Abstract

Social capital is a significant resource for Small and Medium-sized firms. Social Capital resources generate assets for firms which in turn contributes towards the performance of firms. The paper analyzes the relationship of Social Capital with SMEs Performance operating in Sindh.  Research has investigated the impact of the personal, professional, associative, and institutional network towards performance.  To attain the purpose of the paper, the data was gathered using a questionnaire from 395 entrepreneurs of SMEs of Sindh Province. The regression and correlation techniques are employed to evaluate the relationship and to investigate the hypothesis. Results revealed a significant relationship between Social Capital and Firm’s performance

Key Words

Business Performance, Social Capital, Small and Medium Enterprises (SMEs).

Introduction

The economic evolution and growth of the economy are highly related to the potential and output of Small and Medium-sized firms. SMEs have a vital contribution to the economic growth of Pakistan (Haleem et al., 2017). In addition to economic growth, these firms enable the reduction of poverty, income generation, and providing employment (Imran et al., 2018; Nichter & Goldmark, 2009). For an evolving economy like Pakistan, the role of SMEs is highly crucial in contributing to the annihilation of poverty. Nevertheless, it is also important for such firms to channelize their resources and strategies to deliver value for businesses and economies. 

In today’s competitive market, small firms face challenges of attaining resources for business and this constraint hinders progress and performance (Jansen et al., 2011). In this framework, the Entrepreneur’s social capital develops as a source to attain business resources.   Several factors have been studied which contribute towards business performance like knowledge and skills of Entrepreneur, his or her experience in the business, and the business environment. Besides this, resources which are generated through the social capital network is also a crucial factor in enhancing organizational performance. Social capital and firm performance relationship are widely under consideration for researchers in developed economies.   However, little attention is paid by scholars in developing countries and literature is quite limited to developing economies like Pakistan. So, the current study intends to evaluate the impact of this Capital on SMEs' performance.

In addition to this, SMEs' substantial benefits and importance to the economy have motivated researchers in current years and past to study academic disciplines of management and entrepreneurship. Simultaneously the importance of Social Capital in Entrepreneurship research is highly pursued by academic researchers and policymakers. 

 The research aims to contribute to a theoretical, practical, and policy perspective. In the theoretical domain, it attempts to contribute to knowledge and understanding of Social capital. The wide literature on social capital in developed economies is discussed and available whereas it is in the developing phase in developing economies. In terms of practical domain, the study is aimed to contribute towards the importance of social capital in business practices and strategy formulation for SMEs owners and Prospective entrepreneurs. From a policy perspective, research is significant for different stakeholders like SMEDA and Government bodies to understand the nature and dynamics of SMEs' performance from the perspective of Social Capital. 

Literature Review

Social Capital

It may be defined as resources accessible to individuals and groups by participating in some form of networks and may be conceptualized at the individual and collective levels (Moore & Kawachi, 2017).  Social capital may also be defined as social connections that are utilized to attain essential business assets and to enhance business performance by entrepreneurs (Dai et al., 2015). 

According to Pratono et al. (2016), Social Capital springs from social network theory that is taken as a valued resource to Financial Performance. The notion of Social capital also denotes a network of relationships and assets in it. The relationships in different spheres of people and generation of resources through relationships are classified as social capital. This capital is dissimilar to financial and human capital in the sense that it originates and based on collaboration amongst different social actors. The concept is grounded on-premises that people who are well connected with other people and institutions are good at managing and performing organization tasks. They recognized three forms of this capital which can be written as relational, cognitive, and structural. All these three forms of capital are effective for the enhancement of business performance and growth (Pratono et al., 2016; Batjargal, 2003; Nahapiet & Ghoshal, 1998).  

Like other forms of capital, it attempts to enhance the effectiveness and growth of firms by enabling collaboration between members (Lin, 2017). The resources generated through relationships helps in growth and in bringing value for firms. It provides prospects for both bridging and bonding social capital in getting information (Tian, 2016) and it may be exploited for business purposes and for attaining business goals. 

Su?kowski (2017) described it as trust, connections, and social networks which help in getting cooperation. According to the network approach, relationships provide resources and these resources help individuals in attaining social and organization goals. The initial aspect of social capital contributes towards society and the current aspect provides value to individuals in attaining their goals.

Relationships as a source of Social Capital

Social capital and relationships are based on the concept of relationship marketing. It emphasizes that social capital is derived from person individual’s relationship or affiliation networks and from the resources located in it (Carrion et al., 2017) The business owner’s network of relationship or relations of an entrepreneur are considered as firm’s assets because it helps in achieving performance for small firms(Elfrin et., 2014). In social capital, each entrepreneur or an individual owns the different social networks and develops various types of relationships, this may be considered as an inimitable aspect of social capital. Four classifications have been put forwarded to classify networks (Johannisson, 2008) i.e. personal, professional, associative, and institutional networks. 

Based on this approach, the current study has investigated the impact of social capital through a personal, professional, associative, and institutional network of entrepreneurs and owners of these firms.




Personal Networks of Relationship




This network includes relationship and association with close social circle including friends, families, neighbors, and those networks which are based on voluntary associations involving mutual interests and characteristics. The entrepreneur’s network offers substantial support for enterprise development (Kregar & Antoncic, 2016). These relationships facilitate the individual in attaining performance (Cvtanovic et al., 2015).




Associative Networks of Relationship




This network includes relationships with those volunteer organizations and associations to whom the owner of the firm is related. These include any business association, municipal, employment, political, religious, cultural, community advocacy, or sports associations.   It includes relationships with associations an individual belongs to (Lee & Hallak, 2020). 




Professional Networks of Relationship




The professional network includes relationships with different stakeholders of business involving suppliers, partners, consumers, staff, and colleagues. These relationships are associated with an entrepreneur’s professional circle (Davidsson & Honig, 2003). In building the relationship with customers, firms manage social capital for getting useful commercial information which may help them to achieve valuable resources. (Wang, 2016).




Institutional Networks of Relationship 




This represents the relationship with members of various public and private organizations. For entrepreneurs, it refers to the relationship with different bodies or government authorities. These may include tax bodies, public officials, media, and other authorities (Woolcock, 2001). 

Social Capital and Business Performance

Research in managerial sciences has been endeavoring to address the very important notion of social capital impact on different parameters of organization success. Owing to this, various research scholars have studied the effects of entrepreneur social capital and the performance of organizations.  

Pratono (2018) investigated the relationship between social capital and firm performance in Indonesia on 380 SMEs and found a positive relationship. The social networks ameliorate the performance of firms. Agyapong et al. (2017) evaluated the relationship of social capital and small businesses based on data from 500 firms in Ghana and it concluded a positive impact.  The findings of the study in Bangladesh based on the relationship of social capital and firm performance revealed that those firms perform better which are involved in social networking using formal and informal (Saha & Banerjee, 2015). Stam et al. (2014) reviewed firms to find an association between entrepreneurs’ social capital (personal networks) and performance. They found a positive relationship between these two variables. 

Baron and Markman (2003) studied social capabilities and their impact on firms.  Batjargal and Liu (2004) studied features of the network and how an individual's strong network impacts firm performances and how weak networks affect the performance of the entrepreneur and firm.

Social capital has a vital role in entrepreneurship and has become a key area of research in management and social science (Coleman, 1990). Various studies of entrepreneurship have been made to measure and to evaluate the impact of social capital in different contexts. These include entrepreneurial intentions (Liao & Welsch, 2005) growth and performance (e.g., Maurer & Ebers, 2006) new venture financing. These studies reflect the significance of social capital for entrepreneurs and firms. Similarly, investigating the relationship between these variables by researchers has become a concern in entrepreneurship and management.  

Theoretical Framework

The Resource-based view

This theory states that capturing and possession of unique and scarce business resources makes the way of achieving competitive advantage and may contribute towards the growth of enterprises and their monetary goals (Barney, 1991). Firms should continue striving for owning resources and not restricting themselves to one set of resources. Any resources which generate knowledge and capabilities in a firm may be aimed at achieving the firm’s positive performance. Besides this, the resources generate value for firms and help in gaining competitive advantage (Helfat et al., 2007).




The Social Capital Approach

This embodies the evolving theoretic trend of social capital which represents the integral significance of social structures. Based on this approach, Nahapiet and Ghoshal (1998) defined social capital that facilitates transmission and access possessions and resources inherent in those networks of relationships. As association among individuals lies within networks, social capital is related to two fundamentals. One of them is Network characteristics and other is network content, resources which are gained through networks (Batjargal, 2003; Batjargal & Liu, 2004) 

In network characteristics, there exists two concepts and differences are highlighted in them, one of them is bonding and the other is bridging social capital (Gittell & Vidal, 1998). The former focuses on the association among individuals in a group where individuals are familiar with each other.  These include family and near acquittances. These networks are characterized by mutual trust, strong ties, and facilitate the transfer of resources among them (Davidsson & Honig, 2003). 

Bridging social capital is related to affiliation with different groups of individuals. These groups may be volunteer or professional networks (Davidsson & Honig, 2003). They provide valued resources to individuals and firms (Adler & Kwon, 2002). Another concept related to this is linking social capital that is vertical associations with influential groups and societies (Woolcock, 2001). The availability and access to these relationships support organizations and entrepreneurs. 

As per network content, resources that are rooted in individual associations make social capital (Batjargal, 2003) and these resources improve economical condition and performance of the firm. Scholars also defined resources of social capital as support or benefits in attaining knowledge (Dahlstrom, 2010).

Hypothesis

Following hypothesis have been generated:

1: Personal Network is positively and significantly associated with the Business Performance of SMEs

2: Professional Network is positively and significantly associated with the Business Performance of SMEs

3: Associative Network is positively and significantly associated with Business Performance of SMEs

4: Institutional Network is positively and significantly associated with the Business Performance of SMEs

Research Model

Entrepreneur’s Social Capital



Research Methodology

The research is quantitative in nature. In the quantitative analysis of data, generalizations are made to the larger population. The data is cross-sectional, it is collected at one point in time.




Data Collection and Sample Representation




The study is aimed at determining the association between social capital and Performance. The target population of the study is Small and Medium Enterprises in Sindh Province. There are around 3.0 million registered such establishments in Pakistan. From 3.0 Million, 18% are located in Sindh as per the last Economic Census of Pakistan (Zafar & Mustafa, 2017). The data of firms were collected from different governmental bodies and agencies including the Chamber of commerce of different cities. The nonprobability sampling method was employed to select firms from different cities of Sindh based on judgment-based sampling. Judgment based sampling dominates in entrepreneurship studies (Coviello &  Jones, 2004). 

Entrepreneurs are the respondents of the study who also assumes functions of top management. The final sample contained 395 observations that were found complete and included in the analysis. 




Measures




The Regression analysis technique has been used to identify the influence and impact of social capital.  The survey questions were grounded in the literature review. The questionnaire contains questions related to different networks of social capital and different parameters of subjective evaluation of performance All the measures were adopted from earlier studies.




Social Capital




Social capital was measured through personal, professional, associative, and institutional networks. Each network as a separate dimension has six questions. The questionnaire was developed on the study of social capital by Hernández, Camarero & Gutiérrez, 2017




Business Performance




Vorhies and Morgan (2005) “Business performance scale” has been adopted to measure performance. Business performance has been measured by the profitability of the firm over a competitor, the effectiveness of the firm in terms of market, and subjective measurement of customer satisfaction. 

Data Analysis

Respondents Profile

 

The sample profile is based on different demographics. It is classified on Gender, Age, Qualification, and Experience of entrepreneurs. Besides this, the experience of the owner in the firm is also included. In terms of Gender, most of the sample is from male as around 75% of respondents are male. In terms of age, the age bracket of 25-35 years dominates the research sample, next is a 36 to 45-year age bracket as 126 respondents are from that age group. Qualification wise, most of the respondents have a bachelor’s degree and around 35% of respondents have a master’s degree. Firms are divided into two categories Small and medium, 1-20 represents small and 21-250 employees represent medium enterprises. In the small category, there are 196 firms and in the medium category, there are 199 firms. In terms of entrepreneur experience in firms, most of them have experience range from 2 to 5 years.

 

Table 1. Respondent Profile

 

Demographics	Description	Number	Percentage
Gender	Male	293	74.17
	Female	102	25.82
Age	Below 25	36	9.11
	25-35	206	52.15
	36-45	126	31.89
	46-55	21	5.31
	Above 55	06	1.51
Qualification	High School	82	20.75
	Diploma	03	0.75
	Bachelor	172	43.54
	Masters	138	34.93
Employees	1-20	196	49.6
	21-250	199	50.4
Experience	0-1	18	4.55
	2-3	106	26.83
	4-5	102	25.82
	6-10	83	21.01
	More than 10	86	21.77

 

Reliability

 

It is the extent to which measurement tool produces stable and consistent results (Hair et., al, 2014). The generally used technique to evaluate and check the reliability of the study scale is Cronbach’s alpha (Hair et al., 2010). The alpha coefficient of 0.7 and more than 0.7 represents the significance of internal reliability (Schutte et al., 2000). that Cronbach’s alpha coefficients are adequate representing the better internal consistency of the questions. Keeping in view, the reliability analysis technique was used for dimensions of Independent Variable and Dependent Variable. Table 2 depicts Cronbach’s Alpha for both constructs. The Cronbach’s alpha coefficients of all dimensions are higher than 0.7, henceforth, revealing better internal consistency of the questions.

 

Table 2. Reliability

 

Construct	PRN                      PFN                      ARN                  IRN              PERF
Cronbach’s Alpha	0.897                    0.895                     0.946                 .942               0.94

 

Table 3. Model Summary

 

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	.668ª	.447	.44	6.80922	.447	78.696	4	390	.000

 

The Model summary suggests the strength of the relationship. R square determines the influence of the independent variable towards the dependent variable. This suggests that around 44% of the variation in business performance is explained by the model.  The Personal, Professional, Associative, and Institutional Network contributes commutatively in the prediction of the Business performance of SMEs by around 44%.

 

5.3 ANOVA

 

Table 4. ANOVA^b

 

Model	Sum of Squares	df	Mean Square	F	Sig.
Regression	14595.116	4	3648.779	78.696	.000a
Residual	18082.545	390	46.366
Total	32677.661	394

a.     Predictors: (Constant), IRN, PRN, PFN, ARN

b.     Dependent Variable: Perf

The ANOVA table reflects how well the regression equation fits the data. It suggests that the model predicts business performance significantly well since the statistical significance level is less 0.05. It may be inferred that the regression model significantly predicts the outcome variable.

 

Hypothesis Testing

 

To test a hypothesis or to evaluate which variable contributes towards the prediction of the dependent variable, values of Beta and significance are used in regression analysis. Simultaneously, the correlation technique is also considered to investigate the strength of the relationship among variables.

 

Hypothesis One: The sign of the regression coefficient reflects a positive or negative relationship. The Beta value for Personal network is .009 which suggests a positive relationship of personal relationship network with business performance, but the level of contribution is less. Similarly, the value of Sig. which is more than 0.05 tells that the personal relationship network variable is not making a significant contribution to the prediction of business performance. The value of the Pearson correlation is .266 which also signifies a weak relationship. Thus, hypothesis one is rejected based on the significance level and Beta value. Hence it may be concluded that The Personal Network has no significant relationship with business performance.

 

Hypothesis Two: The value of Beta signifies a positive relationship of a professional network with business performance. The highest value i.e. 0.45 suggests that the variable makes the strongest contribution to predicting business performance. The Sig. value <.05, making relationship significant. The value (0.634) of correlation also represents a moderate to a high level of relationship between a professional network and business performance.

 

Table 5. Coefficients

 

Model		Unstandardized Coefficients		Standardized Coefficients	T	Sig.
		B	Std. Error	Beta
1	(Constant)	23.007	1.645		13.985	.000
	PRN	.015	.066	.009	.230	.819
	PFN	.751	.088	.457	8.493	.000
	ARN	.043	.093	.322	4.458	.000
	IRN	.314	.081	.253	3.886	.000

 

 

Table 6. Correlations

 

		PRN	PFN	ARN	IRN	Perf
PRN	Pearson Correlation	1	.395**	.326**	.333**	.266**
PFN	Pearson Correlation	.395**	1	.681**	.629**	.634**
ARN	Pearson Correlation	.326**	.681**	1	.807**	.544**
IRN	Pearson Correlation	.333**	.629**	.807**	1	.563**
Perf	Pearson Correlation	.266**	.634**	.544**	.563**	1

a. Dependent Variable: Perf

 

Hypothesis Three: The associative network relationship with business performance is moderate as the value of correlation is 0.544. Furthermore, beta value also represents a positive relationship. The relationship is significant as the significance level is less than 0. 05. Based on these values, Hypothesis three is also supported.

 

Hypothesis Four: The Beta value for the Institutional relationship network is .253 which suggests a positive relationship with business performance, but the level of contribution is less compared to professional and associative networks. However, the value of Sig. is .000 which tells that relationship is making a significant contribution to the prediction of business performance. The value (0.563) of correlation also represents a moderate to a high level of relationship between these two variables. Hence it may be concluded that Institutional Network has a significant relationship with business performance.

 

Table 7. Summary of Hypothesis

 

Hypothesis	Path	Result
H1	Personal Network               Business Performance	Rejected
H2	Professional Network               Business Performance	Accepted
H3	Associative Network                  Business Performance	Accepted
H4	Institutional Network                Business Performance	Accepted

Discussion

The relationship of four networks with business performance is separately analyzed to determine its impact. Three hypotheses out of four were accepted based on the statistical measures employed in the study. Hypotheses No.1 which investigated the relationship of personal networks with business performance was rejected based on statistical values, representing the insignificant impact of Personal Network on business performance. It can be inferred that relationships with close social circles like family, friends, and neighbors do not help in acquiring resources and in influencing business performance. Hypothesis 02 investigated the relationship of Professional Network with Business performance. It evaluates whether the relationship with business suppliers, customers, partners, and professional fellows helps in generating resources to enhance business performance. Results have confirmed the relationship of a professional network with business performance and hypothesis is accepted which represents a positive and significant relationship of a professional network with performance. Hypothesis 03 which evaluated the relationship of associative network with business performance is also accepted based on research results and it represents that relationships with volunteer organizations like religious groups, trade unions, etc. contribute towards the development of business and its growth.  Finally, hypothesis 04 based on evaluation of the relationship of institutional network with business performance is studied and based on the statistics generated through quantitative data relationship was found to be significant and positive. It confirms that relationship with public and private institutions facilitates in enhancing business performance.   

It may be inferred from all hypotheses of social capital and reported that there is a link among social capital resources and business performance of small and medium enterprises. 

Conclusion and Implications

The research reflects that Social Capital including networks are correlated with the performance. The social capital network generates resources for entrepreneurs and through these resources, social capital network enhances business performance. Furthermore, it is also concluded that not all networks of social capital facilitate entrepreneurs to access relevant resources. In the current study based on entrepreneurs of Sindh, it has been found that that Professional, Associative, and Institutional network contributes towards economic benefits. The findings of social Capital are consistent with the theoretical framework of social capital which values relationships and networks for gains of individuals and social capital role in assessing resources for benefit of business. It may also be inferred that social capital like human and financial capital, has also become important capital to own resources for firms and contributes towards the performance of firms.

The research has recognized the importance and role of social capital networks towards the field of entrepreneurship and in enhancing the business performance of SMEs. By looking at the findings of the study, Entrepreneurs may assess types of relationships that may be developed, maintained, and invested in. They should put effort to identify relationships that may contribute towards owning resources and facilitates business performance. 

The research may be taken as a guideline for entrepreneurs to participate themselves in social activities, associations, trade unions, and business events to strengthen network because networks are found to have a positive and substantial impact on performance. 

Limitations and Future Directions

The study is generalized to all SMEs operating throughout different industries. The outcome may vary in each industry. Secondly, data is mostly collected through convenient sampling from different cities of Sindh province. Due to resource and time constraints, data could not be collected from a few districts. 

Different variables may moderate the relationship between these variables.  Similarly, the study may be conducted further in Sindh Province by targeting different industries and study may be replicated in other provinces of Pakistan.  

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