Human resources policies, learning, and turnover intention in organizations¹

Abstract

Purpose:

The objective of this research is to investigate how human resources policies and the perception of learning opportunities in organizations influence the intention of professional turnover.

Originality/value:

The authors demonstrated that, by understanding the existing relationships between the researched constructs, organizations should increase their investments in improvements in human resources policies, particularly in actions that promote a greater perception of learning opportunities, which reduce the intention of employee turnover of their talents.

Design/methodology/approach:

This research was developed with a quantitative approach and data collection was carried out through a survey. The questionnaires were applied to 250 professionals working in the labor market and students from a private university. Data analysis was performed with a confirmatory factor analysis and, subsequently, a structural equation modeling.

Findings:

The authors presented the research results in a descriptive way, the three hypotheses defined for the study were accepted, and the dimensions of human resources policies were considered significant. The authors presented relevant attributes for the understanding that, even though there are several reasons that can influence a professional in his decision to leave the organization, new factors must be considered, such as the possibilities of a greater offer of knowledge.

Keywords
human resources policies; turnover intention; learning opportunity; people management; quantitative research

Resumo

Objetivo:

Esta pesquisa teve como objetivo investigar de que forma as políticas de recursos humanos e a percepção das oportunidades de aprendizagem nas organizações influenciam a intenção de rotatividade dos profissionais.

Originalidade/valor:

Os autores demostraram que, ao compreenderem as relações existentes entre os constructos pesquisados, as organizações devem aumentar seus investimentos em melhorias nas políticas de recursos humanos, particularmente em ações que promovam uma maior percepção de oportunidades de aprendizagem, reduzindo a intenção de rotatividade de seus talentos.

Design/metodologia/abordagem:

Esta pesquisa foi desenvolvida com abordagem quantitativa e coleta de dados realizada por meio de um survey. Aplicaram-se os questionários a 250 profissionais atuantes no mercado de trabalho e estudantes de uma universidade privada. A análise dos dados foi realizada com uma análise fatorial confirmatória e, na sequência, uma modelagem de equações estruturais.

Resultados:

Os autores apresentaram os resultados da investigação de forma descritiva. As três hipóteses definidas para o estudo foram aceitas, e foram consideradas significantes as dimensões das políticas de recursos humanos. Os autores apresentaram atributos relevantes para a compreensão de que, mesmo existindo diversos motivos que possam influenciar um profissional em sua decisão de desligar-se da organização, novos fatores devem ser considerados, como as possibilidades de uma maior oferta de conhecimento.

Palavras-chave
políticas de recursos humanos; intenção de rotati­vidade; oportunidade de aprendizagem; gestão de pessoas; pesquisa quantitativa

INTRODUCTION

Modern organizations increasingly demand that human resources (HR) management is strategically aligned with their business objectives. The human capital has been a competitive differential for the success of organizations, as the aspirations for thought arise from it, whether at a strategic, tactical, or operational level. Armstrong and Taylor (2014) perceive human capital as the skills, knowledge, and potential talents that employees use to achieve their own professional and organizational goals. Consequently, there is a growing recognition of the importance of human capital in organizations - and the learning opportunities that professionals have - which, due to its complexity and diversity, needs to be managed, led and directed (Barney, 1991; Demo et al., 2011; Maden, 2015).

The literature referring to measures of HR policies and practices is scarce, since the studies published on this topic, for the most part, addressed the need to implement a political model of HR, application of new HR practices, and corporate social responsibility in HR. By deepening this analysis, it is possible to see that some policies have been more researched than others, such as policies for training and development of people, recruitment and selection, working conditions, and remuneration and rewards. All of them have a strong relationship and influence on learning opportunities and talent retention, which configures an important gap to carry out this research (Huselid, 1995; Demo et al., 2011; Demo et al., 2014).

In more recent research, Demo et al. (2018) reaffirm the existence of this gap in the literature and encourage the emergence of new relational studies between HR policies and other little-studied variables and highlight that this knowledge is essential for the advancement of the HR area and the recognition of its strategic role in organizations.

Regarding another research gap, the studies carried out on turnover intention stand out. Over time, studies on this topic have investigated its relationship with organizational behavior, especially with the constructs of well-being at work; psychological capital; climate; rewards; support, control, or pressure exerted by the head; affective support; stress; and organizational commitment, whether from an affective, calculating or normative perspective (Melo & Oliveira, 2008; Carmo & Oliveira, 2010; Yin-Fah et al., 2010; Polizzi Filho & Siqueira, 2012; Luz et al., 2018).

In view of the above, this study intends to answer the following research question:

• What is the influence of HR policies and the perception of learning opportunities in organizations on the intention of professional turnover?

Thus, the aim of this study is to investigate how HR policies and the perception of learning opportunities in organizations influence the intention of professional turnover. Therefore, a survey with 250 undergraduate students in Administration and from technology programs aimed at dif­ferent areas of administration at a private university, located in the city of São Paulo.

In addition to this introduction, the article presents four more sections. The next section is the theoretical framework, with the main conceptual aspects of HR policies and practices, the perception of learning opportu­nities, and the intention of worker turnover. Then the methodology is explained. The fourth section contains the analysis and discussion of the results, and, finally, the fifth section, with the final considerations.

THEORETICAL FRAMEWORK

This section describes the conceptual aspects of HR policies and practices, the perception of learning opportunities in organizations, and the turnover intention at the organizational level.

Human resources policies and practices

Faced with the need to expand its focus of action, the HR area, which, traditionally, was responsible only for tactical-operational activities, ensuring support to other areas without participating in the organizational strategy, assumed an important role in the strategy of organizations (Boxall & Purcell, 2003; Armstrong, 2009; Demo et al., 2014; Manuti & Giancaspro, 2019).

A new definition and distribution of HR policies and practices brought evolutions to the traditional model of the HR area towards a strategic position. The creation of new HR functions and professionals comes from the recognition that people play an important role in achieving results, precisely because they are producers of knowledge, innovation, and organizational capabilities (Demo et al., 2014; Macke & Genari, 2019; Manuti & Giancaspro, 2019).

In this contemporary context, influenced by the strategic vision of HR, people have come to be considered a strategic resource, since their resources and capabilities generate important organizational competitiveness and encourage organizations to adopt policies for attracting, developing, and retaining talent (Boxall & Purcell, 2003; Macke & Genari, 2019). To achieve this goal, organizations turned their attention to the perspective of generating competitive advantage, in accordance with the resource-based approach (resource-based view theory - RBV), presented by Barney (1991), since competitive advantage requires preconditions related to the HR area, considering that resources need to be valuable, rare, and impossible to be imitated or replaced (Demo et al., 2014; Manuti & Giancaspro, 2019).

For Boxall and Purcell (2003), the organization obtains a competitive advantage through people and organizational processes, and this involves strategically thinking about work, employment, information, consulting, and negotiation policies. The strategic management of HR is complex and is under constant discussion - and evolution, especially in academia. Its definition and its relation to organizational aspects are not absolute and researchers have not yet reached a consensus on it (Boxall & Purcell, 2003). In fact, differentiated HR management practices contribute to the sustainable performance of organizations, especially when focused on the development of employees’ skills, work autonomy, and opportunity for professional growth (Combs et al., 2006; Manuti & Giancaspro, 2019).

Also in the HR practice, with regard to the organization’s intentions about which direction to follow, Manutti and Giancaspri (2019) state that strategically aligning both individual and group interests with the organization’s objectives has been an important challenge for organizations, since these practices facilitate and enable the achievement of organizational goals. This alignment requires a planned set of HR policies and practices that address the processes of hiring, retaining, and developing people, in order to achieve transformations in organizational environments arising from innovations, technologies, sustainability, and other external variables.

It is at the core of HR policies and practices that behavior becomes the mediator between the strategy and its effective practice, and, therefore, the practices adopted must promote behavior consistent with the strategy. Thus, having people management integrated into the organization’s values tends to contribute to achieving the organization’s objectives and goals (Armstrong, 2009; Macke & Genari, 2019).

Therefore, the definition of organizational policy is based on the establishment of principles that will determine the conduct of a company. It is a direction through which a set of techniques are worked on constructively, in order to achieve specific goals (Demo et al., 2014). For Armstrong (2009), the organization’s positioning, expectations, and values are defined by the HR policies, which influence the way individuals are treated; they serve as a reference for the development of new practices and decisions that people make, in addition to promoting fair treatment among individuals.

HR policies and practices interfere with organizational results when used in an associated way, promoting high organizational performance (Demo, 2010; Guest & Conway, 2011; Majumder, 2012; Demo et al., 2014; Demo et al., 2018), through employee attitudes and behavior. Attitudes refer to satisfaction, commitment, and motivation, and behaviors refer to absences, turnover, and disputes among workers in an organization (Katou, 2012). In view of this, the first hypothesis of this study is elaborated, which admits:

• H1: HR policies will be negatively related to turnover intention.

The HR policies addressed in this research were: 1. recruitment and selection; 2. involvement; 3. training, development, and education (TD&E); 4. working conditions; 5. performance and skills assessment; 6. remu­neration and rewards. The alignment of these HR policies with the organization’s goals tends to favor the conditions for people to contribute to achieving significant and superior results (Demo et al., 2014, 2018), in addition to its own development and learning.

Perception of learning opportunities

Learning within organizations contributes to the maintenance and development of competitiveness, productivity, and innovation in uncertain technological and market conditions, despite the concept being historically associated with economic analyses of the development of new industries, technologies, and research and development programs until the 1980s, when the international economic scenario was resumed with an emphasis on transformation processes (Almeida & Souza-Silva, 2015).

Since the 1990s, the concept of learning in organizations has gained popularity, even though it has been present for some time in the literature that addresses the economic theory of the firm and the theory of organizations. Over time, this learning gained more space as an HR strategy in the most diverse modalities of TD&E (Aguinis & Kraiger, 2009; Mourão et al., 2014; Mayes et al., 2017; Luturlean et al., 2019).

Brazil has been considered a country with little investment in TD&E, allocating only 0.18% of its net sales, unlike European countries, which, at the beginning of the 21st century, had investments between 0.5% and 3%. We should consider that this difference may be greater than the percentages indicated, since, in European countries, the investment percentages refer to the company’s total costs and not only the net sales (Mourão et al., 2014).

With the rapid technological advance, the numerous and intense changes in the production system generated an increase in both cognitive and practical demands of professionals in organizations, who began to carry out new training, in order to correct the existing gaps in the demands for training and requalification of professionals (Manuti & Giancaspro, 2019) and, with that, promote career development plans for these individuals (Mayes et al., 2017; Luturlean et al., 2019). In the face of such changes, since the beginning of the 21st century, the interest of companies, academics, and consultants for better learning conditions has grown (Almeida & Souza-Silva, 2015), which revealed a conviction that investing in TD&E had become a competitive advantage. Personnel TD&E can be qualified by the effort that organizations make in order to provide learning opportunities for their employees. However, in this context, it is important to recognize that learning occurs when people perform their daily activities and interact (Almeida & Souza-Silva, 2015), sharing new knowledge and information (Gope et al., 2018).

For Mourão et al. (2014), the concept of learning opportunity refers both to induced learning actions - formal educational actions - and support actions for informal (or incidental) learning in the work environment, since not all learning opportunities in organizations result from the formal learning system, although this formal system has received more prominence and investments (Malcolm et al., 2003; Denkowska et al., 2020).

Keeping qualified professionals in the organization has always been a challenge for HR managers, and several actions can be taken to promote the retention of talents. Cangialosi et al. (2020) state that these managers must build a supportive learning environment, in which mistakes can be discussed openly, providing an opportunity to improve the experience and skills of everyone involved. When professionals perceive this learning environment, they feel encouraged to perform beyond the description of their formal functions, becoming more proactive and creative (Islam & Tariq, 2018).

Studies carried out by Boomaars et al. (2018) reveal that professionals tend to learn more often when the reason for learning is associated with their personal development. Thus, when the organization promotes learning opportunities that, in addition to improving their professional skills, influence their employability, they not only engage more, but also perceive the organization’s actions as an investment and this perception is essential for the interest of staying in the organization (Boomaars et al., 2018). With this, the second hypothesis of this study is elaborated:

• H2: HR policies will be positively related to the perception of learning opportunities in the workplace.

Evaluating the employees’ perception of learning opportunities in the workplace can be an important measure for the HR area, since identifying it allows organizations to create strategies to try to manage them, and, consequently, this management can interfere and influence several variables of organizational behavior, such as commitment, job satisfaction, and turnover intention.

Turnover intention

Recently, there has been a growing number of managers and researchers from different areas of knowledge who have started to show interest in the turnover intention construct, since it represents an important factor for the financial performance of organizations. One of the reasons why organizations face this challenge is the awareness that their competitive advantage depends on human capital (Joo & Park, 2010; Manuti & Giancaspro, 2019; Skelton et al., 2020).

In academic research, the term retention has been used with the term turnover. In the literature on retention, it is possible to observe attempts to identify elements that influence the decision of professionals to remain in the organization, and, in the literature on turnover, there are attempts to identify the factors that influence the decision to leave the organization (Griffeth et al., 2000; Mak & Sockel, 2001).

However, studies carried out on the turnover intention address other aspects, since the decision to leave the organization has not yet been made, unlike when discussing turnover. Studies that address the turnover intention construct relate it to well-being at work; psychological capital; organizational climate; rewards; support, control, or pressure exerted by the head; affective support; stress; and organizational commitment, whether from an affective, calculating or normative perspective (Melo & Oliveira, 2008; Carmo & Oliveira, 2010; Yin-Fah et al., 2010; Polizzi Filho & Siqueira, 2012).

Managers seek to identify the causes of the turnover intention and, therefore, find alternatives that influence the forms of staff retention (Scott et al., 2012; Agapito et al., 2015). Kim et al. (2017) draw attention to the importance of organizational culture as the most powerful predictor of turnover intention, followed by climate and the perception of organiza­- tional justice.

Due to these factors, the search for qualified professionals has become more intense and challenging and, to deal with this, organizations have directed actions to develop work environments that provide better oppor­tunities for workers, since these actions increase the possibilities of developing affective commitment, a phenomenon that reduces the turnover intention (Bonilla, 2013; Rasheed et al., 2020).

For Siqueira et al. (2014), leaving the company they work for is an individual’s behavior and its origin is psychological. Generally, this behavior is caused by the lack of understanding and agreement among organizational actors, which somehow culminates in the thinking, planning, and willingness of professionals to leave the organization they work for. Therefore, developing organizational actions that minimize or eliminate the negative aspects that make people want to leave the organization is important for employee retention and should be a concern of HR professionals (Bonilla, 2013; Rasheed et al., 2020; Skelton et al., 2020).

In view of this, the third hypothesis of this study is elaborated:

• H3: The perception of learning opportunities in the workplace will be negatively related to the turnover intention.

At the end of this section, based on the three hypotheses formulated, the conceptual model of this research is developed, in which the three constructs addressed in this work can be identified: HR policies, perception of learning opportunity in organizations, and turnover intention. We established the relationship between these constructs as represented in Figure 1.

Figure 1
Conceptual model

The methods and research techniques used to carry out this study are presented below, followed by the analysis of the results.

RESEARCH METHODS AND TECHNIQUES

This research is characterized as a quantitative study, as this strategy allows the reduction of the phenomenon studied to a set of variables that can be controlled by planning and statistical analysis, which enable the testing of a theory (Creswell, 2010). Objective data originate from empirical measures, and both the validity and the reliability of scores on the instruments lead to meaningful interpretations of the data (Malhotra, 2011).

Questionnaire and scales

Data collection for this research was carried out through a survey composed of three structured questionnaires with validated scales: 1. Scale of Human Resources Policies and Practices (SHRPP); 2. Scale of Perception of Learning Opportunities in Organizations (SPLOO); and 3. Intention to Turnover Scale (ITS).

The first scale - SHRPP - was developed by Demo et al. (2014) with the justification that there is a gap in the literature, since the authors corroborate Huselid’s (1995) statement that measures of HR policies and practices, despite being necessary, are still scarce.

The second scale - SPLOO -, according to the authors Mourão et al. (2014), was built and validated, in order to ascertain the perception of formal and informal learning opportunities that workers have regarding their organizations. The focus is on the perception that these workers have of the TD&E system and the support for learning provided by the organizations they work for. This perception tends to help in the understanding of several factors related to job satisfaction and well-being and, consequently, in the understanding of what may be related to the turnover intention.

The third scale - ITS -, according to Siqueira et al. (2014), is a measure that aims to assess the degree to which a worker makes plans about their exit from the organization they work for. Understanding the turnover intention allows, in a broader way, to identify the causes that can lead to its occurrence, since hiring, integrating, and permanently developing professionals are important for organizations, but retaining them is crucial.

Survey sample

The sample chosen for this research is in accordance with the recommendations made by Selltiz et al. (1987), since they represent the group of people on which the investigated phenomenon focuses. Therefore, the sample consisted of 250 undergraduate students in Administration and from technology programs focusing on different areas of administration at a private university in the city of São Paulo. The respondents work at organizations from different segments and, as they are experienced in the labor market, go through situations related to the phenomenon of turnover intention, here related to HR policies and the perception of learning opportu­nities at work. The diversity of demographic and behavioral characteristics of respondents was considered a positive factor for the purpose of this research (tables 1 and 2).

Table 1
Semester versus gender

Semester	Men	Women	Total
1	32	57	89
2	17	42	59
3	12	23	35
4	0	1	1
5	5	10	15
6	0	0	0
7	0	1	1
8	6	3	9
Total	72	137	209

Source

Table 2
Respondent’s areas of activity

Area	Quantity
1) Commerce (stores, markets, resellers, dealerships)	34
2) Hospitality, restaurants, tourism	5
3) Transport	8
4) Telecommunications	18
5) Financial services - banks and financial institutions	23
6) Insurance and private pension	8
7) Real estate activities	3
8) Computer services	8
9) Public administration	17
10) Research and development	0
11) Education	5
12) Health and social work	22
13) Domestic services	2
14) Industry	12
15) Others (fashion, sewing, beauty, engineering, internship, apprenticeship etc.)	44
	209

Source

Procedures

A pre-test was carried out with 15 respondents belonging to the same universe as the sample considered for this research. The questionnaires were returned with the respective impressions about the words and phrases used in the instrument that could generate doubts. Afterward, the necessary adjustments were made to define the final version of the questionnaire.

Participants were informed that the performance and the participation in the research had no relationship with the courses in progress of their respective programs or with the educational institution itself, both in the pre-test and in the final data collection, and that it was an academic study. Three versions of the questionnaire were printed with the statements in random order to avoid primacy effects.

In data collection, the three structured questionnaires were made available exclusively in person in the classroom, applied sequentially, without a time interval, as the number of items was not considered a challenge in obtaining the data. The items were randomly distributed, as, according to Malhotra (2009), it reduces the risks of social desirability, in which respondents act the way they believe the researcher expects them to.

Criteria for data analysis

In the preliminary analysis of the 250 completed questionnaires, 41 were considered invalid due to missing data or notes of unique responses in all items. The initial exploration of data from 209 valid questionnaires was carried out through the software Microsoft Excel 2007, for recording and consolidating the information obtained. Next, we used the software Statistical Package for Social Sciences (SPSS) for Windows, version 15.0, for descriptive and multivariate statistical analyses. For the confirmatory factor analysis (CFA) and nomological validity of the scales, as recommended by Hair (2010), we used the structural equation modeling (SEM) through the smart software PLS-2.0 M3. Hypotheses with t ≥ 1.96 or p ≤ 0.05 were considered acceptable. The validation criteria of the model proposed by Hair et al. (2013) was also followed, identifying the internal consistency and reliability of the data, convergent and discriminant validity of the model, as well as fit quality indexes.

RESULTS, ANALYSIS, AND DISCUSSION

In this section, the results achieved in this research will be presented and analyzed. Initially, data are observed that characterize the sample of 209 valid respondents, of which 34.8% are men and 65.2% are women, as shown in Table I, which also lists the distribution of students per semester. The age range of respondents varied between 18 and 40 years.

All 209 respondents are professionals working in the labor market, 55 of whom work as managers in their companies (having between 1 and 80 subordinates), and 154 hold positions of subordinates. For a better understanding of the respondents and their work context, the sectors in which they work are shown in Table 2.

Results of the proposed conceptual model - CFA

After the CFA, through SEM, the proposed model for the comparison of scales was tested. This was done using the partial least squares method, based on a correlation matrix, given the possibility that data normality does not occur. This technique is also justified by the sample size and the predictive objectives of this study (Chin, 1998; Hair Jr. et al., 2013).

The adjusted structural model showed positive and significant relationships (p < 5% and t > 1.96) between all constructs, identified by the resampling method bootstrap. The model was able to explain 40.2% of the variance (R²) of the turnover intention and 66.3% of the perception of learning opportunities in organizations.

The tested model had average variance extracted (AVE) above the minimum required and recommended by Tenenhaus et al. (2005). The composite reliability, commonality, and Goodness of Fit (GoF*) indicators found were considered adequate, according to the results presented in Table 3, which suggest consistency, reliability, and good initial adjustment of the data to the proposed model, indicating convergent validity.

Table 3
Fit indicators, convergent validity, consistency, and reliability

Constructs	AVE	Composite reliability	R2	Cronbach’s alpha	Communality
Performance and competencies evaluation	0.760	0.941	0.752	0.921	0.760
Working conditions	0.564	0.838	0.646	0.743	0.564
Involvement	0.652	0.929	0.771	0.910	0.652
Turnover intention	0.915	0.970	0.402	0.954	0.915
Perception of learning opportunities in organizations	0.696	0.967	0.663	0.963	0.696
Recruitment and selection	0.525	0.869	0.457	0.820	0.525
Remuneration and rewards	0.682	0.895	0.709	0.843	0.682
Training, development, and education	0.657	0.920	0.826	0.895	0.657

Source^*2

Obtained by the geometric mean between the mean values of R² and AVE, the GoF* was 0.662 - a value considered above that indicated for the field of social sciences, which is 0.36 -, according to the recommendations of Wetzels et al. (2009).

The AVE of all constructs must be > 0.50, which indicates that the variance of each construct is satisfactory to explain the total variance (Chin, 1998). According to the results obtained, it is observed that the reliability indicators of the composition and the factorial commonality were higher than the recommended value (> 0.50).

Table 4 presents the discriminant validity indicators of the structural model, with the comparison of the square root of the AVE of each construct versus the correlation with the other constructs of the model. Discriminant validity was complemented by cross-load analysis of the items, greater in their respective variables than in the others (^Appendix, Table 7).

Table 4
Discriminant validity indicators

Constructs	Performance and skills assessment	Working conditions	Involvement	Turnover intention	Perception of learning opportunities in organizations	Recruitment and selection	Remuneration and rewards	Training, development, and education
Performance and skills assessment	0.872
Working conditions	0.661	0.751
Involvement	0.661	0.624	0.808
Turnover Intention	-0.498	-0.471	-0.584	0.956
Perception of learning opportunities in organizations	0.719	0.606	0.685	-0.595	0.834
Recruitment and selection	0.496	0.507	0.527	-0.310	0.510	0.724
Compensation and rewards	0.746	0.604	0.702	-0.575	0.727	0.444	0.826
Training, development, and education	0.731	0.738	0.744	-0.563	0.780	0.558	0.710	0.810

SourceValues in bold represent the square root of the AVE.

In Table 5, the structural analysis performed indicated significant paths between the model’s constructs. Thus, it is observed the occurrence of positive and significant relationships between the constructs since the results showed p < 5% and t > 1.96.

Table 5
Final structural indicators

Hypothesis	Direction	Relationships	Original coefficient	Average of 500 subsamples	Standard error	T-test	p-value	Result
H1	Negative	HR policies and practices -> Turnover intention	-0.375	-0.382	0.089	4.195	p < 0.001	Accept
H2	Positive	HR policies and practices -> Perception of learning opportunities in organizations	0.814	0.815	0.024	33.225	p < 0.001	Accept
H3	Negative	Perception of learning opportunities in organizations -> Turnover intention	-0.289	-0.284	0.097	2.9532	0.003	Accept
Dimensions of HR policies		HR policies and practices -> Performance and competency assessment	0.867	0.867	0.018	45.648	p < 0.001	Significant
		HR policies and practices -> Working conditions	0.803	0.805	0.026	30.589	p < 0.001
		HR policies and practices -> Involvement	0.878	0.880	0.015	56.931	p < 0.001
		HR policies and practices -> Recruitment and selection	0.675	0.676	0.042	16.092	p < 0.001
		HR policies and practices -> Compensation and rewards	0.842	0.844	0.019	42.971	p < 0.001
		HR policies and practices -> Training, development, and education	0.908	0.909	0.013	66.136	p < 0.001

Source

Table 6 presents the accuracy indicators (Q²), which assess how close the model is to what is expected of it and the usefulness of building the model (f²), which assesses how important and useful each construct is to the model.

Table 6
Accuracy and usefulness of the construct

Constructs	R2	Q2	f2
Turnover intention	0.402	0.362	-
Perception of learning opportunities in organizations	0.663	0.453	0.463
HR policies	-	0.412	0.412
Performance and skills assessment (monthly)	0.752	0.564	-
Working conditions	0.646	0.357	-
Involvement	0.771	0.523	-
Recruitment and selection	0.457	0.226	-
Compensation and rewards	0.709	0.472	-
Training, development, and corporate education	0.826	0.541	-

Source

Accuracy indicators of the adjusted model or predictive validity (Q²) and effect size or usefulness for building the model (f²) proved to be satisfactory. The values obtained in (Q²) were greater than zero and the values obtained in (f²) were greater than 0.35, which is considered to have a high effect, as recommended by Hair Jr. et al. (2013).

As expected, there is accordance with H1 that “HR policies will negatively related to turnover intention” (Г = -0.376, t₍₄₉₉₎ = 4.195, p < 0.001). This result indicates that, according to the literature, there are numerous authors who defend the creation of HR policies as an important HR strategy, which tends to positively influence the behavior of professionals and provides job satisfaction, commitment, and, consequently, the absence of turnover intention, as presented in the theoretical review of this research (Demo, 2010; Guest & Conway, 2011; Majumder, 2012; Katou, 2012; Demo et al., 2014, 2018).

H2 has also been confirmed: “HR policies will be positively related to the perception of learning opportunities in the workplace”, which was observed quite significantly (Г = 0.814, t₍₄₉₉₎ = 33.225, p < 0.001). With the advancement of technology and the transformations that took place in the production system, there were changes in the cognitive demand of professionals with regard to training and qualification, which caused changes in the HR strategies adopted by companies. When companies decide to invest in TD&E, they are investing in competitiveness, given its association with organizational learning actions (Dodgson, 1993; Aguinis & Kraiger, 2009; Mourão et al., 2014). It is noteworthy that there are still companies that do not perceive learning opportunities as an investment, but as an unnecessary cost.

H3, in which is stated that “the perception of learning opportunities in the workplace will be negatively related to the turnover intention”, was also confirmed (Г = -0.289, t₍₄₉₉₎ = 2.953, p = 0.003). Therefore, permanently integrating and developing talented professionals, with a view to their retention in the organization, become an important strategic action, given that the turnover intention is impacted by organizational socialization (Polizzi Filho & Siqueira, 2012; Rasheed et al., 2020; Skelton et al., 2020).

The dependent variable best explained was the perception of learning opportunities in organizations (R² = 66.3%, Q² = 0.453), with a significantly stronger relationship with HR policies (Г = 0.814, t₍₄₉₉₎ = 33.225, p < 0.001) than with the turnover intention, which also achieved an excellent explanatory value (R² = 40.2%, Q² = 0.362), although with a less strong relationship with HR policies (Г = -0.376, t₍₄₉₉₎ = 4.195, p < 0.001). This suggests that HR policies have a stronger relationship with turnover intention due to their broad possibility of alternatives to dissuade the employee from leaving the organization. There are several alternatives capable of leading the employee to reconsider their intention, depending on the instruments of HR policies. It is noted that the perception of learning opportunities is relevant in the face of HR policies and complements it (Г = 0.814, t = 33.22, p < 0.001) as a potentially efficient instrument in reducing turnover.

This result is in accordance with Boomaars et al. (2018), who state that the age control variable has a significant effect on the perception of learning opportunities. That is, younger employees tend to notice learning opportunities more often. The age group presented by the respondents in this research can be an important factor that explains why the variable perception of learning opportunities has a strong relationship with the variable intention of turnover.

As for the dimensions of HR policies, training, development, and education were the most explained dimension (R² = 82.6%) and it presented more strength in the relationship (Г = 0.908) with the variable HR policies than with the other variables. This corroborates the information that advances in studies on training, development and education have been significant in recent decades, however, the methodological challenges in terms of TD&E research are still expressive (Aguinis & Kraiger, 2009). The other dimensions of HR policies were quite similar (involvement, R² = 77.1%; working conditions, R² = 64.6%; performance evaluation, R² =75.2%; remuneration and reward, R² = 70.9%), except for the recruitment and selection dimension, with a value that does not match the other variables (R² = 45.7%). Anyway, these results corroborate the validity of the applied scale. The structural model also demonstrated significant relationships in the measurement of first-order variables. The relationships of HR policies with recruitment and selection (Г = 0.675, t₍₄₉₉₎ = 16.092, p < 0.001), involvement (Г = 0.878, t₍₄₉₉₎ = 56.931, p < 0.001), training, development and education (Г = 0.908, t₍₄₉₉₎ = 66.136, p < 0.001), working conditions (Г = 0.803, t ₍₄₉₉₎ = 30.589, p < 0.001), performance evaluation (Г = 0.867, t ₍₄₉₉₎ = 45.648, p < 0.001), and compensation and rewards (Г = 0.842, t₍₄₉₉₎ = 33.225, p < 0.001) were all significant.

Relevantly, these results identified the greater role of the perception of learning opportunity in the predictive ability of the entire model (F² = 0.463 versus F² = 0.251 for HR policies). This finding suggests a change in the collaborator’s way of thinking. Not only are HR policies responsible for retaining talents, but also the organization’s ability to provide intellectual growth to its components. Employees are an important source of competitive advantage and, therefore, an alignment of objectives, the employee, and the organization are demonstrated here (Aguinis & Kraiger, 2009; Mourão et al., 2014; Boomaars et al., 2018). These results may be related to the age range of the respondents (between 18 and 40 years old), as well as to other variations present in the sample, such as the position held (whether they are managers or not) or even the sector of activity (Boomaars et al., 2018).

Figure 2 presents the tested theoretical model and its indicators.

Figure 2
Final structural model indicators

FINAL CONSIDERATIONS

This research was carried out with the purpose of investigating the influence of HR policies and the perception of learning opportunities in organizations on the intention of professional turnover in an organization. To this end, three hypotheses were tested: H1 stated that the HR policies would have a negative and significant relationship with the intention of turnover; H2 established that HR policies would have a positive and significant relationship with the perception of learning opportunities in organizations; and H3 asserted that the perception of learning opportunities in organizations would have a negative relationship with the intention of turnover. The three tested hypotheses were confirmed and the dimensions of HR policies were considered significant, achieving, thus, the objectives of this study.

Organizations, through changes in their HR policies, have promoted significant results for HR management, which positively reflect on the satisfaction and commitment of professionals. Although incipient, positively, these changes represent advances in HR practices, despite highlighting the fragility of available resources that, when poorly applied, mobilize dissatisfied workers to manifest a turnover intention and, consequently, the decision to leave the organization.

Practical implications

HR policies, aligned with organizations and strategies, help organizational performance metrics reach significant levels. With this strategic vision of HR policies, people contribute both to a better organizational result and their own development and learning. In this sense, the learning opportunities in the workplace, being perceived by employees, are enhanced as long as HR policies are clearly established and frequently disclosed, so that when they become aware of these policies, employees intend to remain in the organization. Therefore, organizational and employee objectives must be aligned so that the intention of employee turnover is minimized. With that, the retention of talents can contribute to potentializing the competitive advantage of the organization.

Theoretical implications

The research contributes to investigating the strategic role of HR policies and the intention of turnover related to the employee’s perception of learning opportunities, which represents a little-studied context. The conceptual model analyzed also represents a contribution to the theoretical development of the HR area, by relating HR policies with the perception of opportunities and how these perceptions influence the intention of employee turnover. From a methodological point of view, this study con­tributes to the advancement of HR research, by using a confirmatory factorial statistical analysis technique, through SEM, considered unusual in studies in this area, allowing the evaluation of the relationship between the constructs simultaneously.

Limitations and future research

This study had its limitations that should be considered in future works, thus, it is important to continue the investigation of the variables that are the object of this study. It is also recommended that further longitudinal research be carried out with the constructs studied here, in order to understand the main factors that influence the intention of turnover and the retention of talents through HR policies and the perception of learning opportunities in organizations.

• 1
  This paper was carried out with the support of the Research Support Fund (Fundo de Apoio à Pesquisa FAP/Uninove). The funder had no influence on the study design, data collection and analysis, the decision to publish, and the preparation of the article.

APPENDIX

Table 7
Crossloadings

Item	1*	2*	3*	4*	5*	6*	7*	8*
EIR_1	-0.505	-0.450	-0.560	0.960	-0.590	-0.303	-0.573	-0.542
EIR_2	-0.433	-0.427	-0.547	0.956	-0.551	-0.285	-0.550	-0.530
EIR_3	-0.487	-0.475	-0.568	0.954	-0.566	-0.300	-0.525	-0.543
EPOA_1	0.588	0.452	0.623	-0.459	0.874	0.535	0.611	0.642
EPOA_2	0.687	0.500	0.626	-0.514	0.904	0.507	0.687	0.668
EPOA_3	0.590	0.490	0.680	-0.542	0.875	0.485	0.662	0.696
EPOA_4	0.625	0.574	0.616	-0.515	0.877	0.482	0.644	0.729
EPOA_5	0.646	0.540	0.607	-0.451	0.876	0.462	0.640	0.674
EPOA_6	0.619	0.406	0.638	-0.520	0.872	0.448	0.605	0.653
EPOA_7	0.638	0.460	0.555	-0.506	0.845	0.379	0.643	0.649
EPOA_8	0.545	0.482	0.417	-0.454	0.761	0.354	0.511	0.619
EPOA_9	0.539	0.541	0.523	-0.456	0.819	0.339	0.534	0.650
EPOA_10	0.478	0.534	0.519	-0.487	0.710	0.335	0.560	0.587
EPOA_11	0.589	0.573	0.392	-0.467	0.752	0.253	0.528	0.602
EPOA_12	0.610	0.541	0.608	-0.589	0.844	0.436	0.631	0.670
EPOA_13	0.626	0.496	0.573	-0.480	0.809	0.468	0.600	0.605
EPRRH_1	0.328	0.361	0.364	-0.292	0.384	0.671	0.293	0.373
EPRRH_2	0.370	0.335	0.354	-0.231	0.408	0.738	0.378	0.437
EPRRH_3	0.289	0.337	0.361	-0.185	0.350	0.683	0.277	0.324
EPRRH_4	0.210	0.360	0.218	-0.104	0.253	0.700	0.154	0.344
EPRRH_5	0.365	0.352	0.376	-0.183	0.383	0.794	0.313	0.410
EPRRH_6	0.510	0.442	0.539	-0.303	0.405	0.754	0.439	0.496
EPRRH_7	0.575	0.411	0.739	-0.379	0.500	0.404	0.555	0.505
EPRRH_8	0.544	0.607	0.858	-0.526	0.575	0.445	0.560	0.669
EPRRH_9	0.535	0.595	0.855	-0.474	0.531	0.431	0.561	0.623
EPRRH_10	0.561	0.534	0.841	-0.512	0.620	0.442	0.592	0.676
EPRRH_11	0.524	0.435	0.812	-0.497	0.549	0.363	0.609	0.600
EPRRH_13	0.501	0.443	0.756	-0.480	0.597	0.450	0.574	0.559
EPRRH_14	0.497	0.483	0.783	-0.421	0.500	0.446	0.520	0.562
EPRRH_19	0.599	0.599	0.680	-0.461	0.648	0.473	0.602	0.855
EPRRH_20	0.529	0.656	0.528	-0.485	0.620	0.446	0.545	0.773
EPRRH_21	0.617	0.560	0.630	-0.507	0.627	0.442	0.639	0.808
EPRRH_22	0.610	0.607	0.651	-0.494	0.677	0.494	0.623	0.839
EPRRH_23	0.604	0.576	0.597	-0.399	0.644	0.449	0.526	0.812
EPRRH_24	0.596	0.600	0.520	-0.385	0.574	0.407	0.511	0.773
EPRRH_25	0.548	0.801	0.642	-0.414	0.498	0.405	0.521	0.647
EPRRH_27	0.435	0.723	0.367	-0.310	0.428	0.382	0.421	0.529
EPRRH_28	0.509	0.751	0.362	-0.335	0.430	0.354	0.425	0.543
EPRRH_30	0.487	0.725	0.464	-0.346	0.459	0.381	0.436	0.483
EPRRH_31	0.838	0.575	0.497	-0.375	0.549	0.376	0.567	0.629
EPRRH_32	0.877	0.618	0.585	-0.490	0.658	0.428	0.705	0.620
EPRRH_33	0.919	0.621	0.644	-0.487	0.678	0.423	0.715	0.677
EPRRH_34	0.877	0.555	0.628	-0.418	0.648	0.498	0.647	0.667
EPRRH_35	0.847	0.511	0.513	-0.391	0.593	0.434	0.609	0.592
EPRRH_37	0.579	0.478	0.509	-0.573	0.545	0.345	0.738	0.527
EPRRH_38	0.647	0.519	0.538	-0.476	0.616	0.341	0.854	0.601
EPRRH_39	0.699	0.563	0.709	-0.499	0.697	0.459	0.888	0.707
EPRRH_40	0.521	0.420	0.539	-0.348	0.524	0.301	0.817	0,.483

• ^*
  1 - Assessment of performance and skills; 2 - work conditions; 3 - involvement; 4 - intention to rotate; 5 - perception of learning opportunities in organizations; 6 - recruitment and selection; 7 - remuneration and rewards; 8 - training, development, and education.

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Publication Dates

• Publication in this collection
  06 July 2022
• Date of issue
  2022

History

• Received
  04 Nov 2020
• Accepted
  28 July 2021