Introduction
Social entrepreneurship (SE) is a dynamic social phenomenon that holds significant importance for society. It encompasses the development of innovative enterprises or the implementation of strategies in existing ones, all with the objective of improving the quality of life for vulnerable populations (Mair & Martí, 2006; Peredo & McLean, 2006). Extensive global literature on SE has examined it across three major levels, which are underpinned by various theories (Saebi et al., 2019) (see Table 1).
Table 1
Units of analysis within social entrepreneurship
|
Unit of analysis |
Approach |
Characteristics |
|
Individual (Behavioral Theories) |
Behavior |
Considering and evaluating the personality and background of the entrepreneur. The individual prioritizes the social over the financial. |
|
Process |
All the steps that a social entrepreneur takes to start his company; includes detection and identification of opportunities. |
|
|
Institution (Institutional Theory) |
Institutionality |
Little or no action on the part of the public sectors to solve social problems, which are a motivating situation for the emergence of organizations with social purposes. |
|
Organization/ Enterprise (Multiple theories) |
It is a process that takes place within the organizations: |
|
|
Non-lucrative |
Idealize that social entrepreneurship only belongs to organizations that do not seek to make a profit, only social goals. |
|
|
Lucrative |
Social entrepreneurship occurs in the for-profit sector since the concept is described as a set of nuances and elements that provide innovative mechanisms to organizations by promoting the creation of social enterprises. |
|
Note: Author´s own elaboration based on literature review
At the organizational level, there is a debate among the scientific community that divides the literature into two main approaches that consider the SE as a process located within organizations. The first indicates that SE is exclusive to completely social organizations, without the search for monetary returns, the example being non-profit organizations (Dees, 2001; Peredo & McLean, 2006). The second, exposes that SE can be the creation of organizations and business models, which contain an economic perspective and are known as social enterprises (Peris-Ortiz et al., 2016; Urbano et al., 2010). It is under these approaches, that the literature has grown in nations with consolidated economies (Shin & Park, 2019; Son et al., 2018; Urbano et al., 2010), detecting SE as a process with a direct relationship that affects the creation of social value; the latter understood as the perception of the organization that the actions it performs generate a benefit to the community it serves (Di Domenico et al., 2010; Singh, 2016).
However, the situation in emerging countries is marked by significant uncertainty and challenges stemming from the limited recognition of the social enterprise model. This lack of recognition hampers the growth and potential impact of social enterprises in these regions, which makes them particularly appealing due to their ability to operate with constrained resources (Klarin and Suseno, 2023).
For example, Mexico has a large gap in social enterprises, due to the lack of recognition of this business model, as there is no definition, categorization, or localization from the governmental sector in the country. In her investigation, Conde (2015, 2016) makes it clear that there are up to 14 types of organizations in the Mexican scenario that meet the characteristics of social enterprises, according to the EMES1 framework.
The significance of social entrepreneurship (SE) in Mexico lies in its potential to contribute to the development and growth of regions characterized by high levels of inequality among their populations (Lobato-Calleros et al., 2016). However, studies conducted in the Mexican context have identified knowledge gaps that need to be addressed. One such gap pertains to the evaluation of SE as a process within Mexican social enterprises, wherein social value is created through dimensions such as innovativeness, risk management, proactivity, and socialness (Dwivedi & Weerawardena, 2018; Shin & Park, 2019; Syrjä et al., 2019).
Therefore, the present research aims to determine the effect of social entrepreneurship on the creation of social value within the territorial area of the Huasteca Tamaulipeca. This region, located in the northeast of Mexico, was selected due to its distinctive characteristics, which will be discussed further below
This article is structured in five sections, which begin with this introduction. The second section presents the main theory on social entrepreneurship, as well as the dimensions that integrate the construct and its relationship with the creation of social value. The third section describes the methodology used, detailing the selection of the unit of analysis and the steps followed for the statistical analysis. The fourth section provides a description of the results found. The last section reports the conclusions and discussions.
1. Theoretical framework
1.1. Social entrepreneurship as a process within a company.
When examining SE as a process, it is crucial to begin with its definition, which can be described as a collection of elements inherent to the organization’s operations, aiming to achieve a balance between economic and social aspects. It is within this framework that numerous authors (Mair & Martí, 2006; Palacios-Marqués et al., 2019; Peris-Ortiz et al., 2016) argue that SE can also occur within companies that adapt their business strategies to incorporate social elements if it enables them to generate greater value.
These authors emphasize that social entrepreneurship extends beyond the boundaries of dedicated social enterprises, recognizing that traditional businesses can engage in SE by integrating social considerations into their operations. This approach acknowledges the potential for generating both economic and social benefits, demonstrating that SE is not limited to a specific organizational form but rather encompasses a broad spectrum of ventures and initiatives.
Palacios-Marqués et al. (2019) indicates that employing a social nomenclature should not be a reason for exclusion so that an organization can generate financial performance and with a purely internal perspective. It is in this way that social entrepreneurship is defined as the series of actions that make up a process, capable of modifying any business, by implementing activities that aim to increase the economic and social value that an organization offers to society, allowing them to obtain sustainable competitive advantages over their competition (Liu et al., 2015; Palacios-Marqués et al., 2019; Shin & Park, 2019).
The SE construct has three dimensions that are persistent among the different research, being innovativeness, risk management and proactivity (Palacios-Marqués et al., 2019; Peris-Ortiz et al., 2016; Son et al., 2018), which are based on the classic work on entrepreneurial orientation by Covin and Slevin (1991), which described the way in which a company makes decisions by behaving in different ways.
However, the most updated and used proposal corresponds to Kraus et al. (2017) who propose that socialness explains how the organization that is in the social sphere behaves when it aims to generate a direct or indirect benefit for society, being a particular characteristic of the social enterprise. Subsequently, Halberstadt et al. (2020) states that its purpose is to bring together all opportunities and activities that contain an essential essence that allows the company to generate a positive impact. Such is the case that the dimension of socialness has also been recognized as social passion, but from the individual perspective of the entrepreneur, reflecting the tendency to include social elements in their behavior, exposing that including a social part allows differentiating between commercial and social ventures (Satar & Natasha, 2019). Due to the above arguments, for the present study I considered innovativeness, risk management, proactivity, and socialness as dimensions of SE, whose conceptual definitions are exposed in Table 2.
Table 2
Definitions of the SE dimensions
|
Dimension |
Definition |
|
Innovativeness |
Creation and development of innovative ideas, which aim to meet the needs that society requires, allowing to offer cutting-edge solutions to solve problems. |
|
Risk management |
Ability to identify, manage or accept the risk that exists because of the activities carried out in the organization, including plans |
|
Proactivity |
Company’s initiative to anticipate the future, foreseeing any type of situation, as well as managing the direction in which it is headed. |
|
Socialness |
Company’s ability to dedicate itself to creating social value, being the guide to achieve its goals and objectives, giving the economic aspect the same priority as the social element. |
Note: Author´s own elaboration based on the literature review.
1.2. Creation of social value
Social value is considered the most important objective of any social entrepreneurship, since it describes any benefit that emerges from this process, originating the social change observed in the creation of products or the development of services, offering direct and indirect benefits to the community (Caldwell et al., 2017; Felício et al., 2013).
Dees (2001) associates it directly with social entrepreneurs who generate value towards employees and suppliers, while for Tsirogianni and Gaskell (2011) social value, from the individual aspect and spiritual belief of the person, are the values that guide his or her life. In a business environment, Dohrmann et al. (2015) represent it as a tangible good capable of generating monetary returns. The above is explained by the difficulty in differentiating between social value and social value creation; in essence they are quite identical but offer a different operationalization and conceptualization. The former represents the direct result or benefit explicitly delivered by the organization to a beneficiary, while the latter is the business view that the organization, through its activities, is creating benefits for society (Dohrmann et al., 2015; Hlady-Rispal & Servantie, 2018; Singh, 2016).
In this aspect, the creation of social value originates when the social enterprise or hybrid organization, conducts highly social processes, which society perceives as positive, achieving a differentiator against other companies (Caldwell et al., 2017). It is under this idea that a company of any kind offers a social value and an economic value, which varies according to the ideals of each organization (Dohrmann et al., 2015).
Therefore, I define social value creation as all the internal or external mechanisms that the organization performs to manage the way it creates and delivers social value to society, without considering the impact emanating from its activities (Di Domenico et al., 2010; Hlady-Rispal & Servantie, 2018; Singh, 2016).
1.3. Relation between SE dimensions and social value creation
Son et. al (2018) and Syrjä et al. (2019) using mixed methods in the countries of South Korea and Finland, have found results that allow concluding that innovation is an implicit part of social enterprise. In turn, Liu et al. (2015) provides evidence that allows defining that innovativeness boosts the competitiveness of the social enterprise, which will result in greater social value creation, using a comparative study of companies located in United Kingdom and Japan. To date there are no studies where there are negative results in the relationship, the closest is the research by Núñez-Pomar et al. (2020), in which they explain that innovation alone does not provide an indication that the company improves its social value but requires risk management and proactivity. With the arguments presented, the hypothesis proposal is made.
H1a: Innovativeness has a positive effect on social value creation.
Continuing with the relation of risk management and social value creation, empirical studies by Núñez-Pomar et al. (2020), Shin and Park (2019), Son et. al. (2018), Syrjä et al. (2019) and Weerawardena et. al (2019), using qualitative as well as quantitative approaches, have found positive and significant relations, in different units of analysis such as social enterprises and nonprofit organizations.
In this way, Son et. al (2018) and Shin and Park (2019) evaluating social enterprises in South Korea determine through questions related to management decision making how the implementation of new tools and systems, will cause the performance to be improved, regardless of the risk that is propitiated from it, generating greater social. Núñez-Pomar et al. (2020), in Spain, state that risk management has the greatest influence on social performance, through a mixed analysis in organizations with social purposes. On the other hand, Alarifi et al. (2019), indicate that risk management has no direct effect or relationship on the performance of social enterprises, explaining that due to the combination that this type of company prioritizes social benefit and that its resources tend to be limited.
H1b: Risk management has a positive effect on social value creation.
Regarding proactivity, Weerawardena and Mort (2006) originate as one of the first empirical works that find a positive relation between proactivity and the creation of social value, detecting that there is a clear awareness of the implementation of strategic plans for the growth of the social organization, reaching the point of achieving competitive advantages. Based on this, studies such as Kraus et al. (2017) and Peris Ortiz et al. (2016), being proposals for measuring the SE construct, implement proactivity as a key element to create social value. The first of them, carries out a delphi study trough a expert validation and the second it´s related with medium size Spanish companies. Weerawardena et al. (2019) also conclude that strategic plans are an essential part of a SE process. With the described arguments, the hypothesis is posed:
H1c: Proactivity has a positive effect on social value creation.
Furthermore, the relation between socialness and social value creation has found positive validation in the study by Halberstadt et al. (2020) with industrial companies in Austria and Northern Macedonia, distinguishing between 78 start-ups and 230 established companies. That study follows the scales and proposals of Kraus et al. (2017). Gali et al. (2020) find that there is a high correlation between socialness and social performance, i.e., with social value creation, indicating that its use should be taken with caution. Based on the above, the hypothesis proposal is made:
H1d: Socialness has a positive effect on social value creation.
Based on the proposed hypotheses, Figure 1 depicts the model that graphically explains the relations that were proposed; in this model, the relation between innovativeness, risk management, proactivity, and socialness, which make up social entrepreneurship, with the creation of social value, is illustrated. Therefore, once the hypotheses by dimension have been exposed, the hypothesis corresponding to the global research model is presented:
H1 Social entrepreneurship has a positive effect relation on social value creation.
Figure 1
Research model proposal Note: Author´s own elaboration based on literature review
2. Methodology
2.1 Unit of analysis
For the present study, the characterization of social enterprise was carried out, derived from the fact that in Mexico there is no legal figure or database that groups them in a coherent manner (Conde, 2015, 2016; Rubalcava & Zerón, 2020). Conde (2015) and (2016) make contributions to classify social enterprises, through a point system, following the criteria of the EMES approach, which are based on the economic, social and governance dimensions of an enterprise (See Table 3). Their classification describes the existence of multiple forms of social enterprises, given the lack of a legal framework to support them. For this research, the unit of analysis are enterprises registered in the National Statistical Directory of Economic Units (DENUE), specifically micro, small, and medium-sized enterprises.
Table 3
EMES Criteria
|
Dimension |
Criteria |
|
Social |
|
|
Economic |
|
|
Governance |
|
Note: Authors’ own elaboration based on literature review.
The Huasteca Tamaulipeca, is a region of Mexico that is integrated by 14 municipal entities of the state of Tamaulipas. It is a territory that contains economic, social and cultural differences among its inhabitants, given that throughout its territorial extension different environments persist, from an environment located in the mountainous plains of the Tamaulipas highlands (Bustamante, Jaumave, Miquihuana, Palmillas and Tula, where the last three belong to the Huasteca) to a segment of municipalities with a coastline (Soto La Marina, Aldama, Altamira and Ciudad Madero), In addition to integrating one of the most important industrial and tourist areas of Tamaulipas (Altamira, Ciudad Madero and Tampico, where all three are located in the Huasteca), not to mention the rich biodiversity offered by the “El Cielo Biosphere Reserve” (a territory shared by the municipalities of Gomez Farias, Llera, Jaumave and Ocampo, all of which, except Jaumave, are located in the Huasteca Tamaulipeca). The territorial extension is approximately 26880.72 that represents 33.49% of the state territory. Figure 2 explains the location.
Figure 2
Location and layout of the Huasteca Tamaulipeca
Note: Authors’ own elaboration based on Pereda and Padilla (2016).
This territory brings together a total of 42,169 economic units registered in the DENUE (INEGI, 2020), which are part of different primary, secondary and tertiary economic activities, including all types of associations related to the care of people, which with their actions promote the growth of the area. However, when analyzing each municipality, social problems that affect its inhabitants are observed, given that in almost all of them half of the population is affected by poverty or social deprivation, such as access to public and health services (CONEVAL, 2020).
The importance of situating the research in the Huasteca Tamaulipeca is related to the call made by Steiner et al. (2022), who mention the importance of starting to investigate, integrate, and understand the contexts in which social enterprises are located, in order to understand how entrepreneurial behaviors are shaped, which will enable the generation of more effective ideas and strategies to foster entrepreneurial development in the area.
Furthermore, the companies in the region fall into the category of “rural social enterprises” as described by Musinguzi et al. (2023). These enterprises are situated in areas where rural activities such as agriculture, livestock, and nature tourism are predominant. It is in this way that the territory is given the relevance to be evaluated in terms of social entrepreneurship.
2.2. Instrument and data collection
The instrument was structured with two sections. The first one objectively identifies social enterprises by evaluating their characteristics, following the EMES criteria and the operationalization of Conde (2015) through a point system that allows contextualizing how social an organization is based on dichotomous answers, where denial weighs zero units and the positive answer assigns 3 points, for a total of 15 questions. Thus, for a company to be called social, it must exceed a score of 30 points. The second section consisted of 36 items on a 5-point Likert scale, with eight items for innovativeness, seven for risk management, seven for proactivity, five for socialness and nine for social value creation, which come from various instruments analyzed in the literature review (Dwivedi & Weerawardena, 2018; Halberstadt et al., 2020; Shin & Park, 2019; Weerawardena et al., 2019).
The information was collected from November to December of 2022, by sending the digital instrument to 361 economic units that were registered in the DENUE and had an e-mail address, following the classic formula for determining the ideal statistical sample (Münch & Ángeles, 2007). The sample was also validated at the level of inferential statistics using the G*Power tool, which allows the researcher to determine the minimum number of observations to generate a result with a high level of reliability and consistency, which considers the behavior of inferential statistics, providing better management for understanding the sample (Kang, 2021). In this way, 129 units are obtained as the ideal value for the results obtained to possess sufficient power to validate the research.
In this sense, a quota sampling is implemented to obtain the maximum proportional representation for each municipality that integrates the territory, based on the number of companies located per municipality with respect to the population. Finally, the sample collected was 155 surveys out of 361 sent (41.82%).
2.3. Statistical analysis.
The selected procedure was the use of partial least squares structural equations (PLS-SEM), because although the study has an exploratory cut, it is necessary to apply robust quantitative techniques to generate validations in contexts other than those previously analyzed in the literature. The first phase was the prior analysis of the data, by filtering the information collected (N = 155), which was carried out with the evaluation of normality, review of atypical values and outliers, eliminating seven questionnaires (N = 148), through their respective analysis in the PLSv3 software. Following the recommendation of Hair et al. (2019), which indicates that although PLS-SEM does not require normality in the data, it is essential to verify that skewness and kurtosis are not excessive, since this can affect the significance of each parameter. In the second phase, an analysis of the descriptive results was carried out, showing the classification of normal and social enterprises with their respective figures, obtaining a total of 95 social enterprises (64.19%) and 53 normal enterprises (35.81%). As the last step, the model was tested both in first order to review each individual hypothesis, and in second order to validate the global hypothesis; this is since both types of models are used in the SE without identifying which is the best model (Dwivedi & Weerawardena, 2018; Felício et al., 2013; Saebi et al., 2019; Son et al., 2018).
3. Results
3.1. First-order model
Regarding the verification of the first-order model, the algorithm called PLS consistent (PLSc) was used, which is used in common factor models, with greater robustness and eliminates any type of conjecture of this type of model compared to models based on covariance (CB-SEM). In this sense, the three-step method is used to validate the model presented (Dijkstra & Henseler, 2015; Rigdon et al., 2017).
The first step was the assessment of the global model by means of the SRMR, d_UDLS and d_g fit indicators, which are the most accepted. However, caution should be maintained with their reporting, since PLS is under continuous development and further validation research is required (Henseler et al., 2016). In the SRMR indicator, values close to 0 represent perfect fits, whereby values less than 0.08 are accepted. In addition, tests are performed using the Bootstrapping technique, adding 10,000 subsamples to validate confidence intervals, which were satisfactorily located at 95 and 99% (see Table 4).
The second step was the validation of the measurement model, evaluating the indicators of individual reliability, composite reliability, convergent validity, and discriminant validity for each construct. For this, the factor loadings of the items were evaluated, assessing that the values were greater than 0.707 to be taken as valid (Hair, et al., 2017). Therefore, items IN4, IN5, IN6, IN7 and IN8 of innovativeness; items MR1, MR2 and MR7 of risk management; items PR3, PR4, PR5 and PR6 of proactivity; items CVS1, CVS4. CSV5, CSV7 and CSV8 of social value creation, and item SO4 of socialness. (See Table 4). Similarly, it is indicated that items IN3 with factor loadings of 0.622, MR5 and MR6 with loadings of 0.592 and 0.638, were left in their respective constructs, even though their values are below the suggested value of 0.707 (see Table 4); while the proactivity construct groups five items whose loadings are lower than this value. This, because their addition considerably improves the average variance extracted (AVE) as well as the reliability coefficients and a better explanatory power at a theoretical level (Fornell & Larcker, 1981; Hair, et al., 2017).
Subsequently, the reliability of the construct was reviewed, through Cronbach’s Alpha (α) and Composite Reliability Coefficient (ρc) and rho_A. These coefficients must exceed the threshold of 0.7 to be accepted, which happens satisfactorily (Dijkstra & Henseler, 2015) (see Table 4). In addition, convergent validity should be checked, using the average variance extracted (AVE), which is intended to corroborate that the observable variables measure the construct to which they belong. This value must be equal to or greater than 0.5 (Fornell & Larcker, 1981). At this point, the bootstrapping technique (one-tailed test and 10,000 subsamples) is used again to corroborate the confidence intervals of the described coefficients (see Table 4).
Table 4 shows that the proactivity construct has an AVE of 0.390, which does not exceed the thresholds established by Hair et al. (2019) and does not meet convergent validity, so it will not be considered in the model. Likewise, the calculation of discriminant validity was performed, which verifies that the variables are different from each other, preventing the existence of similar measurements. The techniques used were the classic criterion of Fornell/Larcker and the Heterotrait Monotrait Ratio (HTMT) criterion (Fornell & Larcker, 1981; Henseler et al., 2015; Rigdon et al., 2017), which were satisfactorily fulfilled as shown in Table 5.
Table 4
Adjustment and measurement model
|
Adjustment of the model |
|||||||
|
Indicator |
Obtained value |
Confidence interval |
|||||
|
95% |
99% |
||||||
|
SRMR |
0.066 |
0.069 |
0.069 |
||||
|
d_UDLS |
0.666 |
0.729 |
0.729 |
||||
|
d_g |
0.294 |
.389 |
.389 |
||||
|
Validation of the measurement model (Reliability of constructs) |
|||||||
|
Construct |
Ítem Definition |
F. Loading |
Alpha |
rho_A |
CR |
AVE |
|
|
Innovativeness |
IN1. New ways to deliver benefits to society. |
0.734 |
0.763 (0.677 – 0.823) |
0.771 (0.673 – 0.821) |
0.762 (0.675 – 0.821) |
0.519 (0.412 – 0.602) |
|
|
IN2. Supports ideas for new products or services. |
0.794 |
||||||
|
IN3. Creative ways to improve services and products. |
0.622 |
||||||
|
Risk Management |
MR3. Strategies established based on the changes. |
0.794 |
0.822 (0.768 – 0.864) |
0.834 (0.761– 0.875) |
0.816 (0.750 – 0.862) |
0.531 (0.437 – 0.610) |
|
|
MR4. Takes precautions when using the resources. |
0.857 |
||||||
|
MR5. Always considers the risks of a new project. |
0.592 |
||||||
|
MR6. Always considers the benefits of a new project. |
0.638 |
||||||
|
Proactivity |
PR1. Constantly plans the projects it will undertake. |
0.638 |
0.762 (0.703 – 0.807) |
0.763 (0.685 – 0.804) |
0.760 (0.703 – 0.811) |
0.390 (0.320 – 0.455) |
|
|
PR2. Considers it important to be prepared. |
0.674 |
||||||
|
PR5. Introduces new mechanisms to position better. |
0.638 |
||||||
|
PR6. Monitors all external forces that may affect it. |
0.544 |
||||||
|
PR7. It has a high level of impact on the market. |
0.615 |
||||||
|
Socialness |
SO1. Social objectives are more important than generating profits. |
0.853 |
0.867 (0.819 – 0.902) |
0.874 (0.822 – 0.903) |
0.867 (0.819 – 0.901) |
0.622 (0.532 – 0.693) |
|
|
SO2. Our organization places a strong focus on partnerships with other organizations and/or governments. |
0.725 |
||||||
|
SO3. Ambitious targets with respect to sustainability. |
0.712 |
||||||
|
SO5. Realistic targets with respect to delivering benefits to society. |
0.854 |
||||||
|
Social Value Creation |
CVS2. Offering more products and services to society that solve a social problem. |
0.739 |
0.830 (0.773 – 0.872) |
0.832 (0.722– 0.872) |
0.830 (0.772 – 0.873) |
0.619 (0.531 – 0.695) |
|
|
CVS3. Increased the number of people the company benefits |
0.785 |
||||||
|
CVS6. The services and products have an adequate level of quality for society. |
0.834 |
||||||
Note: Confidence intervals based on one-tailed test, with bootstrapping of 10000 subsamples at 5% significance. Authors’ own elaboration based on results obtained from Smart PLS 3 software.
Table 5
Discriminant validity
|
Fornell and Larcker Criteria. * |
||||
|
Construct |
Social Value Creation |
Innovativeness |
Risk Management |
Socialness |
|
Social Value Creation |
0.864 |
|||
|
Innovativeness |
0.631 |
0.823 |
||
|
Risk management |
0.506 |
0.533 |
0.806 |
|
|
Socialness |
0.740 |
0.641 |
0.468 |
0.845 |
|
* To be valid, the AVE must be higher than the squared correlations with respect to the other variables. |
||||
|
HTMT Criteria * |
||||
|
Construct |
Social Value Creation |
Innovativeness |
Risk Management |
Socialness |
|
Social Value Creation |
||||
|
Innovativeness |
0.782 |
|||
|
Risk Management |
0.596 |
0.661 |
||
|
Socialness |
0.865 |
0.787 |
0.554 |
|
|
* To be validated, the values must be <.90. |
||||
Note: Authors’ own elaboration based on results obtained from Smart PLS 3 software.
The third step was the evaluation of the structural model, starting with the evaluation of collinearity statistics (VIF) in the relations between constructs, the calculation of the explained variance ( and the contribution of each variable, effect size ( and the contrast of the hypotheses. These can be seen in Table 6.
Table 6
Structural model tests
|
Hypothesis |
Coefficient (β)* |
T stadistic |
p Values |
LI |
LS |
Supported |
VIF |
f2 |
R2 |
|
|
H1a |
Innovativeness --> Social Value Creation |
.211 |
2.654 |
0.004 |
0.071 |
0.332 |
Si |
1.927 |
0.058 |
0.133 |
|
H1b |
Risk management --> Social Value Creation |
.142 |
1.928 |
0.027 |
0.023 |
0.267 |
Si |
1.452 |
0.035 |
0.071 |
|
H1c |
Proactivity --> Social Value Creation |
It was not possible to perform its verification. |
||||||||
|
H1d |
Socialness --> Social Value Creation |
.538 |
6.166 |
0.000 |
.386 |
.672 |
Si |
1.765 |
0.413 |
0.398 |
|
R2 Total = 60.3% |
||||||||||
Note: Authors’ own elaboration based on results obtained from Smart PLS 3 software. *Calculated via bootstrapping using 10,000 units.
Based on the results, it is indicated that innovativeness has a positive relation with the creation of social value, with a highly significant p-value (0.004). The variable in turn contributes 13.3% of explanation to the model, with a small effect f^2 (0.058). The beta (β) obtains a value of .211, a figure that determines how much it would be affected in a regression. Based on the findings, it is considered that the relation is congruent with what has been reviewed in the literature, accepting H1a hypothesis.
Regarding risk management, a positive and significant effect was detected, which allows us to accept the respective hypothesis. The effect obtained in its f^2 distribution and in its contribution to the model (7.1%) values lower than the previous relation. However, its statistical beta of .142 allows validating the sign of the relationship, so hypothesis H1b is accepted. On the other hand, the relation between productivity and social value creation does not pass the necessary statistical tests, so hypothesis H1 cannot be adequately tested. Lastly, the hypothesis posed between socialness and social value creation is accepted, since it has the expected meaning as well as statistical significance (p = 0.000). Its contribution to the model 39.8% turns out to be the highest, with a substantial and important effect on the f distribution, the relationship being the most important, due to its effect and statistical beta. Next, the validation of the second-order model is carried out to test H1.
3.1.1. Second-order model
The guideline proposed by Sarstedt et al. (2019) for type 1 models, where the model content follows reflexive parameters, recommends a two-stage approach. The first stage corresponds to the calculation of the first-order construct (LOC) values (Sarstedt et al., 2019); in other words, the procedures performed previously, but without considering the structural adjustment. The second stage consists of evaluating and validating the higher order construct (HOC), which will have its own measurement model estimators (Hair, et al., 2017). Thus, social entrepreneurship is the higher order construct (HOC), and the lower order constructs (LOC) are innovativeness, risk management, proactivity, and socialness. The HOC construct of social entrepreneurship has reliability and construct validity, as well as adequate discriminant validity. The path model or structural adjustment is carried out to determine the behavior of social entrepreneurship in the creation of social value. Table 7 and Figure 3 show the results found.
Table 7
Values of the HOC Social Entrepreneurship and results of the model
|
Construct |
Alpha |
rho_A |
CR |
AVE |
||||||||
|
Social Entrepreneurship |
0.782 |
0.812 |
0.788 |
0.560 |
||||||||
|
Discriminant Validity (Fornell-Larcker) |
||||||||||||
|
Social Value Creation |
||||||||||||
|
Social Value Creation |
1.000 |
Social Entrepreneurship |
||||||||||
|
Social Entrepreneurship |
0.838 |
0.748 |
||||||||||
|
Discriminant Validity (HTMT) |
||||||||||||
|
Social Entrepreneurship |
0.839 |
|||||||||||
|
Structural adjustment |
||||||||||||
|
Hypothesis |
Coefficient (β) |
T stadistic |
p Values |
LI |
LS |
Supported |
f2 |
R2 |
||||
|
H1. Social Entrepreneurship >>> Social Value Creation |
.838 |
19.987 |
0.000 |
.741 |
.909 |
Si |
2.366 |
0.703 |
||||
|
*(SRMR, 0.031; d_ULS, 0.010; d_G, 0.07) |
R2 Total 70.3% |
|||||||||||
Note: Authors’ own elaboration based on results.
As indicated in the previous table, the statistical results of the social entrepreneurship (SE) construct provide evidence of both convergent and discriminant validity. This is supported by satisfactory values obtained for AVE (Average Variance Extracted), Fornell and Larcker criteria, and HTMT (Heterotrait-Monotrait) ratios. Furthermore, the reliability of the construct is deemed appropriate, as it surpasses the tests for Cronbach’s alpha, rho_A, and composite validity (CR). Moreover, the model exhibits a strong fit with an R^2 value of 70%, indicating that the model is capable of effectively predicting and explaining the behavior of Social Value Creation based on the Social Entrepreneurship variable.
Figure 3
Test of the second-order model. Source: Elaborated with Smart PLS 3 software
Finally, based on the parameters obtained, the global hypothesis finds statistical support, since its p-value is significant. Likewise, the SRMR model fit indicates that it is below the recommended 0.08 threshold (Hu & Bentler, 1998). Consequently, hypothesis H1 is accepted. Table 8 presents a summary of the hypotheses evaluated.
Table 8
Summary of the hypotheses
|
Nomenclature |
Hypothesis |
Result |
|
|
First-order model |
H1a |
Innovativeness has a positive effect on social value creation. |
Not rejected |
|
H1b |
Risk management has a positive effect on social value creation. |
Not rejected |
|
|
H1c |
Proactivity has a positive effect on social value creation. |
Not verified |
|
|
H1d |
Socialness has a positive effect on social value creation. |
Not rejected |
|
|
Second-Order Model |
H1 |
Social entrepreneurship has a positive effect relation on social value creation. |
Not rejected |
Note: Authors’ own elaboration.
4. Conclusions
The present study has been accomplished by determining the effect of social entrepreneurship in the creation of social value in the territorial area of the Huasteca Tamaulipeca. The territory has spoken, in an analogous way, through the companies located in it. The validation of the SE process for the region has been different, since it has been integrated by innovativeness, risk management and socialness, leaving aside proactivity, but why does this happen?
When analyzing the region and retaking hypothesis H1a, it is feasible that the analyzed companies give relevance to the creation of ideas that promote and support people in precarious conditions, ignoring that, by doing so, they become innovative, derived from the fact that their activities could be reflected in an economic and social spill-over. This situation allows making reflective approaches about the relevance that companies possess, given that they probably develop products or services, without knowing that they will be successful, with a high tacit and explicit knowledge, participating in the regional development of their territories, helping multiple stakeholders (Son et al., 2018; Syrjä et al., 2019).
Regarding hypothesis H1b, the result is like that found in the studies mentioned before demonstrating that social enterprises in the region consider risk as an explicit element within them. Despite the adversities of being in such inhospitable areas, the analyzed enterprises transform themselves, venturing into new areas of opportunity, always seeking the benefit of society.
On the other hand, hypothesis H1c, which could not be tested, given that the construct did not pass the validation tests, omits an in-depth explanation, but mentions that the companies analyzed probably do not have plans and ways of dealing with foreign problems, placing the pandemic as an example of this.
Finally, hypothesis H1d, offers an interesting evaluation, given that the result is congruent with the literature (Gali et al., 2020; Halberstadt et al., 2020), where firstly the inclusion of socialness allows the inclusion of a social axis in the organization, regardless of whether it is for-profit or not, where each company delivers social and economic value to a different extent. The study being in emerging territories and lacking conditions provides relevance to the fact that no matter where it is located, a social enterprise will seek to create social value, planning it and being clear in its goals and objectives (Alarifi et al., 2019; Dwivedi & Weerawardena, 2018).
Referring to the global hypothesis H1, support is provided to the different empirical studies described (Dwivedi & Weerawardena, 2018; Shin & Park, 2019; Son et al., 2018), it is indicated that the analyzed companies do not have adequate strategic planning, but the intention to benefit and safeguard others will always be in force. By presenting the model in first and second order, it provides new nuances to the topic of SE, since it provides clarity on the individual effects of each dimension in the creation of social value, in addition to locating the region so that future studies can be carried out with greater complexity.
Furthermore, selecting the Huasteca Tamaulipeca as the study area highlights the significance of understanding rural contexts, which present unique challenges that differ from those commonly encountered by entrepreneurs in countries with consolidated economies. For instance, in the Huasteca Tamaulipeca region, there are issues concerning limited access to education, healthcare, and inadequate infrastructure that raises inequality among the habitants, shaping a distinct entrepreneurial environment when compared to cases of companies situated in countries like South Korea or Spain. This distinction arises from the presence and influence of social enterprises within the Huasteca Tamaulipeca, that operate without knowing that they are social enterprises, because of the lack of this figure in Mexico.
Talking about Mexico, it has what it takes to provide, through proper management, the coordination between sectors that provides the relevance for the social enterprise model to transcend integrally in society, a situation that, as evidenced in other studies, has not been possible. This type of enterprises represents an engine of growth for the country; it is required that the institutional framework provides tools, through public policies, to improve the way in which social enterprises operate, improving their conditions with laws that capture the social economy.
Furthermore, it is necessary to promote these business models within the Mexican entrepreneurial ecosystem through vinculation programs that engage society. This will contribute to strengthening the development of future entrepreneurs, like students, who choose to establish social enterprises (Cruz-Sandoval et al., 2022) and also to improve the rural social enterprise figure (Musinguzi et al., 2023).
The aforementioned is important because social enterprises play a crucial role in achieving the sustainable development goals outlined in the UN’s 2030 Agenda (Diaz-Sarachaga & Ariza-Montes, 2022). Mexican companies have an opportunity to join this effort from their respective battlegrounds to ensure these goals are met.
Among the future lines of research, I propose that the model should be strengthened with new variables such as organizational performance, organizational climate, level of technological acceptance, marketing capabilities and operations management, to name a few. Specifically, the Agency theory of Jensen and Meckling (1976) will be of interest to deepen the schematization of corporate management, from a governance-based perspective, to explain the decision-making behaviors of a social enterprise.
Finally, the contribution of this study lies in the knowledge discovered in a territory that has been scarcely approached, with difficult conditions both at the regional and institutional levels, providing an important reflection on the figure of the Mexican social enterprise, which needs to be understood by the political and governmental spheres of the country to consolidate and become a model that develops the nation.
Special thanks
The author thanks the National Council of Science and Technology (CONACYT) for its support during his doctoral studies.
Financial Sources
Thanks to the National Council of Science and Technology (CONACYT) for a scholarship.
Declaration of conflict of interest.
The author declares that there is no conflict of interest.
Declaration of data availability
The data is available by mail request to the main author, since it is confidential company information.
1 Emergence of Social Enterprises in Europe, a network of research scholars created since 1996 to carry on studies of Social Enterprise.