About the Author(s)


Pieter K. Smit Email symbol
Department of People Management and Development, Faculty Management Sciences, Tshwane University of Technology, Pretoria, South Africa

Cecile M. Schultz symbol
Department of People Management and Development, Faculty Management Sciences, Tshwane University of Technology, Pretoria, South Africa

Catharina E. van Hoek symbol
Department of People Management and Development, Faculty Management Sciences, Tshwane University of Technology, Pretoria, South Africa

Citation


Smit, P.K., Schultz, C.M., & Van Hoek, C.E. (2021). The relationship between talent management, transformational leadership and work engagement: An automotive artisan perspective. SA Journal of Human Resource Management/SA Tydskrif vir Menslikehul pbronbestuur, 19(0), a1578. https://doi.org/10.4102/sajhrm.v19i0.1578

Original Research

The relationship between talent management, transformational leadership and work engagement: An automotive artisan perspective

Pieter K. Smit, Cecile M. Schultz, Catharina E. van Hoek

Received: 19 Feb. 2021; Accepted: 23 Aug. 2021; Published: 28 Oct. 2021

Copyright: © 2021. 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: Understanding the relationship between talent management, transformational leadership and work engagement from an automotive artisan perspective within South Africa.

Research purpose: The purpose was to determine the relationship between talent management, transformational leadership and work engagement from an automotive artisan perspective within South Africa.

Motivation of the study: Most talent management focuses on understanding the role of the manager, with very little research being dedicated to understanding the effect of talent management on work engagement and transformational leadership amongst South African artisans.

Research approach/design and method: A survey was conducted amongst a non-probability sample of 609 artisans from a population of 1045 artisans. A quantitative research approach was used, and structural equation modelling was used to analyse the data.

Main findings: The results showed that talent management acted as a mediator between the transformational leadership and work engagement of artisans in the automotive industry. There were positive relationships between talent management and work engagement and between talent management and transformational leadership, but not between transformational leadership and work engagement.

Practical and managerial implications: A strategic approach should be implemented that will drive a talent management process with clear rewards and recognition for all stakeholders. This approach should be a part of the business rhythm, business agendas, organisational processes and culture of the industry. Should talent management, as a mediator, not form a part of work engagement and transformational leadership in the automotive industry, these variables will not function properly.

Contribution/value addition: Talent management offers a bridge between the two variables of transformational leadership and work engagement. It was clear in this study that a focus on talent management within the automotive industry is pivotal.

Keywords: transformational leadership; work engagement; talent management; artisans; automotive industry.

Introduction

Background and contextualisation of the study

Sharma and Naude (2021) state that the South African automotive industry, which is the most significant sector in the South African economy, needs to function efficiently to compete globally. The gross domestic product (GDP) of a country is one of the main indicators used to measure the performance of a country’s economy (StatsSA, 2021). The automotive industry is currently a significant contributor to South African GDP (6.8%), with 110 000 people employed across vehicle and component manufacturers. It also has an estimated indirect impact on 1.5 million people (BusinessTech, 2021). In South Africa, the artisan occupation is facing two important issues: the need for expansion and the need for transformation (Teti, 2016). There are widespread claims of a shortage of artisans in South Africa as well as a general agreement that artisan development is crucial (Wildschut & Ralphs, 2016).

Hufkie (2021) states that reskilling of artisans within the automotive industry in South Africa is needed towards Fourth Industrial Revolution (4IR) readiness. Many South African artisans are being deskilled and the remaining artisans are being reshuffled to assembly lines likely to be automated with time (Chigbu & Nekhwevha, 2020). The study of Mey, Poisat and Stindt (2021, p. 1) revealed that:

[T]he retention of skilled, engaged employees requires leaders who can provide them with a sense of belonging, respect, empowerment, support their personal growth and development, and provide them with flexibility and freedom in executing their duties. (p. 1)

Leadership support is vital in endorsing an enabling environment that cultivates talent. Without leadership’s utilisation of opportunities to provide an enabling environment, talent is not secured and will not thrive (Shikweni, Schurink, & Van Wyk, 2019). A transformation leadership style within the South African automotive industry will, therefore, be needed to develop interventions to manage the talent of artisans and to increase their work engagement.

Research gap and purpose

It is essential that a culture is created where talent and engagement can emerge, and where leaders and managers are willing to put practices in place to ensure the development of talented and engaged employees (Savarimuthu & Jothi, 2020). Real leadership is needed in the automotive industry’s competitive environment to guide subordinates so that they share goals, attitudes, values, and work towards the achievement of organisational strategies (Gautam & Enslin, 2019). Leaders also need to stimulate employees’ work engagement through progressive policies and work practices (Decuypere & Schaufeli, 2020). By combining research about talent management, leadership and work engagement, it is possible for managers to develop strategies and approaches to work engagement and talent management that become self-reinforcing. However, such studies conducted in the South African automotive industry from an artisan perspective are not known. This study is, therefore, conducted to close this research gap by investigating the relationship between talent management, transformational leadership and work engagement within the automotive industry from an artisan perspective. Furthermore, it is hoped that this study will contribute to an in-depth understanding of the intervening effect that talent management has on transformational leadership and work engagement.

Literature review

The underpinning theory used in this study was the ability, motivation and opportunity (AMO) theory. According to AMO theory, the components of ability, motivation and opportunity are the three-independent work-system elements that form employee characteristics and eventually lead to organisational success (Shanaz, Dlvin, & Vala, 2020). Ability refers to those practices and policies to ensure that employees obtain the required skills, knowledge and ability to perform their tasks with minimum supervision (Yahya, Tan, & Tay, 2017). Motivation refers to employee performance and the extra efforts that employees put into their jobs (Yahya et al., 2017). The last component is the opportunity-enhancing human resources management (HRM) practices which aim at engaging employee involvement by providing opportunities (Yahya et al., 2017).

Saks and Gruman (2017) propose that drawing from the AMO theory will enable researchers to understand how HRM practices can influence work engagement. Amor, Vázquez and Faíña (2020) stated that managers should be aware of the critical role of the leader in stimulating work engagement. Organisational interventions that promote the development of transformational leadership may be valuable to enhance work engagement. Whilst organisations need to recruit and retain top talent, they also need their talented employees to be engaged in their work (Bakker & Leiter, 2010).

Transformational leadership

The theory of transformational leadership was first coined by Downton (1973). Downton (1973) categorised three leadership tendencies, which are transactional leadership, charismatic leadership and inspirational leadership. Avolio, Waldman and Yammarino (1991) mentioned the four I’s of transformational leadership namely, idealised influence (modelling ethical and socially desirable behaviour, exhibiting enthusiasm about company strategy), inspirational motivation (to impart a vision that is appealing and worthy), intellectual stimulation (empowering employees to constantly be learning) and individualised consideration (giving employees a feeling of ownership in company goals and independence in the workplace).

Idealised influence is described by Hamidianpour, Esmaeilpour and Mashayekh (2016), wherein followers demonstrate respect and loyalty towards a leader who conveys an ideal sense and makes followers consider the leader as a perfect sense model of behaviour. Inspirational motivation is defined by Steinmann, Klug and Maier (2018) as the method in which a transformational leader inspirationally motivates followers to achieve more than expected by sharing his or her vision in order to inspire them towards a more effective and efficient performance of their duties. Intellectual stimulation refers to the leader’s ability to instil innovative and creative capabilities into followers as a way of building their critical thinking and problem-solving skills (Atiku & Anane-Simon, 2020). Individualised consideration is a dimension of transformational leadership whereby a leader pays special attention to individual differences, followers’ personal growth and needs for achievement by acting as a mentor or coach for them (Gonfa, 2019).

Swanwick (2017) opined that developing transformational leadership with training in the four I’s can enhance a leader’s effectiveness and satisfaction. Khorshid and Pashazadeh (2014) maintained that transformational leaders create an atmosphere of trust and motivate employees to work for the organisation beyond their self-interests. Transformational leadership has proven to be a pervasive model, inspiring shared purpose, engaging others and sharing the vision of an organisation (Swanwick, 2017). Mittal and Dhar (2015) also put forth the fact that a transformational leader is one who inspires followers to do more than originally expected.

Talent management

Lewis and Heckman (2006) mentioned that there are three distinct perspectives regarding talent management. The first perspective defines talent management as a collection of typical human resource department practices, functions, activities or specialist areas such as recruiting, selection, development and career and succession management (Mercer, 2005). The second perspective on talent management focuses primarily on the concept of talent pools by focusing on the internal workforce (Schweyer, 2004). Employees who experience a talent management system that is based on an inclusive or stable philosophy are likely to feel supported and valued by their organisation because they work in surroundings that are generally appreciative of their talents (Meyers & Van Woerkom, 2014). A third perspective on talent management focuses on high performing talent (Axelrod, Handfield-Jones, & Michaels, 2002) on the one hand and generic talent (Walker & Larocco, 2002) on the other hand.

New perspectives on talent management by Rhodes and Fletcher (2013) bring approaches that are focused on both the employment and the work relationship and that consider the influence and well-being of role players at multiple levels. Talent management is an integrated, strategic and deliberate activity that is performed to direct how organisations source, attract, select, train, develop, retain, promote and deploy employees (Van Rooyen & Whittle, 2011). Johnson (2015) posits that talent management is about the early identification of key role players and articulation of duties, leading to ownership and clear accountability to ensure organisational success. Ogbari, Onasanya, Ogunnaike and Kehinde (2018) are of the opinion that one of the main components of talent management is continuously training personnel to maintain the required level of performance. Talent management contributes to creating a high-performance work culture within an organisation (Poisat et al., 2018).

Work engagement

Work engagement refers to a positive, affective-motivational state of high energy combined with high levels of dedication and a strong focus on work (Schaufeli & Bakker, 2010). Engaged employees demonstrate vigour, dedication and absorption when executing tasks in the workplace (Schaufeli, Salanova, Gonzáles-Romá, & Bakker, 2002). Dedication and vigour are regarded as the core components of work engagement (Schaufeli, 2013; Taris, Ybema, & Van Beek, 2017). Vigour means enhanced levels of mental resilience and energy and includes employees’ preparedness to put effort into their work (Schaufeli, Martinez, Pinto, Salanova, & Bakker, 2002; Sonnentag, 2017). Employees with dedication feel challenged, proud, inspired and enthusiastic, and experience a sense of significance about their work (Schaufeli et al., 2002a; Sonnentag, 2017). Absorption entails the immersion in one’s work (Schaufeli et al., 2002b).

Individuals who are engaged in their work have high levels of energy, are enthusiastic about their work and are completely immersed in their work activities (Bakker & Albrecht, 2018). The majority of studies have adopted a between-person approach, showing that there are mean level differences in work engagement between individuals as a function of working conditions, personal characteristics and behavioural strategies (Bakker, Demerouti, & Sanz-Vergel, 2014).

Development of the hypotheses

In this study, nine research hypotheses were developed and investigated. The development of each of these hypotheses is discussed in the following sections.

Talent management and transformational leadership

According to the research conducted by Ghafoor, Qureshi, Khan and Hijazi (2011), transformational leadership was positively related to talent management. Transformational leadership has an effect on talent management (Onyango, 2015). Widodo and Mawarto (2020) found that there is a significant relationship between talent management and transformational leadership.

The relationship between transformational leadership and talent management highlighted the following hypotheses:

Hypothesis 1: Talent management (performance planning and motivational processes) will be positively related to transformational leadership.

Hypothesis 2: Talent management (career development) will be positively related to transformational leadership.

Talent management and work engagement

According to research conducted by Church (2013), talent management positively relates to work engagement. The findings of Sopiah, Kurniawan, Nora and Narmaditya (2020) confirmed that talent management positively influences work involvement and employee performance. There is a significant positive relationship between talent management and work engagement (Toka & Hamida, 2020). Ishayama (2021) found that talent management has an impact on work engagement.

The relationship between work engagement and talent management highlighted the following hypotheses:

Hypothesis 3: Talent management (performance planning and motivational processes) will be positively related to work engagement (vigour).

Hypothesis 4: Talent management (career development) will be positively related to work engagement (vigour).

Hypothesis 5: Talent management (performance planning and motivational processes) will be positively related to work engagement (dedication).

Hypothesis 6: Talent management (career development) will be positively related to work engagement (dedication).

Work engagement and transformational leadership

A positive leadership style, such as transformational leadership, has a relatively large correlation with work engagement (Hoch, Bommer, Dulebohn, & Wu, 2018). The findings of Gautam and Enslin (2019) indicated that transformational leadership moderately influenced work engagement more than transactional leadership and there was a positive relationship between these two constructs. An increasing number of studies suggests that transformational leadership influences work engagement (Breevaart et al., 2014; Tims, Bakker, & Xanthopoulou, 2011; Tuckey, Bakker, & Dollard, 2012). Leadership styles can potentially complement the known benefits associated with transformational leadership, particularly in explaining the emergence and maintenance of engagement in dynamic team-based working contexts (Bakker & Albrecht, 2018). Hayati, Charkhabi and Naami’s (2014) investigation of transformational leadership suggested that transformational leadership would likely be the most predictive characteristic of an optimal leader. In support of this statement, Avolio, Bass and Jung (1999) stated that transformational leaders embody characteristics of being charismatic and influential in their ability to make employees do more than expected at work.

The relationship between work engagement and transformational leadership highlighted the following hypotheses:

Hypothesis 7: Work engagement (vigour) will be positively related to transformational leadership.

Hypothesis 8: Work engagement (dedication) will be positively related to transformational leadership.

Talent management, transformational leadership and work engagement

According to Lai et al. (2020), work engagement mediates the relationship between transformational leadership and employees’ task performance and helping behaviour. In addition, transformational leaders can enhance followers’ performance and foster their helping behaviours because they induce members’ work engagement and enable them to exceed expectations. Furthermore, Lai et al.’s (2020) research also depicted that role-based self-efficacy, transactional leadership and work engagement fully mediate the positive relationship between transformational leadership and members’ task performance and helping behaviours (Lai et al., 2020). Sopiah et al. (2020) found that work engagement had a moderating role between talent management and employee performance.

Talent management as a mediator between transformational leadership and work engagement highlighted the following hypothesis:

Hypothesis 9: Talent management mediates transformational leadership and work engagement.

A graphic presentation of the hypotheses is presented in Figure 1.

FIGURE 1: Hypothesised relationships and conceptual model.

Method

Research method

Empirical research, which was conducted in this study, should primarily be embedded in theory. For the purpose of this study, current, proven and tested questionnaires on the variables of transformational leadership, talent management and work engagement were used. In other words, data were directly collected from the sample group. From the analysis of the statistical data gathered, conclusions were drawn.

Research context

This study was conducted at a large organisation that provides training to all artisans in the South African automotive industry. Automotive organisations were represented by automotive brands selling vehicles in all nine provinces in South Africa. From a total of 1045 artisans targeted, 609 respondents completed the questionnaire on transformational leadership, talent management and work engagement.

Sample

For the purpose of this research, artisans from 152 automotive South African organisations were targeted to complete the questionnaire. Purposive sampling was used to target the artisans who attended training at three different training venues at a specific point in time.

Research approach and design

The study takes the ontological position of objectivism, with a positivistic epistemology. According to Botma, Greeff, Mulaudzi and Wright (2010), epistemology determines the methodologies, theories and procedure application throughout the research process. Therefore, a quantitative and non-experimental research approach was adopted. Leedy and Ormrod (2016) highlighted that descriptive quantitative research entails the identification and exploration of characteristics of the phenomenon and possible correlations amongst the multiple phenomena. A self-administered questionnaire survey design was utilised for data collection purposes. Cross-sectional and survey research designs were used in this study.

Research instrument

The following instruments discussed namely, transformational leadership, talent management and work engagement are those that were used in the study.

Transformational leadership measurement

According to Bass and Riggio (2006), the most widely accepted instrument to measure transformational leadership is the Multifactor Leadership Questionnaire (MLQ), which assesses the Full Range of Leadership (FRL) model, including laissez-faire leadership, the components of transactional leadership, namely management by exception (both active and passive forms) and contingent reward, as well as components of transformational leadership. In the study of Louw, Muriithi and Radloff (2017), the Cronbach’s alpha assessment was done to establish the reliability of the scales of the measuring instrument and the scores were considered very reliable compared to the minimum acceptable score of 0.7 (Nunnally, 1978). For all factors, coefficients of greater than 0.7 (Nunnally, 1978, p. 226) were returned. Sufficient evidence of validity and reliability for the scales measuring the independent and dependent variables is thus provided. The specific scores for transformational leadership sub-constructs were: individualised consideration (0.892), idealised influence behaviour (0.844), inspirational motivation (0.868), intellectual simulation (0.869) and idealised influence attributes (0.849). The alpha scores were in agreement with similar studies, thereby making the measuring instrument and data reliable (Hayward, 2005).

Talent management measurement

A questionnaire on talent management was adapted from Van Hoek (2014), it consisted of 29 questions. The instrument was previously used in the study conducted by (Van Hoek 2014). In this study of Van Hoek (2014), performance management obtained the Cronbach’s alpha value of 0.845, however remuneration obtained Cronbach’s alpha of 0.619, finally career development obtained the Cronbach’s alpha value of 0.629. The Cronbach’s alpha should be more than 0.70 to make the scale more reliable, in this case two factors, that is, remuneration and career development obtained the Cronbach’s alpha value just below the acceptable level and performance management obtained an acceptable level of 0.845 of the Cronbach’s alpha value, that made the scale more reliable (Van Hoek, 2014).

Work engagement measurement

Schaufeli et al. (2006) set out to develop a short questionnaire to measure work engagement and validate its scores. This questionnaire was used in this research to measure engagement. In the study of Hoole and Bonnema (2015), Cronbach’s alpha scores of 0.93 and 0.72 were obtained for the Utrecht Work Engagement Scale (UWES) and Performance management system (PMS), respectively. In the case of the PMS, one should take into consideration that reliability also tends to be lower when a scale consists of fewer than 10 items (Pallant, 2005).

Data collection procedure

The questionnaires which are in English were manually distributed to the artisans. Sealed boxes were used for collection in order to ensure anonymity and confidentially. The returned responses with missing values were excluded from the analysis.

Data analysis

The Stata version 15 statistical analysis software was used for the analysis of data. Descriptive statistics were reported in a form of frequencies and percentages. In terms of inferential statistics, the structural equation modelling (SEM) using the partial least squares path modelling approach (PLS-PM) was performed (Hair, Sarstedt, Hopkins, & Kuppelwieser, 2014). Bootstrapping was used to estimate the parameters and associated standard errors in the direct and indirect effect in the statistical analysis of the structural equation model through the non-parametric method.

Measurement model evaluation

Measurement model evaluation is aimed to evaluate the consistency and validity of the manifest variables. Consistency evaluations are through individual manifest and construct reliability tests. Whilst validity of the variables is tested based on convergent and discriminant validity, individual manifest reliability explains the variance of individual manifest relative to latent variable by calculating standardised outer loadings of the manifest variable. Structural equation modelling consists of two parts, namely the measurement model evaluation and the testing of the structural model. Measurement model evaluation is intended to evaluate the validity and consistency of the manifest variables. Validity of the variables is tested based on convergent and discriminant validity, and individual manifest reliability explains the variance of individual manifest relative to latent variable by calculating standardised outer loadings of the manifest variable, whilst consistency evaluations are done through individual manifest and construct reliability tests.

Ethical considerations

Approval was granted by the automotive industry to conduct research on this topic with their artisans. The study was conducted within the approved ethical framework. The participation by respondents was voluntary, and their completed questionnaires were treated as confidential. Permission to conduct this study was obtained from the company under study. Ethical permission was obtained from the High ethical standards that were followed in all aspects of the research process. All possible respondents were provided with an overview of the study, before inviting them to voluntarily participate. Participants were assured of the anonymity and confidentiality of their responses and were informed that they could withdraw from the study at any stage, should they feel it necessary to do so. All participants indicated their consent.

Results

Descriptive statistics

A total of 609 respondents participated in the study, and the response rate was 100%. The data revealed that there were more male respondents (96.72%) than female respondents (3.28%) who participated in the study. The data show that most respondents were Africans with 43.64%, followed by their white counterparts with 31.74%, mixed races represented 15.87% and the remaining 876% represented Indian participants. Thirty-four (34) (5.6%) were in the age group of 31–40 years, 13 (2.1%) were in the age group of 41–50 years and only 2 (0.3%) were over the age of 51 years. With regard to the education of the respondents, the majority of the respondents (56.83%) had grade 12% and 17.7% possessed an N4–N6 qualification. In terms of tenure, the data showed that 77.80% of the respondents who completed the questionnaire had a tenure of service between 1 and 5 years, 14.50% of the respondents had a tenure of service less than 1 year, 5.9% of the respondents had a tenure of service between 6 and 10 years of service, 1% of the respondents had a tenure of service between 11 and 20 years of service, 0.3% of the respondents had a tenure of service between 21 and 30 years of service and 0.50% of the respondents had a tenure of service more than 31 years. The percentage distribution of vehicle petrol mechanics was 78.9% compared to vehicle diesel mechanics representing 18.5%, vehicle spray painter 1% and the other individual fields of work less than 1% each.

Factor and reliability analysis

The results presented in Table 1 show that the Cronbach’s alpha values for all the variables are between the cut-off points of 0.5 and 0.7. Dillon–Goldstein’s rho for all the variables was above 0.7 that indicates homogeneity of the factor. The results suggest that all the variables are reliable with regard to internal consistency. The quality of a measurement model was examined by testing the convergent validity, which shows the degree to which the indicators under the constructs are related. Convergent validity shows the amount of variance the indicators have in common: high factor loading and average variance extracted (AVE). According to Hair et al. (2014), AVE loadings above 0.5 are indicators of convergent validity. The results displayed in Table 1 indicate that the AVE loadings were above 0.5, except for continuance commitment with 0.3. The final model factor loadings are also reported in Table 1.

TABLE 1: Final model: Revised assessment of internal consistency.
Structural equation model results

The direct effect in the statistical analysis of the structural equation model was determined through the non-parametric method. In the analysis of the non-parametric method, the identification of a loading close to 1 indicates a strong relationship, with the Perc 0.975 equal to a 95% confidence interval. Further loadings with a zero involved in the reading of the interval (–0.068:0.154) become insignificant. Furthermore, bootstrapping was used to estimate the parameters and associated standard errors. Table 2 indicates the different paths resulting from the statistical results (see Figure 2). TM1 is significantly related to TL. The relationship is strong and positive. This means that, when TM1 increases, TL also increases. Similarly, TM2 is significantly related to TL; however, the relationship is weak. TM1 has a moderate and positive relationship with WE1 and WE2; however, it is not as strong as with TL. Should TM1 increase, WE1 and WE2 increase. Furthermore, the results show that TM1 is a better predictor of TL than TM2. The relationship between TL and both WE1 and WE2 is not significant. The effect of TL on WE as a whole is not significant. TM2 is significantly related to WE1 and WE2. The relationship is strong and positive. Talent management is significantly related to TL, but not as strongly as to WE1 and WE2. Transformational leadership is not significantly related to WE1 and WE2. The relationship is very weak and not positive.

FIGURE 2: The different paths of influence from statistical results.

TABLE 2: Direct relationship estimation of parameters and associated standard errors.

Bootstrapping was used to estimate the parameters and associated standard errors in the direct and indirect effect in the statistical analysis of the structural equation model using the non-parametric method. Table 3 indicates the total effect of the different paths from the direct and indirect statistical results. TM1 is still significantly related to TL. This relationship is positive. This means that, when TM1 increases, TL also increases. Similarly, TM2 is significantly related to TL, but this relationship is not as positive as the direct estimation analysis only. However, the relationship between TM2 and TL is still weak. The results show that TM1 is still a better predictor of TL compared to TM2. The relationship between TL and both WE1 and WE2 is low and weak and thus not significant. The low and weak effect of TL on WE as a whole is not significant. Goodness of fit (GoF) can be used as a global criterion that helps to evaluate the performance of the model in both the inner and the outer models. Basically, GoF assesses the overall prediction performance of the model. The main drawback with the GoF index is that there is no threshold that allows one to determine its statistical significance. Unfortunately, there is also no guidance about what number could be considered a good GoF value. GoF can be considered as an index of average prediction for the entire model. Although this is not entirely true, it helps in understanding GoF values. The calculated global GoF is 0.479, which exceeds the threshold of 0.36 suggested by Wetzels, Odekerken-Schröder and Van Oppen (2009). This led the researchers to conclude that the research model has a good overall fit.

TABLE 3: Total effect estimation of parameters and associated standard errors.

Discussion of the findings

The purpose was to determine the relationship between talent management, transformational leadership and work engagement from an automotive artisan perspective within South Africa.

Transformational leadership is negatively related to work engagement. This deviates with the findings of Church (2013), Sopiah et al. (2020), Toka and Hamida (2020) and Ishayama (2021).

Talent management is positively related to transformational leadership. This concurs with the findings of Ghafoor et al. (2011), (Onyango, 2015) and Widodo and Mawarto (2020). Work engagement is negatively related to transformational leadership. This deviates with the findings of Hoch et al. (2018), Gautam and Enslin (2019), Breevaart et al. (2014), Tims et al. (2011), Tuckey et al. (2012), Bakker and Albrecht (2018) and Hayati et al. (2014). Talent management acts as the mediator between transformational leadership and work engagement. This deviates with the study of Lai et al. (2020) where work engagement mediated the relationship between transformational leadership and employees’ task performance and helping behaviour. The study of Sopiah et al. (2020) found that work engagement had rather a moderating role between talent management and employee performance.

Transformational leadership provides a better fit for leading today’s complex groups and organisations, where followers not only seek an inspirational leader to help them through an uncertain environment, but also want to be challenged and to feel empowered, if they are to be loyal and perform well (Bass & Riggio, 2006). Employees who experience a talent management system that is based on an inclusive or stable philosophy are likely to feel supported and valued by their organisation because they work in surroundings that are generally appreciative of their talents. Consequently, such employees make positive attributions regarding the goals of talent management (Meyers & Van Woerkom, 2014). The concept of engagement has been researched and conceptualised as the ‘harnessing of organisation members’ selves to their work roles: in engagement, people employ and express themselves physically, cognitively, and emotionally and mentally during role performances’ (Kahn, 1990). The results of the research done by Kahn (1990) reflected that engaged employees put a great deal of effort into their work because they identify themselves with it.

A summary of the outcomes of the hypotheses is presented in Table 4.

TABLE 4: Hypotheses accepted/rejected.

Practical implications

The complex environment that the automotive industry faces today highlights the importance of transformational leadership, talent management and work engagement for the effective management of organisations. This study investigated the relationship between transformational leadership, talent management and work engagement amongst artisans in the automotive industry. This study provides initial support for a complex relationship between transformational leadership, work engagement and talent management. As further research provides greater support, the development of greater validity between these variables could be used as a supplement to transformational leadership to handle the changing corporate environment effectively.

Limitations of the study

Although the current study yielded some interesting results, there are limitations that could negatively impact its generalisability because the study only reflects the views of artisans working in the automotive industry. Cross-sectional and survey research designs were used and can, therefore, not be generalised to other industries as in the case with the study of Mathafena and Grobler (2020). This necessitates repeated longitudinal research for this type of study. The results of the study could be explained better if both quantitative and qualitative methods had been employed in the study. There is an opportunity to explore a pessimistic view that might highlight many intervention opportunities with the next survey process and qualitative research.

Recommendations

In the automotive industry, transformational leadership is needed to guide artisans so that they share goals, attitudes, values, and work towards the achievement of organisational strategies (Gautam & Enslin, 2019). These leaders also need to stimulate employees’ work engagement through progressive policies and work practices (Decuypere & Schaufeli, 2020). Policies and procedures should be reviewed to ensure better compliance towards artisans in this regard:

[O]rganisational executives should focus simultaneously on understanding the broader aspects of work engagement within an organisation as well as providing constant support to develop the leadership skills of managers, particularly transformational leadership skills. (Gautam & Enslin, 2019, p. 139)

Lastly, a talent management strategy that includes transformational leadership and work engagement should be developed to guide the automotive industry on the way forward. Artisan development will take place through strategic processes that are shared at all levels of the organisation. Rewards and recognition will be measured by management with talent management as the mediator.

Conclusion

The purpose was to determine the relationship between talent management, transformational leadership and work engagement from an automotive artisan perspective within South Africa.

The results showed that transformational leadership is negatively related to work engagement, talent management is positively related to transformational leadership and work engagement is negatively related to transformational leadership. Lastly, talent management is a mediator between transformational leadership and work engagement. These results could assist managers to become transformational leaders in order to properly manage talent amongst artisans in the South African automotive industry so that these artisans’ work engagement can improve. A talent management strategy that includes transformational leadership and work engagement should, therefore, be developed to guide the automotive industry on the way forward.

Acknowledgements

Competing interests

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

Authors’ contributions

Dr Smit did the research together with analytical analysis of the researched data and the development of a framework determining the mediating factor. Prof. Schultz was the supervisor for this topic. Dr van Hoek was the co-supervisor to the topic.

Funding information

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Data availability

The data were recorded on an Excel spreadsheet and captured into the SPSS V23 software package. The data were kept electronically as well as in hard copy. The original completed questionnaires were also stored.

Disclaimer

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.

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