1. Introduction
Taking the premise that human capital is a central actor in the sustainability of organizations and that it constitutes fundamental support for the strategic management of companies [1], sustainability, in its socio-economic dimension, is related to the ability to use resources, including human resources, efficiently, seeking to provide welfare conditions (safety, health, and education) and ensuring that these are distributed equitably among social classes and genders to ensure that they remain profitable over time [2]. This definition implies that it is essential to provide human resources with mechanisms that motivate people to increase their commitment to their work and their job satisfaction, seeking to strengthen the relationship between workers and the company, which, in turn, enables companies to remain profitable over time, indicating that the sustainable development of human resources has been achieved. However, the relationship between an employee and their organization is not always good or conducive to the achievement of the desired results. Job satisfaction is a key element that affects the motivation of an employee and therefore increases their level of commitment to the organization [3,4]. Organizational commitment is very important for companies [5], as it is expected to increase the productivity of employees, but it is also an opportunity for the company to reward its employees for the individual and collective effort they make in their job performance. For this reason, it is of great importance for companies to have employees committed to the organization and to therefore know the level or degree of organizational commitment of the staff and the way in which this can be influenced [6].
Likewise, labor resources as well as individual and team motivation are interrelated and have a positive influence on the motivational well-being of employees [7].
On the other hand, it is well known that work commitment and organizational commitment are two essential factors that can indicate the motivational well-being of an employee in their work area [8]. Even though motivation and job satisfaction come from both intrinsic and extrinsic factors, it has been suggested that it is possible to design and promote strategies within organizations to strengthen both work and interpersonal relationships among employees, such as through the psychological contract [9], the differential management of human resources, and other important elements of the work environment that foster the health and psychosocial safety of workers. With this, companies can positively influence the construction of the self-perceptions that each employee has of organizational guidelines, values, and standards and the importance of the work that they do at the company as well as collective positive perceptions of the work environment, promoting productivity, creativity, and sense of belonging to the organization, and finally, can decrease the intentions of employees to quit, therefore limiting staff turnover.
It is in this context where the psychological contract continues to be an essential support tool to generate adequate conditions that motivate workers to have favorable attitudes towards their work and the organization, stimulating positive and proactive behaviors that, in turn, contribute to their own psychological well-being. Likewise, the authors [10] affirm that the chain of elements for this contract starts from the personnel recruitment and selection phases and can be “virtuous” or “vicious” depending on how it contributes to management that encourages the fulfillment of expectations or the violation of the psychological contract.
Of equal importance is the process of organizational socialization, which was addressed by [11] in a study of organizational behavior. This concept is related to the adaptation to work and the development of skills for the job role as well as a growing interest in positive states at work, such as work commitment (characterized by vigor, dedication, and absorption), that can show how the worker identifies with the culture of the organization.
Finally, without an enriched environment with the necessary resources or without opportunities for growth, workers will lack the motivation to carry out their work [12]; in addition, employers who care about promoting psychosocial health conditions in their workers are more likely to implement measures that effectively affect the construction of favorable climates [7].
Starting from the premise that workers flourish or develop when they reach their potential for job satisfaction [13], job satisfaction is probably the most studied work behavior because it is considered a key antecedent and predictor of productivity at work [14]. In this sense, there is evidence to support this position, but there is also evidence of an inverse relationship between them; evidence of a more complex influence, in which other moderating variables intervene contextually; and evidence that the relationship could be spurious. According to the authors [14], three sources have been observed to create the level of job satisfaction: (i) situation, (ii) disposition; and (iii) the interaction between the two.
Regarding situational approaches, they base their explanation of job satisfaction on a series of elements specific to each job, such as its characteristics and the available resources that a company has and provides to their employees to carry out their work. For its part, it must be noted that a healthy workplace has a positive impact on job satisfaction and productivity, so investing in healthy work environments is profitable for companies [15].
On the other hand, there are studies that suggest the importance of financial incentives to influence employee satisfaction, however, it has been observed that the more academic preparation workers have, the greater their demands for the needs that must be covered as part of their level of job satisfaction, and more education and professional experience also contribute to job satisfaction. In addition, economic perception undoubtedly continues to be an important component in job satisfaction as well [16]. However, it is necessary to pay attention to other aspects regarding job satisfaction because, as indicated in [17], the assumption that monetary compensation is what mainly matters for motivation at work is at odds with a number of observations. Furthermore, it has also been indicated that workers in many jobs act as if they care about more than just the highest paycheck.
1.1. Work Commitment
Work commitment is a positive mental state that shows worker satisfaction with their jobs. It is considered extrinsic and depends on the individual relationship that subjects have with their organizational context to a greater extent. Likewise, multiple studies have found a positive relationship between work commitment and improved creativity, contextual performance, proactive behavior, positive ambition, and positive functioning in workers, and it has even been observed that it improves team performance [7,12].
Additionally, work commitment is the psychological attachment of an employee towards their organization [7] and the will to identify with it. The company context fulfills important functions of self-expression for individuals and is the result of the adoption and internalization of the work context to the values, norms, and psychological needs of workers. For [12], work commitment occurs when workers have a positive ambition to conduct their work and when the company provides their employees with growth opportunities.
Furthermore, when people are allowed to perform their work in a way that allows them to express their work identity individually and as a team, the connection between their world and the work context is strengthened. There is evidence that both individual and team resources are positively related to work commitment and organizational commitment [7].
1.2. Organizational Socialization
In [18], organizational socialization was considered to imply the interaction between the individual and the collective, and it can be understood as the process of adaptation of the person to the organization. This process has a cognitive nature and allows those who have been newly hired to assimilate the values, rules, and cultural idiosyncrasies of the organization. Similarly, in [19], organizational socialization refers to the process by which newcomers make the transition from organizational outsiders to insiders. According to [18], this is an important issue for ensuring a sustainable workplace, and socializing new employees is critical in enhancing organizational performance as well as retaining new hires; this, in turn, helps organizations to establish a healthy emotional culture. It has also been stated [20] that organizational aspects, in addition to other job resources, are important elements in achieving work goals and stimulating personal growth, learning, and development. Additionally, to help newcomers adjust to organizations, a supportive climate should be created for newcomers to engage in proactive behaviors [21]. In this sense, in [22], a direct and positive effect of organizational socialization on work commitment was observed. As a consequence, with a suitable workplace atmosphere, the individual may enrich the organization with their technical skills, talents, and personal qualities; this, in turn, makes the organization more competitive [18].
1.3. The Maquiladora Industry
Employees of the maquiladora industry in Mexico are an essential force that moves the Manufacturing Industry, Maquila, and Export Services (which is known by the acronym IMMEX in Spanish), which is considered one of the country’s main productive activities. The conditions under which employees work have benefited organizations in some way, such as through low wages, high productivity, and a large available workforce that is able to complete high-intensity repetitive operations and work under pressure to meet production quotas, among others [23]; in this context, the research subjects of this study are operational workers of maquiladora located in the state of Baja California, Mexico.
1.4. Research Gap/Contribution
The main contribution of this research is to empirically determine the impact of social incentives and benefits on work commitment and organizational socialization, whose relationships have not been sufficiently studied despite the impact that their understanding could have on the definition of policies to properly manage the well-being and performance of employees, which would later result in benefits for organizations. Furthermore, although some research on organizational socialization has been conducted in Asia [24,25], Europe [26], USA [27], and other regions in the world [28], it is necessary to validate empirically a model contemplating this construct in Maquiladora industries where employees have a different culture and idiosyncrasy as well as very particular working conditions.
1.5. Hypotheses
The previous review of the literature led us to the development of the following hypotheses:
Social benefits have a direct and positive effect on work commitment.
The first hypothesis considered in this research outlines that social benefits have a direct and positive effect on work commitment, perhaps because the structural power of organizations will generate feelings of responsibility to complete important tasks, thus encouraging greater commitment when it comes to them [29]. Social benefits also indicate what the authors of [30] affirm regarding the passionate Pygmalion effect, which states that the most passionate employees receive more positive comments for their success and are offered more training and promotion opportunities, causing emotional reactions and more favorable performance results.
Social benefits have a direct and positive effect on organizational socialization.
A second hypothesis outlines that social benefits have a direct and positive effect on organizational socialization, but little is known about the role of companies in determining how to use these benefits. Companies that pay higher profit premiums also have substantially higher acceptance rates of disability insurance (DI) and paid family leave (PFL), as stated by [31], and this relationship is particularly strong among lower-income employees within the company. The results suggest that the use of social security may be affected by changes in the behavior of companies.
Bonuses and incentives have a direct and positive effect on organizational socialization.
The third hypothesis of this research outlines that bonuses and incentives have a direct and positive effect on organizational socialization. This is because it seems that organizational socialization is directly strengthened by the bonuses and incentives that companies have implemented and by the growth of personal networks in organizations that generate emotional resources that mobilize newcomers in some way [32]. Additionally, both the value of the company and its operational performance are improved by the relationship between the capital of the organization and the incentives created by promotion-based tournaments in high-capital companies [33].
Monetary bonus schemes are one of the most used forms of compensation for employees in the contemporary business world; these schemes are mainly made as profits to encourage increased effort and performance at work [34].
Additionally, the analysis of the value created by serious games from the case study by AXA, the number 1 insurance company in the world, is also interesting. This qualitative study revealed that serious games create value according to five dimensions, with socialization holding an important place in addition to conception, optimization, cognition, and emotion [35].
2. Materials and Methods
This study used a cross-sectional survey design to collect data on the impact of bonuses and incentives as well as social benefits on organizational socialization and work commitment. The psychometric method was used for the development and validation of the data collection instrument since it is the most used methodology in social sciences for the measurement of variables [36]. This method has been used as a reference in different studies to validate surveys as measurement instruments, resulting in reliable data for the development of causal models [37,38].
2.1. Instrument
The study used a questionnaire that included questions about demographic and social characteristics such as gender, age, education and marital status, and seniority in the company as well as a section measuring the four research variables: two directly measured variables and two latent variables, which were integrated using six items as indicators. This information is shown in Table 1.
2.2. Data Collection
This research focused on operational workers from the state of Baja California in northern Mexico who were working in large companies (with more than 250 employees) in the IMMEX industry and considered convenience non-probability sampling. To determine the size of the sample, the database of the (Mexican) National Institute of Statistics and Geography was consulted. This database states that in February 2022, there were 331,111 employees working at the operational level in the 930 establishments of this industry in the state [39], resulting in a required sample size of 377 to achieve a level of confidence of 95%, which was determined using the known finite population formula.
The work dynamics consisted of contacting human resources managers of companies in order to present the project to them; later on, in-person visits were carried out at IMMEX companies, where the purpose of the study, the selection criteria, and the instructions for answering the instrument were explained to the operators working there. It was ensured that the participation of the personnel was voluntary, anonymous, and confidential. Finally, participants provided written informed consent, and the research was conducted according to the Declaration of Helsinki of the World Medical Association [40].
2.3. Statistical Analysis
As a preliminary step to structural equation modeling (SEM), assumptions of univariate normality, multivariate normality, multicollinearity, and outlier detection [41] were verified. To measure the univariate normality of the data, skewness was verified, and the standardized kurtosis index was used as recommended by DeCarlo [42]. To verify multivariate normality, Mardia’s multivariate kurtosis was considered [43]. The multicollinearity was measured by the variance inflation factor (VIF), and outliers were detected using the Mahalanobis distance, which statistically represents the distance of a single point to the centroid [44].
Subsequently, an exploratory factor analysis (EFA) was conducted to define the latent dimensions that describe the study phenomenon. For factor extraction, we used the maximum likelihood method and orthogonal varimax rotation because this method produces the clearest separation between the factors and also because it is less likely to produce inadequate solutions [44]. The factorability of the correlation matrix was evaluated by the Kaiser–Meyer–Olkin (KMO) and Bartlett tests and also by calculating the determinant of the correlation matrix. The intercorrelation of the variables was also measured according to the measure of sampling adequacy (MSA). Additionally, to assess the internal consistency and reliability of each construct, Cronbach’s alpha was used [45].
Later, our structural model was developed, but only after the measurement model was estimated and validated. Through this structural model, we represented the hypothetical relationships between bonuses and incentives, social benefits, organizational socialization, and work commitment in the chosen population. These relationships were tested by using structural equation modeling (SEM) and the maximum likelihood estimation (MLE) method. The SEM technique allows for the simultaneous estimation of multiple relationships, which allowed us to test the hypotheses outlined in this research. Another advantage of using SEM is that it allows the incorporation of multiple items to define scales in the analysis [44].
Because our sample size is large, the relative chi-square (CMIN/DF) was calculated to judge the discrepancy of the model. Moreover, in the absolute fit indices category, the goodness of fit index (GFI) and the root mean square error of approximation (RMSEA) were evaluated. Moreover, in the incremental fit indices category, the incremental fit index (IFI), the Tucker–Lewis index (TLI), the normed fit index (NFI), and the comparative fit index (CFI) were evaluated. Furthermore, the following parsimony fit indices were evaluated: the parsimony normalized fit index (PNFI), the parsimony ratio (PRATIO), and the adjusted goodness of fit index (AGFI) [35]. In addition, the direction and the statistical significance of the relationships as well as the direct effects defined by the proposed hypotheses were validated. Finally, the proposed model was also validated by calculating the expected cross-validation index (ECVI) [44]. All of these tests were performed using IBM ® SPSS ® Statistics software version 25, 64-bit edition (IBM company, Chicago, IL, U.S.), as well as its complementary package, AMOS TM.
3. Results
As a result of the data selection, an outlier was eliminated because of its level of statistical significance (p < 0.001), according to [44]. Consequently, the subsequent calculations were made with the remaining answers without lost values.
The univariate normality of variables was verified by the skewness and kurtosis indices, as suggested by DeCarlo [42], resulting in absolute values below 3 in the standardized kurtosis index and 1.96 in the skewness index, showing that the univariate normality condition was fulfilled. To evaluate the multivariate normality, Mardia’s coefficient [43] was used based on a normalized value of the multivariate kurtosis. This assumption was verified by comparing the multivariate kurtosis index computed using SPSS Amos software and the resulting value obtained from the formula p(p + 2), taking p as the variables observed in the model. Considering the eight variables in our model, the calculation showed a value of 80 which is higher than the Mardia’s coefficient index reported by SPSS Amos of 1.022; then, because of the latter, it was possible to conclude that the assumption of multivariate normality was met [46].
Finally, the multicollinearity of the data was reviewed to rule out that two or more variables were highly correlated [46]. For this purpose, the variance inflation factors (VIFs) were analyzed to verify if a variable could be redundant, with redundancy being considered if VIF > 10 [42]; the VIF values ranged from 1.178 to 5.461. Consequently, multicollinearity problems in our database were discarded. Table 2 gathers the indices to evaluate the univariate normality and multicollinearity of the research variables.
3.1. Descriptive Analysis of the Sample
The valid sample consisted of 376 participants working at the operational level of the IMMEX industry, with an average age of 32 ± 9.84 years, a weekly income of USD 70 ± 36, and an average seniority of 20 months, with 67% of the participants owning their homes. Workers at the operational level have the main role of directly producing the goods or services of companies and do not supervise the work of others; they are the ones who are commonly given incentives as a strategy to increase their level of work commitment and loyalty. Table 3 shows the profile of the sample.
3.2. Factor Analysis
Before performing the factor analysis, it was necessary to conduct some tests to assess the factorability of the database. Firstly, the determinant of the correlation matrix was calculated, and because it was different from zero, this analysis was feasible [47]. Then, using Bartlett’s test of sphericity, the null hypothesis indicated that the correlation matrix was equal to the identity matrix, that is to say, whether or not the variables in the population were correlated was tested [48]; with a p < 0.001 and a χ2 of approximately 1709.105 with 15 degrees of freedom, we rejected this null hypothesis. Later, using the Kaiser–Mayer–Olkin test (KMO), a value of 0.771 was obtained, also indicating an adequate relationship between the variables [44]. Additionally, the values of the measured sampling adequacy for the individual variables exceeded the minimum threshold of 0.5 [44]; with these results, we confirmed the applicability of the factor analysis to the data matrix.
For the extraction procedure, the eigenvalues for organizational socialization and work commitment were 3.838 and 1.089, respectively, with a total explained variance of 82.1%. On the other hand, Cronbach’s alpha was used for internal consistency evaluation by considering that the closer the index was to 1, the higher the internal consistency of the instrument was. Thus, the commonly accepted value of 0.70 was accepted as the lower limit for this [44]. Table 4 shows the results of this reliability test, with all of the values being greater than the aforementioned minimum recommended value.
Subsequently, a confirmatory factor analysis (CFA) was conducted. Through this CFA, the measurement model was confirmed, indicating that the constructs organizational socialization and work commitment are adequately represented by fulfilling the necessary goodness of fit indices among which the following stand out: a significant chi-square = 21.545 with 7 degrees of freedom (p < 0.001); a RSMEA = 0.074; NFI = 0.987; a TLI = 0.982; CFI = 0.991; a PRATIO = 0.533; and a PNFI = 0.516.
The convergent validity was assessed by calculating the average variance extracted (AVE) for each construct, obtaining AVE values greater than 0.5 [44]. Likewise, the AVE values found along the diagonal of Table 5 were greater than the squared bivariate correlation between the two constructs. This evidence supports the discriminant validity and indicates the uniqueness of each construct.
3.3. Model Assessment
Once the instrument was validated, a theoretical model indicating the relationships between bonuses and incentives, social benefits, organizational socialization, and work commitment in the chosen population was proposed. The structural equation modeling (SEM) approach with the maximum likelihood (ML) estimator was used to evaluate the relationship between variables.
In the proposed model (Figure 1), all of the hypotheses were significant at the 99% confidence level. In addition, two positive direct effects and two negative effects were observed. The positive effect of social benefits on work commitment (H1) as well as its positive effect on organizational socialization (H2) is shown, whereas a lack of bonuses and incentives presents a negative effect on organizational socialization (H3), and it is additionally shown that a lack of bonuses and incentives directly and negatively influence social benefits.
Besides the chi-square test, 10 additional goodness of fit indices were calculated across three classifications (Table 6) as recommended by Hair [44]. These results supported the good fit of the structural model.
Finally, the expected cross-validation index (ECVI) [43] was calculated to validate the structural model. To do this, two samples comprising 188 responses were selected and labeled as sample A and sample B. The EVCI values for the samples were the following: ECVIA = 0.364, with a 95% confidence interval [0.305 and 0.465], and ECVIB = 0.369, with a 95% confidence interval [0.309 and 0.471]. It can be observed that both the values of ECVI and their confidence intervals are consistent for samples A and B; therefore, the proposed structural model is statistically valid.
4. Discussion
The aim of this research was to determine how the variable of social benefits has a direct and positive effect on work commitment and on organizational socialization in the maquiladora industry of northern Mexico.
Regarding the contribution of this study related to the objectives of sustainable development [53], it was found that this study and its application contribute to at least three of the objectives: The third objective regarding health and well-being is contributed to, as organizations must be aware of the physical and mental health of their workers, which is why they have the right to be treated in hospitals or health care organizations and why they receive other benefits or related incentives, for example by taking disease prevention campaigns to the workplace, supporting maternity, among others. It also supports the eighth objective related to decent work and economic growth. In organizations, there should no longer be exploitation, and if more staff is required, workers are paid overtime or receive other types of compensation, such as the aforementioned productivity bonuses. Additionally, the ninth objective related to the industry is accounted for since it is one of the dynamic and competitive economic forces that generate employment and income. These workers and businesses play a key role in introducing and promoting new technologies, facilitating international trade, and enabling the efficient use of resources. Reducing the digital gap has also been an action undertaken by organizations through training, providing equipment, etc.
The results obtained from this study show that due to the lack of bonuses and incentives, there is a negative effect on organizational socialization and furthermore also negatively affects the perception of social benefits. Likewise, social benefits influence work commitment as well as organizational socialization, as reflected in the theoretical model studied.
Several studies show a positive effect of social benefits on work commitment (H1).
Therefore, it is recommended that compensation be used strategically to raise the satisfaction levels of workers [54] through adequate planning with budget allocation and by taking into account the personal characteristics of the workers and their family environments.
In the specific field of maquiladoras, particularly those of northern Mexico, differentiated aspects were found in regard to work commitment. In the case [55] of the automotive maquiladora industry in Matamoros, Tamaulipas, dimensions such as ergonomic and environmental conditions were rated on average as satisfactory, but dimensions related to recognition, remuneration, positions, or communication were rated as unsatisfactory. In this study, a positive effect of social benefits on work commitment was detected.
Secondly, a positive effect of the social benefits variable on organizational socialization (H2) is shown.
Organizational socialization that allows an individual to complement or acquire the knowledge and skills to take on a specific task in a company has practical implications that need to be taken into account to protect the investment made in workers.
Other studies suggest [56] that organizations should improve socialization tactics—especially of newly incorporated employees—by going beyond the commonly used practices of Human Resources Departments during the recruitment, hiring, training, performance evaluation, and compensation processes.
Regarding social benefits, as [57], who present a model that includes the maximization of social benefits, affirm, the incorporation of work culture with social benefits within an organization is at its highest point today. However, as [58] supports, the challenges that different business people face to produce social benefits remain unexplored.
Nevertheless, pandemic and post-pandemic research regarding organizational socialization is interesting since virtual work and home offices meant a relevant change that also intensified a trend that already existed in companies: how work life is experienced. From this point of view, it is timely to analyze obstacles and opportunities that occur in work socialization. In a study on young people who were newly incorporated into virtual modalities, it was found that the biggest obstacle was the lack of contact with coworkers, and since it was difficult to meet them, this generated a decline in the work motivation of newcomers [59]. Without a doubt, physical contact in one’s job favors organizational socialization.
The lack of bonuses and incentives presents a negative effect on organizational socialization (H3).
Organizational socialization is essential to foster a satisfactory work environment that allows for the creation of favorable conditions both for the worker and for the company. Therefore, an ideal interrelationship between the individual and the organization is desirable, and these two elements even become two factors that are at the very center of the concept of organizational socialization and can be understood as a way to achieve the fit between the individual and the organization [60]. It is undoubtedly a process of an individual adapting to their immediate work environment. It has also been proven with empirical evidence that socialization in the organization has a direct impact on the sense of belonging that workers have in regard to the organization to which they belong [60].
In this sense, [61] states that job incentives impact different aspects of the work life of the worker within a company; for example, it can be a motivational factor and a factor of organizational progress that can raise productivity and improve the quality of the service provided.
In this research, it was also shown that the lack of bonuses and incentives presents a negative effect on organizational socialization (H3). Likewise, it decreases the employees’ perceptions of social benefits; this is because the workers do not feel like they belong to the organization, which, as a consequence, results in a lack of engagement in the organization, an increase in employee absenteeism, and a decline in the work environment as well as in the productivity of the collaborator.
Other studies [62] note that work commitment is influenced by the amount of rewards perceived by collaborators. Additionally, while incentives are usually economic, activities such as continuous training [63], leisure time, vacation days, or verbal recognition can function as an incentive.
Currently, the implementation of thematic bonuses is important, as are the green bonuses that are granted to companies for collaborating with the environment in their projects. Bonuses should be sent to workers with innovative ideas or to workers who implement them to achieve sustainable planning and management.
Another case found in the literature is the last Annual Labor Cost Survey published by the National Statistics Institute (which is known by the acronym INE in Spanish) in July 2020. In Spain, almost EUR 412 per year was allocated to social benefits per worker, with Madrid and the Basque Country being the communities with the highest salaries and highest expenses in this category. However, that is not clearly seen in other countries [64].
At this point, it is important to mention again that care should be taken when establishing only economic incentives as a source of employee motivation: as indicated by [17], an increasing number of economic studies using survey and experimental methods have shown that non-monetary incentives and non-pecuniary aspects of one’s job have substantial impacts on job satisfaction, productivity, and labor supply. Thus, the concept of work has come to represent much more than simply earning an income.
4.1. Theoretical Implications
There is a great variety of existing approaches and methods to analyze the different issues related to human capital: in this case, the issues of motivation, work commitment, and organizational climate were considered; however, quantitative options are prevailing due to the recent boom in data science. This is why this study is quantitative. In addition, there is a general trend in research regarding multidisciplinarity in topics like this one, mainly among the legal, psychological, organizational, managerial, and administrative disciplines. Studies have also been carried out in other industrial sectors, such as in the transport, communications, and services industries, among many others, using a number of theoretical approaches, including qualitative research methods, and, other studies have considered the introduction of new technologies to allow job promotions, make communication more efficient, etc. Finally, this study contributes to work regarding the quality of work life and the emerging issue of happiness that mitigates aspects such as psychosocial risks, depression, anxiety, mobbing, stress, and burnout.
4.2. Managerial Implications
The results reported here also have some managerial implications, with a direct impact on decision-making to promote the search for incentives that favor motivation and that increase the sense of belonging from workers toward the organization. It is important to mention that there are some studies about this topic; however, this work highlights the social benefits that an organization grants to employees as mediating element to achieve work commitment and to improve organizational socialization.
4.3. Study Limitations
This study presents some limitations that should be considered. First, we used a cross-sectional study, and therefore, the results represent how reality is perceived by the respondents at a specific point in time. Second, data were gathered from the maquiladora industry located in northern Mexico. Third, we only surveyed operational workers and not supervisors or managers. These limitations must be taken into account when interpreting the results and when seeking to generalize the results and conclusions presented here.
An additional limitation of this study was that some maquiladora companies did not answer the emails or phone calls made to request participation in the research as a result of the COVID-19 pandemic, so the results of the research could present a response bias.
4.4. Directions for Further Research
After conducting this research, we found some interesting lines for future research; for example, the hypotheses that the employees of companies that participate in innovation activities are more likely to report greater work commitment [65] or that the affirmation that mindfulness and happiness positively and significantly influence the creative performance of employees; it is also suggested that research on this topic be deepened since the mandatory guidelines for leadership of manufacturing organizations suggest different ways of promoting creative performance among employees according to their attitudes [66].
Moreover, this research could be complemented by incorporating new factors that are likely to be associated with the performance of workers that were not included in this study, some of which were previously mentioned, in addition to others that, in the opinion of the researchers, should be analyzed by considering the type of organization, the context, or perhaps the employees’ own experience.
It would also be desirable to analyze the dimensions of social acceptability in the context of digital manufacturing (DM) and industry 4.0, since they propose a novel framework [67].
Additionally, it should be considered that social platforms using virtual reality (VR) are an emerging phenomenon with a growing number of users in the context of the COVID-19 pandemic and in the post-pandemic era. Socialization activities such as meeting with friends using virtual reality platforms are associated with relationships and enjoyment, and recreational and creative activities allow for self-expansion [68].
Finally, some future lines of research could be derived to address the limitations mentioned above.
5. Conclusions
The main aim of this research was to explore the existing relationships between bonuses and incentives and social benefits with organizational socialization and work commitment in the context of IMMEX organizations. This objective was achieved using data collected from operational-level workers and using the SEM technique. From the results obtained, it can be concluded that the social benefits variable has a positive effect on work commitment as well as a positive effect on organizational socialization; however, a lack of bonuses and incentives presents a negative effect on organizational socialization. In addition, it is shown that a lack of bonuses and incentives has a direct and negative influence on social benefits. These results should be interesting for leaders or top managers who are looking to continuously improve their companies through the administration of the most valuable resource, namely human resources, by deploying some strategies such as the establishment of bonuses or other kinds of incentives, not only in monetary terms but also through some actions such as continuous training, leisure time, vacation days, or verbal recognition to increase well-being and the commitment of the workers toward the company goals, thus demonstrating the contribution of these actions to the social component that is so important for the sustainability of organizations.
In this sense, the main contribution of this work is the empirical validation of the existing relationships between bonuses and incentives, social benefits, organizational socialization, and work commitment since these have been little studied in the existing literature despite being important elements affecting the productivity of the workforce in organizations. Specifically, the organizational socialization that has practically remained unstudied.
As previously stated, this research could be complemented by incorporating new factors such as education and training or teamwork as precursors or causes of work commitment and of long-term retention. This study can also be expanded to not only focus on manufacturing industries.
Finally, special attention should be paid to the definition of policies related to incentives in organizations as, although some studies have observed a positive relationship between economic incentives and work commitment [69], other studies have reported adverse effects on both employee satisfaction and performance [70,71,72].
Conceptualization, M.F.A. and M.C.R.-B.; Data Curation, J.L.-R.; Formal Analysis, B.R.G.R. and M.O.-P.T.; Investigation, M.F.A. Methodology, Y.B.-L. and J.L.-R.; Software, Y.B.-L.; Supervision, M.F.A.; Validation, M.C.R.-B. and J.H.B.; Writing—Original Draft Preparation, M.F.A. Writing—Review and Editing, B.R.G.R., J.H.B. and M.O.-P.T. All authors have read and agreed to the published version of the manuscript.
The study was conducted according to the guidelines of the Declaration of Helsinki. The final questionnaire was presented to the Ethics and Research and Post-graduate Evaluation Committee of the Universidad Autónoma de Baja California for its assessment and authorization.
Informed consent was obtained from all subjects involved in the study.
The data presented in this research are available upon request.
We want to thank all those who voluntarily participated in this research.
The authors declare no conflict of interest.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Enlarge this image.Figure 1. Model proposed. Numbers are the standardized regression coefficients and solid lines indicate the direction of the effects. *** Significant at 0.001 level.
Variables considered in the research.
| Variables | Item |
|---|---|
| Bonuses and Incentives (B&I) | B&I: Do you frequently receive bonuses and incentives? |
| Social Benefits (SB) | SB: What are the social benefits that you perceive? |
| Latent Variables | Items |
| Organizational Socialization (OS) | OS1: In my work unit, supervisors regularly congratulate employees in recognition of their efforts. |
| OS2: In my work unit, supervisors use different ways to tangibly recognize employee efforts (for example, more flexibility with schedules, more interesting projects, tickets to cultural or sporting events). | |
| OS3: The bosses take my opinion into account when making decisions in the company. | |
| Work commitment (WC) | WC1: I feel that I have very little reason to consider leaving my organization. |
| WC2: I feel a strong sense of belonging to my organization. | |
| WC3: I consider that I am an important part of the company. |
Source: Developed by authors.
Indices to assess univariate normality and multicollinearity.
| Variable | Skew | Kurtosis | VIF |
|---|---|---|---|
| B&I | −0.481 | −1.768 | 1.178 |
| SB | −0.824 | −1.310 | 1.961 |
| OS1 | −0.266 | −1.474 | 4.736 |
| OS2 | −0.111 | −1.527 | 5.461 |
| OS3 | −0.050 | −1.267 | 1.871 |
| WC1 | −0.411 | −1.405 | 4.359 |
| WC2 | −0.695 | −0.899 | 5.036 |
| WC3 | −0.812 | −0.736 | 2.424 |
Sample profile.
| Number of Participants | Response Rate | ||
|---|---|---|---|
| Gender | |||
| Men | 227 | 60.4 | |
| Women | 149 | 39.6 | |
| Marital status | |||
| Married | 157 | 41.8 | |
| Single | 141 | 37.5 | |
| Civil union | 65 | 17.3 | |
| Divorced or separated | 13 | 3.4 | |
| Number of children | |||
| Childless | 168 | 44.7 | |
| One | 71 | 18.9 | |
| Two | 83 | 22.0 | |
| Three | 41 | 10.9 | |
| Four or more | 13 | 3.5 | |
| Education | |||
| Elementary school | 26 | 6.9 | |
| Middle school | 164 | 43.7 | |
| High school | 172 | 45.7 | |
| Bachelor’s degree | 14 | 3.7 | |
| Hours worked per week | |||
| 40–47 | 240 | 63.8 | |
| 48–56 | 135 | 35.9 | |
| More than 56 | 1 | 0.3 | |
Source: Developed by authors.
Reliability test results.
| Variables | Items | Mean | Standard Deviation | Cronbach’s Alpha | Range of Correlation Item-Total Correlation |
|---|---|---|---|---|---|
| Organizational Socialization | 3 | 2.766 | 0.100 | 0.897 | 0.634–0.848 |
| Work Commitment | 3 | 3.160 | 0.228 | 0.880 | 0.598–0.884 |
Correlation and AVE values.
| Latent Variable | Organizational Socialization | Work Commitment |
|---|---|---|
| Organizational Socialization | 0.764 | 0.284 1 |
| Work Commitment | 0.533 2 | 0.739 |
1 Value above the diagonal is squared correlation between constructs. 2 Value below the diagonal is correlation between constructs.
Model fit indices estimates.
| Acceptable Level | Values | References | |
|---|---|---|---|
| MODEL FIT | |||
| Chi-square (χ2) | 53.415 | ||
| Degrees of freedom (df) | 16 | ||
| χ2/df | Less than <5 | 3.338 | [ |
| ABSOLUTE FIT INDICES | |||
| RMSEA | Less than 0.08 | 0.079 | [ |
| GFI | Close or >0.90 | 0.981 | |
| SRM | Less than 0.05 | 0.043 | [ |
| INCREMENTAL FIT INDICES | |||
| NFI | Close or >0.90 | 0.974 | |
| TLI | 0.967 | [ |
|
| IFI | 0.981 | ||
| CFI | Greater than >0.95 | 0.981 | |
| PARSIMONY FIT INDICES | |||
| PRATIO | From 0.5 to 1 | 0.571 | |
| PNFI | 0.556 | [ |
|
| AGFI | 0.561 | ||
Source: Developed by authors.
References
1. Vergara-Romero, A.; Márquez Sánchez, F.; Sorhegui-Ortega, R.; Olalla-Hernández, A. Capital humano: Actor central para la sostenibilidad organizacional. Rev. Venez. De Gerenc.; 2021; 26, pp. 297-307. Available online: https://www.redalyc.org/articulo.oa?id=29066223019 (accessed on 11 August 2022).
2. Barile, S.; Quattrociocchi, B.; Calabrese, M.; Iandolo, F. Sustainability and the viable systems approach: Opportunities and issues for the governance of the territory. Sustainability; 2018; 10, 790. [DOI: https://dx.doi.org/10.3390/su10030790]
3. Yanchovska, I. The relationship between job satisfaction and individual performance of it employees. Proc. CBU Econ. Bus.; 2021; 2, pp. 141-148. [DOI: https://dx.doi.org/10.12955/peb.v2.267]
4. Astuti, W.; Amalia, L. The Relationship between Work Motivation, Job Satisfaction, and Employee Performance: The Moderating Role of Psychology Capital and The Mediating Role of Organizational Commitment. J. Manaj. Teor. dan Ter. J. Theory Appl. Manag.; 2021; 14, 102. [DOI: https://dx.doi.org/10.20473/jmtt.v14i2.26192]
5. Varma, C. Importance of employee motivation & job satisfaction for organizational performance. Int. J. Soc. Sci. Interdiscip. Res.; 2018; 6, pp. 10-20. Available online: https://ssrn.com/abstract=3073813 (accessed on 22 August 2022).
6. Coronado-Guzmán, G.; Valdivia-Velasco, M.; Aguilera-Dávila, A.; Alvarado-Carrillo, A. Compromiso Organizacional: Antecedentes y Consecuencias. Conciencia Tecnológica. Concienc. Tecnológica; 2022; 60, pp. 1-15. Available online: https://www.redalyc.org/articulo.oa?id=94465715006 (accessed on 12 August 2022).
7. Hu, Q.; Dollard, M.F.; Taris, T.W. Organizational context matters: Psychosocial safety climate as a precursor to team and individual motivational functioning. Saf. Sci.; 2022; 145, 105524. [DOI: https://dx.doi.org/10.1016/j.ssci.2021.105524]
8. Avunduk, Y. The Relationship between Organizational Commitment and Job Satisfaction. J. Educ. Issues; 2021; 7, 146. [DOI: https://dx.doi.org/10.5296/jei.v7i2.18966]
9. Peng, L.; Li, Z. Psychological Contract, Organizational Commitment, and Knowledge Innovation: A Perspective of Open Innovation. Probl. Perspect. Manag.; 2021; 19, pp. 418-432. [DOI: https://dx.doi.org/10.21511/ppm.19(2).2021.33]
10. Máynez, A.I.; Cavazos, J.; Reyes, G. Efecto de la violación del contrato psicológico y el agotamiento emocional sobre el cinismo del empleado. Estud. Gerenc.; 2017; 33, pp. 124-131. [DOI: https://dx.doi.org/10.1016/j.estger.2017.04.002]
11. Calderón-Mafud, J.L.; Pando-Moreno, M.; Preciado-Serrano, M.; Colunga-Rodríguez, C. Efecto de la Socialización Organizacional en el Engagement de Trabajadores Mexicanos: Claridad y Futuro. Psicogente; 2020; 23, pp. 1-22. [DOI: https://dx.doi.org/10.17081/psico.23.43.3084]
12. Hirschi, A.; Spurk, D. Ambitious employees: Why and when ambition relates to performance and organizational commitment. J. Vocat. Behav.; 2021; 127, 103576. [DOI: https://dx.doi.org/10.1016/j.jvb.2021.103576]
13. Thomas Lang. Job Satisfaction and Implications for Organizational Sustainability: A Resource Efficiency Perspective. Sustainability; 2021; 13, 3794. [DOI: https://dx.doi.org/10.3390/su13073794]
14. Cernas, D.A.; Mercado, P.; León, F. La varianza del método común en la relación entre la satisfacción laboral y la satisfacción con la vida. Estud. Gerenc.; 2017; 33, pp. 321-329. [DOI: https://dx.doi.org/10.1016/j.estger.2017.11.004]
15. Voordt, T.v.d.; Jensen, P.A. The impact of healthy workplaces on employee satisfaction, productivity and costs. J. Corp. Real Estate; 2021; [DOI: https://dx.doi.org/10.1108/JCRE-03-2021-0012]
16. Madero-Gómez, S.M.; Olivas-Luján, M.R. Análisis de los factores del comportamiento organizacional en jóvenes que están iniciando su carrera laboral. Estud. Gerenc.; 2016; 32, pp. 51-59. [DOI: https://dx.doi.org/10.1016/j.estger.2015.12.001]
17. Lea, C.; Meier, S. Nonmonetary Incentives and the Implications of Work as a Source of Meaning. J. Econ. Perspect.; 2018; 32, pp. 215-238. [DOI: https://dx.doi.org/10.1257/jep.32.3.215]
18. Choi, Y. When in Rome, Feel as the Romans Feel: An Emotional Model of Organizational Socialization. Soc. Sci.; 2018; 7, 197. [DOI: https://dx.doi.org/10.3390/socsci7100197]
19. Bauer, T.N.; Bodner, T.; Erdogan, B.; Truxillo, D.M.; Tucker, J.S. Newcomer adjustment during organizational socialization: A meta-analytic review of antecedents, outcomes, and methods. J. Appl. Psychol.; 2007; 92, pp. 707-721. [DOI: https://dx.doi.org/10.1037/0021-9010.92.3.707]
20. Frögéli, E.; Annell, S.; Rudman, A.; Inzunza, M.; Gustavsson, P. The Importance of Effective Organizational Socialization for Preventing Stress, Strain, and Early Career Burnout: An Intensive Longitudinal Study of New Professionals. Int. J. Environ. Res. Public Health; 2022; 19, 7356. [DOI: https://dx.doi.org/10.3390/ijerph19127356]
21. Wan, J.; Yilin, A.; Linlin, W.; Chundong, Z. Newcomers’ reaction to the abusive supervision toward peers during organizational socialization. J. Vocat. Behav.; 2021; 128, 103586. [DOI: https://dx.doi.org/10.1016/j.jvb.2021.103586]
22. Song, Z.; Chon, K.; Ding, G.; Gu, C. Impact of organizational socialization tactics on newcomer job satisfaction and engagement: Core self-evaluations as moderators. Int. J. Hosp. Manag.; 2015; 46, pp. 180-189. [DOI: https://dx.doi.org/10.1016/j.ijhm.2015.02.006]
23. Rivera, B.R.G.; Martínez, I.A.M.; Cox, J.L. The Hidden Face of Mobbing Behavior Survey Application of the Cisneros Inventory in a Maquila Facility in Mexico. Contad. Adm.; 2014; 59, pp. 175-193. [DOI: https://dx.doi.org/10.1016/S0186-1042(14)71248-3]
24. Rajiani, I.; Kot, S. Javanese Indonesia: Human Resource Management Issues in a Uniquely Collectivist Culture. Cult. Manag. Sci. Educ.; 2020; 4, pp. 9-21. [DOI: https://dx.doi.org/10.30819/cmse.4-2.01]
25. Liao, G.; Zhou, J.; Yin, J. Effect of Organizational Socialization of New Employees on Team Innovation Performance: A Cross-Level Model. Psychol. Res. Behav. Manag.; 2022; 15, 1017. [DOI: https://dx.doi.org/10.2147/PRBM.S359773]
26. Manuti, A.; Spinelli, C.; Giancaspro, M. Organizational Socialization and Psychological Contract: The Vulnerability of Temporary Newcomers. A Case Study from an Italian Call Center. Empl. Responsib. Rights J.; 2016; 28, pp. 225-245. [DOI: https://dx.doi.org/10.1007/s10672-016-9285-x]
27. Fang, R.; Duffy, M.K.; Shaw, J.D. The Organizational Socialization Process: Review and Development of a Social Capital Model. J. Manag.; 2011; 37, pp. 127-152. [DOI: https://dx.doi.org/10.1177/0149206310384630]
28. Batistič, S.; Kenda, R. Toward a model of socializing project team members: An integrative approach. Int. J. Proj. Manag.; 2018; 36, pp. 687-700. [DOI: https://dx.doi.org/10.1016/j.ijproman.2018.03.003]
29. Williams, M.J.; Lopiano, G.; Heller, D. When the Boss Steps up: Workplace Power, Task Responsibility, and Engagement with Unpleasant Tasks. Organ. Behav. Hum. Decis. Process.; 2022; 170, 104140. [DOI: https://dx.doi.org/10.1016/j.obhdp.2022.104140]
30. Wang, K.; Bailey, E.R.; Jachimowicz, J.M. The Passionate Pygmalion Effect: Passionate Employees Attain Better Outcomes in Part Because of More Preferential Treatment by Others. J. Exp. Soc. Psychol.; 2022; 101, 104345. [DOI: https://dx.doi.org/10.1016/j.jesp.2022.104345]
31. Bana, S.; Bedard, K.; Rossin-Slater, M.; Stearns, J. Unequal Use of Social Insurance Benefits: The Role of Employers. J. Econom.; 2022; [DOI: https://dx.doi.org/10.1016/j.jeconom.2022.02.008]
32. Bakker, S.R.; Hendriks, P.H.J.; Korzilius, H.P.L.M. Let It Go or Let It Grow?—Personal Network Development and the Mobilization of Intra-Organizational Social Capital. Soc. Netw.; 2022; 68, pp. 179-194. [DOI: https://dx.doi.org/10.1016/j.socnet.2021.06.002]
33. Boubaker, S.; Hasan, M.M.; Habib, A. Organization Capital, Tournament Incentives and Firm Performance. Financ. Res. Lett.; 2022; 46, 102468. [DOI: https://dx.doi.org/10.1016/j.frl.2021.102468]
34. Elbæk, C.T.; Lystbæk, M.N.; Mitkidis, P. On the Psychology of Bonuses: The Effects of Loss Aversion and Yerkes-Dodson Law on Performance in Cognitively and Mechanically Demanding Tasks. J. Behav. Exp. Econ.; 2022; 98, 101870. [DOI: https://dx.doi.org/10.1016/j.socec.2022.101870]
35. Allal-Chérif, O.; Lombardo, E.; Jaotombo, F. Serious Games for Managers: Creating Cognitive, Financial, Technological, Social, and Emotional Value in in-Service Training. J. Bus. Res.; 2022; 146, pp. 166-175. [DOI: https://dx.doi.org/10.1016/j.jbusres.2022.03.083]
36. Price, L. Psychometric Methods: Theory into Practice; The Guilford Press: London, UK, 2017.
37. Malhotra, M.K.; Grover, V. An assessment of survey research in POM: From constructs to theory. J. Oper. Manag.; 1988; 16, pp. 407-425.
38. Flynn, B.B.; Sakakibara, S.; Schroeder, R.G.; Bates, K.A.; Flynn, E.J. Empirical research methods in operations management. J. Oper. Manag.; 1990; 9, pp. 250-284.
39. INEGI, Instituto Nacional de Estadística y Geografía. Estadística Manufacturera y Maquiladora de Exportación. Mexico. Available online: https://www.inegi.org.mx/sistemas/bie/ (accessed on 4 May 2022).
40. World Medical Association. Medical Research Involving Human Subjects. Declaration of Helsinki (Version 2013); World Medical Association’s: Geneva, Switzerland, 2013.
41. Kline, R.B. Basic statistical concepts. Principles and Practice of Structural Equation Modeling; 2nd ed. The Guilford Press: New York, NY, USA, 2016.
42. DeCarlo, L.T. On the meaning and use of kurtosis. Psychol. Methods; 1997; 2, pp. 292-307.
43. Mardia, K.V. Applications of some measures of multivariate skewness and kurtosis in testing normality and robustness studies. Sankhy Indian J. Statist. B; 1974; 36, pp. 115-128.
44. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E. Confirmatory factor analysis. Multivariate Data Analysis; 7th ed. Pearson: London, UK, 2014.
45. Cronbach, L.J. Coefficient alpha and the internal structure of tests. Psychometrika; 1951; 16, pp. 297-334.
46. Khine, M. Application of Structural Equation Modeling in Educational Research and Practice; Sense Publishers: Dordrecht, The Netherlands, 2013.
47. Schumacker, R.E.; Lomax, R.G. SEM basics. A Beginner’s Guide to Structural Equation Modeling; 4th ed. Taylor & Francis: New York, NY, USA, 2016.
48. Pituch, K.A.; Stevens, J.P. Applied Multivariate Statistics for the Social Sciences; 6th ed. Routledge: New York, NY, USA, 2016.
49. Bollen, K.A. A new incremental fit index for general structural equation models. Sociol. Methods Res.; 1989; 17, pp. 303-316. [DOI: https://dx.doi.org/10.1177/0049124189017003004]
50. Browne, M.; Cudeck, R. Alternative ways of assessing model fit. Testing Structural Equation Model; Bollen, K.A.; Long, J.S. Sage: Newbury Park, CA, USA, 1993.
51. Steiger, J.H. Point estimation, hypothesis testing and interval estimation approach. Multivar. Behav. Res.; 1990; 25, pp. 173-180. [DOI: https://dx.doi.org/10.1207/s15327906mbr2502_4]
52. Mulaik, S.A.; James, L.R.; Van Alstine, J.; Bennett, N.; Lind, S.; Stilwell, D.C. Evaluation of goodness-of-fit indices for structural equation models. Psychol. Bull.; 1989; 105, pp. 430-445. [DOI: https://dx.doi.org/10.1037/0033-2909.105.3.430]
53. Organización Mundial de las Naciones Unidas. Objetivos del desarrollo sostenible. Available online: https://www.un.org/sustainabledevelopment/es/objetivos-de-desarrollo-sostenible/ (accessed on 21 July 2022).
54. Torres-Flórez, D. Estrategia de compensaciones como herramienta de satisfacción laboral. Rev. Geon; 2019; 6, pp. 4-9. [DOI: https://dx.doi.org/10.22579/23463910.181]
55. Prince, I.G.; Cazares, E.D.; Rodríguez, D.G.G.; Mercado, C.G.O.; Álvarez, M.Á.M. Satisfacción laboral en industria maquiladoras. Rev. Glob. Neg.; 2020; 8, pp. 23-32. Available online: http://www.theibfr2.com/RePEc/ibf/rgnego/rgn-v8n1-2020/RGN-V8N1-2020-2.pdf (accessed on 22 August 2022).
56. Batistič, S. Looking beyond—Socialization Tactics: The Role of Human Resource Systems in the Socialization Process. Hum. Resour. Manag. Rev.; 2018; 28, pp. 220-233. [DOI: https://dx.doi.org/10.1016/j.hrmr.2017.06.004]
57. Gupta, P.; Mehlawat, M.K.; Aggarwal, U.; Khan, A.Z. An Optimization Model for a Sustainable and Socially Beneficial Four-Stage Supply Chain. Inf. Sci.; 2022; 594, pp. 371-399. [DOI: https://dx.doi.org/10.1016/j.ins.2022.02.032]
58. Aparicio, S.; Audretsch, D.; Noguera, M.; Urbano, D. Can Female Entrepreneurs Boost Social Mobility in Developing Countries? An Institutional Analysis. Technol. Forecast. Soc. Chang.; 2022; 175, 121401. [DOI: https://dx.doi.org/10.1016/j.techfore.2021.121401]
59. Ghielen, J. Newcomers’ Experiences of the Organizational Socialization Process from Home during COVID-19 Regarding Their Work Motivation and the Barriers and Opportunities They Face. Available online: https://theses.ubn.ru.nl/bitstream/handle/123456789/11465/Ghielen%2C_Jurre_1.pdf?sequence=1 (accessed on 20 July 2022).
60. Espinoza, A.V. Socialización Organizacional y Liderazgo Como Predictores del Bienestar Laboral en Miembros de Organizaciones. 2021; Available online: http://bibliotecavirtual.dgb.umich.mx:8083/xmlui/handle/DGB_UMICH/6280 (accessed on 22 August 2022).
61. Aguiar, M.; Perèz, F.; Madriz, D. Incentivos Laborales Como Aporte a La Productividad y a La Calidad de Servicio En Las Empresas Del Rubro Farmacias. Available online: https://core.ac.uk/display/48298003 (accessed on 20 July 2022).
62. Vega, M.M.C.; Botello, C.M.S.; Partido, A.N.; Rodrigo, M.J.M. Clima organizacional y satisfacción laboral. Una comparación entre hospitales públicos de alta y baja complejidad. Salud De Los Trab.; 2011; 19, pp. 5-16. Available online: https://www.redalyc.org/articulo.oa?id=375839297002 (accessed on 22 August 2022).
63. Carrillo-García, C.; Martínez-Roche, M.E.; Gómez-García, C.I.; Meseguer-DePedro, M. Satisfacción laboral de los profesionales sanitarios de un Hospital Universitario: Análisis general y categorías laborales. An. De Psicol. ÍA/Ann. Psychol.; 2015; 31, pp. 645-650. [DOI: https://dx.doi.org/10.6018/analesps.31.2.169791]
64. Encuesta Anual de Coste Laboral (EACL). Available online: https://www.ine.es/prensa/eacl_2021.pdf (accessed on 21 July 2022).
65. Grolleau, G.; Mzoughi, N.; Pekovic, S. An Empirical Analysis of the Relationship between Innovation Activities and Job Satisfaction among French Firms. J. Vocat. Behav.; 2022; 133, 103689. [DOI: https://dx.doi.org/10.1016/j.jvb.2021.103689]
66. Khan, S.M.; Abbas, J. Mindfulness and Happiness and Their Impact on Employee Creative Performance: Mediating Role of Creative Process Engagement. Think. Ski. Creat.; 2022; 44, 101027. [DOI: https://dx.doi.org/10.1016/j.tsc.2022.101027]
67. Kumar, A.; Agrawal, R.; Wankhede, V.A.; Sharma, M.; Mulat-weldemeskel, E.A. Framework for Assessing Social Acceptability of Industry 4.0 Technologies for the Development of Digital Manufacturing. Technol. Forecast. Soc. Chang.; 2022; 174, 121217. [DOI: https://dx.doi.org/10.1016/j.techfore.2021.121217]
68. Barreda-Ángeles, M.; Hartmann, T. Psychological Benefits of Using Social Virtual Reality Platforms during the COVID-19 Pandemic: The Role of Social and Spatial Presence. Comput. Hum. Behav.; 2022; 127, 107047. [DOI: https://dx.doi.org/10.1016/j.chb.2021.107047]
69. Liu, W.; Liu, Y. The Impact of Incentives on Job Performance, Business Cycle, and Population Health in Emerging Economies. Front. Public Health; 2022; 9, 778101. [DOI: https://dx.doi.org/10.3389/fpubh.2021.778101] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35223756]
70. Roos, M.; Reale, J.; Banning, F. A value-based model of job performance. PLoS ONE; 2022; 17, e0262430. [DOI: https://dx.doi.org/10.1371/journal.pone.0262430]
71. Qiao, D.; Lee, S.-Y.; Whinston, A.B.; Wei, Q. Mitigating the Adverse Effect of Monetary Incentives on Voluntary Contributions Online. J. Manag. Inf. Syst.; 2021; 38, pp. 82-107. [DOI: https://dx.doi.org/10.1080/07421222.2021.1870385]
72. Kuvaas, B.; Buch, R.; Dysvik, A. Individual variable pay for performance, controlling effects, and intrinsic motivation. Motiv. Emot.; 2020; 44, pp. 525-533. [DOI: https://dx.doi.org/10.1007/s11031-020-09828-4]
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Details
; Baez-Lopez, Yolanda 2
; Limon-Romero, Jorge 2
; Ramírez-Barón, María Concepción 1 ; Blanca Rosa García Rivera 1
; Melina Ortega-Pérez Tejada 1
; Jacqueline Hernández Bejarano 3 1 Faculty of Administrative and Social Sciences, Universidad Autónoma de Baja California, Valle Dorado, Ensenada 22890, BC, Mexico
2 Faculty of Engineering, Architecture and Design, Universidad Autónoma de Baja California, Ensenada 22860, BC, Mexico
3 Faculty of Administrative Sciences, Universidad Autónoma de Baja California, Mexicali 21330, BC, Mexico