Empirical research on the role of internal social capital upon the innovation performance of cooperative firms

Abstract

BACKGROUND:

Internal social capital in the cooperative firms has emerged in recent years as an important concept for improving innovation performance.

OBJECTIVE:

We explore whether the cohabitation of the different interacting social groups, namely cooperative members, and non-cooperative members, will generate disparate impacts on the circumstance for enhanced innovation.

METHODOLOGY:

A sample of 180 cooperative firms in Ethiopia, with two respondents per firm, consisting of one adherent and one non-adherent member, we reflected on the theory of social capital, and by adopting a relational, cognitive, and structural concept. We conducted Structural Equation Modeling (SEM) through PLS to analyze the importance of each group for innovation performance.

RESULTS:

Our results suggested that the internal interaction between adherent and non-adherent members of cooperative enterprises positively influences their “innovation performance”. The findings also revealed that non-adherent members were more involved in building innovation than adherent members.

CONCLUSIONS:

The results provide empirical evidence that internal social factors are essential assets for effective innovation in cooperatives, and established a new line of research within an empirical perspective.

Keywords

Innovation performance internal social capital cooperative firm knowledge creation

Mr. Kashosi Gad David is a PhD candidate at Don links School of Economics and Management, University of Science and Technology Beijing. His research interests lie in strategic management, and technology innovation and entrepreneurship.

Professor Yang Wu is a professor at Don links School of Economics and Management, University of Science and Technology Beijing. His research interests are in technology innovation strategy and management; intellectual property strategy and Management, and Enterprise Strategy.

Miss Epede Mesumbe Bianca is a PhD candidate at Don links School of Economics and Management, University of Science and Technology Beijing. Her research interests are in business management.

Dr. Gutama Kusse Getele is a PhD research scholar at Don links School of Economics and Management, University of Science and Technology Beijing, China. He graduated with MSc degree in computer science and technology, from university of electronics and technology of China. In 2015, Dr. Gutama has been teaching commination engineering at Chengdu University of Information Technology. He has a wealth of experience in cloud computing security, SCM & CSR. His research interests are in supply chain management, and he published many academic research papers in high-quality SSCI, EI, ESCI and international journals on SCM and CSR.

1 Introduction

In today’s business environment, the need for innovative business practices has increased. Over the past decade, the Ethiopian government has revived its interest in collective action, including cooperatives, to foster innovation, share information and overcome smallholder marketing constraints [1]. The development of cooperatives in Ethiopia has accelerated, but research is limited and some studies show that cooperatives are not viable in the long term [2, 3]. Mojo D, Fischer C, Degefa T [4] report that the unsegregated services of cooperatives to members and non-members have given rise to serious concerns about the long-term self-sustainability of cooperatives. In this regard, it is essential to understand how internal sources contribute to innovation performance and how they are used to generate it.

The literature recognizes the significance of internal social capital (SC) as a major element in the development of innovation performance and defines it as a firm value that is created through relationships among its members, aiming to cooperate, exchange information as well as coordinate group activities [5 –7]. In this regard, numerous research studies examined the influence of internal SC on innovation [8 –11] and revealed that internal SC is essential for innovation development [12, 13]. However, for most studies, internal SC is approached similarly, independent of the groups of members or collectivities that coexist in the organization [14 –16]. This approach is probably not an adequate illustration of the overall situation since more than one social group co exist in an organization. Hence, there are formal groups, for example, project teams, subdivisions, divisions, departments, and informal groups such as committee directors, founders or in particular family members [17]. These communities may not necessarily share identical dynamics; relationships, and social interactions, which in turn could potentially affect the different aspects of the development of internal SC of an organization. Therefore, working in a community with the same principles and values as in a cooperative firm can be a considerable asset for the exchange of knowledge.

In the same vein, studies have been conducted for years on the role of internal SC in a family business to explain these aspects [18]. According to the study of Pearson, Carr and Shaw [19], they considered SC in the family business to be conceptually relevant, while the study of Salvato and Melin [20] worked with a business case analysis to further explore the connection between internal SC and value creation in a family-owned business. Arregle, Hitt, and Sirmon [14] are concerned that a family business is unique, even though it works as a single unit, but several forms of SC exist side by side; the family’s and the firm’s.

A few studies have analyzed the relationship between internal SC and innovation capability within cooperative enterprises [21 –24]. However, less work includes the two social groups that make up these enterprises: the group of adhering members and non-adhering members. Our study attempts to fill this gap and expand the understanding of the relationship between these two groups and their role in promoting innovation performance in the perspective of cooperative firms.

This work provides some contribution to the literature by connecting cooperative business with internal SC in a way that is coherent with the research of [18]. Besides, we introduced a theoretical framework based on empirical evidence and suggested that the influence of interactions in cooperative businesses and relationships within and between each group contribute significantly to the firm’s ability to innovate and identify innovative opportunities that could not be identified and expanded [25]. Based on a sample of 180 Ethiopian cooperative businesses, our results present convincing evidence that demonstrates the vital contribution made by these two distinct social groups to the continuing procedure in the cooperative activity.

This research paper is structured as follows. After the introduction, we present the theoretical background in section 2. Section 3 formulates the research hypotheses. Section 4 presents the data and methodological approach. In section 5 we provide the results and analysis of the research. Section 6 present discussion and Finally, in section 7, we summarize the principal conclusions, implication and limitations.

2 Theoretical background

The importance of social capital as a determinant of innovation performance has received significant attention in recent years[10 , 26–29]. Several researchers consider two components of SC: the relationships between individuals or groups working in the organization (internal SC) and inter-organizational relationships (external SC) [30]. The present research is focusing on the internal SC that is increasingly seen as a valuable intangible asset for firms, as it provides a unique idiosyncratic network of relationships [26, 31]. Internal SC provides valuable learning resources and facilitates the development of a unique knowledge base that can be essential for generating innovation and value creation [10, 15]. In addition, internal SC facilitates innovation by fostering communication and coordination of activities among different members of the firm [15 , 31–33].

As mentioned by Wenpin Tsai and Ghoshal [11], the firm’s internal SC includes social interaction, trust relationships and value improved creativity in a social group to which the research of Yen, Tseng and Wang [34]added the supposed stimulating role of external networks in the process leading to social innovation. Also, the survey of Nahapiet and Ghoshal [32], suggested that a conceptual framework for examining the dimensions of SC and proposed to discern three interconnected dimensions of SC: the structural dimension, the cognitive dimension, and the relational dimension. The structural dimension concerns the direct and indirect links between various members [35]. The social relationship can allow people to get to know each other, share important information, access to the resources owned by their associates which encourages the production and application of new ideas [11]. The relational dimension describes the dynamics of the structure that leads to the formation of SC through the analysis of the nature of the inter-individual relationships which are built through the history of their interactions. It indicates the specific facets of relationships, for example, trust, friendship, commitment, and distinctiveness that influence behavior [32 , 37]. The cognitive dimension consists of shared representations and systems of meaning. These are common language and codes, as well as shared history among network members [38].

This dimension acts as a bridging device that supports the organization’s partners in combining resources; it can mediate disputes and contribute to the negotiation and the establishment of common objectives [39]. Sharing an objective within a network inspires its members to have similar perceptions of how they should act. In this regard, Zheng [40] and Martinez-Canas [41] argue that the three dimensions (structural, relational, and cognitive) are essential to understand the formation of SC in intra-company relations and to explain their innovation performance. In this sense, internal SC reduces the opportunism of the actors and the divergence of interest within the company [42, 43]. Internal SC encourages the cooperation and “associability” of actors, that is, the subordination of individual objectives and actions to collective goals and activities. In a cooperative business perspective, it allows limiting the control needs that would result from the opportunism of the actors and the risks of misappropriation of resources by the agents [44].

2.1 SC and the cooperative enterprise

A company’s innovation performance requires that the knowledge held by its employees be converted into organizational learning through the intensive intra-organizational exchange mechanism. For this reason, some authors consider cohesion as a necessary prerequisite for the emergence of innovation [45]. Indeed, the existence of a shared vision is one of the mechanisms that lead members of a group to a perception of belonging and a willingness to maintain the group’s overall characteristics. From this point of view, cooperative enterprises can have a high degree of SC characteristics since they bring people to work together in a democratic and equal way.

Researchers identify cooperatives as one of the most vital organizations for developing strong relationships [46]. Because of their democratic, sharing, mutual support and solidarity values, cooperatives play a critical role in economic and social integration [47, 48]. It fosters among members, a perception of cooperation and solidarity for a common purpose and a shared interest in something meaningful. Cooperatives, as an organization of the social economy, embody this democratic ideal. This is recognized by several national legislations, especially in Ethiopia [49].

According to Ethiopian Law “cooperative societies proclamation No. 147-1998 establishing the general status of cooperatives, power is exercised democratically and the members of the collective work with a view to the general interest of all shareholders. According to this definition, the term “cooperative” refers to an organization of common objectives with visions that influence actors’ behaviors to mature relationships [50]. Therefore, in the view of Salvato C, Melin L [20], we suggest that cooperatives are considered as organizations characterized by socially intense interactions, the singularities of the approaches they cultivate may well be dependent on their fundamental idiosyncratic SC. In the opinion of Iliopoulos, Värnik, Filippi [51] the cooperative is a source of SC by providing members with a framework for expression, and thus a means of mobilizing social capital.

Therefore, this premise will lead us to suggest that the main way to stimulate innovativeness is to create organizational and institutional conditions that foster the emergence of internal SC. They are mainly based on the existence of a shared vision and values among the members of the group, and their interdependent works [52]. For this reason, we examine the impact of the internal SC of members of cooperative enterprises on innovation performance. Their SC will thus be considered as the primary “brick” of innovation. However, scholars believed that most people employed in cooperatives do not have the same status. According to Kroll and Henning [53]; at least two social groups are present in most cooperatives with divergent interests: the owners of the company (adherent members) who are motivated by solidarity, collective defense of interests, specificity power and those who manage it (non-adherent members) motivated by individual performance and financial success [54]. The adherent, as well as the group of non-adhering members, create a context in which group interactions can strongly influence the creation of SC.

3 Hypotheses development

3.1 SC of adherent members and innovation performance

The systematic interactions between members of a cooperative are at the heart of the construction of their specificity, making it possible to develop particular capacities and sources of differentiation [55]. Stability, democracy, shared visions and objectives, and a sense of shared responsibility is thus highlighted as criteria for the specificity of cooperative enterprises [22]. The membership can shape and develop a long-term vision when these members are deeply involved in the company. The study of Eddleston and Powell [56] present a means of these associations that can be used to improve innovation. It is thus, the long-term vision that leads this type of company to develop a differentiation, a source of value creation over generations.

The concept of SC makes it possible to bring together different ideas that already existed about the family, based on the conceptualization developed by [32]. Researchers believe that relationships between adhering members establish an ideal environment where SC is naturally created and that these relationships are essential factors in creating a competitive advantage [27, 57]. This implies the development of innovation because adhering members can generate and exchange useful and cheap information which facilitates the mobilization of available resources and knowledge.

According to Molina-Morales and Martínez-Fernández [58], these resources are difficult to value, but what is certain is that they enrich an organization’s ability to solve and classify issues. Moreover, it reduces opportunistic behavior and provides the ability to share tacit and high knowledge. As such, links between adhering members are therefore essential to facilitate interaction and the exchange of knowledge. It provides information on the existence and location of relevant knowledge [59]. Consequently, we argue that the ability to adhere members to work together harmoniously and effectively facilitates the achievement of more significant innovation. Given these arguments, we propose the following hypothesis on the SC of the adhering members of the cooperative society and its innovation performance:

Hypothesis 1. The SC of the adhering members positively influences the innovative performance of the cooperative firm.

3.2 SC of non-adherent members and innovation performance

Non-adherent members are another distinctive human resource group of the cooperative enterprise. Just like the administrators, this group of persons with internal SCs, notably: relational (personal relationships); cognitive (shared vision, mission, and objective); and structural (communication and social interactions), are also essential to foster innovation performance. Indeed, non-adhering members guarantee quality services for companies by clearly defining objectives, promoting a professional, transparent, trustworthy environment, developing work routines, and utilizing their extensive networks outside the company through interactions with various external actors. Non-adherent members of the cooperative are motivated by a broad range of reasons, notably the possibility of achieving greater influence, fulfilling personal visions and objectives, developing greater autonomy, and enhancing membership and collegiality [60].

According to Whetten DA, Felin T, King BG [61] the diversity and heterogeneity of non-adhering members promote entrepreneurship and innovation. Therefore, SC of non-subscribing members can promote creativity in exchanges between non-members by assisting them to maintain a constant flow of positive creative thinking. In this regard, as Zheng W. [62] points out, social exchanges with external actors are a driver of innovation. Network contacts outside the cooperative are likely to gather a wide range of information on a wide range of innovation opportunities. Therefore, we assume that the non-adherent members directly and positively affect the innovative performance of a cooperative society:

Hypothesis 2. The SC of non-adhering members positively influences the innovation performance of cooperative firms.

The adherent group has many positive aspects, such as the availability of funding and a high level of support and trust, but it also constitutes a close and intense community where members have interactions with each other that may be locked in a tight and restricted circle [63, 64]. Therefore, this group tends to be overly cohesive with time and needs access to external knowledge to exchange, disseminate and transfer knowledge and thus develop new specifications or technical solutions [65, 66]. In contrast, the non-adherent’ group is composed of less intense and close relationships than the adherent group. In addition, this group can be impartial and attentive to the company’s situation and can contribute significantly to increasing resources [67]. Non-adhering members, through their connections and the diversity of their experiences and skills, not only facilitate the amplification of innovation within the firm Nahapiet J, Ghoshal S.[32], but also bring more heterogeneity Watson WE, Johnson L, and Merritt D. [68] and professional expertise to the firm [69 –71]. Therefore, we believe if we accept that the non-adherent group has the privilege of diversity, heterogeneity, and professional skills, compared to the adherent group, non-adhering SC group can generate more innovations in the cooperative firm.

Hypothesis 3. The impact of SC of non-adhering members on innovation is more powerful than the impact of SC of Adhering members in cooperative firms.

4 Research methodology

4.1 Data collection and sampling techniques

The research data was collected from 180 cooperative firms in Ethiopia, with two respondents per firm, notably, one member of the cooperative and a non-cooperative member (both with management responsibilities). The surveyed firms operate in sectors such as; artisanal production, agriculture, and fish industries. We targeted firms with employees falling within the range of 30–249 employees. The reason we adopted this range of firms is explained by the fact that most cooperative firms in this area are small and medium enterprises.

Ethiopia is an exciting testing ground for cooperative businesses since it has a high concentration of cooperative firms and a predominance of the cooperative-owned businesses [3, 72]. The sampling method used was the non probability method. This method consists in choosing the most accessible and available individuals. The survey was conducted between April 2019 and July 2019. The questionnaire was distributed randomly among cooperative enterprises located in Dire Dawa, Harari, and Benishangul. We contacted 201 companies and collected 180 responses. Only functional managers with an average working experience between 4 and 8 years in the same firm were involved. Table 1 provides the summarized demographic information of the respondent cooperative firms of the sample.

Table 1
Descriptive analysis of the respondent cooperative firms

Description Number % of total

Industry

Product artisans 25 13.8%

Agriculture 103 57.22%

Fish industry 52 28.8%

Respondent’s age

<40 18 10%

40–50 124 68.8%

52–60 29 16.11%

>60 9 5%

Firm’s age

<15 24 13.33%

15–19 145 80.5%

>19 11 6%

Number of employees

10–50 32 17%

51–100 47 26.11%

150–200 90 50%

200–249 11 6%

Description	Number	% of total
Industry
Product artisans	25	13.8%
Agriculture	103	57.22%
Fish industry	52	28.8%
Respondent’s age
<40	18	10%
40–50	124	68.8%
52–60	29	16.11%
>60	9	5%
Firm’s age
<15	24	13.33%
15–19	145	80.5%
>19	11	6%
Number of employees
10–50	32	17%
51–100	47	26.11%
150–200	90	50%
200–249	11	6%

4.2 Measuring innovation performance

4.2.1 Innovation performance

Innovation performance was measured using the 19-item scale developed by [73]. This instrument was investigated based on a four-dimensional conceptualization: product/service, process, marketing and organizational, that has been used in several innovation studies [74]. In this study, for each item, the respondents were asked to rank to what extent they agree with the following statement on a scale of 1 to 5 (from “Strongly Disagree” to “Strongly Agree”). Product/service innovation was measured by the mean of 6 items “InnovPS”. Process innovation was measured by the mean of 4 items “InnovPr”. Marketing innovation was measured by the mean of 5 items“InnovM”. Organizational innovation was measured by mean of 4 items“InnovO”.

4.3 Social capital

For capturing the social capital, the 6 items used by Tsai W, Ghoshal [39] and commonly used by Rao and Gebremichael [74], were developed by measuring structural SC (2 items), cognitive SC (2 items) and 2 items measuring relational SC respectively. The structural dimension measures the links forming the network bringing together adherent and non-adherent members of the same cooperative. The relational dimension corresponds to the nature of the relationships forged between members working in the same company. This dimension includes relational attributes that regulate exchanges between members of the company, namely: trust, norms, perception of shared obligations, and collective identity. The cognitive dimension measures the facilitation of the combination and exchange of knowledge [75]. All items for these variables were measured on scales from 1 to 5 (ranging from “Strongly Disagree” to “Strongly Agree”).

4.4 Control variables

In addition, we included parameters that could influence a firm’s innovation performance, such as the size of the firm, measured by the number of employees; the industry, operationalized as a dummy variable representing each industry included in our empirical study; and the age of the firm, expressed by the number of years of activity since its inception.

5 Results and analysis

To test our hypotheses, we proceeded by confirmatory analysis carried out using partial least squares structural equations modeling (PLS). There are several reasons for this choice: first, PLS is intended to be a more robust method since its application does not require a large sample size. Second, it supports both a small number of measurement scales and a small distribution of minimum residues [76]. Based on the methodology of Anderson JC, Gerbing DW [77], we opted to proceed in two steps. First, we revalidated the measurement model before testing the hypotheses to the extent that our constructions were based on previous work. And second, we verified the statements of the conceptual model (e. g. [78]).

5.1 Evaluation of the measurement model

We proceeded by reliability model examination, which includes tests such as; internal consistency reliability, convergent validity and discriminant validity based on Urbach and Ahlemann [76] validation guidelines suggestion. The measurement model was tested through unidimensional construct model. According to Urbach and Ahlemann [76], unidimensional construct is verified when items have factor loading contributions greater than 0.6.

The reliability of each construct was validated by a high level of estimated composite reliability (exceeding 0.7) and a high Cronbach alpha. Cronbach’s alpha with a value of more than 0.6 shows that internal consistency is consistent [79]. An alternative measure to Cronbach’s alpha is composite reliability (CR), expected to be above 0.70 [76]. All the constructions have composite reliability values higher than 0.75.Thus, the results of our empirical investigation show that all the variables in our research have acceptable values.

In Table 3, the results indicate that the diagonal values (representing the square roots of the EVs) are higher than the values below the diagonal, this means that the relationships between latent variables are weaker than those between constructs and their indicators. Therefore, the discriminating validity of our construct is validated.

Table 2
Measurement of the model

Variables Items Loadings^a C R^b Cro^c AVE^d

Adherent in Cooperative SC-ST 0.759

SC-ST 0.774 0.878 0.833 0.547

SC-RT 0.737

SC-RT 0.757

SC-CO 0.622

SC-CO 0.777

No Adherent in cooperative SC-ST 0.742

SC-ST 0.715

SC-RT 0.763

SC-RT 0.626 0.862 0.811 0.511

SC-CO 0.711

SC-CO 0.723

Innovation performance CInnoPS 0.793

CInnovM 0.766 0.840 0.746 0.568

CInnovO 0.744

CInnovPr 0.708

Variables	Items	Loadings^a	C R^b	Cro^c	AVE^d
Adherent in Cooperative	SC-ST	0.759
	SC-ST	0.774	0.878	0.833	0.547
	SC-RT	0.737
	SC-RT	0.757
	SC-CO	0.622
	SC-CO	0.777
No Adherent in cooperative	SC-ST	0.742
	SC-ST	0.715
	SC-RT	0.763
	SC-RT	0.626	0.862	0.811	0.511
	SC-CO	0.711
	SC-CO	0.723
Innovation performance	CInnoPS	0.793
	CInnovM	0.766	0.840	0.746	0.568
	CInnovO	0.744
	CInnovPr	0.708

^aAll items loadings are >0.5, indicating Reliability. ^bAll composite reliability values (CR) are >0.7, indicating internal consistency. ^cAll Cronbach’s alpha values are >0.7, indicating reliability. ^dAll Average Variances Extracted (AVE) are >0.5, indicating convergent Reliability.

Table 3

Discriminatory validity of concepts

Variables	Non-adhering members	Innovation Capability	Adhering members
Non-Adhering members	0.875
Innovation performance	0.740	0.753
Adhering members	0.752	0.752	0.715

5.2 The correlation between the SC of non-adhering members and innovation performance

In this study, the Pearson correlation coefficient was used to determine the relationship between each dimension of SC and the innovation performance of cooperative firms. Concerning the association between overall SC and the firm innovative capacity, Table 4 above shows a strong positive significant correlation at a 95% confidence level (r = 0.647, p > 0.05). The findings reported above suggest that a statistically significant and positive relationship exists between firm innovation performance and overall SC (r = 0.0.621, p > 0.05). Looking at the relational SC and innovation performance, we observe a significant and positive relationship (r = 0.472, p > 0.05). Also, the result shows a statistically significant positive correlation between cognitive SC and innovation (r = 0.450, p > 0.05).

Table 4
The correlation of the SC of non-adhering members and the innovation performance

Variables 1 2 3 4 5

1 Structural Dimension 1

2 Relational Dimension .438^ 1

3 Cognitive Dimension .409^ .207^ 1

4 Overall SC .676^ .623^ .610^ 1

5 Innovation performance .621^ .472^ .450^ .647^ 1

	Variables	1	2	3	4	5
1	Structural Dimension	1
2	Relational Dimension	.438^**	1
3	Cognitive Dimension	.409^**	.207^**	1
4	Overall SC	.676^**	.623^**	.610^**	1
5	Innovation performance	.621^**	.472^**	.450^**	.647^**	1

^*Correlation is significant at the 0.01 level. ^**Correlation is significant at the 0.05 level, N = 180.

5.3 The correlation between the SC of adhering members and innovation performance

Concerning the association between overall SC and firm innovation performance, the results presented in Table5 below show that there is a strong positive and statistically significant correlation at the 95% confidence level (r = 0.536, p > 0.05). The results reported below also demonstrate the positive and statistically significant relationship between the innovative performance and overall SC (r = 0.509, p > 0.05). A positive and statistically significant correlation was also perceived between relational SC and innovation (r = 0.449, p > 0,05). At the same time, the result shows a significant and positive relationship between cognitive SC and innovation (r = 0.290, p > 0.05). As shown in Tables 4 and 5, the correlation proved that the SC of adherent members and the SC of non-adherent members are both significantly and positively related to innovation performance. Our results also showed that the SC of non-adherents has a stronger influence on the development of the innovation performance of cooperative firms, as compared to the SC of the affiliates members.

Table 5
The correlation of the SC of Adhering members in cooperatives and the innovation performance

Variables 1 2 3 4 5

1 Cognitive Dimension 1

2 Relational Dimension .429^ 1

3 Structural Dimension .219^ .385^ 1

4 Overall SC .428^ .474^ .601^ 1

5 Innovation performance .290^ .449^ .509^ .536^ 1

	Variables	1	2	3	4	5
1	Cognitive Dimension	1
2	Relational Dimension	.429^**	1
3	Structural Dimension	.219^**	.385^**	1
4	Overall SC	.428^**	.474^**	.601^**	1
5	Innovation performance	.290^**	.449^**	.509^**	.536^**	1

^*Correlation is significant at the 0.01 level. ^**Correlation is significant at the 0.05 level. N = 180.

5.4 Boot strapping regression analysis

To test the impact of the SC of the adhering members and the non-adhering members simultaneously on the innovation performance, we used partial least squares structural equations modeling (PLS: Partial Least Squares) for multiple regression to take into account several factors (or independent variables) and dependent variables. The findings have shown that the R-squared is 0.8, which means that the two explanatory variables (SC of participants and non-participants) can explain about 80% of the change in innovation performance. The regression results (Table 6) indicated positive effects on innovation, as shown by the results of the regression between non-adherent members and innovation performance (f = 0.705, β= 0.64, p < 0.05) and between adhering members and innovation performance (f = 0.06, β= 182, p > 0.05). The null hypothesis (H₀) is rejected. In other words, the explanatory variables significantly reflect the behavior of the dependent variable, suggesting that SC has a significant impact on innovation performance. Furthermore, the relationship between the non-adhering members has a strong effect on innovation, as compared to the adhering members of cooperative firms (see Fig. 1).

Table 6
The results of the Structural model analysis

Path Std. B St. Error T Statistics P Values

Group Non -Adherent ->Innovation performance 0.64^ 0.06 10.669 0.000

Group Adherent ->Innovation performance 0.182^ 0.057 3.2 0.002

Control variables

Industry sector ->Innovation performance 0.069^ 0.04 1.695 0.087

R&D intensity ->Innovation performance 0.099^ 0.04 2.461 0.014

Firm Size ->Innovation performance 0.046^** 0.035 1.31 0.188

R² 0.8

R Square Adjusted 0.794

Path	Std. B	St. Error	T Statistics	P Values
Group Non -Adherent ->Innovation performance	0.64^**	0.06	10.669	0.000
Group Adherent ->Innovation performance	0.182^**	0.057	3.2	0.002
Control variables
Industry sector ->Innovation performance	0.069^**	0.04	1.695	0.087
R&D intensity ->Innovation performance	0.099^**	0.04	2.461	0.014
Firm Size ->Innovation performance	0.046^**	0.035	1.31	0.188
R²	0.8
R Square Adjusted	0.794

^*Correlation is significant at the 0.01 level. ^**Correlation is significant at the 0.05 level, N = 180.

Fig. 1

Hypothesis testing, bootstrapping direct effect results.

6 Discussion

Our research attempts to shed light on the concept of internal SC of cooperative enterprises and their innovation performance. We suggested a conceptualization and assessment of internal social capital, focusing on the following three components: relational, structural, and cognitive. Our objective was to explain innovation performance by showing the importance of each internal dimension of SC on innovation.

The results of our empirical investigation showed us that the three dimensions of the internal SC are positively associated with innovation performance. Indeed, studies on sources of innovation have shown that a company’s innovation depends strongly on its SC [73], in all its different dimensions: relational, structural and cognitive. The importance of these dimensions has also been studied by [32 , 80–83]. All these authors agreed that innovation is considered a result of internal social capital.

We also focused on a fundamental characteristic of the cooperative firm, namely the multiplicity of roles played by its members and the influence that each group can have on their company’s innovation performance. Our focus on internal SC through the distinction between adherent and non-adherent members is relatively new in the literature. We believe that the role and mission of each group in the company, as well as their interaction, may influence in one way or another its innovation performance.

The correlation and regression coefficients presented in Tables 4, 5 and 6, above, show that there is a positive and significant relationship between the non-adherent member and innovation capacity. This adds detail to the work of Carrosco-Hernández [84] who had shown that the non-family member’s relationship in a family business increased the ability of the firm to develop and identify opportunities that otherwise could not be identified. The regression analysis confirms the positive and significant effect of internal social capital of adherent members on innovation performance. This finding confirms the theories of [18] and offers a new direction of study related to internal social capital in cooperative firms.

Regarding the importance of the internal social capital of both groups in promoting innovation, the authors found that internal SC of the two groups (adhering and non-adhering) promotes cooperative activity, thus fostering the emergence of new types of association and innovation performance. However, SC intensity may fluctuate over time, and thus its influence on innovation may be expected to be negative [58]. For instance, over time, relationships between employees can lock the company into tight networks and make the company dependent on a few sources of creativity.

Innovation processes are born of diverse sources and, more particularly, of the continuous exchanges and the fertilization of ideas, concepts and technologies [10]. Naturally, when trust is at a higher level, there is less need to regulate the behavior of others. In such environments, individuals may not be scared to exploit others and therefore are more willing to share knowledge and information, which are major contributors to the creation of innovations. This observation occurs with the adherent members. By definition, these groups are more interested in the cooperative concept than the non-adherent member is, but in contrast, the results show that their impact on innovation is less important than that of the non-adherent member. This confirms the research of [85] which shows that widespread trust reduces the risk of R&D project investments and innovative activities and therefore decrease innovation performance.

7 Conclusion, implications and limitation

By drawing on a comprehensive model of internal social capital in cooperative firms, this research has several implications in theory and practice. The study extends research in the area of internal social capital, innovation performance, and the development of cooperative firms.

This research has theoretical implications in three main areas; first, to a number of new research findings that call for practical support of the hypothesis that internal SC drives innovation. Thus, based on family firm literature, this research brings a new angle to the study of cooperative enterprises by pointing out the two social groups and suggest the value of internal CS in cooperative enterprises. Second, the research results suggest that the influence of non-adherent members’ SC on the innovation of these cooperative enterprises is stronger than the influence of adherent members’ SC. These results call for further observation of these two social groups in an enterprise and their impact on innovation.

Thirdly, the study simultaneously examines the social capital factors which allow a good understanding and gives a richer vision of how cooperative enterprises differ, by considering the group of adherent and non-adherent members of the cooperative to realize innovation and shows that non-participants are more diversified.

From a practical perspective, the results of our research imply that cooperative enterprises need to manage their internal relationships in a way that stimulates the acquisition of knowledge and strengthens innovation activities. In this case, managers should carefully assess the benefits of having close and collaborative relationships between members and non-members involved in a cooperative enterprise, and members of each group should be encouraged to share their resources and knowledge within the enterprise.

This study opens new perspectives for further empirical and theoretical studies. Aspects such as the status of the enterprise in the sector and for example the cultural and organizational context within which it operates to affect the internal stock and use of social capital. Although it is beyond this research to discuss this variable, we would like to challenge the authors to consider other additional aspects that may influence or be incorporated as factors that may shape the relationship between internal SC and innovation capacity. For example, the relationship between knowledge management (KM) and SC corresponds to the introduction of innovation into an organization. This implies justifying the association between KM and managerial innovation and the use of the SC concept to characterize an organization.

There are some limitations to this research, First, we focused only on one component of the company’s internal social context. The finding needs to be approached and interpreted wisely, considering important differences in the values, operational and organizational behavior, among cooperative enterprises across the world. Furthermore, some interpretations, such as knowledge exchange and membership skills, are not measured directly, although we believe that they play a central role in interpreting assumed relationships. Another limitation could be related to data collection, by dividing the cross-sectional area of the study into a core set of dynamic concepts (CS and innovation); this allows for timely analysis of institutional situations rather than overall behavior over a given period. Although other studies suggest additional time frames for data collection, this has not been implemented due to time and cost constraints.

Footnotes

Appendix A: Variable and items Likert (1–5)

MEASURE OF ADHERING-MEMBERS SC adapted from [18]

Appendix B: Variable and items Likert (1–5)

Innovation performance measurements Adapted from [73, 74]

Items	Description	Practice
	Product and service innovation	InnPS
Item1	We regularly motivating and supporting the informal R&D, internal technological performance, and training activities
Item2	The products we have introduced to the market are multiple and innovative.
Item3	Our organization continuously look for new services and product
Item4	We regularly monitoring and evaluating technology trends
Item5	The launch of new product led to considerable changes in the industry
Item6	Our company developed more new services than our main competitors.
	Process innovation	InnovPr
Item7	We regularly use various techniques of creativity and idea generation
Item 8	We generally implement the acquisition of innovative ideas through networking and external relations
Item9	We usually make significant investments to incorporate new computer techniques, new equipment, and/or new programmers.
Item10	We frequently train our employees in new technologies trend in this sector
	Marketing innovation	InnovM
Item 11	We are dynamic in creating and using new sales channels
Item 12	We often introduce new strategies for pricing our services
Item 13	We often introduce new strategies or channels for advertising our services.
Item 14	Our rivals or competitors use our advertising and marketing methods as factor of reference
Item 15	The new advertising and marketing strategies we have integrated have been new to this sector
	Organizational innovation	CInnovO
Item 16	We regularly introduce organizational modifications to enhance the division of duties and decision making.
Item 17	We often introduce new techniques for managing external relationship with different institutions or public organizations
Item 18	We regularly enhance skill ability of employees and adequacy of firm’s services in the commercialization sector
Item 19	We often use joint venturing and different financing techniques to commercialize innovation

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Empirical research on the role of internal social capital upon the innovation performance of cooperative firms

Abstract

BACKGROUND:

OBJECTIVE:

METHODOLOGY:

RESULTS:

CONCLUSIONS:

Keywords

1 Introduction

2 Theoretical background

2.1 SC and the cooperative enterprise

3 Hypotheses development

3.1 SC of adherent members and innovation performance

3.2 SC of non-adherent members and innovation performance

4 Research methodology

4.1 Data collection and sampling techniques

4.2.1 Innovation performance

4.3 Social capital

4.4 Control variables

5 Results and analysis

5.1 Evaluation of the measurement model

Table 4 The correlation of the SC of non-adhering members and the innovation performance Variables 1 2 3 4 5 1 Structural Dimension 1 2 Relational Dimension .438** 1 3 Cognitive Dimension .409** .207** 1 4 Overall SC .676** .623** .610** 1 5 Innovation performance .621** .472** .450** .647** 1

7 Conclusion, implications and limitation

Footnotes

Appendix A: Variable and items Likert (1–5)

Appendix B: Variable and items Likert (1–5)

References

Table 4
The correlation of the SC of non-adhering members and the innovation performance

Variables 1 2 3 4 5

1 Structural Dimension 1

2 Relational Dimension .438^ 1

3 Cognitive Dimension .409^ .207^ 1

4 Overall SC .676^ .623^ .610^ 1

5 Innovation performance .621^ .472^ .450^ .647^ 1