Over the last two decades, professionals and academics have redirected their work from organizations to the study of knowledge and results in relation to innovation. In addition, this field has become a multidisciplinary area of ​​knowledge in which scientific knowledge can be generated (Kamasak et al., 2016; Shafique, 2013). In this sense, creating, adopting or adapting innovations in the rural sector has become complex and must be combined locally through tacit and implicit knowledge and, on ther other hand, derived from specialization through explicit knowledge (Esparcia, 2014). For this reason, studies regarding both themes in the agricultural sector worldwide have been reflected in various scientific articles highlighting technical characteristics (Ho et al., 2019; Totin et al., 2020), such as the knowledge and study of soils (Chenu et al., 2019; Techen et al., 2020), pest management (Abtew et al., 2016; Khan and Damalas, 2015) and various economic tools, strategies and models (Baloch and Thapa, 2016; Djanibekov et al., 2015; Dolinska and d’Aquino, 2016).

In Mexico, agricultural producers have also been studied, both in indigenous communities and in areas that have marked the history of land ownership in the country. The relevance tehreof is that these areas have a great cultural richness and important traditions, such as Chiapas, Oaxaca, Michoacán and Jalisco. Studies on supply and new crop varieties (Badstue et al., 2007; Bellon and Hellin, 2011; Honorato-Salazar and Sadhukhan, 2020), viability in agricultural production and utilization (Castillo et al., 2014; Cortez-Arriola et al., 2015), the study of soils (Sánchez-Osorio et al., 2017), and climatic conditions and ecological factors (Allende et al., 2016; Campos et al., 2014) have been performed.

Particular to northwestern Mexico, in the Yaqui Valley (YV), diverse researches have been conducted (Meza et al., 2004) regarding the management of water and soil chemical components, as well as bacteria in crops, (Villa-Rodríguez et al., 2019; Meza-Montenegro et al., 2012) irrigation and fertilizers (Millar et al., 2018), remote sensing of crops (Lobell et al., 2003; Méndez-Barroso et al., 2008), and vulnerability to global warming (Lares-Orozco et al., 2016; Luers et al., 2003).

A literature review revealed little research in this sector with an organizational focus, specifically regarding the generation of empirical studies related to knowledge management (KM) and innovation in the YV, a sector where it is possible to generate contributions to knowledge. For this reason, this study seeks to determine the relationship between KM and innovation among the YV agricultural organizations.

The internal validity of the instrument was determined using the database through tests for normality (asymmetry and kurtosis), and the consistency of the internal factors of the instrument was tested with an exploratory factor analysis (tables 5 and 6).

Table 5. Table 5. Results of factor analysis: KMO-Bartlett-Chi-variance Source: own work

Table 6. Table 6. Matrix and rotated component model Source: own work

Table 5 presents the KMO (Kaiser, Meyer and Olkin) test results to search for correlations between the variables. The KMO test indicates a correlation when the result is close to 1. In this case, 0.833 is remarkable and can be deemed a partial correlation of the variables. The results of Bartlett’s sphericity test are presented in the same table 5. These results indicate significance because the value is less than 0.05, meaning that the null hypothesis is rejected and factorial analysis can be applied.

Another criterion approved in the internal validation is shown, as with the principal components (PC) extraction method, there is clarity in the extraction of the internal factors of the instrument when selecting those items that are greater than 0.333 and are not grouped into more than two factors. In the end, the three main components explain 64% of the total variance of the variables.

As observed, in the end, the model consists of 18 items grouped into two factors, all above 0.333 and loading clearly onto one factor. The grouping was performed through the Varimax rotation method and the CP extraction method. Therefore, the previous structure is the one validating that the items of the instrument are highly correlated with each other. Once the factor analysis was performed, it was proposed to review the reliability of the items covering the three variables of the instrument (table 7). Due to these facts, the database was applied again, and the items were subjected to the Cronbach’s alpha test.

Table 7. Table 7. Reliability of variables Source: own work

Once the database was analyzed in the system, the corresponding statistical tests were performed. In the first instance, it is crucial to report the results regarding the hypotheses. The hypotheses proposed in the theoretical section of the project are accepted:

H1. KM and innovation are positively and significantly related.

H2. Greater KM generates more innovation.

To obtain the above results, a correlation test was performed (table 8). From this test, it is evident that KM and innovation have a correlation percentage greater than 44%, which indicates a significant relation between the variables at a significance level of 0.01, being greater than zero and positive.

Table 8. Table 8. Correlation between KM and INNO Source: own work Note:

Significant at .01 (2 tailed).

It should be noted that table 8 demonstrates an effective relationship, and this is considered acceptable within the parameters noted by Pearson, as the percentage presented explains 20% of the shared variance among its elements. Therefore, there are elements to consider within the agricultural organizations that underpin this relationship. For example, the items KM1 and KM2, which quantify whether the producers have activities for the generation and acquisition of knowledge, present an average value above 3.8, with which the data confirm a level of response according to the activities of generation and acquisition that relates to item INNO19 that, in turn, shows the same tendency to generate changes in the processes and products as time passes.

According to this last statement, in the YV the activities that generate and provide knowledge, and favor innovation are mainly they training by third parties, i.e., an empirical knowledge already proven as mentioned by the interviewee 4 and 7, respectively; “the little, medium or regular knowledge I acquired in the development bank, and whether or not you want in the field, where you become a professional, this does not happen in school or books” (I4); “we have been involved in several events, in various training and knowledge transmission forums by the Secretariat of Agriculture, Livestock, Hydraulic Resources, Fishing (SAGARHPA) Trusts Instituted in Relation to Agriculture (FIRA) and Rural Finance” (I7). Consequently, the relationship between the variables shows an influence that the KM generates on innovation; it is observed in detail with a linear regression (table 9).

Table 9. Table 9. Linear regression between KM and INNO Source: own work Note:

R 2 = .20 (N = 95, p <.001). CI = confidence interval for B.

In particular, the results shown in table 9 above indicate that KM predicts 20% of innovation in YV agricultural organizations; therefore, it is estimated that the remaining 80% is dispersed in other variables not considered in this study. This result stresses the importance of sharing and transferring knowledge so that innovation in YV may increase in terms of new crop varieties and new techniques offered by the talks promoted by governmental agencies.

In addition, what prevails is getting to know new technologies in these talks and conferences, in some cases to acquire and modify them: “there are very modern four-row tractors and we made six-furrow seeders, then it is faster” (I3); and in some aspects related to product packaging, innovations are also highlighted to reduce costs: “we received that machine, but we adapted it to what we wanted, is currently a band that is totally different with which we could decrease a time of 80% to what normally makes a normal band” (I7). The modification and relation to the processes are highly oriented to the production process in which the INNO13 item is highlighted. It presents an average value higher than 3.8, which creates a trend in the agricultural organizations in the Yaqui Valley. In other words, there are new ways to improve your production flexibility.

Therefore, it is important to consider the fundamental aspects that generate the results of the knowledge management dimensions: creation and acquisition, transfer and application, which are related to the innovation dimensions: products, processes and services, technology and development, which can be interpreted as follows:

The creation and acquisition of knowledge in the Yaqui Valley is largely due to the training and practice of the know-how, which is induced by a transfer of knowledge in various areas as mentioned by interviewees 4, 5 and 6: “with the example, the daily practice and the mechanization in the field” (I5); “I studied, that is why I prepared myself, I don’t want to be boastful but everything we do we must be prepared” (I6); “I acquired the few, medium or regular skills in development banking, and in the daily basis” (I4); “With technical advice, there were programs related to technical advice that at the time they were applied by the rural bank and generated the technical knowledge for the agriculture management” (I5). The training by third parties is then highlighted as an essential factor in the explanatory model of the relationship between both variables.

Products, processes and services have been innovated through the acquisition of technology. In this case, crop varieties, new planting techniques and changes in machinery and process development were referred to by the interviewees 1, 2 and 6: “there are several products that are derived from this. First is the plant, where we are working on extraction of essential amino acids for insect repellents”, “in the mechanical part or harvest there is not a single company or person in the world that harvests mechanically as we do” (I1); “the changes were related to the addition of foliar fertilizer” (I2); “I have diversified to other types of crops, such as corn, safflower, sesame, beans. Looking for the optimization of both financial and machinery resources, because if we are going to plant in large areas we need many elements for large areas” (I6).

Consequently, with the two previous aspects, factors directly involved in that relationship are identified: training by third parties, transference and adaptation through informal talks between the producers. “There are producers who know a lot, who know much more than myself, who I have a lot of respect for, and whom I have learned” (I4); the family itself, creator of knowledge: “when my father started to prepare the land for some crop I was always attentive to see how he did it, then you learn and improve it” (I2); in addition, the family is confirmed as a source of ideas that are transmitted by generations “my father is from the culture of work and effort that he inherited them from his grandfather, which is his dad, and then he would be my grandfather; hence, I have had patterns that I have copied them, this way we transmit the knowledge” (I4).

All the foregoing, after a deep analysis, provides a broader picture on how knowledge is managed in the YV and, in turn, provides elements that transform into innovative ideas that relate to and impact the regional economy and directly interfere in a constant change reflected in production techniques. This is an essential part of the process innovation. Similarly, the improvement in business methods leads to the generation of additional services by encouraging the introduction of new markets and the generation of new products that are presented through the explanatory model (figure 3).

Figure 3. Figure 3. Analysis of the relationship between KM and Innovation in the VY Source: own work

According to the main findings presented herein, it is necessary to detail the most salient discussions from an empirical perspective. To do so, the main elements of the variables researched in other agricultural and rural areas of the world are presented using different methodologies.

The generation of knowledge through multiple sources of information among the small agricultural producers of the districts of Kenya is what Munyua and Stilwell (2010) emphasize in their quantitative and qualitative study. Using a sample of 224 producers in the districts making up the local agricultural system and several meetings through focus groups, they determined that the labor links with the other producers are weak. However, the groups were effective in promoting and expanding new technologies, innovation and improved cultivation methods. This situation is similar to what is occurring now in the YV in the sense that agricultural producers transfer ideas through informal talks and, therefore, there is an accurate communication of information to generate their own knowledge. From the same perspective, Rees et al. (2000) determined that the main sources of knowledge that small producers have in five of the seven districts of Kenya are local ones, such as neighbors, families, markets, and community-based organizations. Similar to the above, in the YV the family plays a fundamental role in the management of information to generate knowledge, since the YV has given all authority to the collective ejido producers (composed by families) as their only means to increase the standard of living of the peasants and their families belonging to these working groups (Cárdenas-García, 2016).

In the case of innovation in agriculture, now it is pertinent to discuss the work by Dolinska and d’Aquino (2016) carried out in agricultural cooperatives in France, who performed a qualitative study of agricultural cooperatives in France to examine the role of communities (CoPs) of farmers according to the innovation process. Their findings are interesting because they demonstrate that farmers belonging to these communities are better trained for innovation than those who work individually with the expert’s support. In YV occurs the opposite: farmers are individualistic and do not use groups to strengthen their innovation processes but, rather, as a strategy to link their membership to a union or society through financing strategies or government resources.

In the same way, it is necessary to share knowledge about the innovation process among farmers, the scope of doing a systematized work of innovation and its benefits. According to this, in YV happens something different, institutions specializing in research and improvements in product and technical processes are trying to work with producers to give them new practices, as the interviewee 6 considers: “there is innovation in crop diversity, all people are given training, talks about marketing , costs…” (I6). However, they are, themselves, the ones creating barriers to the entry of that new knowledge in favor of innovation, as told by the interviewee 4: “there are producers who do not approach because they say to me no one will tell me what I have to do” (I4).

To continue the discussion of the findings, it is pertinent to reevaluate the empirical evidence for the relationship of KM and innovation. On this regard, Dos Santos-Ferreira and Santos (2014) confirm this fact through their study in Portugal, in which they determine the influence of KM on innovation practices; the knowledge creation dimension is the most important factor contributing to innovation in these organizations. In this sense, as in YV and for agricultural producers, knowledge creation is a fundamental element, and statistical data above average (3.8) are relatively consistent with this research.

In the same vein, Moos et al. (2013) present a research on manufacturing companies; they determine an optimal relation between innovation and technological knowledge and emphasize the strategy of applying that knowledge as a determinant and important element for the success in innovation. Regarding the organizations in YV also prove to be congruent with this fact, as the practices and management of the new technology are elements favoring innovation because the organizations agree that they are the first to introduce new methods and technologies in YV.

Regarding the final contributions, it is concluded that the research objective is satisfactorily attained. On one hand, the correlation between the variables of the study is positive and significant. So it can be said that in YV, agricultural producers in the process of KM (creation, acquisition and transfer of knowledge) will also be considered innovative in terms of any innovation type.

On the other hand, the influence of KM on the innovation was acceptable, as the activities of generation of knowledge are related to the activities of innovation, although not strongly. Nevertheless, a correlation exists and can be considered a preliminary contribution of this study. With these results, it is necessary to underline the contribution of this study to the theory, taking into account the assumptions used to explain that KM influences innovation. In this sense, it is stated that, at least in YV, the influence is positive and significant for the agricultural producers.

Another important aspect to consider is the empirical contribution of this work to future studies, as this work can serve as a reference in organizational research for the agricultural sector, and particularly in YV. For this reason, we must underline the great gap existing so far and the new challenges that require working empirically with studies related to the variables of organizational analysis in a sector that usually is characterized by technical products.

It is extremely important to mention that YV is an unexplored area in the organizational sphere. The agricultural producer organizations found in this territory are covered by different lines of research mentioned in the field work, including the family, sustainability, climatic changes, governmental policies, modernity and tradition, among others.

As far as the family is concerned, it was observed that family is the first source to get information for the construction of knowledge and is involved in the societies created with strategic purposes. This way, most of the producers legally establish their farming societies with family members to obtain governmental funding and support.

It is necessary to take into account different possible methods for strengthening the present study. First, we can study the YV with the same variables but using different instruments or harvesting techniques. It would be interesting to create focus groups to debate the ideas and questions that may arise from the results and contrast them with the results from researches conducted at a global extent, thus obtaining benefits for the productive subjects involved in this sector.

On the other hand, it is necessary to include a greater number of participants to obtain opinions and data that provide us with a closer look at the organizational reality in which the agricultural organizations of the YV operate. It is possible that through academic and governmental partnering, some work could be performed to achieve the goal of covering the majority of the researched sector.

Regarding future researches, it is important to include a study to explore the family topic. The succession of agricultural families in YV is a topic that will allow diverse perspectives and will complement this research, especially regarding the values, customs and traditions attached to the cultural variable. This claim is supported by the fact that more than 80% of the land planted in the agricultural sector belongs to common land sectors, whose legislation is mainly made up of families.