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Article

The Mediating Effect of Affective Commitment on the Relationship between Competence Development and Turnover Intentions: Does This Relationship Depend on the Employee’s Generation?

by
Ana Moreira
1,2,3,*,
Carla Tomás
4 and
Armanda Antunes
3
1
APPsyCI—Applied Psychology Research Center Capabilities & Inclusion, ISPA—Instituto Universitário, 1149-041 Lisboa, Portugal
2
School of Psychology, ISPA—Instituto Universitário, Rua do Jardim do Tabaco 34, 1149-041 Lisboa, Portugal
3
Faculdade de Ciências e Tecnologia, Universidade Europeia, Quinta do Bom Nome, Estr. da Correia 53, 1500-210 Lisboa, Portugal
4
Department of Psychology and Sports, Instituto Superior Manuel Teixeira Gomes, 8500-590 Portimão, Portugal
*
Author to whom correspondence should be addressed.
Adm. Sci. 2024, 14(5), 97; https://doi.org/10.3390/admsci14050097
Submission received: 26 February 2024 / Revised: 3 May 2024 / Accepted: 6 May 2024 / Published: 8 May 2024
(This article belongs to the Special Issue Human Resource Development and Retention in the Digital Age: Best Practices and Technologies for Maximizing Positive Employee Outcomes)
Browse Figure
Versions Notes

Abstract

:
The main objective of this investigation was to study the effect of organizational competency development practices on turnover intentions and whether affective commitment explains this relationship. Another of the study’s objectives was to test whether these relationships vary according to the generation to which the participant belongs. The study sample consisted of 2123 participants working in Portuguese organizations. The results indicate that organizational competency development practices (training, individualized support, and functional rotation) negatively and significantly affect turnover intentions and that affective commitment mediates this relationship. However, these relationships vary according to the participant’s generation. For Generation Y and Generation X, this mediating effect is found in all dimensions of organizational competency development practices. For the baby boomer generation, there is only a mediating effect of affective commitment in the relationship between individualized support and turnover intentions. These results indicate that human resources should consider the generation to which the participant belongs when implementing competency development practices.

1. Introduction

One of the main challenges organizations face is how to retain employees and encourage them to have a strong sense of loyalty to the organization (Ahmad Saufi et al. 2023). The loss of highly experienced personnel translates into significant replacement costs, making today’s high staff turnover a severe issue for organizations and, by extension, Human Resource Management (Reiche 2008). Because they are seen as essential resources for the company and its human capital sets it apart from competitors, holding onto the finest workers is crucial (Sepahvand and Khodashahri 2021). According to the “resource-based view” theory, organizations that can retain their top people will have an advantage over their competitors in a job market that is constantly changing. This is because their human capital will be more difficult for competitors to replicate (Afiouni 2007; Barney 1991). According to several authors, the best approach to accomplishing this retention is to make employees feel that the organization is concerned about them (Eisenberger et al. 1986) by investing in developing their competencies (Jimenez-Jimenez and Sanz-Valle 2013).
This investment in the development of specialized competencies in employees can be seen in the context of Schultz’s human capital theory (Schultz 1961), which views knowledge as a type of capital. When employees see these procedures as highly valuable, they become emotionally invested in the company and put in more effort to meet its goals (Arthur 1994; Wood and Menezes 1998). According to Colquitt et al. (2014), it is the outcome of a conversation between the company and the worker in reaction to the proper treatment they receive. In such circumstances, the employee experiences affective commitment to the company or emotional attachment, which decreases their turnover intentions (Meyer et al. 1993).
However, organizations have another problem: their workforce is made up of employees from different generations. These differences can affect the way companies recruit, develop employees’ skills, motivate, and stimulate them to increase productivity, competitiveness, and service effectiveness (BeitKovsky 2016). Generational differences are not linear due to cultural changes that occur gradually and require time to mold individual personality and attitudes. It should also be emphasized that the formation of personality and attitudes is also partly influenced by the values transmitted by parents (Campbell et al. 2015). For Mahmoud et al. (2021), due to these changes and differences in character between the generations, generation has become a significant psychological variable that can be used to analyze employee behavior in an organizational context.
This study aims to investigate two main questions. First, does affective commitment mediate the relationship between organizational competency development practices (training, individualized support, and functional rotation) and turnover intentions? If so, how? Secondly, does this relationship change depending on the participant’s generation?

2. Literature Review

2.1. Organizational Competence Development Practices

In the modern work environment, where there are many challenges, employee competencies are essential, as they can be seen as the step between theory and practice (Bach and Suliková 2019). Organizational support methods that employees believe advance their professional development are known as Organizational Competence Development Practices (OCDPs) (Campion et al. 1994; Schneider et al. 1996). Employees place a high value on OCDPs because they help them become more competent and knowledgeable in a particular area that improves performance. OCDPs also make them feel more employable; the more highly they value OCDPs, the more likely they will stay in their current position (Campion et al. 1994; Schneider et al. 1996).
According to Bitencourt (2005), the elements that stand out in the development of competences can be summarized through the existence of the following factors:
  • Competencies are associated with the development of concepts, competencies, and attitudes.
  • They require competencies and translate into mobilizing resources in work practices.
  • They imply the articulation of resources and serve as a pillar in the search for better performance.
  • They produce constant questioning and trigger a process of individual learning, in which the greatest responsibility must be attributed to the individual themselves (self-development).
  • They are transferred and consolidated through relationships with other people (interaction).
“All activities carried out by the organization and the employee to maintain or improve the employee’s functional performance, learning, and competences” is a comprehensive definition of OCDPs, according to De Vos et al. (2011, p. 440). Therefore, OCDPs include career development programs, efforts to enhance on-the-job learning, and more conventional training formats. Van der Heijden et al. (2009) assert that it is crucial to consider various learning modalities when examining competence development.

2.2. Turnover Intentions

Turnover intentions are understood as employees’ desire to leave their current organization within a certain period and start looking for a new place of work (Benson 2006; Lestari and Margaretha 2021), considered the best predictor of voluntary turnover (Hom et al. 2017). This response can be interpreted through the theory of planned behavior, since behavioral intentions are causal antecedents of behavior (Ajzen 2012). In the view of Kakar et al. (2023), when an employee intends to leave the organization where they work, this is the final step towards leaving the organization, whether by resignation or through termination. Despite the existence of authors who question this relationship (Cohen et al. 2016), this is one of the reasons why this construct has been widely studied, especially when one of the current objectives of organizations is to retain the best employees (Long et al. 2012; Park and Shaw 2013). Organizations register substantial financial losses when turnover intentions are high, as the loss of a highly competent employee will affect the organization’s reputation, profitability, and performance (Kumar et al. 2021; Kakar et al. 2023).

Organizational Competence Development Practices and Turnover Intentions

As mentioned earlier, the development of employee competencies has become crucial in organizations, so they must invest in practices aimed at this, with these employees expressing fewer turnover intentions (Kim 2005). Eisenberger et al. (2001) state that employees normally do not reveal turnover intentions when they believe that the company values them and is working to help them enhance their competencies, which can be interpreted based on the premise of social exchange (Blau 1964) and the norm of reciprocity (Gouldner 1960). Another theory we can use to explain this relationship is the social comparison theory (Adams 1965). This author tells us that employees tend to compare the organization where they work with other organizations. If they perceive that yours offers them better competency development, they will stay with the organization. Hira and Rusilowati (2020) studied the effect of competence development and career development on turnover intentions and concluded that both have a negative and significant effect. Additionally, it was discovered in a study by Martini et al. (2023) that employee competency development had a negative and significant impact on turnover intentions. The first hypothesis is thus formulated:
Hypothesis 1. 
OCDPs have a negative and significant effect on turnover intentions.

2.3. Affective Commitment

Organizational commitment is a psychological state that binds employees to their organization (Meyer and Allen 1991). According to Ng (2015), this psychological connection is a stabilizing force that binds employees to organizations. According to the Meyer and Allen (1991) model, organizational commitment comprises three components: affective commitment, calculative commitment, and normative commitment.
Affective commitment is the employee’s emotional attachment to, identification, and involvement with the organization (Meyer and Allen 1984). Affective commitment results from an exchange between the organization and the employee (Colquitt et al. 2014), i.e., when the employee feels that they are treated well by the organization, they develop affective feelings towards it, manifesting a high level of affective commitment. According to Kumari and Afroz (2013), employees with high affective commitment have high feelings of belonging to the organization and feel psychologically attached to it. Recent investigations highlighted the impact affective commitment has on critical variables for organizations, like job performance (Bizri et al. 2021; Khan et al. 2019; Shao et al. 2022), organizational citizenship behaviors (Khaola and Rambe 2021), job satisfaction (Meredith et al. 2023; Nauman et al. 2021), and innovative work behavior (Bak 2020).

2.3.1. Organizational Competence Development Practices and Affective Commitment

According to Shore et al. (2006), social exchange connections that foster employee sentiments of commitment are linked to higher levels of organizational investment. They are therefore motivated by this sense of duty to go above and beyond the call of duty to further the organization’s interests. Accordingly, OCDPs considerably affect employee attitudes and behaviors based on the reciprocity norm (Gouldner 1960) and the social exchange theory (Blau 1964). OCDPs can affect workers’ perceptions of their professional worth, which may encourage workers to do their jobs in a more upbeat manner (Maurer et al. 2002). According to Moreira et al. (2022), employees see that organizations that prioritize competency development can demonstrate their concern for them, encouraging them to commit more to the organization. In a recent study by Hermansyah et al. (2024), which aimed to study the effect of competence development, work motivation, leadership, and compensation on affective commitment and implications for performance, they found that the variable with the strongest effect on affective commitment was work motivation, followed by skill development.
Hypothesis 2. 
OCDPs have a positive and significant effect on affective commitment.

2.3.2. Affective Commitment and Turnover Intentions

Nowadays, most organizations find it difficult to retain their best employees. From the perspective of Luturlean and Prasetio (2019), an employee stays with the organization due to the affective commitment they develop towards it. The components of organizational commitment, especially affective commitment, are negatively associated with behaviors that are detrimental to the organization and positively associated with behaviors that are favorable to the organization.
Among the consequences of affective commitment is a reduction in turnover intentions to leave the organization, since, if the employee feels emotionally attached to the organization, they will feel that they should remain there, leading to a reduction in their turnover intentions as well as unjustified absences from work (Meyer et al. 2002). Meyer and Allen (1991) state the great interest in studying affective commitment is because it is considered the best reducer of turnover intentions. Moreira and Cesário (2021) conducted a study investigating which of the three components of organizational commitment had the strongest effect on turnover intentions and concluded that this component was affective commitment. In a study by Nguyen et al. (2020), the authors also confirmed that affective commitment is the best reducer of intentions to leave. In a study of healthcare professionals, İbrahim et al. (2021) also concluded that affective commitment has a negative and significant effect on turnover intentions. This is the reasoning that leads us to formulate the following hypothesis:
Hypothesis 3. 
Affective commitment negatively and significantly affects turnover intentions.

2.4. Mediating Effect of Affective Commitment

Recent empirical research has revealed a retention path between employee development and turnover intention, mainly due to increased employees’ affective commitment towards their employer (Koster et al. 2011; Lee and Bruvold 2003; Rodrigues et al. 2019).
Lee and Bruvold (2003) reported that affective commitment mediates the relationship between OCDPs and turnover intentions, and more recent studies have reached similar conclusions (Koster et al. 2011; Nguyen et al. 2020; Rodrigues et al. 2019). Mehbooba and Hijazib (2017), in a study of employees in the information technology sector, also concluded that organizational commitment mediates the relationship between perceived investment in competence development and turnover intentions. The common conclusion of previous studies is that when an organization takes care of its employees by investing in their development, employees reciprocate through more significant commitment and decreased turnover intentions. More specifically, OCDPs increase affective commitment, reducing turnover intentions. This relationship can be explained through the psychological contract theory developed by Rousseau (1989, 2004), especially balanced psychological contract. Balanced psychological contract promotes dynamic and open-ended employment agreements, emotional involvement is high, the organization promotes the development of competences to promote the employability of its employees, and both the employee and the organization contribute to each other’s learning and development. In the presence of a solid psychological contract, employees want to stay in the organization.
This is the reasoning that leads us to deduce that affective commitment is the mechanism that explains the relationship between OCDPs and turnover intentions, thus formulating the hypothesis:
Hypothesis 4. 
Affective commitment has a mediating effect on the relationship between OCDPs and turnover intentions.

2.5. Generations

For Marshall (1983), as well as Rhodes (1983), age-related influences on work values can be considered as “cut-off effects, age effects and period effects”, with age effects being related to development, i.e., caused by psychosocial and biological ageing. Age effects, according to which it would be expected that as the years go by, young people become like their elders, are in opposition to cut-off (or generational) effects, which arise from the interaction between the environment and experiences, remaining relatively stable, because, despite differences, individuals who were born in a certain period have a strong identification with that period of history, feeling, thinking and acting similarly (Beldona et al. 2009). In this context, the term generation refers to people who were born in the same period and who share the same historical and social experiences, with each generation developing a unique personality that determines their feelings towards authority and the organization, what they want from work, what kind of work they want, and how they plan to satisfy their desires (Kupperschmidt 2000; Smola and Sutton 2002). From the perspective of Parry and Urwin (2011), generation results from the impact that a particular set of historical events and shared cultural phenomena have on a group of individuals and differentiates them from others. Smola and Sutton (2002) suggest that the effects of these experiences remain relatively stable throughout their lives. Although there is little consistency in the time it takes to classify each generation, behavioral sociologists suggest that each generation lasts around twenty years and then fades away to give way to a new generation (Shepard 2004).
The differences between generations can affect companies in many ways, from the way they recruit and develop teams to how they deal with change, and how they motivate, stimulate, and manage employees to increase productivity, competitiveness, and the effectiveness of their services. Organizations gain competitive advantages and benefits through the ability to manage this diversity of generations, leading to their success (BeitKovsky 2016). Organizations, HR specialists, and researchers have recently shown a growing interest in studying generational disparities. This interest is due to the need to adapt to new work values and behavioral patterns in the organizational practices of the new generations (Özek 2021). According to Saba (2013), there are three reasons for this interest:
  • Employees from different generations work together for extended periods due to rising retirement ages.
  • They are said to have incompatible values and expectations regarding their jobs.
  • There are no practices tailored to the needs of each generation.
The needs for skill development and the values attached to these practices may vary throughout generations if they have different expectations and attitudes regarding the nature of employment.
This study will consider three generations: baby boomers, Generation X, and Generation Y (or Millennials).
The baby boomer generation owes its name to the fact that 17 million more babies were born in this period than in previous census periods (O’Bannon 2001). The individuals of this generation were born after the Second World War and were influenced by the civil rights and women’s rights movements. They were brought up in an abundant and healthy economy, which created an era of optimism, opportunities, and progress, as they grew up in families where both parents were present, with safe schools and job security (Gursoy et al. 2008). Born between 1946 and 1964, baby boomers are known for being workaholics who believe in hard work and sacrifice themselves for success (Santos et al. 2011), they respect hierarchy and authority (Gursoy et al. 2008); they value face-to-face communication, getting up and going to another colleague to deal with work-related issues (Eisner 2005), they feel loyal to the organization (The Ken Blanchard Companies 2009), and they value seniority in the organization (Gursoy et al. 2008).
Born between 1965 and 1981, Generation X experienced the transition to technological development (Cogin 2012) and the economic instability that led to social changes (Cennamo and Gardner 2008). The following aspects characterize this generation: they value professional success without neglecting their family and are not interested in working beyond their working hours (Babel’ová et al. 2020; Santos et al. 2011); they are more cooperative (Cogin 2012); they enjoy working in teams; they are flexible and entrepreneurial; they enjoy feedback and short-term rewards (Tulgan 2004), as they still need support, feedback, and recognition from their colleagues (Babel’ová et al. 2020; Mahmoud et al. 2021); they believe that developing one’s skills is the best way to ensure one’s job and career security (Eisner 2005; Reisenwitz and Fowler 2019); and they are more devoted to their profession than to their employer.
Last but not least, the primary traits of Generation Y, who grew up with rapid technological development, economic expansion, and violence, are used to receiving all information almost instantaneously (Mahmoud et al. 2021; Rani and Samuel 2016). This generation, defined as those born between 1982 and 2000, are as follows: they are less autonomous and require more supervision (The Ken Blanchard Companies 2009), presumably because their parents tried to monitor everything their kids did, socially, academically, and even at work (Glass 2007); they question authority (Veloso et al. 2012); they are the most knowledgeable about new technologies (Cogin 2012; Santos et al. 2011); they enjoy daily feedback and seek out new challenges that push them to the limit (Lancaster and Stillman 2002); they value the development of competences for career progression (Deloitte 2011); they do not value job stability (Martin 2005), because they live for today and rarely make long-term plans (Bencsik et al. 2016); and what keeps them engaged and enthusiastic is the meaning and value of their work (Morrison et al. 2006).
The model shown in Figure 1 summarizes the hypotheses formulated in this study.

3. Method

3.1. Data Collection Procedure

A total of 2134 participants took part in this study on a voluntary basis. However, only 2123 were considered, since 11 of the participants did not meet the essential condition for taking part in this study, which was to have been working for at least six months in organizations located in Portugal. The sampling process was non-probabilistic, convenient, and intentional snowball sampling (Trochim 2000). This method makes data collection quicker and cheaper, since the participants in this study did not receive any reward for their answers to the questionnaire.
The questionnaire, which was posted online on the Google Forms platform, and its link were sent via LinkedIn in a private message to the researchers’ contacts. At the beginning of the questionnaire, all the information about the purpose of the study was given, and it stated that the confidentiality of the answers would be guaranteed. The participants were also informed that their individual data would never be known, as it would only be processed as a whole. After reading the informed consent form, the participants had to answer a question about their willingness to take part in the study. If they did not agree to take part in the study, they were referred to the end of the questionnaire. They were referred to the next section if they agreed to participate in the study. The questionnaire comprised seven questions to characterize the sample (age, gender, educational qualifications, seniority in the organization, seniority in the position, type of employment contract, and sector of work) and three scales (organizational practices for developing competencies, affective commitment, and turnover intentions). The data were collected between 2019 and 2021.

3.2. Participants

As far as gender is concerned, the number of female and male participants was almost identical (Table 1). However, regarding the generation to which the participants belonged, they mainly belonged to generation Y (Table 1). Regarding academic qualifications, the highest percentage of participants had a degree (Table 1). Most participants had a permanent contract, had been with the organization for 5 years or less, and worked in the private sector (Table 1). Before the COVID-19 pandemic, 1990 individuals (93.7%) answered the questionnaire, and 133 individuals (6.3%) answered after the pandemic.

3.3. Data Analysis Procedure

The initial step was importing the data into the IBM Corp., Armonk, NY, USA SPSS Statistics 29 program. Initially, each instrument’s validity was examined. Factor analyses were conducted to confirm the factor structure of the instruments in this study’s sample. Since the turnover intention instrument only has three questions, an exploratory factor analysis was performed. After calculation, the KMO value was determined to be more than 0.70 (Sharma 1996). Additionally, we computed the total variance explained, which ought to exceed 50%. Every item with a factor weight higher than 0.50 was considered when calculating each item’s factor weights. Using AMOS Graphics for Windows 29 software (IBM Corp., Armonk, NY, USA), confirmatory factor analysis was used to assess the validity of the remaining two instruments. A “model generation” logic was followed in the process (Jöreskog and Sörbom 1993). By the established guidelines (Hu and Bentler 1999), the following six fit indices were combined: Root Mean Square Error of Approximation (RMSEA), Root Mean Square Residual (RMSR), Goodness-of-fit Index (GFI), Tucker–Lewis Index (TLI), Chi-square ratio/degrees of freedom (χ2/gl), and Comparative Fit Index (CFI). It is acceptable if the chi-square/degrees of freedom ratio (χ2/gl) is less than 5. A good fit is indicated by values above 0.90 for the CFI, GFI, and TLI, and an adequate fit is indicated by values above 0.80. A good match is indicated by RMSEA values less than 0.08 (McCallum et al. 1996). The fit is better when the RMSR is lower (Hu and Bentler 1999). Next, we examined the construct reliability for every dimension on the scale, where a value greater than 0.70 is expected. The average variance extracted (AVE), which should be more than 0.50, was used to test for convergent validity (Fornell and Larcker 1981). However, AVE values larger than 0.40 are acceptable, suggesting good convergent validity when Cronbach’s alpha value is greater than 0.70 (Hair et al. 2011). The square root of the AVE’s value must be higher than the factor’s correlation value for discriminant validity to be present (Anderson and Gerbing 1988; Fornell and Larcker 1981).
By calculating Cronbach’s alpha, which needs to be greater than 0.70, the internal consistency of each instrument was evaluated (Bryman and Cramer 2003).
Finally, the items’ sensitivity was tested to see if they could discriminate between subjects. All response points on the items must have an answer, the median cannot be near one of the extremes, and the absolute kurtosis and skewness values cannot be greater than 2 or 7, respectively (Finney and DiStefano 2013). To perform descriptive statistics on the variables under study and to test whether the participants’ answers differed significantly from the scale’s central point, the parametric one-sample Student’s t-test was used. The effect of generations on the variables under study was tested using the one-way ANOVA parametric test after checking the respective assumptions. The association between the variables under study was tested using Pearson’s correlations. The hypotheses formulated in this study were tested using multiple linear regressions after testing the respective assumptions. To test hypothesis 4, as it presupposes a mediating effect, the procedures proposed by Baron and Kenny (1986) were followed.

3.4. Instruments

We employed the De Vos et al. (2011) tool, translated into Portuguese by Moreira and Cesário (2022), to assess organizational competence development practices. Twelve items make up this measure, which is rated on a 5-point Likert scale (1 being “Never” to 5 being “Always”). These 12 items fall under three dimensions: training, individualized support, and functional rotation. Confirmatory factor analysis was used to assess their validity. The obtained adjustment indices (χ2/gl = 3.75; GFI = 0.99; CFI = 0.99; TLI = 0.99; RMSEA = 0.036; SRMR = 0.029) were deemed sufficient. Nevertheless, items 1 and 6 had to be eliminated because of their low factor weight. Training scored 0.93, individualized support scored 0.72, and functional rotation scored 0.78 regarding construct reliability—values above 0.70 (Bryman and Cramer 2003). Training and functional rotation had respective AVE values of 0.74 and 0.64, indicating strong convergent validity. Individualized support was the only one with an AVE value of 0.47 (below 0.50), although the convergent validity was still considered adequate because it had a Cronbach’s alpha value over 0.70 (Hair et al. 2011). Regarding internal consistency, all dimensions exhibited Cronbach’s alpha values greater than 0.70, including training at 0.88, individualized support at 0.71, and functional rotation at 0.78.
The corresponding subscale of Meyer and Allen’s (1997) organizational commitment instrument, which consists of six items rated on a seven-point Likert scale (ranging from 1 for “Strongly Disagree” to 7 for “Strongly Agree”), was utilized to measure affective commitment. Additionally satisfactory are the fit indices found in the confirmatory factor analysis (χ2/gl = 2.62; RMSEA = 0.028; GFI = 0.99; CFI = 0.99; TLI = 0.99; RMSEA = 0.028; SRMR = 0.024). This subscale had a construct reliability of 0.88 and convergent validity with an AVE of 0.56. A Cronbach’s alpha value of 0.89 was found for internal consistency.
The three items that comprise the instrument created by Bozeman and Perrewé (2001) were used to test turnover intentions, and the results were rated on a 5-point scale (1 being “Strongly Disagree” to 5 being “Strongly Agree”). An exploratory factor analysis was performed, since there were only three items in this instrument. The results showed a KMO of 0.68 and an explained variance of 68.52%. Additionally, the results of Bartlett’s test of sphericity were significant at p < 0.001, suggesting that the data originated from a multivariate population that is normally distributed (Pestana and Gageiro 2003). Its Cronbach’s alpha value for internal consistency was 0.77. Additionally, it was discovered that none of the components of the three instruments seriously deviated from normality.
The generations were categorized by Twenge’s (2010) guidelines. After providing their birth year, participants were divided into three groups: baby boomers (1946–1964), Generation X (1965–1981), and Generation Y (1982–2000).
As control variables, we included the sociodemographic variables in the questionnaire and another variable created according to the data collection date, using the COVID-19 pandemic as a reference point.

4. Results

Two models were tested, with one factor and five factors. The fit indices of the one-factor model proved to be inadequate (χ2/gl = 21.99; GFI = 0.87; CFI = 0.86; TLI = 0.82; RMSEA = 0.099; SMRM = 0.307). In turn, the fit indices of the six-factor model proved to be adequate or very close to adequate (χ2/gl = 3.37; GFI = 0.98; CFI = 0.99; TLI = 0.98; RMSEA = 0.033; SMRM = 0.067). It can therefore be concluded that the theoretical conceptualization, which determined five variables, adequately represents the observed data. The correlations are consistent with the theorized pattern of relationships.

4.1. Descriptive Statistics of the Variables under Study

Initially, we tried to understand the position of the answers given by the participants in the variables under study. The results show that the participants in this study had a perception of organizational skill development practices that was significantly below the central point of the scale (3) (Table 2). They revealed high turnover intentions, significantly above the scale’s central point (3) (Table 2). They also revealed themselves to be affectively committed to the organization where they work, since the results obtained were significantly above the central point of the scale (4) (Table 2).

4.2. Association between Sociodemographic Variables and the Variables under Study

Next, the association between the sociodemographic variables and those under study was tested. To this end, several multiple linear regressions were carried out, in which the predictor variables were sociodemographic variables, and the dependent variables were the variables under study. Gender was found to have a positive and significant association with training and individualized support and a negative and significant association with turnover intentions (Table 3). Length of service in the organization was positively and significantly associated with all the variables under study (Table 3). The sector of activity had a significant and negative association with individualized support, functional rotation, and affective commitment, as well as a positive and significant association with turnover intentions (Table 3). Generations had a significant and negative effect on training and a positive and significant effect on individualized support (Table 3).

4.3. Association between Variables under Study

Pearson’s correlations show that training, individualized support, functional rotation and affective commitment were negatively and significantly associated with turnover intentions (Table 4). Training, individualized support, and functional rotation were positively and significantly associated with affective commitment (Table 4).

4.4. Hypothesis

4.4.1. Hypothesis 1

The results show that training, individualized support, and functional rotation negatively and significantly affected turnover intentions (Table 5). Among the socio-demographic variables, only seniority in the organization positively and significantly affected turnover intentions (Table 5). The model explains 13% of the variability in turnover intentions (Table 5).
Next, the effect of organizational competency development practices on turnover intentions was tested, separating the participants by generation. For Generation Y, work contract, training, individualized support, and functional rotation negatively and significantly affected turnover intentions (Table 6). Seniority in the organization had a positive and significant effect on turnover intentions (Table 6). The model explains 14% of the variability in turnover intentions (Table 6).
For Generation X, training, individualized support, and functional rotation negatively and significantly affected turnover intentions (Table 6). Seniority in the organization had a positive and significant effect on turnover intentions (Table 6). The model explains 10% of the variability in turnover intentions (Table 5).
For the baby boomer generation, only individualized support negatively and significantly affected turnover intentions (Table 6). The model explains 25% of the variability in turnover intentions (Table 6).
Hypothesis 1 was supported.

4.4.2. Hypothesis 2

The results show that organizational seniority, generations, training, individualized support, and functional rotation positively and significantly affected affective commitment (Table 7). The model explains 26% of the variability in affective commitment (Table 7).
Next, the effect of organizational competency development practices on affective commitment was tested, separating the participants by generation. For Generation Y, organizational seniority, work contract, training, individualized support, and functional rotation positively and significantly affected affective commitment (Table 8). The model explains 26% of the variability in affective commitment (Table 8).
For Generation X, organizational seniority, training, individualized support, and functional rotation positively and significantly affected affective commitment (Table 8). The model explains 25% of the variability in affective commitment (Table 8).
For the baby boomer generation, only organizational seniority and academic qualifications positively and significantly affected affective commitment (Table 8). The model explains 26% of the variability in affective commitment (Table 8).
Hypothesis 2 was partially supported.

4.4.3. Hypothesis 3

The results show that affective commitment negatively and significantly affected turnover intentions (Table 9). Seniority in the organization had a positive and significant effect on turnover intentions (Table 9). The model explains 29% of the variability in turnover intentions (Table 8).
Next, the effect of affective commitment on turnover intentions was tested, separating the participants by generation. For Generation Y, affective commitment negatively and significantly affected turnover intentions (Table 10). Seniority in the organization had a positive and significant effect on turnover intentions (Table 10). The model explains 29% of the variability in turnover intentions (Table 10).
For Generation X, affective commitment negatively and significantly affected turnover intentions (Table 9). Seniority in the organization had a positive and significant effect on turnover intentions (Table 10). The model explains 28% of the variability in turnover intentions (Table 10).
For the baby boomer generation, affective commitment negatively and significantly affected turnover intentions (Table 10). Seniority in the organization and sector had a positive and significant effect on turnover intentions (Table 10). The model explains 37% of the variability in turnover intentions (Table 10).
Hypothesis 3 was supported.

4.4.4. Hypothesis 4

In accordance with Baron and Kenny (1986), the assumptions for testing the mediating effect were tested in hypotheses 1, 2, and 3.
To test this hypothesis, a two-step multiple linear regression was carried out. In the first step, control variables (sociodemographic variables) and predictor variables were introduced as independent variables. In the second step, the mediating variable was introduced as an independent variable.
The results show a total mediating effect of affective commitment on the relationship between training and turnover intentions, since training, when the mediating variable was introduced into the regression equation, no longer significantly affected turnover intentions (Table 11).
As for the mediating effect of affective commitment on the relationship between individualized support and turnover intentions and on the relationship between functional rotation and turnover intentions, there was a partial mediation effect, since the effect of individualized support and functional rotation on turnover intentions continued to be significant but decreased in intensity when the mediating variable was introduced into the regression equation (Table 11).
The model explains 31% of the variability in turnover intentions. There was a significant increase in variability of 18%.
The mediating effect was then tested according to the generation to which the participant belonged.
For Generation Y, the results show a total mediating effect of affective commitment in the relationship between training and turnover intentions, since training, when the mediating variable was introduced into the regression equation, no longer significantly affected turnover intentions (Table 12). As for the mediating effect of affective commitment on the relationship between individualized support and turnover intentions, and between functional rotation and turnover intentions, there was a partial mediation effect, since the effect of individualized support and functional rotation on turnover intentions continued to be significant but decreased in intensity when the mediating variable was introduced into the regression equation, (Table 12). The model explains 28% of the variability in turnover intentions. There was an increase in variability of 15%.
For Generation X, the results show a total mediating effect of affective commitment on the relationship between training and turnover intentions, between individualized support and turnover intentions, and between functional rotation and turnover intentions, since training, individualized support, and functional rotation, when the mediating variable was introduced into the regression equation, no longer significantly affected turnover intentions (Table 12). The model explains 30% of the variability in turnover intentions. There was a significant increase in variability of 16%.
The mediating effect of affective commitment was not tested for the baby boomer generation, as the conditions proposed by Baron and Kenny (1986) were not verified. Hypothesis 4 was partially supported.

5. Discussion

This study aimed to study the effect of organizational skill development practices (training, individualized support, and functional rotation) and whether this relationship was mediated by affective commitment. Another objective was to test whether these relationships changed depending on the generation to which the participant belonged.
Hypothesis 1 was confirmed, since training, individualized support, and functional rotation negatively and significantly affected turnover intentions. These results align with the literature, which states that developing employees’ competences reduces their turnover intention (Martini et al. 2023). This relationship can be explained through Adams’s social comparison theory (Adams 1965). According to this theory, employees compare their organizations with others, and if they perceive that their organization cares more about their competency development than others, they decide to stay in the organization. It should be noted that individualized support was the dimension that had the strongest effect on turnover intentions. This dimension is based on career development, and according to Talluri and Uppal (2023), subjective career success has a negative and significant effect on turnover intentions, being stronger in the presence of adequate competencies. However, when it was tested whether these relationships varied according to the generation to which the participant belonged, it was found that, for Generation Y and Generation X, the results remained the same. However, this was different for the baby boomer generation, where only individualized support negatively and significantly affected turnover intentions.
Hypothesis 2 was partially confirmed, since the results indicate that generation, training, individualized support, and functional rotation positively and significantly affected affective commitment. These results are also in line with the literature, since Nguyen et al. (2020) state that when an organization is concerned with developing the competences of its employees, they feel emotionally attached to it. These results can be explained by the premise of social exchange (Blau 1964) and the norm of reciprocity (Gouldner 1960), according to which employees repay the organization for its investment in developing their competencies by developing a strong emotional bond with it. Once again, for Generations Y and X, the results remain the same. For Generations X and Y, training had the strongest effect on emotional commitment. However, for Generation Y, individualized support for practice had the strongest effect on affective commitment. This is in line with the results obtained in a study by Naim and Lenka (2017), which concluded that this support and sharing of knowledge have a positive and significant effect on affective commitment. However, for the baby boomer generation, none of the OCDPs affected affective commitment. The effect of training on affective commitment is practically null. It should be noted that this dimension contained items referring to on-the-job training. In the study carried out by Galliart (2020), this author concluded that, for the baby boomer generation, excessive learning by doing can be prejudicial.
Hypothesis 3, which assumed a negative and significant effect of affective commitment on turnover intentions, was also confirmed. These results also corroborate what the literature tells us: affective commitment has a negative and significant effect on turnover intentions, since employees stay with the organization when they feel affectively committed to it (İbrahim et al. 2021; Luturlean and Prasetio 2019; Meyer and Allen 1991). This result holds for participants from all three generations. The strength of the effect was practically the same between the three generations. Once again, among the variables under study, the one that proved to be the best reducer of intentions to leave was affective commitment, in line with the results obtained in previous studies (Moreira et al. 2022; Martins et al. 2023).
Finally, a total mediation effect of affective commitment was confirmed in the relationship between training and turnover intentions. Only a partial mediation effect was confirmed in the relationship between individualized support and turnover intentions and in the relationship between functional rotation and turnover intentions. These results confirm what the literature tells us: that affective commitment mediates the relationship between OCDPs and turnover intentions (Koster et al. 2011; Nguyen et al. 2020; Rodrigues et al. 2019). When an organization takes care of its employees by investing in their development, employees reciprocate through more significant commitment and decreased turnover intentions. This relationship can be explained through the theory of the balanced psychological contract because if the organization is concerned with developing employees’ competencies to develop and increase their employability, they feel a strong emotional attachment to the organization and stay with it (Rousseau 1989, 2004). For Generation Y, there was a total mediation effect in the relationship between training and turnover intentions. There was a partial mediation effect in the relationship between individualized support and turnover intentions and in the relationship between functional rotation and turnover intentions. These results align with the literature, as the development of competences boosts the affective commitment of Generation Y employees, leading to their intention to stay with the company and reducing their turnover intentions (Naim and Lenka 2018). For Generation X participants, there was a total mediation effect in the relationship between all OCDPs and exit intentions. These results indicate that OCDPs are essential for boosting their affective commitment and reducing their turnover intentions. The mediating effect was not tested for the baby boomer generation, since the assumptions for testing the mediating effect with OCDP dimensions were not met (Baron and Kenny 1986).
When the descriptive statistics of the variables under study were produced, it was found that the participants in this study had a low perception of the existence of OCDPs in their organization. Training was perceived as the most frequent, and functional rotation was perceived as the least frequent. These results align with previous studies’ findings that training is the most frequently perceived practice (Boselie et al. 2005; Cesário 2015; Moreira et al. 2022). To Whitener (2001), these practices often exist but are not perceived by employees as the organization would like. The participants who perceived training as most frequent were those from the baby boomer generation. As for individualized support, the Generation Y participants perceived it most frequently. These results are natural, since the items in this dimension refer to support for career progression. Generation Y values developing competences for career progression (Deloitte 2011; Naim and Lenka 2018) and looking for quick leadership programs (Glass 2007). Turnover intentions were significantly above the mid-point of the scale, and the baby boomer participants showed the highest turnover intentions. These results go against what was expected, since, according to the literature, Generation Y does not value job stability, jumping from project to project, position to position, department to department, or organization to organization (Martin 2005). About affective commitment, the participants in this study showed high levels of affective commitment, with the baby boomer generation showing the highest levels. This result is in line with the literature, since this generation has the greatest loyalty to the organization where they work (The Ken Blanchard Companies 2009), making it logical that they should develop a greater affective commitment to it.
Among the sociodemographic variables, the one that had a positive and significant effect on all the variables under study was seniority in the organization. These results regarding OCDPs are contrary to the literature. However, regarding seniority in the job, the participants who had been in their current job for less time had a greater perception of individualized support and functional rotation. These results are in line with the literature. In accordance with some authors (e.g., Van Dam 2003), employees with less seniority in the job and the organization had a more positive attitude towards participating in practices to develop their competencies and promote employability. The participants who had been with the organization the longest had the greatest affective commitment. These results align with the literature, as seniority in the organization is one of the sociodemographic variables that most contributes to affective commitment (Meyer et al. 2002). As for gender, female participants had a higher perception of training and individualized support but fewer turnover intentions.
In terms of sector of activity, participants from the public sector had a higher perception of individualized support, functional rotation, and greater affective commitment, but lower turnover intentions. These results may be because, in Portugal, mobility is the order of the day in the public sector, hence the high perception of functional rotation. On the other hand, a job in the public sector is still considered almost lifelong, thus explaining why public sector employees had lower turnover intentions than those in the private sector.

5.1. Limitations

The main limitations were the procedures employed for collecting the data and the fact that the questionnaires were self-reporting tools with closed-ended questions and required responses, which may have influenced the participants’ responses.
Another limitation is the small number of participants from the baby boomer generation compared to the other generations. This limitation may be due to two factors: the baby boomer generation is close to retirement age and has a smaller presence in the labor market; the data were collected online, mostly via LinkedIn, and as we know, these employees’ IT skills are lower than those of other generations.
The use of the word “generations” instead of the word “age” may have been a limitation, as there is no consensus on whether one term is correct or not.
Another limitation of this study was that it did not take into account the transition groups between the generations, known as the BBX generation (transition group between the baby boomer and X generations), the XY generation (transition group between the X and Y generations), and the YZ generation (transition group between the Y and Z generations). Individuals in this transition group may identify more with the generation in which they were not included.
Lastly, because the study was cross-sectional, it was unable to determine a causal association between the factors. It would take a long-term investigation to investigate causal linkages. Several methodological and statistical guidelines were followed to lessen the impact of common method variance (Podsakoff et al. 2003).

5.2. Theoretical Implications

It should be noted that the perception of organizational skill development practices is fundamental for establishing an exchange relationship between organizations and employees (Bach and Suliková 2019). If employees perceive that the organization cares about developing their skills, this perception establishes social exchange relationships between the two which benefit both parties. Under these conditions, employees work hard to achieve the organization’s objectives while at the same time developing a greater emotional commitment to the organization (Hermansyah et al. 2024; Moreira et al. 2022). When there is adequate implementation of organizational skill development practices, and employees correctly perceive these, in response they develop a greater affective commitment to the organization while at the same time expressing their intention to stay with it (Nguyen et al. 2020).
The negative and significant relationship between affective commitment and intentions to leave confirms what several authors have told us, including Nguyen et al. (2020), that organizational commitment is the variable that best predicts intentions to leave the organization, even in different contexts of organizational change. Moreira and Cesário (2021) state that, among the three components of organizational commitment, the one with the strongest relationship with intentions to leave is affective commitment. In line with previous analyses, the relationship between organizational skill development practices and exit intentions is also significant and negative (Martini et al. 2023). In the view of Bach and Suliková (2019), skill development has become so crucial for organizations that they must invest in practices that develop their employees’ skills and lead to a decrease in their intention to leave the organization.
This study has not only confirmed the relationships between organizational competence development practices, affective commitment, and turnover intentions, but it has also shed light on a crucial aspect—the significance and intensity of these relationships vary according to the generation to which employees belong, as highlighted by BeitKovsky (2016). This finding underscores the importance of understanding and addressing the unique values and expectations about work that different generations bring. As Saba (2013) points out, they are not easily compatible.
Having outlined the theoretical implications of this study, it is our hope that these findings will inspire and encourage other researchers to delve deeper into this field, replicating and expanding upon the results found here. The potential for further research in this area is vast, and we look forward to seeing how it unfolds.

5.3. Practical Implications

In accordance with Saba (2013), one of the reasons it has become so important to investigate the generational effect is that, as this study demonstrates, generations variably view and value the competency development strategies that organizations support.
This study also shows that, although employees do not view competency development activities as the organization would like them to be, there is still a need for organizations to invest more in them and make them visible to staff (Whitener 2001). Human resource management uses these techniques frequently. Employees do not, however, view them as they would like, maybe due to their lack of clarity and the fact that they are not given the credit they merit for improving their abilities. This low perception may be because the competence development policy is still very much based on classical training that only offers specific competencies, whose purpose is not always perceived as useful by employees (Bach and Suliková 2019). For employees, the main problem is practical relevance, i.e., how to put what they have learnt into practice.
One of its strongest points is this study’s indication of the existence of an affective organizational commitment mediating influence on the relationship between OCDPs and turnover intentions. Organizations must use specific competency development practices appropriate for their workforce to retain their best employees. This is because these employees are difficult to replace and, according to the “resource-based view” theory (Afiouni 2007; Barney 1991), they become a competitive advantage in today’s labor market.

6. Conclusions

At a time when one of the biggest problems facing organizations is high employee turnover (Reiche 2008; Martins et al. 2023), leading to substantial financial losses for organizations, as the loss of a highly competent employee will affect the organization’s reputation, profitability, and performance (Kumar et al. 2021; Kakar et al. 2023), this study has confirmed that if an organization wants to retain its best employees, it must invest in developing their skills in order to boost their emotional commitment and reduce their intentions to leave (Koster et al. 2011; Nguyen et al. 2020; Rodrigues et al. 2019). It was also concluded that, of all the development practices studied, individualized support acts as the greatest reducer of intentions to leave, results that are maintained when analyzing the effect by generation. This dimension is made up of three items: one referring to career development support, another to coaching, and another to mentoring. In other words, this dimension is based on career development. In Talluri and Uppal’s (2023) view, subjective career success in the presence of adequate competencies has a stronger effect on turnover intentions.
Another indication from this study is that organizations should consider the generation to which the employee belongs, especially regarding competency development, as interests and needs vary from generation to generation (Kapoor and Solomon 2011). By knowing how to manage this diversity of generations, organizations gain competitive advantages and benefits that will lead to their success (BeitKovsky 2016). It should be noted that, for the baby boomer generation, only individualized support had a negative and significant effect on turnover intentions, which means that despite being the oldest generation, they still consider career development to reduce their turnover intentions.
Among the other socio-demographic variables, seniority in the organization proved to be the most important, as it had a significant effect on all the variables under study, followed by seniority in the job.

Author Contributions

Conceptualization, A.M., C.T. and A.A.; methodology, A.M. and C.T.; software, A.M.; validation, A.M., C.T. and A.A.; formal analysis, A.M.; investigation, A.M. and C.T.; resources, A.M.; data curation, A.M.; writing—original draft preparation, A.M., C.T. and A.A.; writing—review and editing, A.M. and C.T.; visualization, A.M.; supervision, A.M., C.T. and A.A.; project administration, A.M.; funding acquisition, A.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study, as all participants (before answering the questionnaire) needed to read the informed consent. After reading the informed consent, they had to answer a question as to whether they agreed to answer the questionnaire. Only if they agreed could they complete the questionnaire. If they disagreed, they could not do so. The participants were informed about the study’s purpose and the confidentiality of the results, since the individual results would never be known and would only be analyzed as a whole.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author. The data are not publicly available because, in their informed consent, participants were informed that the data were confidential and that individual responses would never be known, as data analysis would be of all participants combined.

Acknowledgments

I would like to thank the Quilbot and Grammarly programs that helped me translate the manuscript from Portuguese into English and improve the grammar of the text.

Conflicts of Interest

The authors declare no conflicts of interest.

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Admsci 14 00097 g001
Figure 1. Research model.
Figure 1. Research model.
Admsci 14 00097 g001
Table 1. Sample descriptive statistics.
Table 1. Sample descriptive statistics.
VariableFrequencyPercentage
GenderFemale (0)106450.1%
Male (1)105949.9%
GenerationGeneration Y (1)135163.6%
Generation X (2)69332.6%
Baby Boomer (3)793.7%
Academic qualifications12th year or less (1)34116.1%
Degree (2)95745.1%
Master (3)82538.9%
Work contractUncertain Term (1)27412.9%
Fixed-term (2)43120.3%
Effective (3)127860.2%
Other (4)1406.6%
Seniority in the organization1 year or less (1)66931.5%
1 to 5 years (2)83239.2%
5 to 10 years (3)24511.5%
10 to 15 years (4)1597.5%
More than 15 years (5)21810.3%
Seniority in the function1 year or less (1)56926.8%
1 to 5 years (2)91042.9%
5 to 10 years (3)31014.6%
10 to 15 years (4)1476.9%
More than 15 years (5)1878.8%
SectorPrivate (0)193591.1%
Public (1)1888.9%
COVID-19Pre-COVID-19 (0)199093.7%
Post-COVID-19 (1)1336.3%
Note. Between parentheses are the codings of sociodemographic variables.
Table 2. Descriptive statistics of the variables under study (OCDPs, affective commitment, and turnover intentions).
Table 2. Descriptive statistics of the variables under study (OCDPs, affective commitment, and turnover intentions).
VariabletdfpdMeanSD
Training−27.95 ***2122<0.0010.612.430.93
Individualized support−36.53 ***2122<0.0010.792.211.00
Functional rotation−37.29 ***2122<0.0010.812.081.14
Turnover intentions9.91 ***2122<0.0010.223.261.20
Affective commitment19.17 ***2122<0.0010.424.631.52
Note. *** p < 0.001.
Table 3. Association between sociodemographic variables and the variables under study (OCDPs, affective commitment, and turnover intentions).
Table 3. Association between sociodemographic variables and the variables under study (OCDPs, affective commitment, and turnover intentions).
Independent VariableDependent Variable
TrainingIndividualized SupportFunctional RotationAffective CommitmentTurnover Intentions
Gender 0.06 **0.05 *0.030.03−0.05 *
Organizational seniority0.12 ***0.07 *0.27 ***0.23 ***0.056 ***
Academic qualifications0.01−0.02−0.03−0.01−0.02
Job seniority 0.02−0.10 ***−0.17 ***−0.09 ***0.02
Work contract0.030.020.010.06 ***−0.04
Sector−0.02−0.07 **−0.09 ***−0.06 ***0.05 *
COVID0.010.020.030.01−0.03
Generations0.09 **−0.14 ***0.010.030.01
R2a0.040.040.060.050.01
F11.11 ***11.46 ***17.12 ***14.09 ***3.40 **
Note. * p < 0.05; ** p < 0.01; *** p < 0.001.
Table 4. Pearson’s correlation results.
Table 4. Pearson’s correlation results.
1.11.21.323
1.1. Training-
1.2. Individualized support0.47 ***-
1.3. Functional rotation0.44 ***0.46 ***-
2.   Turnover intentions−0.26 ***−0.33 ***−0.24 ***-
3.   Affective commitment0.40 ***0.40 ***0.35 ***−0.51 ***-
Note. *** p < 0.001.
Table 5. Effect of OCDPs on turnover intentions.
Table 5. Effect of OCDPs on turnover intentions.
Independent VariableDependent VariableFpR2aβp
GenderTurnover Intentions30.55 ***<0.0010.13−0.030.169
Organizational seniority0.11 ***<0.001
Academic qualifications−0.030.218
Job seniority−0.020.430
Work contract−0.030.146
Sector0.020.369
COVID−0.020.350
Generations−0.020.571
Training−0.13 ***<0.001
Individualized support−0.22 ***<0.001
Functional rotation−0.10 ***<0.001
Note. *** p < 0.001.
Table 6. Effect of OCDPs on turnover intentions by generation.
Table 6. Effect of OCDPs on turnover intentions by generation.
Independent VariableBaby BoomersGeneration XGeneration Y
Gender−0.10−0.01−0.025
Organizational seniority0.090.10 *0.11 ***
Academic qualifications−0.09−0.01−0.02
Job seniority−0.11−0.040.00
Work contract−0.020.01−0.06 *
Sector0.190.02−0.01
COVID−0.09−0.00−0.03
Training−0.04−0.11 *−0.15 ***
Individualized support−0.43 ***−0.17 ***−0.21 ***
Functional rotation0.06−0.13 **−0.10 **
F4.33 ***9.08 ***22.42 ***
R2a0.250.100.14
Note. * p < 0.05; ** p < 0.01; *** p < 0.001.
Table 7. Effect of OCDPs on affective commitment.
Table 7. Effect of OCDPs on affective commitment.
Independent VariableDependent VariableFpR2aβp
GenderAffective Commitment69.76 ***<0.0010.26−0.000.918
Organizational seniority0.16 ***<0.001
Academic qualifications0.000.985
Job seniority−0.050.046
Work contract0.040.024
Sector−0.030.181
COVID0.000.979
Generations0.06 **0.022
Training0.20 ***<0.001
Individualized support0.28 ***<0.001
Functional rotation0.11 ***<0.001
Note. ** p < 0.01; *** p < 0.001.
Table 8. Effect of OCDPs on affective commitment by generation.
Table 8. Effect of OCDPs on affective commitment by generation.
Independent VariableBaby BoomersGeneration XGeneration Y
Gender0.07−0.01−0.01
Organizational seniority0.27 *0.17 ***0.11 ***
Academic qualifications0.17 *−0.020.01
Job seniority−0.19−0.02−0.02
Work contract0.04−0.010.06 *
Sector−0.14−0.03−0.00
COVID0.09−0.020.00
Training0.130.20 ***0.20 ***
Individualized support0.170.22 ***0.30 ***
Functional rotation0.110.14 ***0.10 ***
F4.45 ***24.39 ***46.51 ***
R2a0.260.250.26
Note. * p < 0.05; *** p < 0.001.
Table 9. Effect of affective commitment on turnover intentions.
Table 9. Effect of affective commitment on turnover intentions.
Independent VariableDependent VariableFpR2aβp
GenderTurnover Intentions96.88 ***<0.0010.29−0.040.058
Organizational seniority0.18 ***<0.001
Academic qualifications−0.020.205
Job seniority−0.030.152
Work contract−0.010.636
Sector0.010.487
COVID−0.020.240
Generations0.020.330
Affective commitment−0.54 ***<0.001
Note. *** p < 0.001.
Table 10. Effect of affective commitment on turnover intentions by generation.
Table 10. Effect of affective commitment on turnover intentions by generation.
Independent VariableBaby BoomersGeneration XGeneration Y
Gender−0.08−0.02−0.04
Organizational seniority0.22 *0.18 ***0.15 ***
Academic qualifications0.01−0.02−0.01
Job seniority−0.16−0.0040.01
Work contract0.050.00−0.03
Sector0.21 *0.01−0.01
COVID−0.07−0.01−0.03
Affective commitment−0.55 ***−0.55 ***−0.53 ***
F8.29 ***36.61 ***66.72 ***
R2a0.370.280.29
Note. * p < 0.05; *** p < 0.001.
Table 11. The mediating effect of affective commitment on the relationship between OCDPs and turnover intentions.
Table 11. The mediating effect of affective commitment on the relationship between OCDPs and turnover intentions.
Independent VariableStep1Step2
Gender−0.03−0.03
Organizational seniority0.11 ***0.19 ***
Academic qualifications−0.03−0.03
Job seniority−0.02−0.04
Work contract0.03−0.01
Sector0.020.01
COVID−0.019−0.02
Generations−0.020.01
Training−0.13 ***−0.03
Individualized support−0.22 ***−0.08 ***
Functional rotation−0.10 ***−0.05 *
Affective commitment −0.48 ***
F30.55 ***77.35 ***
R2a0.130.31
ΔR2 0.18 ***
Note. * p < 0.05; *** p < 0.001.
Table 12. The mediating effect of affective commitment on the relationship between OCDPs and turnover intentions by generation.
Table 12. The mediating effect of affective commitment on the relationship between OCDPs and turnover intentions by generation.
Independent VariableGeneration XGeneration Y
Step1Step2Step1Step2
Gender−0.01−0.02−0.03−0.03
Organizational seniority0.10 *0.18 ***0.11 ***0.16 ***
Academic qualifications−0.01−0.02−0.02−0.01
Job seniority−0.04−0.050.00−0.01
Work contract0.010.01−0.06 *−0.03
Sector0.020.00−0.01−0.01
COVID−0.004−0.01−0.03−0.02
Training−0.11 *−0.01−0.15 ***−0.05
Individualized support−0.17 ***−0.06−0.21 ***−0.07 *
Functional rotation−0.13 **−0.06−0.10 **−0.06 *
Affective commitment −0.50 *** −0.47 ***
F9.08 ***27.70 ***22.42 ***52.01 ***
R2a0.100.290.140.30
ΔR2 0.19 *** 0.16 ***
Note. * p < 0.05; ** p < 0.01; *** p < 0.001.
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Moreira, A.; Tomás, C.; Antunes, A. The Mediating Effect of Affective Commitment on the Relationship between Competence Development and Turnover Intentions: Does This Relationship Depend on the Employee’s Generation? Adm. Sci. 2024, 14, 97. https://doi.org/10.3390/admsci14050097

AMA Style

Moreira A, Tomás C, Antunes A. The Mediating Effect of Affective Commitment on the Relationship between Competence Development and Turnover Intentions: Does This Relationship Depend on the Employee’s Generation? Administrative Sciences. 2024; 14(5):97. https://doi.org/10.3390/admsci14050097

Chicago/Turabian Style

Moreira, Ana, Carla Tomás, and Armanda Antunes. 2024. "The Mediating Effect of Affective Commitment on the Relationship between Competence Development and Turnover Intentions: Does This Relationship Depend on the Employee’s Generation?" Administrative Sciences 14, no. 5: 97. https://doi.org/10.3390/admsci14050097

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