Relationship between business information, business networking, access to finance and financial performance of social enterprises: Perspective of resource-based view and signalling theory

Abstract

The objective of this paper is to explore the relationship between business information, business networking, access to finance and financial performance of social enterprises. It broadens on theoretical threads from the perspective of resource-based view theory and signalling theory. Hypotheses are tested to assess the possible effect of business information, business networking, access to finance as well as financial performance of social enterprises. A cross-sectional survey was conducted by using the standardized questionnaire to collect primary data from a total of 384 owners/directors of social enterprises. Simple random sampling method was applied to select social enterprises functioning in the country. A Partial Least Square Structural Equation Modelling was applied to examine the data. This study found a positive and significant direct relationship between business information, access to finance, and business networking on financial performance of the social enterprises in Pakistan. The results supported the moderation effect of access to finance on business information and financial performance whereas, access to finance does not have a significant moderation impact between business networking and financial performance. Therefore, this study recommends that social enterprises in Pakistan should provide great emphasis on business networking and business information to introduce financially creative solutions for the societal problems, which are essential for overall wellbeing of different stakeholders of the social enterprises.

Keywords:

• business networking
• business information
• access to finance
• financial performance
• signalling theory
• resource-based view theory

1. Introduction

The term social enterprise (SE) is relatively new, and over the course of the past two decades, people in several regions of the world have shown a rising interest in this sector (Kraus et al., 2014). The concept of SE was firstly used in Europe during the 1980s, but the term was not extensively applied until the 1990s. This type of business exists in the third sector, which is situated between markets, government policies, and public societies (Defourny & Nyssens, 2006). Scholars and business professionals are becoming more and more interested in social enterprise, which is shown by the increasing many research network systems and academic forums in this field (Kraus et al., 2017). Despite the fact that there is no widely accepted definition of social enterprise (Alegre et al., 2017). According to Yunus (2020) SEs may combine social benefit and personal profit, and mostly, it is a combination of both personal profit and social benefit.

There are two primary schools of thought (Dees & Anderson, 2006). First one, the Social Enterprise School of Thought says that social enterprises are the companies that are focused on the market and use a strategy to make money to fulfil a social mission. The second one is, The Social Innovation School, says that social enterprises are businesses that solve social issues or meet social needs. The researchers used the definition of DiDomenico et al. (2010), for this research, which not only gains a solid reputation among academics, but also appears to successfully combine the two above- mentioned points of view (i.e., Social Enterprise School of Thought). Based on these writers, SEs are businesses that try to reach a social goal or set of goals by selling products and/or services. By doing this, they hope to be able to support themselves financially without help from the government or other donors. This definition also fits with the European idea of SE, which is the businesses with a social mission and a clear financial incentive for doing it. Social enterprises (SEs) may combine social benefit and personal profit, and mostly, it is a combination of both personal profit and social benefit (Yunus, 2020). SEs are those types of organizations that possess the characteristics of the profit of the businesses and for organizations that are connected to the society and community. They normally deal with both financial and social resources to generate the activities for the enterprise and the benefit of the society in a broader perspective (Somerville & McElwee, 2011).

More and more people are starting to realize that social enterprises play a key role in solving problems in society by using new approaches, especially when resources and skills are limited (DiDomenico et al., 2010). The performance of these enterprises is low due to critical factors, lack of access to finance, lack of business networking (Asad et al., 2016). Business information, access to finance and business networking have been seen as valuable resources that increase the financial performance for a long time in the business. The ideas of business information, access to finance and business networking stand out in the existing literature. Business network is a group of businesses that work together to achieve their business goals (Ozcan & Eisenhardt, 2009). Most of the time, these objectives are both operational as well as strategic, and business networks utilise them in accordance with their position in the competitive environment of the market (Ford et al., 2014). Business network is a social business network that enables business people to join and interact with other entrepreneurs and executives in order to develop business interests through the formation of mutually profitable business connections (Soda et al., 2004). Business network is one of the strategically key resources that makes it possible for small businesses to expand in an environment that is both dynamic and competitive in the business world. Business networks connect small business owners and other owners of medium and small enterprises (SMEs) with other persons and companies in order to gain, share, as well as exchange information and resources (Machirori & Fatoki, 2013).

Business information is observed as one of the very important sources in any industry (Okello-Obura et al., 2008). Business information has been a very useful resource in every sector or sub-sectors of the economy of the country. It was listed as the fourth factor of output. No doubt, the organizations and the governments of the developed world are spending a great deal on this achievement. This is because the collection of the true information would lead to the quality choices that will have an impact on revenue and overall performance (Ojo et al., 2015).

Ability to gain advantage from both internal and external sources of financial support, with financial and non-financial barriers being kept to a minimum or removed completely. Access to finance plays a role as an external resource (Anwar et al., 2018). Access to important resources, like finance, is one of the most essential and important elements that encourage business activities in the economy (Xavier et al., 2013).

In Pakistan, social entrepreneurs face many problems, like lack of business networking, financial difficulties, an insufficient amount of information, bad infrastructure, and using old technology. All of these things make it hard for small businesses to grow and ultimately poor performance (Sherazi et al., 2013). In a country such as Pakistan, it is strongly recommended that SEs develop the awareness that will have a major effect on their performance (Ahmed et al., 2019). SEs’ performance is influenced by a wide range of factors, including business information, access to finance and business networking (Anwar et al., 2018; Bhattaraia et al., 2019; Caseiro & Coelho, 2019). But there is not any evidence on measuring the impact of business information, access to finance and business networking on the performance, particularly financial performance of SEs in Pakistan.

So, the aim of this article is to analyse the impact of business information, access to finance and business networking on the financial performance of SEs in Pakistan. According to best knowledge of the researchers, this research is the first academic effort to conduct a comprehensive analysis on the business information, access to finance, business networking, and financial performance of the SEs in Pakistan.

2. Literature review and hypotheses development

It is agreed that the performance is a multi-dimensional phenomenon (Gerba & Viswanadham, 2016). Previously, researchers have used growth and success as indicators that can be interchangeable for business performance (Wiklund & Shepherd, 2005).

Measuring the performance of SEs might be useful in the process of decision-making, as it would provide SEs with the information, they need to locate new opportunities and enhance the effectiveness and profitability of their operations (Arena & Azzone, 2010; Haider et al., 2017)). SEs are involved in a variety of business sectors, including education, service sectors, agriculture, health, as well as social services; thus, their organizational structures are different from one another (Alter, 2004), it may result in the use of different metrics for assessing their performance (Herman & Renz, 1997; Hussain et al., 2023). This research provides relevant measuring dimensions for a SE. It focuses specifically on financial performance as methods to measure performance of the SE.

Bae et al. (2018) carried out a study in South Korea about the performance of the social enterprises. By using network centrality, researchers analysed the financial performance of social businesses. This study measured financial performance by using return on sales, growth rate of sale, and growth rate of net profit. According to the findings, a social enterprise that maintained a higher degree of centrality within the network of frequent meetings was able to produce better results on financial performance.

Another study by Cheah et al. (2019) conducted in Malaysia and Singapore. According to a resource-based perspective, this empirical research developed a framework to evaluate the impact of the most important internal oriented resources, business planning, entrepreneurial orientation, as well as social salience on the financial performance of social enterprises. This study measured financial performance by using increase in revenue, increase in sales, and net profit. The findings of this study showed that internally oriented resources have a significant effect on financial performance.

2.1. Access to finance and performance

Access to finance is defined as the ability of individuals, households, entrepreneurs, and companies to access and utilize various financial services if they choose to do so (Adomako et al., 2016). Access to Finance increases financial inclusion and contributes to the deepening of the financial sector and overall economic growth. Access to finance also plays an essential role in the development of Small and Medium Enterprises (SMEs) (Kimani & Ntoiti, 2015). Moreover, the results of previous studies found that business information of the SMEs increase their access to financial resources through the timely dissemination of business information that can be used to related parties, such as bankers or lenders, thereby convincing funders. However, SMEs with business information, have good impact on access finance (Mashizha & Sibanda, 2017).

In addition, the result of previous studies found that resources like business information improves the access to finance, thereby improving business performance (Adomako et al., 2016; Hussain et al., 2018; Kimani & Ntoiti, 2015).

According to the above-mentioned discussion, the present study develops the following hypotheses.

H1:

Access to finance has a positive and significant effect on the financial performance of social enterprises in Pakistan.

H4:

Access to Finance moderates the relationship between business information and financial performance of social enterprises in Pakistan.

2.2. Business information and performance

Business information is observed as one of the very important sources in any industry (Okello-Obura et al., 2008). A common concept of the information is that it is the data that has been organized in such a way that it becomes meaningful. It includes a method that is used to create information that includes gathering the data and then exposing them to a process of transformation to create knowledge. The discrepancies between good and poor information can be recognized by evaluating whether the quality of the information has a few or all the attributes. The attributes can be relevant to the timing, content, and type of information (Hardcastle, 2008).

There is a fact that using the sources of business information supports the overall business performance. Haliso and Okunfulure (2010) confirms that use of business information by companies adds to the competitive edge that is required to support their enterprise. Similarly, Okello-Obura et al. (2008) mentioned that business information has become a leading source and relies on handling and usage. Keh et al. (2007) revealed that there was a significant and a positive relation between information use and the performance of SMEs. Moorthy et al. (2012) also supported were exposed that there is also a positive and a significant relation between usage of marketing information as well as the performance of the small medium enterprises in Malaysia.

A study conducted by Xiaoqing et al. (2019) to see the relationship of information, traditional social activity, gender, and education on the performance of the small businesses in China. This research measured business information by categorized into five stakeholders, supplier information, government information, distributor customer, competitor information as well as society related information. The findings of the research showed that information about government as well as policies of the industry has a positive and substantial effect on the performance. Moreover, gender as well as education have moderating impacts on the relation between information and performance in a small firm.

According to the existing literature, this research attempts to develop the following hypotheses to recognize the impacts of business information on the financial performance (FP) of the SEs in Pakistan. Bunyasi et al. (2014) described in their research on the effects of accessing business information on the financial performance of small medium enterprises that access to business information has a significant effect on performance of small medium enterprises. Nguyen et al. (2022) described a positive relation between social activities and financial performance. Jamaludin et al. (2022) and observed a positive impact on performance. Moreover, the research conducted by Okoro et al. (2019) demonstrated that business information has a substantial and favourable impact on the performance of MSMEs. The authors eventually described based on the data that BI enhances the performance. Therefore, in the light of previous discussion, this research develops the following hypotheses.

H2:

Business information has a positive and significant effect on the financial performance of social enterprises in Pakistan.

2.3. Business networking and performance

The network of SEs and social entrepreneurs can play a vital role in communicating best practices. They tie social companies to other organizations, with similar features and goals to help to establish a platform for cooperation and assisting in the spread of people and ideas (DCMS & BEIS, 2017). When contractors begin to plan a new project and attaining information, learning new skills, tools, and business connections, they need to mobilize a broader social network and involve people, they may need in the future and most likely be part of the preparation process (Greve, 2003). A significant correlation between business networking and performance was found in some previous studies (Cisi et al., 2016; Kim & Lee, 2018; Zacca et al., 2015). Another study was done in Pakistan to see the relationship between business networking and performance of small enterprises and found a positive and significant relation between them (Asad et al., 2016).

Mlotshwa (2019) performed research in South Africa. This study explained the relation between business networking, social networking, managerial networking, and performance. This study measured business networking by categorized into six stakeholders, relationships with government agencies, relations with your competitors, relations with suppliers, and relations with customers, member of association, and participation in trade fairs and seminars. According to the results of the research, business networking and managerial networking management have a positive effect on business performance. Networking activities help to gather environmental change information quicker and to respond to changes to external resources. Thus, the financial performance can be affected by interactions in the society and business networking have a positive and significant effect on the performance of SEs (Cho & Kim, 2017).

ALI and LI (2021) conducted a study in China and described that networking positively effect on the financial performance of social enterprises. Another study was conducted in Brazil by (dos Santos et al. (2021) and found a positive and significant impact on networking and financial performance. Bae et al. (2018) carried out a study in South Korea about the networking and financial performance of the social enterprises. They found a positive and substantial relation between business networking and financial performance of the SEs. A study was conducted in Pakistan and described that business networking has a moderated effect on performance of small enterprises (Asad et al., 2016). According to Canning and Szmigin (2016) described that improving network expertise enables entrepreneurs to gain access to the vital tools owned by others to achieve the better performance of the industry. So, this research develops the following hypothesis.

H3:

Business networking has a positive and significant effect on the financial performance of social enterprises in Pakistan.

Business networking play a positive role to strengthen and boost the relationship between access to finance and performance of MSEs (Wales et al., 2013). The role of access to finance helps the small enterprises to perform better than those MSEs that have certain issues accessing finance (Newman et al., 2014). Thus, these studies indicate a positive relationship between access to finance and performance of MSEs. But on the other hand, a few studies contradict the existence of positive relationship between access to finance and performance of MSEs (Mochona, 2006; Thio et al., 2006). Le and Nguyen (2009) described a study in Vietnam and suggest that the relationship between business networking with suppliers and social ties and access to finance and SMEs growth have insignificant.

A study was conducted in the Buffalo City Municipality in the Eastern Cape Province of South Africa by Leroy (2012). This study investigates the impact of networking on access to finance and performance of small and medium enterprises (SMEs). The objectives of this study are to examine whether networking is related to access to finance and performance. The results reveal that there is a positive relationship between networking and access to finance and performance of SMEs. The results of this study further reveal that access to finance partially mediates the relationship between networking and performance of SMEs. According to the above-mentioned discussion, this study develops the following hypothesis.

H5:

Access to Finance moderates the relationship between business networking and financial performance of social enterprises in Pakistan.

2.4. Supporting theories

The resource-based view (RBV) and the signalling theory supported as the foundation for the development of this research framework. It is presumable that the performance will be affected by the independent variables in this piece of writing, which is supported by the resource-based view theory. In addition, the connection between information about a company’s operations and the performance of those operations is frequently thought to be more consistent with the signalling theory.

The resource-based view, also known as the RBV theory, has emerged as one of the most prominent performance theories. In today’s business world, the resource-based view theory is widely regarded as one of the most impactful schools of thought concerning entrepreneurship (Barney & Barney, 1991). In the performance of the social enterprises industry, the resource-based view has been a frequently discussed (Dees, 1998). For example, the works of Lee (2018); Liu et al. (2015) and Liu et al. (2014) are few empirical studies in the area of social enterprises that also applied the RBV theory. It is essential that the fact that not all resources have a significant effect on organizational performance be taken into account. Some of the resources that are utilized and controlled by the company, specifically those resources that are valuable, rare, inimitable, and non-substitutable (VRIN), have the ability and potential to develop the competitive advantage, which results in better performance (Barney & Barney, 1991).

Barney and Barney (1991) gives a more detail description of a company’s resources, which includes physical, human, and organizational resources in addition to other types of resources. Intangible resources of the company include things like human capital and organizational structure, whereas tangible resources include things like inventory and machinery. Most of the research on RBV has focused on intangible assets like business information and business networking (Sampler, 1998). Information is one of the most valuable resources of any organization (Shafiee & Moqadam, 2017). Access to finance plays a role as an external resource (Anwar et al., 2018). Business networks are composed of intangible resources, and small businesses enhance their performance in a highly competitive market by leveraging these intangible resources (Machirori & Fatoki, 2013). A better and more extensive use of networking activities in SEs leads to excellent performance (Squazzoni, 2009).

Signaling theory is used to strengthen the link between information about a business and performance. Signaling theory is useful for figuring out the behaviour of two parties (individuals and organizations) which receive the information (Certo et al., 2011). Signaling theory examines the link between signals and their qualities, which explains why some signals are accurate and other signals are not (Donath, 2007). Business information has a positive and significant effect on businesses and helps them to increase the performance (Asif et al., 2021; Keh et al., 2007). Companies can increase the performance if they have access to the right information (Bendoly & Swink, 2007).

The proposed relationship among the variables in this study can be presented in a graphical format as below (Figure 1).

Figure 1. Research framework.

3. Methodology

3.1. Survey design, sample size and sampling technique

In order to compile the primary data and ensure that the research was successful in achieving its goals, it was designed and carried out as a cross-sectional survey. The organization, and more specifically the social businesses that are registered in Pakistan, serves as the unit of analysis for this particular research. The survey was carried out completely online across the entire country of Pakistan.

The participants in this study are Pakistani organizations that are officially recognized as social enterprises. The majority of SEs in Pakistan are found in the informal sector. In Pakistan, there are approximately 3.2 million companies that have been officially registered; however, very close to 90 percent of these companies fit the definition of a small business (SMEDA, 2018). However, the number of SEs is not reported in any record that has been made public by the government. The number of registered SEs can only be found in the report that was put out by the British Council (2016), which states that there are 448,203 organizations. This research estimates the sample size using the table developed by Krejcie and Morgan (1970) based on the data presented here. This research decided to employ a sample size of 384.

The list of the data compiled from various sources, including (PPAF, SMEDA, SECP, NRSP, and the British Council in Pakistan), as well as from the WhatsApp community groups of SE owners and managers which was made by British Council during the programme of “The State of Social Enterprise in Pakistan”. In this research, a simple random sampling technique was applied. Each person in a population has an equal chance of being chosen for a sample that is drawn at random from that population. A population that is both small and homogenous is preferable if it can be achieved. The random numbers that were collected will serve as the basis for selecting the various components. When the sample size is low, it is simple to calculate, but it becomes impractical when the sample size is high. Moreover, Beh and Shafique (2016) stated that There was a response rate of 46% from the Pakistani small businesses. The number of businesses that were included in this study’s sample was increased to 700 in order to achieve a high level of participation and reduce the influence of the non-response error (Salkind, 2012).

3.2. Data collection procedure

The data were obtained by selecting a subset of respondents to answer questions presented in an online survey. We obtained the respondents’ email IDs and other contact information from the State Bank of Pakistan as well as from the WhatsApp community groups that directors and managers of SEs belong to. The survey’s questionnaire was emailed to all 700 respondents, along with a request for their participation in the survey, and the total number of respondents was 700. After a week had gone, a gentle reminder in the form of an email asking respondents to fill out and return the questionnaire was delivered to their e—mails. There was a total of 384 people who participated in the study and provided feedback. Therefore, there were a total of 384 directors and managers of social enterprises included in this study’s sample. The participants were asked to provide their responses and opinions in an unbiased manner.

3.3. Measurement of the variable

Business information (BI), access to finance (AF), and business networking (BN) are included in this research to evaluate the financial performance of the SEs in Pakistan. The variables as well as their measurements are defined below.

The financial performance was assessed by adapting the financial performance indicators created by Lee (2018).This research will measure financial performance by using return on investment (Bakar et al., 2014; Lee, 2018), sales growth (Abbas et al., 2019; Bhattaraia et al., 2019; Lee, 2018; Li & Zhang, 2007; Zhou et al., 2005), market share growth (Gali et al., 2020; Li & Zhang, 2007; Zhou et al., 2005), and profit growth (Bhattaraia et al., 2019; Gali et al., 2020). The financial performance (return on investment, market share growth, sales growth and profit growth) was measured by asking the respondents from one of the seven options: 0%, 1–10%, 11–20%, 21–30%, 31–40%, 41–50%, or over 50% (Lee, 2018).

Business information has the ability to contribute to success, and organizations must have accessibility to adequate information, sources of information and challenges of information to boost productivity and to assist market access. Business information was measured by adapting scale of Ojo et al. (2015). This study used 7-point Likert- scale (1 is strongly disagree, and 7 is strongly agree). This study measured business information by using availability of information (Chiware, 2008; Ogunsola & Babalola, 2020; Ojo et al., 2015), accessibility of information (Ogunsola & Babalola, 2020; Ojo et al., 2015) and quality of information (Chavez et al., 2015; Gorla et al., 2010; Li & Lin, 2006).

Access to finance refers to the availability of various forms of financial resources, including internal resources, loans, and equity. Access to finance was measured by adapting scale of (Dzomonda, 2022). This study used 7-point Likert- scale (1 is strongly disagree, and 7 is strongly agree).

The basic objective of business networking is to inform others about your company and, ideally, convert them into your clients. Business networking adapted scale by using 7-point Likert- scale (1 is strongly disagree, to 7 is strongly agree) from (Mlotshwa, 2019). This research measured business networking by using networking with suppliers (Abbas et al., 2019; Huang et al., 2012; Mlotshwa, 2019), networking with customers (Abbas et al., 2019; Huang et al., 2012; Mlotshwa, 2019), networking with competitors (Abbas et al., 2019; Huang et al., 2012; Mlotshwa, 2019), networking with society (Bucktowar et al., 2015; Cho & Kim, 2017) and networking with complementary business which would be the contribution in business networking. All the questionnaires are attched in appendix one.

To summarize, a seven-point Likert scale was used to assess the business information, access to finance and business networking variables, and one of the seven options was chosen to evaluate financial performance. At each point on the scale, the participants indicate the degree to which they agree or disagree with the corresponding statement. On the scale, 1 = “strongly disagree”, 2 = disagree“, 3 = slightly disagree, 4 =neutral”, 5= slightly agree“, 6= agree” and 7= strongly agree”.

The first part of the analysis was carried out by concentrating on the demographic profile of the participants, which will include aspects such as age, gender, education, managerial position in the firm’s hierarchy, and the type of industry. The SPSS version 25 was used to perform the descriptive analysis, which consisted of calculating the mean, minimum, maximum, and standard deviation. In the second section of the investigation, a method called partial least squares structural equation modelling (PLS-SEM), which is also called as variance-based structural equation modelling (SEM), was applied with the help of the SmartPLS 3.3.2 software.

4. Analysis of the data and findings

4.1. Demographic profile of the respondents

As indicated in Table 1, this section provides an account of the individuals who contributed to the research. The information that pertains to those who participated in the survey is included in the demographic data. The demographic information for the people who took part in this research is presented in Table 1. In terms of demographics, the proportion of male respondents was 61.72%, while the proportion of female respondents was 38.28%. According to the table, 8.07% of respondents were between the ages of 21 and 29 years, 35.68% of respondents were in between the ages of 30 and 39, 37.24% of the participants were between 40 to 49 years old, 10.42% of participants were between 50 to 59 years old, and 8.59% of respondents were over the age of 60. As a result, the majority of the respondents consist of 37.24% from age between 30 and 39 years old.

Table 1. Demographic data

Demographics	Frequency	(%)
Male	237	61.72
Female	147	38.28
From the age group
21 to 29 years	31	8.07
30 to 39 years	137	35.68
40 to 49 years	143	37.24
50 to 59 years	40	10.42
60 years and above	33	8.59

4.2. Assessment of the measurement model

In this research, the researchers investigated both the validity and the reliability of the model that was employed in the process of analysing the outer model (also called measurement model), which served as the basis for the research. Figure 2 presents an illustration of the outer factor loadings for the comprehensive measurement model used in this research. It is abundantly clear that all of the components had values that were substantially higher than the bare minimum requirement of 0.70. The findings indicate that the outer factor loadings are adequate to enable the model to be accommodated within the framework (Figure 2). As a result, the model can be utilized in the subsequent stage of the analysis process, which is the reliability and validity test.

Figure 2. Assessment of the measurement model.

4.2.1. Internal consistency reliability and convergent validity

In order to determine the reliability of the model’s internal consistency, it was necessary to investigate the composite reliability (CR) of the model. Table 2 showed that every value was higher than 0.60, which indicates that the criteria were satisfied and that the conditions were met (Sarstedt et al., 2019). Similarly, convergent validity is defined by (Hair & Ringle, 2017) as to what extent a latent construct is able to define the variance in its indicators. In addition, Table 2 depicts that fifty percent of the total variance is identified by each of three variables (AVE is greater than 0.50), which is higher than the cut-off value provided by (Hair & Ringle, 2017).

Table 2. Indicator loadings, internal consistency reliability, and convergent validity

Construct	Items	Loadings	Cronbach’s Alpha	Composite Reliability	Average Variance Extracted
Business Networking	BN1	0.818	0.910	0.927	0.614
	BN2	0.811
	BN4	0.738
	BN5	0.825
	BN6	0.807
	BN7	0.767
	BN8	0.755
	BN10	0.741
Financial Performance	FP1	0.729	0.712	0.822	0.536
	FP2	0.683
	FP3	0.816
	FP4	0.694
Access to Finance	AF1	0.902	0.903	0.932	0.774
	AF2	0.877
	AF3	0.864
	AF4	0.876
Business Information	BI1	0.762	0.976	0.978	0.654
	BI2	0.782
	BI3	0.832
	BI4	0.779
	BI5	0.83
	BI6	0.838
	BI7	0.804
	BI8	0.815
	BI9	0.827
	BI12	0.786
	BI13	0.79
	BI14	0.811
	BI15	0.816
	BI18	0.803
	BI19	0.799
	BI20	0.848
	BI21	0.815
	BI22	0.838
	BI23	0.83
	BI24	0.818
	BI25	0.831
	BI26	0.795
	BI27	0.745

4.2.2. Discriminant validity

The square root of the AVE, which was supported by Fornell and Larcker (1981) defines discriminating validity. In addition to this, the value of the square root of the AVE should be greater than the values of the latent variable, which will indicate discriminating value. Table 3 reveals that the value of the whole diagonal is greater than the value of the other latent variables. In a similar vein, the second requirement is to determine whether or not the construct is valid (Gold et al., 2001; Kline, 2015). This finding suggests that the measurement model used in this research does not contain any errors. In other words, the discriminant validity was achieved by the factors that were taken into account in this study.

Table 3. Discriminant validity matrix

	Access to Finance	Business Information	Business Networking	Financial Performance
Access to Finance	O.880
Business Information	0.566	0.809
Business Networking	0.518	0.702	0.783
Financial Performance	0.505	0.689	0.636	0.732

4.3. Assessment of the structural model

In this research, the structural model was analysed as a follow-up to the measurement model that was previously examined. According to the Sarstedt et al. (2019), a structural model can assist in analysing the path coefficients as well as the t-values of the direct and indirect links in order to achieve a better understanding of how they interact with one another. Additionally, Henseler et al. (2009) said that in order to determine whether or not the relation is significant, the t-value needs to be greater than 1.64. This value will then be used to guide decision-making regarding the hypotheses presented earlier. Figure 3 illustrates the structure model for the study that was used. For the purpose of measuring the structural model of this research, PLS-SEM algorithm and the bootstrapping approach were utilized. The evaluation of the structural model includes to investigate the connections between the latent constructs. Figure 3 illustrates the connections (also known as “paths”) that can be made between exogenous constructs and endogenous constructs. During the evaluation of the structural model, each and every one of the direct relationships (also known as direct hypotheses) was put to the test.

Figure 3. Assessment of structure model.

5. Hypotheses testing and discussion

Table 4 shows that the hypotheses that were supported in this study have an at-value greater than 1.64. So, out of five (05) hypotheses that were tested in this study, four hypotheses were supported, and one hypothesis was rejected. The first hypothesis is verified, which indicates that the relationship between access to finance and financial performance is positive and significant (beta value = 0.257; t = 4.257; P = 0.000 and P < 0.05). This confirms that the first hypothesis is accepted. Likewise, the findings show that the second hypothesis, which says that business information has a positive and significant impact on financial performance, is also accepted (beta = 0.369; t = 5.596; P = 0.000, and P < 0.05), which demonstrates that the second hypothesis is supported by the data. Similarly, the results demonstrate third hypothesis, that business networking has a significantly positive impact on financial performance (beta = 0.234; t = 3.225; P = 0.001 and P < 0.05).

Table 4. Summary of the results of hypotheses testing

	Relationship	Std. Beta	Std. Error	t Values	p Values	5.00%	95.00%	Decision	R^2	Q^2
H1	AF→FP	0.275	0.064	5.447	0.000	0.162	0.372	Accepted	0.570	0.285
H2	BI→FP	0.369	0.066	6.087	0.000	0.255	0.473	Accepted
H3	BN→FP	0.234	0.073	4.151	0.001	0.119	0.357	Accepted
H4	BI→AF→FP	0.127	0.054	2.324	0.010	0.038	0.213	Accepted
H5	BN→AF→FP	0.002	0.057	0.037	0.486	−0.089	0.097	Rejected

Note: BN = Business Networking, AF= Access to finance, BI = Business Information, FP = Financial Performance.

6. Moderation analysis

The aim of this study is to determine whether the moderator (access to finance) play a significant effect on the relationship or not. Furthermore, using SmartPLS software, the PLS algorithm calculated the standard beta coefficient value, and R² value for access to finance and financial performance respectively. However, to calculate the T-value and p-value results, the study followed the bootstrapping procedure.

Table 4 revealed that access to finance significantly moderates the relationship between business information and financial performance. Hypothesis (H4) results revealed that access to finance has positive and significant moderate the relation between business information and financial performance (beta = 0.127; t = 2.324; P = 0.010 and P < 0.05). According to the analysis results, this hypothesis is accepted. On the other hand, the findings of the fifth hypothesis show that access to finance has a positive but insignificant moderate relationship between business networking and financial performance, so this hypothesis is rejected (beta = 0.002; t = 0.037; P = 0.486, and P > 0.05), which demonstrates that the fifth hypothesis is not supported by the data.

As in moderation analysis, the change in R² is an essential matter (Ramayah et al., 2018). For the current study, the previous R² for financial performance (before interaction term) was 0.570, while the value of R² for financial performance (after interaction term) became 0.586. this change of 0.016 indicates that with the addition of interaction term, the R² had got additional variance of about 1.6%. The effect size (f²) of moderating relationship is calculated through the effect size (f²) equation below. The result of effect size (f² = 0.039) is large as per guidelines of Aguinis et al. (2005) and Kenny (2018) regarding effect size (f²) of moderation analysis (i.e., 0.005, 0.01, 0.025 for small, medium, and large respectively).

$\mathrm{E}\mathrm{f}\mathrm{f}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}\left(\mathrm{f}2\right)=\frac{\mathrm{R}2\hspace{0.17em}\left(\mathrm{i}\mathrm{n}\mathrm{c}\mathrm{l}\mathrm{u}\mathrm{d}\mathrm{e}\mathrm{d}\right)-R2\left(excluded\right)}{1-\mathrm{R}2\hspace{0.17em}\left(\mathrm{i}\mathrm{n}\mathrm{c}\mathrm{u}\mathrm{l}\mathrm{d}\mathrm{e}\mathrm{d}\right)}$

$\mathrm{E}\mathrm{f}\mathrm{f}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}\left(\mathrm{f}2\right)=\frac{0.586-0.570}{1-0.586}$

$\mathrm{E}\mathrm{f}\mathrm{f}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}\left(\mathrm{f}2\right)=\frac{0.586-0.570}{1-0.586}$

$\mathrm{E}\mathrm{f}\mathrm{f}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}\left(\mathrm{f}2\right)=0.039$

7. Discussion

The research investigated whether or not there was a correlation between business networking and the financial performance of social enterprises. The goal of this research is to explore the effect of business networking, access to finance and access to relevant business information on financial performance of Pakistan’s SEs. Two different independent variables and one moderator were selected so that their influence on the dependent variable could be evaluated. Five (05) hypotheses were developed and formulated based on this research goal and the underlying issues that needed to be addressed. In order to carry out the statistical analysis, the software programs SPSS version 25 and PLS-SEM version 3.3.2 were utilized throughout the process. Four hypotheses have a positive and significant relationships on the social enterprises that are located in Pakistan, but one indirect hypothesis has insignificant relationship.

The findings and results of this research revealed that there is a correlation that could be deemed statistically substantial between the business information and the financial performance of the SEs. This finding lends support to the first hypothesis by showing that business information does, in fact, improve financial performance (H1). These findings demonstrated that there is a correlation between the two variables. According to the findings, there is a significant demand for information that could be of use to your company from the perspective of gaining a competitive advantage (Khan et al., 2021). By integrating its internal and external environments through the utilization of business information, a social enterprise is also able to broaden its scope of operation all the way up to the global level. A local social enterprise that makes use of business information can compete successfully with other social enterprises located all over the world. According to the findings of a number of studies, providing subjects with more and more accurate information makes it possible to more effectively improve their performance (Boone et al., 2005; Mani et al., 2010; Ogunsola & Babalola, 2020).

In addition, the present study found a positive and statistically substantial relation between business networking and financial performance in social enterprises. This finding lends support to hypothesis number two (H2). According to the research results, an appropriate level of business networking in social enterprises could lead to enhancements in the financial performance of the social enterprises. Previous research has found a positive and significant relationship between social enterprise business networking and financial performance (Ali & Li, 2021; Bae et al., 2018; dos Santos et al., 2021).

Moreover, this study has a positive and significant relation between access to finance and financial performance. This supports to the third hypothesis (H3). This implies that access to finance is important metric for social enterprises. The findings of this study are supported by other studies conducted in different contexts (Cecchetti & Kharroubi, 2015; Fowowe, 2017). However, finance is a major problem in developing and emerging economies due to the lack of enough internal resources for the start-up of the enterprise. So, they need to take finance from any external source such as banks or family members.

Additionally, a positive and statistically significant moderation impact of access to finance was found to have on the relationship between business information and financial performance of the social enterprises. It signifies the confirmation of hypothesis four (H4). The findings indicate that the moderation impact of access to finance can make a significant contribution to the social enterprises. The studies by Hussain et al. (2018) and Adomako et al. (2016) also reported similar findings. Lastly, the moderation effect of access to finance on the relationship between business networking and financial performance of social enterprises found insignificant indication which means hypothesis five (H5) is rejected. The study of Le and Nguyen (2009) also reported similar findings.

8. Conclusion

In light of the results of this study, the researchers are in a position to give responses to research questions in the following order: According to the findings of our research, the financial performance of SEs in Pakistan is significantly influenced by the extent to which they engage in business networking. In addition to that, the importance of business information to the overall financial performance of social enterprises is brought to light in this article as well. According to the findings and results of the research, business networking is likely responsible for a sizeable portion of the financial performance achieved by social enterprises in Pakistan. This research also found that having a reasonable number of networking can perform a very vital role in improving the financial performance of SEs. In a similar vein, the findings of this paper indicated that business information has a substantial and positive impact on the financial performance of Pakistani SEs. Likewise, access to finance has a positive and significant effect on the financial performance of SEs in Pakistan. The findings of this study may provide a better knowledge and understanding regarding the business networking, access to finance and business information in social enterprises, all of which can influence the improvement of the financial performance of social enterprises in Pakistan. These findings broaden the application of the RBV to social enterprises and demonstrate how these resources like business networking, access to finance and business information can be utilized to improve the magnitude of the financial impact.

In addition, the empirical findings of this research can be helpful for the top management of social enterprises to make strong decisions and produce goods and services in order to give superior support for their customers. In conclusion, the findings of this research may be helpful to policymakers, government regulators, and other relevant parties in the design as well as implementation of more effective policies and regulations for increased business networking, access to finance and business information in order to confirm the long-term improvement of Pakistani social enterprises.

8.1. Limitations and future research recommendations

The participants in this research come from different social enterprises in Pakistan; however, they need to broaden their scope and look at other industries as well. This research is appropriate only for SEs operating in less developed countries. In order to widen the scope of this study, it should have been carried out by SEs from low-income countries all over the world. This research is only limited to SEs of developing countries like Pakistan. So, the results of this research cannot be generalized to the whole SEs and may vary in developed countries due to their different cultural backgrounds, different socio-economic conditions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Appendix

Organizational performance

The following statements relate to the (Financial & Social performance). Please indicate the extent to which the following items describe your organization.

(1 represents “Strongly disagree”, 2 “Disagree”, 3 “Slightly Disagree”, 4 “Neutral”, 5 “Slightly agree”, 6 “Agree” and 7 “Strongly agree”.)

Table

	Financial performance	0%	0–10%	10–20%	20–30%	30–40%	40–50%	<50%
FP1	How many percent of return on investment (ROI) for your business has increased during the last three years	0%	0–10%	10–20%	20–30%	30–40%	40–50%	<50%
FP2	How many percent of your business’s market share has increased during the last three years?	0%	0–10%	10–20%	20–30%	30–40%	40–50%	<50%
FP3	How many percent of profit growth rate of your company has increased during the last three years?	0%	0–10%	10–20%	20–30%	30–40%	40–50%	<50%
FP4	How many percent of your product sales have increased during the last three years?	0%	0–10%	10–20%	20–30%	30–40%	40–50%	<50%

Table

	Social Performance	Strongly disagree	Disagree	Slightly disagree	Neutral	Slightly agree	Agree	Strongly agree
SP1	Our business promotes communication and cooperation with our stakeholders to increase their awareness about social enterprise.	1	2	3	4	5	6	7
SP2	Our company use social media/blog/website to promote social enterprise.	1	2	3	4	5	6	7
SP3	Our business prioritized in solving local community ‘s problem.	1	2	3	4	5	6	7
SP4	Our company hire/employ disabled people.	1	2	3	4	5	6	7
SP5	Our business helps to increase employment rate among the poor.	1	2	3	4	5	6	7
SP6	Our business provides more social and environmentally friendly services to the community.	1	2	3	4	5	6	7
SP7	Our business help to decrease environmental issues (green environment, waste, pollution, and climate change).	1	2	3	4	5	6	7
SP8	Our company make sure that we achieve at least 60% of the company’s target for social welfare.	1	2	3	4	5	6	7

Section three

The following statements relate to the business networking. Please indicate the extent to which the following items describe your organization.

(1 represents “Strongly disagree”, 2 “Disagree”, 3 “Slightly Disagree”, 4 “Neutral”, 5 “Slightly agree”, 6 “Agree” and 7 “Strongly agree”.)

Table

	Business networking
BN 1	Our company is a member to at least one of business-related association/chamber of commerce.	1	2	3	4	5	6	7
BN 2	Our company regularly joins trade fairs and attend business seminars.	1	2	3	4	5	6	7
BN 3	We always attend events organized by our business friends.	1	2	3	4	5	6	7
BN 4	Our company always build good bond/connection with our business friends.	1	2	3	4	5	6	7
BN 5	Our company always get family members involved in our social activities.	1	2	3	4	5	6	7
BN 6	Our company always invites government officials to attend our company’s events.	1	2	3	4	5	6	7
BN 7	7- Our company usually invites all our suppliers to a yearly dinner.	1	2	3	4	5	6	7
BN 8	Our company communicate with our customers and gives discounts to them so they will not forget about our company and keep buying from us.	1	2	3	4	5	6	7
BN 9	Our company always keep good repo with our competitors	1	2	3	4	5	6	7
BN10	Our company always share knowledge and resources with other companies who sell products that can complement our products.	1	2	3	4	5	6	7

Section four

The following statements relate to the business information. Please indicate the extent to which the following items describe your organization.

(1 represents “Strongly disagree”, 2 “Disagree”, 3 “Slightly Disagree”, 4 “Neutral”, 5 “Slightly agree”, 6 “Agree” and 7 “Strongly agree”.)

Table

	Business Information
BI 1	I know where to get business information.	1	2	3	4	5	6	7
BI 2	I always read newspapers/trade reports/business magazines/journals/government publications to gather information about suppliers’ company.	1	2	3	4	5	6	7
BI 3	I rely on internet sources and experts’ opinion to collect information regarding market demand of our product.	1	2	3	4	5	6	7
BI 4	I rely on social media such as Facebook, twitter, WhatsApp, and Instagram to get information on consumer’s preferences.	1	2	3	4	5	6	7
BI 5	I rely on electronic media such as radio and television to get information on consumer’s preferences.	1	2	3	4	5	6	7
BI 6	Informal information from leaders, employees, colleagues, and other people is easily available for our business.	1	2	3	4	5	6	7
BI 7	Information regarding financial aid is often available	1	2	3	4	5	6	7
BI 8	I know that I can access to information about suppliers that related to my product.	1	2	3	4	5	6	7
BI 9	I know that I can access to information of other competitor firms that offer similar product as mine.	1	2	3	4	5	6	7
BI 10	I know that I can easily get information about product development that are related to my products.	1	2	3	4	5	6	7
BI 11	Information about Pakistan’s government rule and regulation related to business is easily accessible to me.	1	2	3	4	5	6	7
BI 12	I can easily access to most of the sources of the business information.	1	2	3	4	5	6	7
BI 13	I can easily collect business information from other sources like social media and electronic media (TV, Radio).	1	2	3	4	5	6	7
BI 14	I rely on social media and electronic media (TV, Radio) because I can get business information very quickly.	1	2	3	4	5	6	7
BI 15	I rely on print media because I can get business information very quickly.	1	2	3	4	5	6	7
BI 16	To collect business information physically from government institutions is complicated.	1	2	3	4	5	6	7
BI 17	I only gather the business information that are freely available	1	2	3	4	5	6	7
BI 18	I believe published business information that I gather from official sources (like government agencies’ website or company’s annual report) is relevant.	1	2	3	4	5	6	7
BI 19	I believe business information that I get from other sources (social media, electronic media, print media) is relevant.	1	2	3	4	5	6	7
BI 20	I believe published business information that I gather from official sources (like government agencies’ website or company’s annual report) is reliable.	1	2	3	4	5	6	7
BI 21	I believe business information that I get from other sources (social media, electronic media, print media) is reliable.	1	2	3	4	5	6	7
BI 22	I believe published business information that I gather from official sources (like government agencies’ website or company’s annual report) is accurate.	1	2	3	4	5	6	7
BI 23	I believe business information that I get from other sources (social media, electronic media, print media) is accurate.	1	2	3	4	5	6	7
BI 24	I believe published business information that I gather from official sources (like government agencies’ website or company’s annual report) is complete.	1	2	3	4	5	6	7
BI 25	I believe published business information that I gather from official sources (like government agencies’ website or company’s annual report) is adequate/sufficient.	1	2	3	4	5	6	7
BI 26	I believe published information that I gather from official sources (like government agencies’ website or company’s annual report) is adequate/sufficient.	1	2	3	4	5	6	7
BI 27	I believe business information that I get from other sources (social media, electronic media, print media) is adequate/sufficient	1	2	3	4	5	6	7