Happiness Index for Human Resource Management Practitioners Associated with the Professional Body

The study explored the perceptions of human resource management (HRM) practitioners in South Africa, using the following happiness dimensions: positive emotions, job-related wellbeing, affective commitment, employee engagement and distributive justice. The research approach was quantitative, and the research design was descriptive and longitudinal (i.e. over a two-year period). The convenience sampling technique was used to select participants. In 2016, the sample size was 204, and in 2017, the sample size was 76. The data were collected at the conventions hosted by the Institute of People Management (IPM). The major findings were that the majority of the participants were females, were employed on a full-time basis, had degrees, earned R40 000 and above, and were not unionized. Participants rated the positive emotions negatively, suggesting that they were disaffected with their remuneration, and they rated the job-related wellbeing, affective commitment, employee engagement and distributive justice items positively. The implication of this study for policymakers is that they must review their remuneration policy and practices. The implication for managers is that they might struggle to keep HRM practitioners effective, motivated, and having cordial relationships.   

profit targets. In this study, the dimensions of happiness index discussed are positive emotions, job-related wellbeing, affective commitment, employee engagement and distributive justice.

Job-Related Wellbeing:
Another happiness index dimension with almost the same definition as positive emotions is job-related well-being. However, it is related to energy, inspiration, fulfilment and excitement (Bakker & Oerlemans, 2011;Keeman, Naswall, Malinen & Kuntz, 2017;Kirsten, Van der Walt & Viljoen, 2009;Rodríguez & Sanz, 2013), which leads to organizational success (Page & Vella-Brodrick, 2009). The study conducted by Warr and Inceoglu (2017), which comprised of two groups, found no significant differences between them in relation to wellbeing.

Affective Commitment:
A happiness index dimension that may ultimately enhance employees' loyalty to organizations is known as affective commitment (Abdullah, Ling. & Peng, 2016;Ghaffaripour, 2015;Ha & Ha, 2015;Hechl, 2017;Lambert, Kim, Kelly & Hogan, 2013;Simons & Buitendach, 2013;Toga, Qwabe & Mjoli, 2014). It is suggested that employees who are affectively committed to their organizations are productive, do not take leave on a regular basis, and do not resign from their organizations (Akar, 2018). Studies in India and the Orange County Interscholastic Athletic Association (OCIAA) in the United States of America found no differences in the affective commitment scores of men and women employees (Sharma, 2015;Rainayee & Zaffar, 2013;Voloshin, 2017).

Employee Engagement:
A happiness index dimension that is closely related to job-related wellbeing is employee engagement (Albrecht, 2012). Employee engagement refers to employees' cognitive (Moradi, Jafari & Abedi, 2005;Shuck & Wollard, 2010) and emotional attachment to their roles (Bakker & Schaufeli, 2014;Rich, Lepine & Crawford, 2010), which leads to an employee being motivated to do more at work (Joo & Lee, 2017). One element that distinguishes it from positive emotions and job-related well-being is that it is related to successful implementation of the organization's strategy (Maleka, Schultz, Van Hoek, Dachapalli & Ragadu, 2017), especially when union members are involved (Maleka, 2018;Nienaber & Martins, 2016). The empirical research by Wilson (2009) found no difference between the participants with supervisory job titles and non-supervisors. A recent study conducted by Vorina, Simonic and Vlasova (2017), found that there is no difference between gender and employee engagement. Similarly, Tshilongamulenzhe and Takawira (2015) found that male and female employees demonstrated almost equal levels of engagement to their work.
Distributive Justice: Whereas the other happiness index dimensions discussed above are about emotions and strategy implementation, distributive justice is" the perceived fairness of outcome one receives" (Ha & Ha, 2015, p. 109) based on income (Bayarcelik & Findikli, 2016;Ohana & Meyer, 2016). and job (Demir, 2016). Employees who deemed work practices to be fair were happy, and performed optimally (Kalay & Turkey, 2016;Nasurdin & Khuan, 2011). Hataman, Fardid and Kavosi (2013) study found no differences in the distributive justice scores of nurses in general and speciality in Shiraz's hospitals. Distributive justice originates from Adams' (1965) equity theory. Akram, Qamar, Answer, Malik and UI Haq (2015) compared organizational justice and commitment in public universities in Pakistan, and found that there is no statistically significant difference between the scores of male and female university teachers. In another study, Brienza and Bobocel (2017) found that there was no statistically significant difference between the distributive justice scores of younger and older employees. However, Mendryk's (2017) study on the impact of procedural and distributive justice on the organizational commitment of employees of different ages found a difference in the distributive justice scores of younger and older age groups. The literature clearly shows the paucity of studies that measure the happiness dimensions' index of HRM practitioners attending a professional body convention. Some of the previous research found no significant difference in terms of age (Brienza & Bobocel, 2017) and gender (Vorina et al., 2017). The research methods used to achieve the study objective are discussed in the next section. The majority of the participants were permanently employed. This appears to suggest that their organizations invested in their skills development, as the cost (i.e. around R10 000.00) of their convention attendance included convention fees and accommodation.

Methods
The discussion in this section focuses on the research design, participants' biographical data, the research procedure, measuring instrument, and data analysis.

Research Design and Participants' Biographical Data:
The research design was longitudinal (i.e. i.e. over a two-year period). The convenience sampling technique was used to select participants. As it can be observed from Table 1 below, in 2016, 250 questionnaires were printed and only 204 were completed, while 3 had missing information, and were therefore discarded. The majority of the participants were females (56.57%), were employed on a permanent basis (96.47%), had degrees and post-graduate qualifications (78.20%), ranged in age from 35 to 65 (7.30%), earned R40000 and above (62.24%), and were not unionized (64.32%). Seventy-six questionnaires were completed in 2017 and 200 questionnaires were distributed. The response rate was 39%. The 2017 data revealed that 68.52% of the participants were females, 96.05% were employed on a permanent basis, had degrees and post-graduate qualifications (94.80%), ranged in age from 35 to 65 (72.37%), and earned R40000 and above (60.53%). Almost sixty-seven percent (66.70%) of the participants were not unionized. Procedure: Ethical clearance for this study was granted by Tshwane University of Technology (TUT). Content validity was achieved by presenting the research instrument to human resource department experts (Struwig & Stead, 2013) at TUT. Once ethical clearance was granted, one of the researchers who attended the IPM convention took the research instrument to the convention, and in both years, the master of ceremonies informed the HRM practitioners about the objective of the study. HRM practitioners participated voluntary, and their confidentiality and anonymity were guaranteed by not writing their names and contact numbers on the questionnaires.

Measuring Instrument:
The questionnaire used to biographical (see Table 1) and happiness related data. The following happiness index scales were used to collect the data: positive emotions and job-related wellbeing (Van Katwyk, Fox, Spector & Kelloway, 2000), affective commitment (Allen & Meyer, 1990), employee engagement (Schaufeli & Baker, 2003) and distributive justice (Price & Mueller, 1986). Respondents rated 24 items in the study on a 7-point Likert scale (1 =strongly disagree to 7 = strongly agree).
Data Analysis: Descriptive statistics were frequencies and means and standard deviations. Principal components analysis (PCA) was used to extract items (Leedy & Ormrod, 2015). The T-test was calculated to determine group differences (Bless, Higson-Smith & Sithole, 2013). The data were analyzed in the Statistical Package of Social Sciences (SPSS) version 25.

Results
In this section, factor analysis, means and standard deviations and T-test are discussed.
Factor Analysis: It can be argued that construct validity was achieved because the Kaiser-Meyer-Olkin (KMO) since was above 0.80 (Melewer & Alwi, 2016), and the KMO and it was above the threshold of 0.5 limit recommended by Field (2013). The Bartlett's Test of Sphericity was statistically significant, with p<0.5 (Pallant, 2016). PCA components revealed the presence of five happiness dimensions with eigenvalues above 1, explaining 56.52% of the total variance. The rotated solution revealed a five-factor model (refer to Table 2), where the first factor was labelled positive emotions, with four statements or items. The item with 0.96 loading was, "I generally feel inspired about my remuneration", and the second factor, with four items, was labelled job-related well-being and had four items. The highest item of job-related wellbeing, with a factor loading of 0.99, was, "My job makes me excited." The third factor was labelled affective commitment, and it had two items. The highest item on affective commitment had a factor loading of 0.96, and it was, "I feel emotionally attached to my organization." The fourth factor was labelled employee engagement, and it had two items. The highest item on employee engagement had a factor loading of 0.90, and it was "When I am working, I forget everything around me." The fifth factor was labelled distributive justice, and it had three items. The highest item on highest distributive justice had a factor loading of 0.93, and it was, "Overall the rewards I receive here are quite fair." The cut-off point to include items in the factor loading was 0.3 (Field, 2013;Pallant, 2016). The Cronbach's alphas ranged from 0.78 to 0.98, which suggests that the happiness index dimension or factors were reliable (Maree, 2016). The data presented in Table 3 show that the 2016 group had slightly higher positive emotions mean score (M=3.84, SD=1.70) than the 2017 group (M=3.73, SD=1.66). Since their mean scores were below 4, it can be argued that HRM practitioners were not happy with their remuneration. Participants rated other happiness index dimensions (i.e. job-related wellbeing, affective commitment, employee engagement and distributive justice) positively, since their mean scores were above 4. Prior to conducting the statistical difference test, the researchers conducted a normality test using the skewness test, and found that the skewness values were less than +-1 (Leech, Barrett & Morgan, 2015). The P-P plots centred on the diagonal straight lines (Pallant, 2016) of the happiness index dimensions. These statistics suggested that the data were normally distributed. Based on these statistics, the researchers deemed the T-Test an appropriate statistic to determine if there are statistically significant differences in the happiness index dimensions. The data displayed in Table 4 below showed that there is no statistically significant difference in the happiness index dimension means scores of two groups (i.e. HRM practitioners who attended the 2016 and 2017 IPM conventions). Consistent with previous research in this area, the data in this study revealed that HRM practitioners rated positive emotions (i.e. remuneration items) negatively (Maleka, Mmako & Swarts, 2017). The results were surprising because the majority of the respondents earned R40 000 and above.

Discussion:
The trend looked similar to the living wage study that was conducted on low-income workers who earned between R1500 to R4500 (Maleka, 2016). This might have negative managerial implications for organizations, as other scholars have found that unhappy employees are not effective (Rodriques & Sanz, 2013;Weserat et al., 2014), motivated (De Neve et al., 2013), and they end-up having bellicose or adversarial relationships with managers (Roehling et al., 2000). The data showed that most participants were aged 35 years and above. This suggested that most of the HRM practitioners were not millennials, as millennials are aged between 18 and 24 years (Migacz & Petrick, 2018). Most of the participants were not unionized and had tertiary qualifications (undergraduate and postgraduate). International scholars also found that educated employees are not unionized, and that management plays a role in discouraging the unionization of employees (Evans, Pyman & Byford, 2016). Prior to this study, there was no happiness index for HRM practitioners in South Africa, using the dimensions considered in this study. The happiness index dimensions were developed using EFA (Refer to Table 2). Since the happiness index dimensions Cronbach's alphas were above 0, 7, the cut-off suggested by Maree (2016), it can be argued that they were reliable.
Even though 2016 groups were happier than those who attended the 2017 convention, there were statistically significant differences amongst the happiness index dimensions. In terms of policy-makers, this study suggested that they should review the remuneration practices for HRM practitioners. This study had several limitations. Firstly, there was limited literature measuring the statistically significant differences of HRM practitioners attending a professional body convention. Therefore, in address the aim of the study, the researchers relied on studies that measured biographical differences (Brienza & Bobocel, 2017;Choi, Lee & Lee, 2014;Rainayee & Zaffar, 2013;Sharma, 2015;Tshilongamulenzhe & Takawira, 2015;Voloshin, 2017;Vorina et al., 2017), other groups, such as dysphonic and non-dysphonic (McMakin et al., 2009), and supervisors and non-supervisors (Wilson, 2009). Secondly, the sample sizes were very small, data were collected using the non-probability sampling technique, and the researchers did not collect data from HRM practitioners attending other professional bodies' conventions in South Africa. Consequently, the study findings cannot be generalized to all HRM practitioners in South Africa. Despite the limitations of this study, it contributed to the body of knowledge by developing a happiness index for HRM practitioners using reliable and valid measuring scales.
Future research should be qualitative, in order to further explore the subtle narratives of why HRM practitioners have negative perceptions of their remuneration. Using a qualitative approach, an in-depth investigation should be conducted as to why employees who earn R40 000 and above are still unhappy with their salaries. Future research should focus on millennials and be extended to include other HRM professional bodies in South Africa, as well as other African countries. A larger and more representative sample should be selected from the IPM database, and an online survey should be conducted. As indicated by Leedy and Ormrod (2015) and Bless et al. (2013), this will help to achieve external validity. It is also recommended that organizations do the following in order to enhance employees' happiness: 1) review and benchmark remuneration practices; 2) investigate and implement best HRM practices and non-remuneration practices that will keep employees excited, energized and inspired; 3) engage employees so that they are invigorated and work intensely to be productive; 4) treat HRM practitioners well, so that they are affectively committed to the organization; and 5) implement fair rewards practices.