A staff retention model for state-owned enterprises in South Africa

Abstract

The aim of this quantitative study was to develop a model of staff retention for state-owned enterprises (SOEs) in South Africa. The literature review phase explored the concept of staff retention, the measurement of staff retention, and the evaluation of existing models and frameworks of staff retention to determine their applicability to SOEs in South Africa.

The literature review indicated that staff retention can be defined as the organisation’s effort to retain required, high-performing, momentously skilled, and talented employees with the purpose of achieving organisational strategic objectives and goals. It also indicated that staff retention can be accurately measured by the use of existing reliable and valid instruments, although it is difficult to find one comprehensive instrument that measures all possible factors associated with staff retention. Thus, the common practice is to use various existing instruments in combination to measure the factors separately that contribute to staff retention. The literature review also revealed that various staff retention models and frameworks exist that can be used to better understand staff retention. The literature also emphasised that any model of staff retention that is utilised or developed should be organisation context-specific, as there is no one-size-fits-all approach.

Based on the literature review, a new theoretical model of staff retention for SOEs in South Africa was proposed. The proposed theoretical model included five biographical factors, namely (1) gender, (2) age, (3) educational qualifications, (4) tenure, and (5) job grade, as well as 12 organisational factors, namely, (1) compensation and benefits, (2) job characteristics, (3) training and development, (4) supervisory support, (5) career growth and development, (6) work-life balance, (7) employee engagement, (8) organisational support, (9) ethical leadership, (10) job satisfaction, (11) meaningful work, and (12) organisational culture. These five biographical factors and 12 organisational factors were the most globally researched and indicated an empirical relationship with staff retention, which was operationalised as intention to leave and which was used to measure staff retention. During the empirical phase of the study a survey was conducted within a South African SOE (n = 685) and the results of the survey were subjected to Structural Equation Modelling (SEM) with the aim of determining whether the hypothesized theoretical model fitted the collected data. The SEM process subsequently identified three statistically significant staff retention factors that could be used to ensure the retention of staff in South African SOEs, namely, (1) organisational culture, (2) compensation and benefits, and (3) training and development. A hierarchical moderator regression analysis (HMRA) was then conducted to determine whether the biographical variables of gender, age, educational qualifications, tenure, and job grade statistically significantly moderated the relationship between the staff retention factors (independent variables) and intention to leave (the dependent variable). The analysis indicated that the five biographical variables had no statistically significant effect on the relationship between the staff retention factors and intent to leave in a South African SOE. It was consequently recommended that SOEs in South Africa could use the above-mentioned three-factor validated model of staff retention to manage staff retention and that the model does not have to be adapted to account for the impact of gender, age, educational qualifications, tenure, and job grade on intent to leave the organisation.

Die doel van hierdie kwantitatiewe studie was om ’n model vir werknemerbehoud vir ondernemings in staatsbesit (OSB) in Suid-Afrika te ontwikkel. Die literatuuroorsigfase het die begrip werknemerbehoud, die meting van werknemerbehoud en die evaluering van bestaande modelle en raamwerke van werknemerbehoud ondersoek ten einde hulle toepaslikheid vir ondernemings in staatsbesit in Suid-Afrika te bepaal. Volgens die literatuuroorsig kan werknemerbehoud omskryf word as die organisasie se poging om benodigde, hoë presterende, betekenis-volgeskoolde en talentvolle werknemers te behou, ten einde organisatories-strategiese oogmerke en doelwitte te behaal. Dit het ook aangetoon dat werknemerbehoud akkuraat gemeet kan word deur van bestaande, betroubare en geldige instrumente gebruik te maak, hoewel dit moeilik is om een omvattende instrument te kry wat al die moontlike faktore wat met werknemerbehoud geassosieer word, te kan meet. Die algemene praktyk is derhalwe om verskillende bestaande instrumente in kombinasie te gebruik om die faktore wat tot werknemerbehoud bydra, individueel te meet. Die literatuuroorsig het ook bevind dat verskeie werknemerbehoudsmodelle en -raamwerke bestaan wat gebruik kan word om werknemerbehoud beter te verstaan. Die literatuur het ook uitgewys dat enige model van werknemerbehoud wat gebruik of ontwikkel word, organisasie-inhoudspesifiek moet wees omdat daar geen een-grootte-pas-almal-benadering is nie. 'n Nuwe teoretiese model van werknemerbehoud vir ondernemings in staatsbesit in Suid-Afrika, wat op die literatuuroorsig gegrond is, word voorgestel. Die voorgestelde teoretiese model sluit vyf biografies faktore in, naamlik: (1) geslag, (2) ouderdom, (3) onderwyskwalifikasies, (4) dienstyd, en (5) posgradering; asook 12 organisatoriese faktore, naamlik: (1) vergoeding en voordele, (2) werkseienskappe, (3) opleiding en ontwikkeling, (4) toesighoudende ondersteuning, (5) loopbaanopgang en -ontwikkeling, (6) werk-lewe-balans, (6) werknemerbetrokkenheid, (8) organisatoriese ondersteuning, (9) etiese leierskap, (10) werkbevrediging, (11) betekenisvolle werk, en (12) organisasiekultuur. Hierdie vyf biografiese en 12 organisatoriese faktore is die faktore wat wêreldwyd die meeste nagevors is en ’n empiriese verwantskap met werknemerbehoud toon, wat geoperasionaliseer is as die voorneme om die werkplek te verlaat en wat gebruik is om werknemerbehoud te meet. Gedurende die empiriese fase van die studie is ’n ondersoek in ’n Suid-Afrikaanse onderneming in staatsbesit (n = 685) van stapel gestuur en die resultate van die ondersoek is aan strukturele gelykstellingsmodellering onderwerp met die doel om vas te stel of die veronderstelde teoretiese model by die ingesamelde data pas. Die strukturele gelykstellingsmodelleringsproses het daarna drie statisties betekenisvolle werknemerbehoudsfaktore geïdentifiseer wat gebruik kan word om die behoud van personeel in Suid-Afrikaanse ondernemings in staatsbesit te verseker, naamlik: (1) organisasiekultuur, (2) vergoeding en voordele, en (3) opleiding en ontwikkeling. ’n Hiërargiese moderatorregressie-analise (HMRA) is hierna gedoen om vas te stel of die biografiese veranderlikes van geslag, ouderdom, onderwyskwalifikasies, dienstyd, en posgradering statisties betekenisvol die verwantskap tussen werknemerbehoudsfaktore (onafhanklike veranderlikes) en die voorneme om weg te gaan (die afhanklike veranderlike) modereer. Die ontleding het aangetoon dat die vyf biografiese veranderlikes geen statisties betekenisvolle uitwerking op die verwantskap tussen die werknemerbehoudsfaktore en die voorneme om weg te gaan in ’n Suid-Afrikaanse onderneming in staatsbesit gehad het nie. Daar word derhalwe aanbeveel dat ondernemings in staatsbesit in Suid-Afrika die bogenoemde driefaktor- geldigverklaardemodel van werknemerbehoud gebruik om werknemerbehoud te bestuur en dat die model nie aangepas hoef te word om die invloed van geslag, ouderdom, onderwyskwalifikasies, dienstyd en posgradering op die voorneme om die organisasie te verlaat, te verantwoord nie.

Maikemišetšo a nyakišišo ye ya khwalithethifi e be e le go tšweletša mmotlolo wa tshwarelelo ya bašomi wa dikgwebo tša mmušo (di-SOE) ka Afrika Borwa. Kgato ya tshekatsheko ya dingwalo e lekotše kgopolo ya tshwarelelo ya bašomi, kelo ya tshwarelelo ya bašomi, le tekolo ya dika tše di lego gona le diforeimiweke tša tshwarelelo ya bašomi go laetša go šoma ga tšona go di-SOE ka Afrika Borwa. Tshekatsheko ya dingwalo e laeditše gore tshwarelelo ya bašomi e ka hlalošwa bjalo ka maitapišo a mokgatlo a go swarelela bašomi bao ba nyakegago, bao ba šomago gabotse, bao ba nago le bokgoni bjo bo bohlokwa, le bao ba nago le bokgoni bja go nepiša go phihlelelo ya maikemišetšo le dinepo tša maano a mokgatlo. E laeditše gape gore tshwarelelo ya bašomi e ka elwa gabotse ka tšhomišo ya didirišwa tše di lego gona le tša mmakgonthe, le ge e le gore go thata go hwetša sedirišwa se tee sa kakaretšo seo se elago mabaka ka moka ao a kgonegago ao a amanago le tshwarelelo ya bašomi. Ka go realo, mokgwa wa tlwaelo ke wa go šomiša didirišwa tša go fapana tše di lego gona ka go di kopanya go ela ka thoko mabaka ao a tsenyago letsogo tshwarelelong ya bašomi. Tshekatsheko ya dingwalo e utollotše gape gore dika tša go fapafapana tša tshwarelelo ya bašomi le diforeimiweke di gona tšeo di ka šomišwago go kwešiša bokaone tshwarelelo ya bašomi. Dingwalo gape di gateletše gore mmotlolo ofe goba ofe wa tshwarelelo ya bašomi wo o šomišwago goba o tšweletšwago o swanetše go ba wo o lebanego le seemo sa mokgatlo, ka ge go se na mokgwa wa kakaretšo ya tšohle. Go ya ka tshekatsheko ya dingwalo, go šišintšwe mmotlolo wo moswa wa teori ya tshwarelelo ya bašomi wa di-SOE ka Afrika Borwa. Mmotlolo wa teori wo o šišintšwego o be o akaretša dintlha tše tlhano tša taodišophelo, e lego (1) bong, (2) mengwaga, (3) mangwalo a thuto, (4) lebaka la mošomo le (5) maemo a mošomo, gammogo le dintlha tše 12 tša mokgatlo, (1) phumulameokgo le dikholego, (2) dimelo tša mošomo, (3) tlhahlo le tlhabollo, (4) thekgo ya bohlokomedi, (5) kgolo ya mošomo le tlhabollo,(6) tekatekano ya mošomo le bophelo, (7) thwalo ya bašomi, (8) thekgo ya mokgatlo,(9) boetapele bja maitshwaro, (10) kgotsofalo ya mošomo, (11) mošomo wo bohlokwa le (12) setšo sa mokgatlo. Dintlha tše tše tlhano tša taodišophelo le dintlha tše 12 tša mokgatlo e bile tšeo di nyakišišitšwego kudu lefaseng ka bophara le go laetša kamano ya diphihlelelo le tshwarelelo ya bašomi, yeo e šomišitšwego bjalo ka maikemišetšo a go tloga le yeo e šomišitšwego go ela tshwarelelo ya bašomi. Nakong ya kgato ya iphirikhale ya nyakišišo, nyakišišo e dirilwe ka gare ga SOE ya Afrika Borwa (n = 685) gomme dipoelo tša nyakišišo di ile tša dirwa ka fase ga Tshekatsheko ya Kamano ya Dibopego (Structural Equation Modeling (SEM)), ka maikemišetšo a go bona ge eba mmotlolo wa teori wo o akantšwego o swanetše datha ye e kgobokeditšwego.

Ka morago ga moo tshepetšo ya SEM e laeditše mabaka a mararo a bohlokwa a dipalopalo a tshwarelelo ya bašomi ao a ka šomišwago go kgonthiša tshwarelelo ya bašomi ka di-SOE tša Afrika Borwa, e lego, (1) setšo sa mokgatlo, (2) phumulameokgo le dikholego, le (3) tlhahlo le tlhabollo. Tshekatsheko le kamano ya khuetšo ya tatelano (hierarchical moderator regression and analysis (HMRA)) e dirilwe morago go bona ge eba diphetogo tša taodišophelo ya bong, mengwaga, mangwalo a thuto, nako ya mošomo, le maemo a mošomo ka dipalopalo di lekanyeditše kudu kamano gare ga mabaka a tshwarelelo ya bašomi (diphetogo tše di ikemetšego) le maikemišetšo a go tloga (phetogo ye e sego ya ikemela). Tshekatsheko e laeditše gore diphetogo tše tlhano tša taodišophelo ga se tša ba le khuetšo ye bohlokwa ya dipalopalo go kamano gare ga mabaka a tshwarelelo ya bašomi le maikemišetšo a go tloga mo go SOE ya Afrika Borwa. Mafelelong go šišintšwe gore di-SOE ka Afrika Borwa di ka šomiša mmotlolo wo o boletšwego ka mo godimo wo o kgonthišitšwego ka mabaka a mararo a tshwarelelo ya bašomi go laola go swarelela bašomi le gore mmotlolo ga o hloke go fetošwa go ikarabela ka khuetšo ya bong, mengwaga, mangwalo a thuto, lebaka la mošomo, le maemo a mošomo ka maikemišetšo a go tlogela mokgatlo.