Open access peer-reviewed chapter
Reliability and validation convergent.
Abstract
The proposal of this study is to analyze a model in which the effect of each of the dimensions of organizational commitment (OC) on organizational learning (OL) and its influence on innovation (INN) is examined. A questionnaire was applied to managers of 347 agribusiness small and medium-sized enterprises (SMEs) from the three states of the Bajío zone of the Mexican Republic. A quantitative study was carried out, for which a model that presents the different relationships proposed as hypotheses was validated, and with the use of structural equations the results were known. The findings show that affective commitment and continuance commitment have a positive and significant effect on OL, however, normative commitment was found to be non-significant on OL. The last hypothesis of the influence of OL on INN was positive and significant. The findings show that in the agribusiness SMEs examined, the feeling of belonging of employees in the organization should be promoted to a greater extent, as well as the desire to remain in the organization due to the benefits and guarantees that the company offers them to promote learning and the INN in them.
Keywords
- organizational commitment
- organizational learning
- innovation
- agribusiness
- México
1. Introduction
Today every company faces important challenges, especially with the changes that happened in a vertiginous way due to the health crisis due to COVID-19. As a result, companies had to make changes almost immediately and in some cases, they are still processing actions related to innovation (INN) in the way they serve their market. INN requires as a background a high level of commitment and collaboration on the part of all members of the company at different levels, from top management to operational levels.
It is important for management to encourage all employees to give their ideas in order to create innovations within the company. In organizations, it is necessary to know which of the different strategies to promote commitment within the company influences in generating changes that allow breaking the established routines that provoke innovative ideas.
On the other hand, the agribusiness sector is an important sector in Mexico and requires support in its management in order to give the necessary impulse to generate new and better products, as well as the generation of more employment and more entrepreneurial actions.
In terms of organizational management, it is relevant to know what type of commitment to promote in employees to provoke more organizational learning (OL) and thereby increase innovation, since there is literature that has addressed the issue of organizational commitment (OC), examining the influence of the concept in its entirety. However, it is relevant to know specifically how each of its dimensions contributes to the generation of OL and INN.
The objective of this study is to analyze to what extent the dimensions of OC influence OL within the organization and how this influences agribusiness innovation.
From the literature examined on Innovation, it is found that Schumpeter [1, 2] was one of the initiators of the study on the topic of innovation, and regarding the concept, he points out that it is the process of incorporating new goods and services into the market, new production methods, the creation of a new market, a new source of raw material supply, a new form of management, which in turn classifies it into incremental and radical innovation. The incremental innovation considers developing aspects for the improvement of products, processes, and management systems and the radical ones break with what has been defined so far in the organization since they make stronger changes than the first ones.
For its part, the Organization for Economic Cooperation and Development (OECD) updates its concept of innovation by stating that “An innovation is a product, process (or combination of both) that differs significantly from previous products and processes, and that has been made available to potential users (products) or implemented in the organization (processes)” [3], currently INN is one of the effective strategies used in changing environments and situations [4], in turn, product innovation can help companies gain customers and market acceptance, maintain competitiveness and improve performance and profitability [5].
There are studies that indicate that OL is a strong element for innovation to occur in companies. The positive influence of the OL construct with the INN construct has been analyzed and discussed in various studies [6, 7, 8, 9], especially because the OL prepares the organization for the continuous change that is required and manages to integrate knowledge in the company [10], it also allows transforming the knowledge of the people who belong to the organization individually in the knowledge that is incorporated into the company [11]. Obtaining knowledge through OL allows companies to have advantages over the competition [12], thereby developing an innovative process that allows exploiting the development of new products [7]. This is why the improvement of skills, knowledge, and aptitudes is a reflection of the OL that also allows innovation processes [8].
On the other hand, if the people within the organization share the same vision, the top management must make it known and promote it in such a way that everyone in the organization goes after the same objectives and that the top management maintains an open mentality to accept that all the collaborators within the company feel free to propose new ideas for the improvement of processes, products and management systems or any new idea that allows an improvement for the company and that on the part of management there is a commitment to continually learn that allows the necessary changes to face the challenges of the environment, this will provide an environment conducive to innovation within organizations.
Some results of studies on the relationship of OL with INN is that of Gomes et al. [9] in which they find that OL acts as a facilitator for INN to be generated concluding that the management of managers should be more proactive and creative, continuously promoting new ideas. There is also the research of Fonseca [7] who concludes that the level of OL implementation makes change more possible. For their part, Atitumpong and Badir [13] conclude in their empirical study that OL within the organization is related to innovative work behavior. On the other hand, Abbas et al. [8] point out as a result of their study that recognizes the critical part of OL in initiating and sustaining INN.
In the same order of ideas, as a precedent to OL within the company, is that people commit themselves. OC is the psychological link of the employee with the company and determines the degree of his connection with the organization [14]. It also determines worker behaviors in unwritten contracts [15]. It can be of three types [16], the first is the “affective” and is defined as “the feeling of belonging to the organization” [17], which has to do with the personality and experience of the employees. It includes social exchange processes that benefit the organization [18]. The second is “continuance” considered as the desire to remain in the organization because the employee sees benefits and guarantees that other companies do not give them and needs to remain in it [19]. The employee evaluates the investments in wasted effort and time in the event of leaving the organization [20]. The third is “normative” commitment, in which employees remain as a result of a sense of obligation since they are forced to remain [19], either out of loyalty or feeling a duty to provide correspondence [20].
OC has been linked to various variables of organizational results [20] with the implementation of innovations [21, 22] with job performance [23] and with the implementation of changes [21].
Regarding the relationship between OC and OL, it has been found that there are antecedent variables that can influence different types of commitment and that in turn cause a variation in other constructs, including OL [24], furthermore, to the extent that there is commitment at the different levels of an organization, the greater the ability to learn may be [25].
In the literature there are studies that demonstrate that there is an influence between OC and OL within the organization since the former supports questioning the values of the organization and promoting the rupture of the daily routines established in the company, this causes a change and generates learning [6, 26], evidence is also confirmed in the relationship between affective and continuance commitment with the OL [27].
It is then expected that regardless of the type of commitment that the employee manifests within the organization (affective, continuance, or normative), there is a bond with the organization and the desire to remain in it, this will allow their behaviors to influence participation in sharing the vision of the institution and with its actions to achieve it in the indicated future, it is also expected that it will be influenced by having an open mind on the part of all members of the organization to share knowledge and ideas for improvement since they will be committed to continuously learn that leads them to present beneficial proposals for the organization.
In order to fulfill the objective of the study and after having presented the evidence in literature on the antecedents of the OC dimensions on the OL and its relationship with INN, the following hypotheses are presented.
H1: Affective commitment has a significant and positive influence on organizational learning.
H2: Continuance commitment has a positive and significant influence on organizational learning.
H3: Normative commitment has a positive and significant influence on organizational learning.
H4: Organizational learning has a positive and significant influence on innovation.
Figure 1 shows the conceptual model that is evaluated in this study and on which the structural analysis will be performed to test the study hypotheses.
Figure 1.
Conceptual model.
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2. Methodology
The target population for the development of the study was the small and medium-sized enterprises (SMEs) in an area of the Bajio region of Mexico belonging to the agribusiness sector. For the selection of the total population, manufacturing, commerce, and service SMEs were identified from the National Statistical Directory of Economic Units [28], which was a total population of 4891 SMEs in the three states in which the study was conducted and on which the sample of 347 agribusiness SMEs was determined (with an error of +/−5% and a confidence level of 95%), of which corresponded to 110 SMEs in Aguascalientes, 141 in Guanajuato and 96 in Jalisco.
The information was obtained through a questionnaire applied personally to the managers or owners of each agribusiness SME in the sample selected for the Bajio region of Mexico.
The measurement of the scales for each of the study variables was based on a careful review of the literature. All the study variables were operationalized using multi-item scales. For the OC variable, the scale with 18 questions proposed by Allen and Meyer [14] was used, which includes three dimensions corresponding to the three types of commitment, affective, continuance, and normative, each with six questions. For the OL variable, an adaptation of the scale suggested by Sinkula et al. [29] was applied, with three dimensions, commitment to learning, shared vision, and open-mindedness, with a total of 18 questions, with six questions for each dimension. Finally, to measure the INN variable, a scale adapted by the Spanish Association of Accounting and Business Administration [30] and used by García-Pérez de Lema et al. [31] was used, the said variable is subdivided by products/services, processes, and management [30].
To confirm the reliability of these measures, Cronbach’s Alpha was analyzed, where the values ranged from 0.758 to 0.888. According to the literature, the reliability of the scales is confirmed as long as values greater than 0.7 are obtained [32]. In this case, the criterion is met.
Confirmatory factor analysis (CFA) was carried out to evaluate the measurement model using the Analysis of Moment Structures (AMOS) software version 25, where a good fit was confirmed with a Chi2/df = 1.771 below the criterion level which indicates that it should be less than 5 [33] and all the indexes adhered to the criteria indicated by the theory RMSEA = 0.047, less than 0.05 according to Hair et al. [34]; IFI = 0.958; NFI = 0.908; CFI = 0.957, following Byrne [35] these values indicate a good fit due to the fact that they are close to 1.
The reliability of the scale was also verified using the composite reliability index (CRI) [36] and the index of variance extracted (IVE) [37]. In all the measures of the constructs, these indices were above the values according to the evaluation criteria, resulting in higher values of 0.7 for the CRI and 0.5 for the IVE. This confirmed the reliability of the constructs used in the instrument (see Table 1).
| Construct | Item | Standardized load | Average load | Alpha Cronbach | CRI | IVE |
|---|---|---|---|---|---|---|
| Commitment to learning (COA) | COA1 | 0.645 | 0.820 | 0.850 | 0.860 | 0.682 |
| COA3 | 0.923*** | |||||
| COA4 | 0.882*** | |||||
| Shared vision (VIC) | VIC1 | 0.869*** | 0.820 | 0.888 | 0.890 | 0.681 |
| VIC2 | 0.902 | |||||
| VIC3 | 0.806*** | |||||
| VIC5 | 0.710*** | |||||
| Open mindedness (MEA) | MEA1 | 0.725 | 0.800 | 0.875 | 0.880 | 0.650 |
| MEA3 | 0.860*** | |||||
| MEA4 | 0.897*** | |||||
| MEA5 | 0.727*** | |||||
| Affective commitment (CA) | CA1 | 0.872 | 0.770 | 0.850 | 0.860 | 0.602 |
| CA2 | 0.842*** | |||||
| CA3 | 0.722*** | |||||
| CA6 | 0.647*** | |||||
| Continuance commitment (CC) | CC3 | 0.660 | 0.780 | 0.810 | 0.830 | 0.626 |
| CC4 | 0.947*** | |||||
| CC5 | 0.739*** | |||||
| Normative commitment (CON) | CON1 | 0.867 | 0.770 | 0.812 | 0.820 | 0.601 |
| CON2 | 0.797*** | |||||
| CON3 | 0.646*** | |||||
| Products and services (PS) | PS1 | 0.839*** | 0.850 | 0.843 | 0.840 | 0.730 |
| PS2 | 0.869 | |||||
| Process (PC) | PC3 | 0.830*** | 0.780 | 0.758 | 0.760 | 0.616 |
| PC4 | 0.737 | |||||
| Management systems (SG) | SG5 | 0.762*** | 0.830 | 0.865 | 0.870 | 0.688 |
| SG6 | 0.855*** | |||||
| SG7 | 0.867 | |||||
| Chi2/df = 1.771 (p = 0.000); RMSEA = 0.047; IFI = 0.958; CFI = 0.957; NFI = 0.908 | ||||||
Table 1.
p < 0.001.
Source: Authors (2023).
To check the convergent validity, it was verified that all the questions of the factors were significant and that the average is above 0.7 [38], which was fulfilled in all the items of the factors of the model because they presented values between 0.770 and 0.850, which suggests a good convergent validity [39]. See Table 1.
To check the discriminant validity, the Heterotrait-Monotrait Ratio of Correlations (HTMT) test was used, which is a real estimate of the correlation of two constructs. If it were perfect, values close to one mean a lack of discriminant validity [40]. The HTMT analysis performed in AMOS 25 indicates that there are no warnings or validity problems for the model used in this study (≤0.824) since the values are below the level (0.90) allowed in the theory [41]. See Table 2. In general, the result of the HTMT analysis is acceptable, which supports the discriminant validity between the variables.
| COA | VIC | MEA | CA | CC | CON | SG | PC | PS | |
|---|---|---|---|---|---|---|---|---|---|
| COA | 1 | ||||||||
| VIC | 0.647 | 1 | |||||||
| MEA | 0.523 | 0.579 | 1 | ||||||
| CA | 0.305 | 0.325 | 0.361 | 1 | |||||
| CC | 0.276 | 0.245 | 0.270 | 0.503 | 1 | ||||
| CON | 0.162 | 0.262 | 0.214 | 0.508 | 0.572 | 1 | |||
| SG | 0.360 | 0.364 | 0.296 | 0.194 | 0.197 | 0.176 | 1 | ||
| PC | 0.381 | 0.412 | 0.305 | 0.253 | 0.166 | 0.192 | 0.824 | 1 | |
| PS | 0.296 | 0.274 | 0.218 | 0.223 | 0.105 | 0.185 | 0.813 | 0.796 | 1 |
Table 2.
HTMT analysis discriminant validity.
Source: Authors (2023) according to the results of the HTMT criterion in AMOS.
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3. Results
After verifying the validity and reliability of the study variables and the measurement model, structural equation modeling was developed to test the hypotheses, using the AMOS statistics program version 25, with maximum likelihood estimation as the technique for testing the model. The model fit is satisfactory (Chi2/df = 2.245; RMSEA = 0.060; IFI = 0.926; CFI = 0.925; NFI = 0.874).
We proceeded with the analysis of the study hypotheses, finding that hypothesis 1 is accepted since the results show a path coefficient of 0.283 with a t-value = 4.124, which confirms that affective commitment influences OL in a positive and significant. Hypothesis 2 has a path coefficient of 0.165 with a t-value = 2.644, this confirms the acceptance of hypothesis 2 since continuance commitment influences OL in a positive and significant way. In hypothesis 3, the results indicate a path coefficient of 0.094 with a t-value = 1.437, this shows that there is a positive, but non-significant, relationship between normative commitment and OL, so this hypothesis is not accepted. In hypothesis 4, the results indicate a path coefficient of 0.462 with a t-value = 6.276, therefore, there is a positive and significant relationship between the OL and INN, so hypothesis 4 is accepted. See Table 3.
| Hypothesis | Path (t) | P | Results | |||
|---|---|---|---|---|---|---|
| H1 | Affective commitment | → | Organizational learning | 0.283 (4.124) | *** | Support |
| H2 | Continuance commitment | → | Organizational learning | 0.165 (2.644) | ** | Support |
| H3 | Normative commitment | → | Organizational learning | 0.094 (1.437) | 0.151 | Not supported |
| H4 | Organizational learning | → | Innovation | 0.462(6.276) | *** | Support |
| Model fit measures of the general model: Chi2/df =2.245 (p = 0.000); RMSEA = 0.060; IFI = 0.926; CFI = 0.925; NFI = 0.874. | ||||||
Table 3.
Results of structural analysis.
p < 0.01.
p < 0.001.
Source: Developed by the authors (2023).
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4. Conclusions
The most outstanding contribution that can be pointed out as conclusions is the fact of being able to know how the influence of OC on OL, measured separately in each of its dimensions, was evaluated in order to know which of them influences to a greater extent to promote the strategic orientation of learning within a sector with very particular characteristics such as agribusiness, In this sense, the affective commitment and continuance are the necessary antecedent to promote OL, which has relevant implications in management, since it is necessary to promote the development of a link between the employee and the organization derived from the employee feeling that he/she is treated fairly by his/her employer, and at the same time it will be necessary to encourage the employee to recognize that staying in the company gives him/her guarantees and benefits that are difficult to find in other organizations.
The normative type of commitment, which is determined by the moral obligation of the worker to remain in the company, does not have a significant influence on the processes of change necessary to bring about more innovation through learning. On the other hand, it is verified in the sample analyzed that OC generates the changes in routines necessary to develop higher levels of INN within agribusinesses.
For future lines of research, it is advisable to analyze more closely the behaviors that are generated in each type of commitment on the part of the worker in order to establish the most appropriate policies within the company that will lead to greater permanence and better levels of innovation. In other words, to move from evaluation to the generation of management elements that support the sector.
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Acknowledgments
We acknowledge the Autonomous University of Aguascalientes for the facilities and funding for the development of this research.
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