Introduction

Employees enable organisations to meet their objectives and are generally recognised as their most valuable resource (Ali & Anwar, 2021; Stefurak et al., 2020). In addition, the capabilities that allow the company to survive and develop to a large extent, on the talent and enthusiasm of its workforce (Clement & Eketu, 2020), as they are the ones who carry out activities such as environmental monitoring, decision-making, product and process development, among others. Furthermore, organisational development in terms of growth, financial performance, quality of products and services, or improved competitive capabilities depends on them (Marethabile, 2017).

In the competition for better quality and innovation of their processes or products, human resources play a crucial role (Wen, 2020); it is therefore said that the competitiveness of companies is not only manifested in their efforts to obtain a larger market share or better performance than their rivals, but also in terms of the development of knowledge in their employees in terms of capacity building, specialisation and experience, as well as their retention (Sandhya & Supley, 2020). Companies invest time, money and effort in recruiting, hiring, training, motivating and monitoring their human resources, so when an employee leaves, he or she takes some of the company's knowledge with him or her, and this incurs costs (Mitrovska & Eftimov, 2016; Sandhya & Sulphey, 2019).

However, increased globalisation allows employees to move around more easily, making talent retention a challenge in today's business (Munyeka & Ndlovu, 2020). It is, therefore, necessary for top management to pay attention to the needs, expectations and environment in which the company operates (Aminyan, 2019). In this way, managers could monitor the morale of their staff. Thus their desire to continue working in the company (Novitasari et al., 2020), as retaining qualified employees is a challenge that must necessarily be taken up in order to ensure their survival and optimal development (Munyeka & Ndlovu, 2020).

In this order of ideas, the pursuit of satisfaction and other elements of the subjective well-being of the workforce is a problem that highlights the need to find the most appropriate ways to retain human talent (Demir, 2020). The importance of employee satisfaction has led to considerable research on the subject, especially about the effect of this item on productivity (Novitasari et al., 2020), among other aspects. On the other hand, the perception of organisational justice has been evaluated as a promoter of development in the company, especially about productivity or as a determinant of individual behaviour (Sadeghi & Omranzadeh, 2020). Likewise, satisfaction and organisational justice have also been analysed as inhibitors of job disengagement. In essence, a worker who perceives a pleasant and fair work environment will seek to stay at work (Gupta & Singh, 2020).

Beyond these elements, the work climate conditions could also affect employees' job disengagement and even influence their levels of satisfaction and perception of fairness. For example, the perception of trust refers to the freedom to communicate about personal or work-related issues with the company's leaders, with the complete certainty that this information will be part of the interpersonal relationship between the participants (Arteaga, 2020). Alternatively, innovation support refers to the support of top management in promoting innovative ideas or collaborative working methods (Galván-Vela & Sánchez, 2019).

About the above, and to find new ways of management to inhibit job desertion and the costs that this may cause to the company. The authors of this paper set the research objective of identifying the influence of perceived fairness, job satisfaction, innovation support and trust on employee turnover.

The following sections detail a theoretical review of the constructs that make up the proposed model and justify the relationship's hypotheses. Finally, the results are discussed in light of other recent findings. In addition, future lines of research are proposed to contribute to the knowledge of human talent management from the perspective of job desertion.

Literature Review

As already announced in the introduction, the aim of this paper is twofold: on the one hand, to explore how the variables of organisational justice, job satisfaction, innovation and trust affect the job abandonment of workers in the food industry sector. Moreover, on the other hand, to put on the academic table that this association constitutes a business incentive in the era of Industry 5.O. Therefore, it is appropriate to carry out a literature review of all the dimensions that make up the academic corpus of this research. Furthermore, it will establish the guidelines for the design of our empirical research and the choice of measurement scales and establish the theoretical framework of our research hypotheses. The literature consulted for the development of this study is described below.

Organisational Justice

Organisational justice refers to employees' perceptions of the fairness of the treatment received by their superiors or colleagues in an organisation and their reactions to such perceptions (Nadiri & Tanova, 2010). Generally, this construct has its origins in equity, motivational and humanistic theories and can be analysed from its different dimensions, among the most representative of which are distributive justice, procedural justice and interactional justice (Ríos & Loli, 2019). Broadly speaking, the first involves the employees' perception of what the company gives them in return for their effort; the second is the perception of the fairness of the company's procedures and decision-making; and the third is the perception of the existence of dignified and respectful treatment by their superiors (Novitasari et al., 2020). Studying this multidimensional variable is important because previous studies have focused on individual dimensions related to the quality of the relationship between this variable and turnover intention. Little research has found relationships between the dimensions of this construct with turnover intention or other human talent management elements (Nadiri & Tanova, 2010). Therefore, the first hypothesis of our research will be:

H1: Organisational justice has a negative influence on job dropout intention.

Job Satisfaction

Job satisfaction can be conceived as a company's strategic asset since its impact can be measured in relative and absolute terms (Salessi & Omar, 2016). It is said that there is no consensus for its concept. However, it refers to a pleasant and positive emotional state originating from workers' experience with their job (Andersen et al., 2007). This perception has its origins in the specific conditions of each individual, given that their cultural, behavioural, or personality differences mark their behavioural patterns. Hence, it is difficult to assert precise indicators for measuring satisfaction (Ramírez & Gañan, 2020). However, different social science disciplines have tried to explain this variable as a predictor of behaviour or other positive results, specifically in the business sphere, it is related to increased employee commitment (Cherif, 2020; Kanchana, 2012), with productivity increases (Ko & Choi, 2018), as an inhibitor of job abandonment (Labragueet et al., 2020), with engagement (Heyns & Rothmann, 2018), with trust (Sarikava & Kara, 2020), among other aspects. By the above, the second study hypothesis is proposed:

H2: Job satisfaction has a negative influence on job dropout intention

Trust and Innovation

Trust and innovation are two factors that are part of the organisational climate. A multidimensional construct includes autonomy, cohesion, trust, pressure, support, recognition, fairness, and support for innovation (Koys & DeCottis, 1991). Support for innovation refers to the perceived intention of superiors to take risks, support creativity or new ideas. Arteaga (2020) mentions that it is also related to the intention to take on new work areas with little or no experience.

Galván, et al., (2020) define business innovation as the company's capacity to develop acts of design and support for ideas related to new products or services. In turn, trust is the freedom that employees have to exercise reciprocal relationships and effective communication exchanges with their hierarchical superiors (Arteaga, 2020). In this sense, (Nurhayati et al., 2020) refer to trust as the employees' sense of what they expect to receive from the company. Therefore, it significantly affects the decision to leave their jobs.

On the other hand, Ahmad, et al., (2020) statistically show that the variables leadership and trust are determined by job disengagement. Similarly, (Nurhayati et al., 2020) argue that organisational trust and organisational justice reasonable job satisfaction, and hence, job disengagement. Previous studies such as the article by (Zeffane & Bani, 2017) had numerically evidenced the link between trust, satisfaction and job disengagement. It is directly affected by the experience and educational level of workers.

There is little empirical evidence to support this construct's relationship with employee turnover about the innovation variable. Regardless of this fact, innovation plays a vital role in employees' desire to continue their jobs. Based on this idea, (Bhatnagar, 2012) shows that psychological empowerment, engagement and innovativeness predict employee turnover. (Wang & Ma, 2013) also find that an innovation-oriented psychological climate reduces employee turnover.

Under these theoretical and ethical approaches, the following two working hypotheses are formulated:

H3: Innovation has a negative influence on job dropout intention.

H4: Trust has a negative influence on job dropout intention.

Job Dropout Intention

Since the beginning of the 20th century, many scientists have tried to define the construct of job desertion (Ngo & Hena, 2018). Of the many definitions of this concept, many of them agree that job desertion manifests itself when the employee questions their membership in the company and wishes to leave.

Ngo-Hena (2018) notes that "...refers to the situation where an employee ceases to be a member of an organisation..." (p. 2760). In this sense, (Lambert et al., 2000) express that leaving work is "...final cognitive decision making process of voluntary turnover..." (p.34). On the other hand. (Rahman & Nas, 2013) suggest that an employee's cognitive process is to voluntarily and permanently leave their employment.

Of the different theories that analyse job exit, one of the most important is the Theory of Organisational Equilibrium (TOE). This theory assumes that the perceived contributions determine the decision to leave a job that the organisation makes to the lives of its employees (Ahmad & Azumah, 2012). According to the TOE, the process of leaving a job is linked to the following factors: job satisfaction, job mobility or firm size (Ngo & Hena, 2018). On the other hand, Social Exchange Theory mentions that decisions are subject to the conditions and quality of social exchanges within organisations (Cropanzano & Mitchell, 2005). This theory also advocates the importance of the conditions of reciprocity. Relationships are valued according to what an individual gives and receives from this effort and on his or her perception of the fulfilment of the agreements on this interrelationship (Holtom et al., 2008).

Following on from the above, (Joo, 2010) found that job disengagement is a consequence of employee dissatisfaction. Likewise, (Rahman & Nas, 2013) show that the employee development perception dimension predicts job disengagement. In this regard, (Kim et al., 2017) argue that organisational justice influences employee turnover. Likewise, (Zahednezhad et al., 2021; Chen & Wu, 2017) find that transformational leadership lowers employee turnover. Finally, in line with this study, (Grant et al., 2017) show that subjective well-being and commitment significantly reduce job attrition.

In virtue of all that has been read in this subheading, the last hypothesis of this study is put forward:

H5: Organisational justice, job satisfaction, trust and innovation have positive and significant correlations with each other.

Methodology

The method of analysis is quantitative, non-experimental and cross-sectional. Its scope is explanatory since the behaviour of each element was analysed in itself. The influence of the variables in this study on each other was also determined in order to ascertain their causality.

The study subjects are the human capital of companies belonging to the food industry in Baja, California (Mexico). These people voluntarily agreed to answer the questionnaire designed by the authors of this article on the variables: organisational justice, trust, innovation and labour abandonment. It took place in April 2021.

It should also be noted that the questionnaire is composed of scales validated in other research (seven-point Likert scale). The instrument was adapted and presented by the research team in digital form. At the same time, the company's human resources staff ensured that their colleagues answered it. It gave a sample population of 555 individuals.

The job satisfaction variable is measured with the (Salessi & Omar, 2016) scale, composed of seven items. First, the scales of (Patlán et al., 2014; Niehoff & Moorman, 1993) were used about the organisational justice dimension. The latter measures justice concerning three dimensions: distributive justice, procedural justice and interactional justice. For the parameters innovation and trust, the work climate scale of (Koys & Decottis, 1991) was used. Finally, the variable job desertion measurement was carried out with (Mobley's Scale, 1977), widely used in studies on this subject. In this way, the validity and reliability of the empirical construction of our theoretical model can be ascertained (Figure 1).

In this sense, it should be noted that Cronbach's alpha test measured the conditions of reliability and consistency of the items. Moreover, the existence of convergent and discriminant validity conditions by the Composite Reliability Index (CFI) and the Average Variance Extracted (AVE).

Finally, the covariance method structural equations technique (CB-SEM) was undertaken. This flexible multivariate analysis allows the study of latent variables with multiple relationships. This technique is beneficial for designing theoretical models in business (Hair et al., 2014).

Results

The classification data of the 555 subjects show that 53.88% belong to the male gender. The average age of the workers is 38.6 years. The standard deviation is high as the age range is between 19 and 67 years. Regarding the level of education, the people surveyed have a low academic qualification, with 52.26% having only primary and secondary education.

See Table 1

Table 1   Classification Data
Variable	Descriptive result
Sex	Female=256; 46.12%Male
	= 299; 53.88% Male
	= 299; 53.88% Female=256; 46.12
Age	Limits: 19 to 67 yearsMean=
	38.6 years
	Standard deviation= 11.04
Level of education	Middle school or less=290; 52.26%High
	school=160; 28.83%Undergraduate
	school=99; 17.84%Graduate
	school=6; 0.01%
Company experience	Limits: 0 to 41 yearsMean=
	5.14 years
	Standard deviation= 8.27

An Exploratory Factor Analysis (EFA) was then carried out. It allowed us to determine the grouping of the constructs into a single factor whose determinant was optimal as it was close to zero (0.003). The KMO was 0.923, and Barlett's test of sphericity was also significant. In this same construct, the total explained variance of the indicators was 71.64%. Concerning organisational justice, it was found that it explains 73.98% of the construct's variance as a whole.

Similarly, there was a determinant close to zero of 5.94e-10. The correlations are all significant in their dimensions, as shown by Barlett's test of sphericity and the KMO with 0.962. This sense points out that the four confidence items present high and significant correlations (a determinant of 0.018, a KMO of 0.847 and an explained variance of 86.32%). On the one hand, the same happens with the innovation variable, where the five items analysed show a strong correlation (a determinant of 0.013; a KMO of 0.901; an explained variance of 80.74%). Moreover, on the other hand, the dropout dimension, which also has high significant correlations (a determinant of 0.039; a KMO of 0.768 and an explained variance of 91.89%).

With this information, we went on to determine the correlations between the constructs resulting from the PFA. It was found that all the variables are strongly correlated with each other. About the dimensions: organisational justice, job satisfaction, innovation and trust, they have negative correlations with the dimension of job abandonment.

See Table 2

Table 2 Correlations Between Variables
	Justice	Satisfaction	Innovation	Trust	Turnover intention
Justice	1
Satisfaction	.745**	1
Innovation	.828**	.647**	1
Trust	.807**	.695**	.781**	1
Turnover intention	-.741**	-.599**	-.575**	-.559**	1

**. Correlation is significant at the 0.01 level (2-tailed).

Once all these statistical tests have been carried out, the measurement model is analysed regarding its reliability, convergent validity and discriminant validity. When using structural models, it is convenient to demonstrate that the proposed indicators can be considered the initial theoretical construct elements. Therefore, in the constructs explored, these tests were carried out to identify the measurement model.

The reliability indicators were calculated using Cronbach's alpha and the Composite Reliability Index (CFI). Both indicators recommend values above 0.700. Convergent validity was estimated using the mean-variance extracted. Likewise, discriminant validity was determined using the variance explained by each factor on a leading diagonal. The results of these tests show that the reliability and validity conditions are met (Table 3).

Table 3 Reliability, Convergent Validity and Discriminant Validity
Discriminant Validity						Reliability and Convergent Validity
	Justice	Satisfaction	Innovation	Trust	Turnover Int	Cronbach's Alpha	IFC	AVE
Justice	0.7398					0.969	0.9731	0.806
Satisfaction	0.555025	0.7174				0.93	0.9463	0.845
Innovation	0.685584	0.418609	0.8027			0.938	0.9531	0.896
Trust	0.651249	0.483025	0.609961	0.8632		0.946	0.9619	0.929
Turnover in	0.549081	0.358801	0.330625	0.31248	0.9183	0.955	0.9712	0.958

The following analysis consisted of a three-step test. The first is the verification of a fully identified model. The second is assessing the structural model fits, and the third is the testing of our theoretical model in figure 2.

The graph above shows that the structural model is identified in all its parameters according to the rule of degrees of freedom. This model has 652 degrees of freedom. From this, we can deduce the existence of an excellent parsimonious fit. Among other findings, an absolute excellent fit is found in the model. It is because Xi2, measured by CMIN, has twice as many degrees of freedom. Another indicator of overall fit is the RMSEA. The values obtained agree with the literature for this model, which proposes a value between 0.05 and 0.08 points.

Regarding the incremental fit measures, an adequate comparative fit index was observed with a CFI value=0.913. In addition, the incremental fit index is within the thresholds allowed for this test. This index stands at IFI=0.013 and a Turkey Lewis Index or TLI of 0.906. The same is true for the CMIN/DF indicator with a value of 4.262. For (Marsh & Hocevar, 1985). Such a record indicates a good fit and shown in Table 4.

Table 4  Structural Modelfit Indicators
Fit index	Expected Value	Obtained Value	Fix
CMIN	Double the degrees of freedom	2778.871, DF=652	Acceptable
RMSEA	0.05<to>0.08	0.077	Acceptable
IFC	0.90 – 1	0.913	Acceptable
IFI	0.90 – 1	0.913	Acceptable
NNFI or TLI	0.90 - 1	0.906	Acceptable
CMIN/DF	1<to>3	4.262	Limited

Concerning the hypotheses set out above. Table 5 shows the effect of the variables of organisational justice, job satisfaction, innovation and trust on job disengagement. The results of the model suggest that organisational justice is found to be negatively related to job disengagement. It means that H1 is accepted. On job satisfaction, the findings show a negative relationship with job disengagement. Therefore, H2 is accepted. Furthermore, this research shows that innovation and confidence are associated with job disengagement. This finding is in contrast to what we expected to obtain in our theoretical model.

On the other hand, it is necessary to mention that the relationships found are causal and that the correlations of these variables indicate a negative relationship when evaluated by covariance. In this sense, hypotheses H3 and H4 are partially rejected. Regarding H5, the results suggest that justice, job satisfaction, innovation and trust have positive and statistically significant relationships. Therefore H5 isaccepted.Observe Table 5.

Table 5  Hypothesis Testing
Hypothesis	Variables			Effect	S.E.	C.R.	P	Contrast
H1	Turnover intention	<---	Justice	-1.85	0.21	-8.796	0	Not rejected
H2	Turnover intention	<---	Satisfaction	-0.23	0.08	-3.003	0	Not rejected
H3	Turnover intention	<---	Innovation	0.327	0.1	3.317	0	Partially not rejected
H4	Turnover intention	<---	Trust	0.345	0.09	4.015	0	Partially not rejected
H5	Satisfaction	<-->	Justice	1.234	0.12	10.62	0	Not rejected
	Innovation	<-->	Justice	1.976	0.17	11.89	0
	Trust	<-->	Justice	1.88	0.16	12.1	0
	Satisfaction	<-->	Innovation	1.563	0.14	10.87	0
	Satisfaction	<-->	Trust	1.635	0.14	11.57	0
	Innovation	<-->	Trust	2.576	0.19	13.31	0

Conclusion

This study aims to identify the influence of perceived fairness, job satisfaction, innovativeness and trust on job dropout, and the relationship of these predictors to each other—the findings of this research show three things. The first is that organisational justice is positively linked to the variables job satisfaction, innovativeness and trust. Second, innovation and trust positively influence job satisfaction and trust. And third, the existence of negative causalities between the factors innovation and trust concerning job disengagement. Therefore, it is assumed that these constructs are not determinants of employees' voluntary decision to leave the company.

It is essential to point out that this research has limitations regarding the choice of geographical framework for this research. In the future, it would be interesting to carry out this type of work in other territories. Furthermore, it could contribute to the implementation of attractive management models. Finally, it is recommended that company managers implement human resources policies aimed at increasing job satisfaction and the creative talent of workers.

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