed, using convenience sampling, to a pilot group of 10 respondents, as no previous questionnaire existed for research of this nature. The questionnaire was validated, and changes were made by modifying and making the questions clearer before it was administered. The researcher distributed 450 questionnaires, of which 276 usable questionnaires were received – a response rate of 61.3%. Of the 276 questionnaires, 72.88% came from respondents in private (52.23%) and public (20.65%) organisations, 14.17% came from those in universities and 13.12% represented other sectors.

Over-sampling ensured that the researcher received enough responses to represent each different generation (i.e. sample size of 450). The highest frequency of responses was from respondents born 1981–2000 (57.14%); the second-highest response rate was from respondents born 1965–1980 (33.2%), and the lowest was from respondents born 1946–1964 (9.65%). This represented the profile of the current age demographics in the work environment, with the youth being the next-largest generation in the workforce, followed by those who will soon retire (Borngraber-Berthelsen, 2008).

The 9.65% responses from respondents born 1946–1964 might not have been adequate to do a comprehensive comparison, so the results need to be interpreted with caution in this regard. However, by using the mixed-methods approach, the researcher succeeded in triangulating the data, which increased the validity and reliability of the study. The sample size was based on the central limit theorem, which recommends that the sample size should be at least 30 for the normality assumption not to be violated regardless of the shape of the distribution (Ghasemi & Zahediasl, 2012).

The questionnaire as a measuring instrument included a section requesting demographic data to compile a demographic profile of the respondents. Table 2 provides a summary of the demographic questions. These questions yielded facts about the respondents, which the researcher analysed according to frequency, to determine the profile of respondents born from 1981 to 2000, to compare it to the profiles of employees born from 1946 to 1964 and 1965 to 1980.

In the next section of the questionnaire, 30 closed-ended matrix questions for attraction were answered using the Likert scale, which provided respondents with a standardised set of response choices based on five categories, ranging from 5 (very important) to 1 (not important at all). The closed-ended questions were a combination of facts, knowledge and intent related to reward categories and elements from the total rewards models (remuneration, benefits, performance recognition, career development and work–life) and other literature (safety and security and social support), as described in Table 1.

The questionnaire further included open-ended questions testing if the researcher had excluded any reward elements available in the respondents’ organisations or the larger external environment that they deemed important. In addition, rank order questions were included. Respondents had to rank their reward preferences on the Likert scale from 1 to 5, with 1 being the least important and 5 the most important.

Research participants

Table 3 provides a summary table of the profile of the respondents who participated during the quantitative phase of the study.

Data analysis of the quantitative methods

Statistical data analysis was used to profile the respondents born from 1981 to 2000 (i.e. Generation Y) compared to the profiles of employees born from 1946 to 1964 (i.e. Boomers) and 1965 to 1980 (i.e. Generation X). Frequency distributions, standard deviations, means, graphs and charts were used. Multivariate analysis was then conducted, to compare the results by birth year group, total rewards elements and demographic characteristics to determine if there were significant relationships between the three generations. Multivariate statistical analyses and non-parametric tests included chi-square tests and Kruskal–Wallis and factor analysis, which were performed to test the null hypotheses. The Kruskal–Wallis test was used because the assumption of the chi-square test that none of the cells of the contingency table should have an expected frequency of less than five was violated and the variables were grouped by year of birth.

Reliability and validity of the scale

Cronbach’s coefficient was used to measure the reliability of the questionnaire. The results of 0.827 for attraction for the 30 items were deemed a good result, as these indicated a high degree of reliability and consistency of the questionnaire items (Hair, Black, Babin, Anderson, & Tatham, 2006).

Qualitative methods

The researcher conducted semi-structured interviews. The interview guide was developed based on the set of themes derived from the questionnaire utilised in Phase I of the research. The questions were then aligned with the hypotheses being tested, the research objectives and the outcomes of the quantitative research.

For the qualitative phase, race and gender profiles of the interviewees were diverse and well represented. Of those interviewed, three were married and eight were single or had never been married. Of the eight interviewees, seven were living on their own and one was living with parents. Years of birth ranged from 1981 to 1990, and experience ranged from 2 weeks to 14 years.

The interview guide contained predetermined themes and open-ended interview questions that were formulated by the researcher, as no relevant interview guide existed. A pilot interview was conducted to determine the understanding of the question and duration of the interview. Following the pilot interview the researcher, who was the interviewer, was satisfied with the outcome data which were gathered by means of 11 interviews.

The interviews were audio-recorded, except for the telephonic interviews. The sample size was guided by the saturation point principle (Mason, 2010). The interviews were fully transcribed verbatim using transcription software (https://transcribe.wreally.com). The two telephonic interviews were transcribed from handwritten notes immediately following the telephonic interviews.

Data analysis of the qualitative methods

The data was categorised into themes, trends and patterns, around which a narrative was written. Member checking was conducted by comparing answers of participants for understanding of the questions posed and where required additional explanations were provided. Following the quantitative data analysis, the preliminary findings were shared during the interviews, which allowed participants to validate the preliminary findings, provide additional information and inputs if necessary. The participants were able to explain the relationships found through the analysis of the responses to the questionnaires.

The frequency analysis of the codes was then conducted. Spearman’s rho (also Spearman’s rank correlation coefficient) was calculated to determine if there was a relationship between the groups’ codes, based on frequency values. There was no requirement for normality, as it is a non-parametric statistic.

Reliability and validity

Using the mixed-methods approach and triangulation increased the credibility of the data. The researcher conducted the interviews, ensuring the interviews were electronically recorded and then transcribed; data collection was not limited to taking notes during the interviews, which guaranteed that no information was missed or misinterpreted during the analysis.

Ethical considerations

Ethical clearance was granted by the University of South Africa (UNISA) Ethics Committee. Approval was received from the professional associations. A publicly funded institution gave the researcher permission to conduct the research, followed by a parastatal. During the research, the researcher gained permission from professors and senior lecturers to distribute the survey questionnaires to graduate and postgraduate students. Participation was voluntary, and informed consent was obtained from each participant. Participants were assured that the information they shared would be kept confidential and that their anonymity was guaranteed. Research Ethics Review Committee (GSBL CRERC) Ref no: 2015:SBL/DBL_019_FA.

Results

Respondents answered the quantitative questions on a defined Likert scale, and the results from these responses are presented in Table 4 by the total rewards element (in the left column), with corresponding year of birth across and frequency of response downwards. The highlighted numbers indicate the highest percentages by group.

Considering the results in Table 3, the highest degree of similarity was found between the three groups, 1946–1964, 1965–1980 and 1981–2000, for career and growth opportunities, learning and development opportunities, resources, retirement fund, supportive management and salary or pay. The 1981–2000 group scored highest for career and growth opportunities, learning and development opportunities, retirement fund, medical aid and salary or pay. For respondents born 1965–1980 and 1981–2000, the lowest-scored reward elements included smaller bonuses intermittently and lower base salary with unlimited bonus potential.

Figure 1 shows the top seven preferences for the three groups, 1946–1964, 1965–1980 and 1981–2000, for attraction based on the results of the frequency analysis in Table 3.

FIGURE 1: Quantitative findings: Top seven rewards for attraction.

Frequency distribution for attraction

Table 5 below describes the frequency distributions of the variables used to investigate the factors of attraction of the youth to organisations. For the group born 1946–1964, the median was high, ranging between 3 and 5, indicating that most respondents gave positive responses, except to higher base salary with limited bonus. The distributions were negatively skewed, indicating that there was less variability in this group and, therefore, more consensus.

For the groups born 1965–1980 and 1981–2000, the median was high, ranging between 4 and 5 in most instances, indicating that most respondents gave positive responses and there was a high degree of consensus within the groups. The standard deviation was relatively small, and the data were concentrated near the mean. The distributions were negatively skewed.

Total reward categories’ ranking

In this section of the questionnaire, the researcher tested how respondents would summarise their preferences. The question was further included to test the consistency in responses against that of the previous section. The question posed in the questionnaire was: ‘On a scale of 1 to 5, with 1 being the least important and 5 the most important, how do you rank the following by importance when deciding to join an organisation?’ (i.e. remuneration, benefits, social support, security and safety, work–life, career development opportunities and performance recognition).

Table 6 provides a summary of the groups’ responses; the highlighted areas are the top-ranked categories, greater than 50% for attraction, as these are the ones that were considered for the developed total rewards framework for the youth. The results indicated that the group born 1946–1965 had strong preferences, with performance recognition ranked highest for this group for attraction followed by career development and remuneration. For the group born 1965–1980, the highest ranked for attraction was remuneration. The top-ranked for the group born 1981–2000 was career development.

Hypothesis testing results for attraction

The researcher tested evidence from the sample that either supported the hypothesis (H0) or rejected it and supported the alternative hypothesis (Ha). A non-parametric test was used to verify the equality of variances in the sample (homogeneity of variance) – p> 0.05 (Nordstokke & Zumbo, 2010). The Kruskal–Wallis test, a non-parametric test, was performed to test the null hypotheses because the assumption of the chi-square test that none of the cells of the contingency table should have an expected frequency of less than 5 was violated. Variables were grouped by year of birth.

The significance level of the chi-square value (i.e. probability) being > 0.05 indicated that there was no statistically significant association between 20 of the 30 variables and that the null hypothesis was not rejected. Ten showed a significant difference between the youth generation born 1981–2000 and the previous generations born 1946–1964 and 1965–1980. The alternative hypotheses for these elements were correct; however, because for more than 50% of elements the null hypotheses were not rejected, the overall finding was that, for attraction, the youth have rewards preferences like those of previous generations. Figure 2 presents the hypothesis outcomes of the significant differences for attraction.

FIGURE 2: Hypothesis test summary of significant differences for attraction.

Based on the results from the quantitative findings, leave proved to be more important to youths than to the other generations. Furthermore, the youth value employee discounts more than what the other generations do. The results for higher base salary with limited bonus potential and lower base salary with unlimited bonus potential indicated that the youth do not value these two components. The results imply that leave is the reward preference for the youth and should be considered by organisations when trying to attract them.

From the findings, although it appears that career development is important to all age groups, it is more important to youths than to older generations. This might be explained by the mere fact that at a young age, an employee aspires to develop his or her career unlike an older person, who in most cases might have developed his or hers already. This was the same for the results for career and growth opportunities, learning and development, experience working in different organisations to maximise career growth and experience working in different organisations to maximise career earnings potential, these are important to all age groups but more important to youths than older generations. The preference of youths regarding long-term job security and a safe work environment is different to that of older generations.

Factor analysis

Factor analysis was then completed, using IBM SPSS^® software, to determine the common factors among the observed correlated variables. Data were summarised so that relationships and patterns could easily be interpreted and understood (Yong & Pearce, 2013). Based on the scores, factor analysis looked at the similarities and differences between the scores observed; the variables of interest of the objects were then grouped into clusters with others with similar scores (Diamantopoulos & Schlegelmilch, 2000). Table 7 provides a summary outcome of all 30 variables for attraction. Nine components were extracted from the data, which explained 67.4% of the variability in the data for attraction.

Ranking the reward factors from the quantitative and qualitative findings

The youth reward preferences identified from the results of the frequency analysis for attraction of the youth to organisations in order of importance were: (1) career development, (2) benefits, (3) remuneration, safety and security, (4) resources, (5) social support, (6) safety and security and (7) career development and work–life.

Factor analysis extracted nine reward preferences for attraction. The ranking of the reward factors determined in the study through factor analysis was (1) social support and environment, (2) benefits, (3) performance incentives, (4) career and individual development, (5) work–life, (6) informal recognition, (7) remuneration and formal recognition, (8) traditional remuneration and (9) non-traditional remuneration. This implies that the most important reward preferences for the youth, in order of importance, are (1) social support, development and environment, (2) benefits and (3) performance incentives.

The results from the qualitative findings determined the association between the total reward categories for attraction. From the qualitative data analysis, the top reward preferences were found to be (1) leadership and environment (emerged theme), career development, security, flexibility and pay; (2) benefits (retirement fund, medical aid, leave); (3) performance incentives (long- and short-term incentives, share options); (4) individual development, a safe and secure working environment; (5) work–life and resources (employee discounts, extended time off, tools to execute work, wellness); (6) informal recognition and non-financial rewards; and (7) formal recognition and lump sum annual bonus payments. These categories were created by factor analysis.

The results of the quantitative research were then integrated with the results of the qualitative research, which informed the development of a new total rewards framework. After integrating the results from the quantitative and qualitative findings, for attraction, the top reward preferences were found to be (1) leadership and environment, career development, security, flexibility and pay; (2) benefits (retirement fund, medical aid, leave); (3) performance incentives (long- and short-term incentives, share options); (4) individual development, a safe and secure working environment; (5) work–life and resources (employee discounts, extended time off, tools to execute work, wellness); (6) informal recognition and non-financial rewards; and (7) formal recognition and lump sum annual bonus payments. The framework is shown in Figure 3.

FIGURE 3: Total rewards framework for the youth.

Based on the findings, the existing total rewards models are relevant as proposed by the different authors, but a model that better reflects the preferences of the youth would be more effective.

Discussion

This study set out to evaluate the effectiveness of the reward categories of the total rewards models and other elements for attraction, with specific emphasis on the youth. The aim was to identify the factors of attraction of the youth and, subsequently, to develop a more relevant total rewards framework for the youth by improving on the existing total rewards models, such as that described by WorldatWork (2015). It aimed to answer the following research questions:

• Which rewards factors attract Generation Y to organisations?
• How can a total rewards framework for the attraction of Generation Y be conceptualised best?

To ensure rigour and enhance the credibility of the study, the researcher assessed whether generational theories could be applied as predictors of what would attract the youth. The study utilised the reward categories of the identified total rewards models, customised with elements from the literature.

Generational theory

The findings, based on the similarity of the responses in the quantitative and qualitative phases of the research, support the literature and the similarities between generations posited by Howe and Strauss (1991, 2007), who developed similar collective personae. The research highlights that each generation has distinct characteristics that affect how the war for talent is waged (Twenge, 2010) and will therefore require a different approach for attraction. This implies that, if the framework is applied in an organisation, the organisation will be able to attract the youth more effectively, because it includes all the preferences of the youth.

After addressing the objectives, the researcher was able to develop a more effective total rewards framework for the youth and answer the research questions. The total rewards framework for the youth that was developed after considering all the important preferences of the youth is shown in Figure 3. This new framework can be regarded as an improved or modified version of the WorldatWork (2015) framework, with additional reward components.

A total rewards framework for the attraction of Generation Y employees born 1981–2000

Leadership, environment, career development, security, flexibility and pay

In the present study, according to the qualitative data analysis, leadership and environment was rated the highest of all the categories, for attraction. This included the elements supportive management and work environment, resources, safe and secure work environment, career and growth opportunities, learning and development opportunities, longer-term job security, salary or pay and flexible work arrangements.

Supportive management and work environment

It is clear from the results that organisations that focus on leadership and developing talent will be in a stronger position to retain key employees as the war for talent intensifies (Boxall & Purcell, 2011). Like the WorldatWork (2015) total rewards model and some other models, the themes of culture and work environment emerged in response to the open-ended questions in the quantitative phase of the study, which the researcher grouped with supportive work environment. This was validated during the qualitative phase, when interviewees indicated that the culture of an organisation was very important for attraction of the youth.

Resources

Youths value tools and devices, to the point that they would use their own in the workplace. The devices and tools given to them to perform their work were rated as very important in both the qualitative and quantitative phases of the research.

Safe and secure work environment

The elements that formed part of this category for attraction were long-term job security and safe and secure work environment. Long-term job security and a safe and secure work environment are important to the youth.

Longer-term job security

Longer-term job security (>12 months) was ranked as very important in the quantitative phase, and in the qualitative phase it was important for some of the youth interviewed but not all. Long-term job security is important to the youth, but they consider pay more important. They will also sacrifice security for job satisfaction and opportunities to grow and learn. They are not afraid of risks but take calculated risks, as purported by Howe and Strauss (2007).

Career, growth and learning and development opportunities

These elements represent opportunities designed to enhance employees’ applied skills and competencies. As described by WorldatWork (2015) in their total rewards model, development encourages employees to perform better and enables leaders to advance their people strategies. This aspect includes a plan for employees to advance their own career goals and may include advancement to a more responsible position in an organisation. The organisation supports career advancement internally, so that talented employees are deployed in positions that enable them to deliver their greatest value to the organisation (Quinn, Anderson, & Finkelstein, 1997).

Salary or pay

The respondents rated an attractive salary or pay as important. The qualitative phase of the present study indicated that companies need to pay market-related salaries to attract the youth. Salary and other monetary benefits are a significant consideration for the youth, as they are for previous generations. This finding supports those of Martin and Tulgan (2006) and Rollsjö (2009). The qualitative phase of the research illustrated that youths are not unrealistic about their earning potential, but they do want to be paid market-related salaries. They are also aware that their qualifications and years of experience impact their earning potential. This result contradicts the literature stating that promotion is very important to members of Generation Y but that they want this with minimal effort, perhaps reflecting a sense of entitlement that is the product of a pampered upbringing (Ng, Schweitzer, & Lyons, 2010, Corporate Leadership Council [CLC], 2008). This generation ‘wants it all and wants it now’ in terms of better pay and benefits, rapid advancement, work–life balance, interesting and challenging work, and contributing to society (Ng et al., 2010, p. 282). The reason for this was not investigated in the present study.

Benefits

Benefits ranked second in importance for attraction. The study found that the most important benefits, in rank order, are retirement fund, medical aid and leave. A benefit that youths find important that emerged from the quantitative phase of the present study was study leave. They want a work–life balance and therefore do not want to take annual leave when their study leave becomes depleted. Youth find the current allocation of study leave insufficient. Sabbaticals or other scheduled time reductions were ranked fifth for attraction.

Performance incentives

Ranking third for attraction was long- and short-term incentives and share options.

Career and individual development

Ranking fourth for attraction, career and individual development includes formal coaching or mentoring programmes, experience working in different organisations to maximise career progression, experience working in different organisations to maximise career earnings potential, corporate social responsibility and a 13th cheque.

Work–life balance and resources

Ranking fifth for attraction, this factor included employee discounts, sabbaticals or other scheduled time reductions, the employee wellness offering and flexible work arrangements. Analysis of the responses to the open-ended questions in both the quantitative and qualitative phases highlighted the importance of a work–life balance to the youth.

Recognition

Recognition ranked sixth for attraction. The elements included in this factor are informal recognition, and non-financial rewards. Being recognised and rewarded is a need of the youth. This research found that both formal and informal recognition motivate them, but not in equal measure. Formal recognition was rated higher than informal recognition in the questionnaire section of the study, and informal rated higher during the interviews.

Formal recognition

This research found that formal recognition drives and encourages the youth. This finding supports that of Rollsjö (2009). Youths grew up receiving rewards for good behaviour and are expecting the same in their work life.

It was found that both formal and informal recognition are motivational. Spontaneity and fun in the work environment appealed to 60% of the youth interviewees. One of the themes that emerged during the interviews was the need of young employees to receive feedback. When they do not receive this feedback, they will source it from their managers.

The researcher considered the results of both Phases I and II and reviewed the literature, to develop an accurate and defendable set of rewards for the youth; these rewards were investigated empirically.

This new framework can be regarded as an improved or modified version of the total rewards framework, with additional reward categories. This implies that, if the framework is applied in an organisation, the organisation will be able to attract and retain the youth more effectively, because it includes all the preferences of the youth. The framework was informed by a scientific study, in which the data that were collected were objectively analysed.

The sample of college and university students might have had a negative impact on the findings of the study and consequently its credibility because of its being a homogeneous sample that lacked a wide range of perspectives. Furthermore, the racial composition of the sample might also have impacted negatively on the representativeness of the sample.

Conclusion and recommendation

The preceding sections summarised the research findings. This section offers recommendations based on the study findings and makes recommendations for future research.

The findings of the present study support those of the CLC (2008) that customised reward frameworks positively impact levels of skilled labour attraction to organisations, leading to greater levels of productivity and improved organisational performance. A different approach is required for the attraction of the youth, and the one-size-fits-all approach of the past will not be sufficient in the future. For organisations to survive in the long-term, they need to offer customised solutions for attracting and retaining the youth.

Future research opportunities

The focus of this research was on the rewards preferences of skilled, and undergraduate and postgraduate young employees. Future studies could include non-graduates.

Acknowledgements

The author would like to thank the University of South Africa, School of Business Leadership for their assistance in conducting this research.

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

M.H.R.B. was the principal supervisor and was responsible for the design of the project and writing up the article. K.M.P. was the researcher and responsible for the design of the project, fieldwork and writing up the research and article. P.S.-Z. was the assistant supervisor and was responsible for writing up the article.

Funding for this study was provided by the University of South Africa, School of Business Leadership.

Data sharing is not applicable to this article as no new data were created or analysed in this study.

The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.

References