Director-Generals’ Human and Social Capital, and Management Performance of Farmers’ Cooperatives: Evidence from China’s Fujian

For human capital, some scholars focused on the relationship between business performance and the personal characteristics of entrepreneurs, such as age, education, personality, remuneration, and professional background. For example, researchers studied 508 telecommunications companies in the USA [Karami et al., 2006]. They found that entrepreneur education and work experience, but not age, affected business performance. However, earlier studies found that an entrepreneur’s age was negatively correlated with business performance, and another study suggested that formal education does not seem to be a determining factor of cooperative success [Bantel and Jackson, 1989; Davidsson and Honig, 2003]. A relationship also exists between business performance and entrepreneur’s personal background and ability. For example, researchers argued that work experience, management experience, and prior entrepreneurial experience are related to firm activity, and that entrepreneurial experience is a prerequisite for starting a company and ultimately affects organizational performance [Cooper et al., 1994; Dimov and Shepherd, 2005]. In addition, directors’ human capital, including prior experience and education, benefit firm performance because human capital is likely to make them more effective at monitoring management and providing advice [Khanna et al., 2014]. It is suggested that entrepreneurial competencies include both innovation and management abilities [Chandler and Hanks, 1994]. Management abilities are linked to economic performance by boosting corporate profits and market share [Becker and Gerhart, 1996]. Skills, such as computer skill, have a significant impact on human capital [Eicher, 1996]. Research found that stronger leadership through enhanced relational skills underlines communication skills as an element of individual competency [McCallum and O’Connell, 2009]. Moreover, honor and rewards are thought to be able to create human capital [Coleman, 1988]. Survey data from several hundred US companies proved that the remuneration level of managers had an obvious influence on the performance of organizations [Hall and Liebman, 1998]. Thus, we propose three constructs for human capital, as shown in Section 3.2 and Table 1. The hypotheses (H1a)–(H3d) about the relationship between human capital and performance are proposed in Section 4.2 and Table 2.

Social capital refers to the assembly of relationships, context, trust, and norms that encourage suitable behavior for knowledge sharing [Anklam, 2002]. Affection relationships, and the diversified relationships that help to build bridges between agents, are sources of social capital [Davidsson and Honig, 2003]. Scholars have argued that social capital is generated from the internal networks of organizations through which tangible and intangible capital can be obtained and used to help organizations achieve their goals [Leenders and Gabbay, 2013]. Actually, social networks are heterogeneous due to member diversity and associational type [Stolle and Rochon, 2001; Ruben and Heras, 2012]. Both internal and external social capitals provide a basis for the creation of organizational advantage [Yli-Renko et al., 2002]. It has been shown that social capital building was associated with enhanced business, knowledge, and innovation performance [Cooke and Wills, 1999]. Furthermore, the use of social capital by organizational managers can play an active role in productive activities, improvement of the organizational environment, and optimization of the organization’s relationships with business institutions, the public sector, and customers [Westlund and Bolton, 2003]. Social capital developed from managerial networking and social relationships with top managers at other firms, government officials (political leaders and bureaucratic officials), and community leadership enhance organizational performance [Acquaah, 2007]. Trust relationships based on strong and weak bonds lead to the creation of cognitive social capital, contributing to entrepreneurial learning and exploration of opportunities [Lechner and Dowling, 2003]. Moreover, commercial relations of social capital improve the business performance of startups [Bosma et al., 2004]. Consequently, four constructs for social capital are proposed in Section 3.2 and Table 1. The hypotheses (H4a)–(H7d) about the relationship between social capital and performance are proposed in Section 4.2 and Table 2.

To avoid deviations that may be caused by the areas and industries of the cooperatives, we chose farming cooperatives in Fujian Province as the research objects. Referring to the evaluation standards for model farmers’ cooperatives, we selected as the study objects those cooperatives listed in the 2014 roster of model cooperatives announced by the Agriculture Department of Fujian Province.

Data were collected using the questionnaire method. The measurement scale and questionnaire were designed according to the rules proposed by Hinkin [1998]. We prepared the initial questionnaire based on literature review. Following discussion with industry experts, we then selected an appropriate measurement scale and descriptions for the questionnaire. After exploratory and confirmatory factor analysis, we tested the validity and reliability of the questionnaire, then deleted any unscientific measurement scale. Once the scales were finalized, it was presented as a formal questionnaire, and a large-scale survey was conducted. The questionnaire included the human and social capitals of farmers’ cooperatives’ director-generals and business performance. The questionnaire had five parts: basic information, human capital, social capital, management effectiveness, and cooperative performance. There were 45 items related to the relevant variables, and a five-point measurement method was adopted.

We selected 400 cooperatives as survey candidates based on geographic area and business scope. The completed questionnaires were then collected and screened. Incomplete questionnaires and those with obvious errors were regarded as invalid and excluded. Of the 400 questionnaires administered, 356 were collected. Excluding invalid questionnaires, 303 questionnaires were obtained (85.1%).

Reliability and validity are metrics for evaluating whether the structure of a theoretical model, the design of the indexes for each variable, and the observation data are reliable and accurate. Reliability refers to consistency within the scale, measuring the deviations caused by different measurement items. Cronbach’s alpha is a tool for assessing the reliability of scales [Santos, 1999]; generally, reliability is high when Cronbach’s alpha is >0.7.

Human capital, social capital, management effectiveness, and operational performance comprise several dimensions. Since each dimension contains different measurement factors, it is necessary to analyze its structural validity. When Bartlett’s test of sphericity is significant, factor analysis is recommended. In that case, no further analysis is needed for Kaiser–Mayer–Olkin (KMO) values <0.6. For KMO values ranging from 0.6 to 0.7, theoretical analysis is used as the basis to decide whether to perform factor analysis according to the actual situation. For KMO values >0.7, factor analysis is conducted [Ferguson and Cox, 1993]. In this study, SPSS 17.0 and AMOS 17.0 were used for factor analysis.

To verify the degree of consistency between the factor model of the scale and the data collected from the questionnaire, i.e., the fitness of using the index variable to measure the latent variable, construct reliability was further checked. We verified whether the variables fit well by validating the structural equation modeling (SEM)-based measurement model.

The SEM model integrates regression analysis, confirmatory factor analysis, and path analysis, which are often used to construct, evaluate, and test causal relationship models. In our study, the exogenous latent variables included knowledge, ability, and motivation with regard to human capital; internal, commercial, political, and innovative social capital; resource acquisition ability and management ability in management effectiveness. The endogenous latent variables included financial performance, customer-focused performance, internal performance, as well as learning and growth performance in the overall operational performance.

First, in terms of the impact on financial performance, motivation human capital had the greatest impact, with an impact coefficient of 0.43. This indicates that director-generals’ motivation human capital, composed of the material and spiritual awards received, has a great impact on the financial performance of cooperatives. In particular, the higher the shareholding ratio of the director-general, the more the director-general is concerned with the cooperative’s financial performance, which may result in higher levels of performance.

Second, in terms of the impact on internal process performance, motivation human capital had the greatest impact, with an impact coefficient of 0.31, followed by ability human capital, with an impact coefficient of 0.18. This indicates that a director-general who has a certain shareholding ratio or has received more awards pays more attention to the standardizing of internal processes and maintains normal cooperative operating activities.

Third, in terms of the impact on growth performance, motivation human capital had the greatest impact, with an impact coefficient of 0.31. Knowledge human capital was next, with an impact coefficient of 0.19. Ability human capital also had a certain impact (0.16). These results indicate that the higher the human capital of the director-general, the more emphasis the director-general may place on the ability of cooperative members and the innovation ability of the cooperative. Thus, the training of cooperative members is promoted, and the brand development and product certification of cooperatives are strengthened.

First, in terms of the impact on financial performance, the impact coefficient of commercial social capital on financial performance was the greatest, reaching 0.70. Internal social capital was next, with an impact coefficient of 0.25. The impacts of innovative social capital and political social capital were relatively small (0.15 and 0.15, respectively). This shows the importance of commercial social capital in cooperatives’ financial performance.

Second, in terms of the impact on customer-focused performance, the impact coefficient of political social capital on the customer-focused performance of cooperatives was the greatest, reaching 0.22. The impact of commercial social capital was second, with an impact coefficient of 0.18. Internal social capital also had an impact, with an impact coefficient of 0.15. This suggests that several types of social capital have certain impacts on the customer-focused performance of cooperatives, but those impacts are low.

Third, in terms of the impact on internal process performance, internal social capital had the greatest impact, with an impact coefficient of 0.56, followed by commercial social capital, with an impact coefficient of 0.45. Political social capital had a small impact, with an impact coefficient of only 0.14. These results suggest that the trust and support that director-generals receive from other members of the organization have a great impact on the operations of cooperatives and the processes of operating activities. Establishing good internal key processes is, therefore, an important precondition for maintaining long-term normal operational activities.

Fourth, in terms of the impact on growth performance, commercial social capital had the greatest impact, with an impact coefficient of 0.43, followed by innovative social capital, with an impact coefficient of 0.29. Internal social capital also had a fairly large impact (0.27), while political social capital had a weak impact (0.16). This suggests that commercial social capital has a significant impact on cooperative members’ abilities and cooperatives’ innovation abilities.

Lastly, based on these results, we can see that while a certain positive relationship exists between a director-general’s political social capital and the cooperative’s operational performance, the relationship is weak due to the smaller path coefficient. This suggests that director-generals have inadequate ability to cultivate, accumulate, and exert political and social capital. Thus, the extent of the impact of political social capital on the performance of cooperatives is not significant.

We have proposed that there may be a mediating effect between a director-general’s human and social capitals and the cooperative’s operational performance. In other words, the director-general’s human and social capitals influence the performance of cooperatives through mediating variables. This assumption is supported by the empirical results.

Some limitations of this study should be noted. First, similar research reports about farmers’ cooperatives’ director-generals are relatively few, so we refer to enterprises for some of the indicators. Thus, our theoretical model may not consider all the potential factors. Second, the performance may be influenced by many other factors, such as policy support, sector type, and business size, apart from director-generals’ human and social capitals. Although the criterion for inclusion of standard cooperative samples is introduced, these factors may also work on performance. Therefore, these factors may be taken into account in future research. Third, the farmers’ cooperative performance measurement is not mature, so indicators are borrowed from the Balanced Scorecard approach [Kaplan and Norton, 1995]. National conditions and properties of farmers’ cooperatives are incorporated into performance measurement items. Although optimized, these measurements may introduce some scholarly described items, which may cause variation in understanding the questionnaire. Finally, the investigated territory is restricted to nine cities of Fujian Province, making our conclusions applicable to limited areas, i.e., similar coastal regions of East China. However, it is not clear whether the imbalance in the development of the regional economy could cause significant differences in performance attributed to director-generals’ human and social capitals. Currently, no statistics is available, and no related research has been reported about the differences. Future large-scale and cross-region investigations should be performed to address the generality of our conclusion. The proposed implications can be absorbed by other country regions, but with caution according to local circumstances. Overall, the outcomes of this study can benefit cooperatives’ director-generals and human resource personnel in terms of understanding the influence of director-generals’ human and social capitals on organizational performance. The results may also be useful for policymakers to establish a better environment for the development of cooperatives.