The impact of symbiotic relations on the performance of micro, small and medium enterprises in a small-town context: The perspective of risk and return

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Research in International Business and Finance 56 (2021) 101388

Available online 16 January 2021

Full length Article

The impact of symbiotic relations on the performance of micro, small and medium enterprises in a small-town context: The perspective of risk and return

Ploypailin Kijkasiwat

^a^,

*, Nirosha Hewa Wellalage

^b

, Stuart Locke

^b

a123 Faculty of Accountancy and Business Administration, Khon Kaen University, Khon Kaen, 40002, Thailand

bSchool of Accounting, Economics and Finance, University of Waikato, Hamilton, 3216, New Zealand

A R T I C L E I N F O JEL classification:

Z130 G00 G30 M1: M140 Keywords:

Symbiotic relationship Business networks Risk and return

Micro, small and medium enterprises

A B S T R A C T

This study uses a financial lens to investigate and discuss how symbiotic relationships can enhance business performance, particularly in terms of risk and return for micro, small and medium enterprises (MSMEs). A mixed-method approach, using both Partial Least Square Structure Equation Modelling (PLS-SEM) and thematic analysis, is employed to analyse the information from 200 MSMEs. The findings indicate that symbiotic relationships among businesses help MSMEs to reduce risks and increase returns. The study provides a model that is potentially applicable to other settings and pertinent for policymakers, trade associations and MSMEs.

1. Introduction

Globalisation and changes in economic conditions can intensify competitive behaviour among businesses. While increased business competitiveness may have minimal effects on the business performance of large-sized firms, it can create challenges for micro, small and medium enterprises (MSMEs). Limitations of resources and finance, and volatility and opacity can push these businesses to a crisis (Becka et al., 2006). Cooperation is one strategy for meeting these challenges and attaining success; correspondingly, many businesses dispense with the idea of flying solo and adopt a synergistic model of working where everyone can benefit from cooperation (Azmi et al., 2019; Karami and Tang, 2019; Partanen et al., 2020; Sadeghi and Biancone, 2018). Symbiotic relationships can help MSMEs (symbionts) to overcome their resource scarcity, market competition, and achieve long term sustainable growth (Li et al., 2018). In other words, when symbiosis is adopted as a strategic tool it can improve MSMEs’ performance (Partanen et al., 2018).

Although, there are obvious benefits of symbiotic relationships especially for MSMEs (Li et al., 2018; Sharma et al., 2019), there are dissenting views in the literature about their value (Watson, 2007). The majority of the studies indicate that symbiotic relationships develop and maintain mutually beneficial associations for symbionts, having neither conflicting interests nor competition for scare resources (Li et al., 2012). Therefore, in a symbiotic relationship, all symbionts can perform well, compared to other types of strategic alliances. Conversely, some studies claim that excessive networking is likely to be counter-productive (Watson, 2007). In particular, information can be leaked via interconnections between several businesses, resulting in the loss of competitive advantages (Tan et al.,

* Corresponding author.

E-mail addresses: [email protected] (P. Kijkasiwat), [email protected] (N.H. Wellalage), [email protected] (S. Locke).

Contents lists available at ScienceDirect

Research in International Business and Finance

journal homepage: www.elsevier.com/locate/ribaf

https://doi.org/10.1016/j.ribaf.2021.101388

Received 19 December 2019; Received in revised form 5 January 2021; Accepted 6 January 2021

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Research in International Business and Finance 56 (2021) 101388

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2016). Additionally, a number of studies argue that the positive impacts of symbiotic relationships can be seen only at the early stage of operation (Partanen et al., 2018) or among large-sized firms (Li et al., 2012).

Despite these existing studies on symbiotic relationships, the effect of symbiotic relationships on firm level performance is still inconclusive. Although there are studies that utilise a financial framework to discuss the positive contribution of symbiosis on financial performance (Mitsuhashi and Greve, 2009; Simmonds, 1990), the effects on risk and return among symbionts in a symbiotic relationship have still not been evaluated comprehensively. Additionally, prior literature on small firms’ symbiotic relationships is limited mainly to strategic alliances between small and large firms (Mitsuhashi and Greve, 2009). Correspondingly, there is space for further elaboration on business symbiosis, the underlying interaction of all parties involved and the effect on firm level risk and return. To address this research gap, the current research study selects MSMEs to focus on all the elements relating to their risk and return. From a small business perspective, risk is caused by an increase in expenditure and an inability to access financial capital and trade credit (Carbo-Valverde et al., 2016). Following Ullah (2020), the current study concentrates on factors causing uncertainty in business performance as a risk. Rather than measuring risk in the form of beta as is usually done with listed firms, this study evaluates risk from elements relating to costs and expenses by using subjective measurements (Chong et al., 2013; Hammoudeh and McAleer, 2013;

Marom and Lussier, 2014). Return here is defined as a value added to both financial and non-financial factors affecting business performance (Altman et al., 2010; Bassett and Chen, 2001). Following (Morched and Jarboui, 2020), the study uses the change in net profit as objective measurement of return. Additionally, the study evaluates the element of return by using a subjective evaluation based on semi-structured interviews (Vij and Bedi, 2016). Employing a financial lens, this study attempts to answer the following question:

How do symbiotic relationships among different types of MSMEs associate with risk and return indicators?

In order to answer the research question and to understand the impacts of business symbiosis in small towns, this research uses Cambridge, New Zealand as a case study. Initially, a questionnaire was completed by 200 participants and subsequent follow-up interviews with 96 of the original participants to provide further insights into the dynamics of the symbiotic process. MSMEs’ sta- bility is important to regional economic development and there is a greater dependence on local resources and initiatives. The current situation therefore increases the significance of this study on the impact of symbiosis on firm performance.

This research contributes to the literature in the following three ways. Firstly, to our knowledge, this is the first study to look at symbiotic relationships and their impact on firm level risk and return, particularly perspective of MSMEs. Although some studies adopt a financial framework to evaluate the impacts of business symbiosis, they limit their consideration of the effects on MSME performance in different ways. These include types of connection (Watson, 2007), the number of contacts (Semrau and Werner, 2014), business interactivities (Dubois, 2015), period spent in cooperation (Gu et al., 2016), intensity (frequency) of contact between entities (Tan et al., 2015), and network position (Turkina and Van Assche, 2018). The second contribution of the current study relates to the data and the methodological approach.. The analysis uses primary data from a survey and in-depth interviews to provide a comprehensive picture of linkages among MSMEs in different industrial clusters, enhancing understanding of the relative importance of business connections in those clusters.

Additionally, a mixed-method approach identifies what MSMEs convey about their networks and relationships with others, capturing both manifest information expressed directly and latent meanings below the surface of explanations. Finally, this research study can offer ideas for public policy and possible adjustments for MSMEs who wish to enhance their sustainable returns. The study could be used to promote policies for the provision of infrastructure and industrial help for business symbiosis to happen. The frameworks set up by local governments to encourage networking can enhance business symbiosis and add value to the community.

Further, this research could inform decisions of policymakers when they are deciding on the allocation of funds to particular networks.

Policymakers may need to differentiate between the circumstances and contexts of firms having a connection with each other (Cumming et al., 2009), so they can provide appropriate support.

The next section of this paper provides a literature review, and section three follows with the research methodology. The empirical results and discussion in section four lead to the final section, which summarises the conclusions of this study.

2. Literature review

2.1. Business performance from a resource dependence theory perspective

Resource Dependence Theory is widely mentioned in organisational and strategic management as it explains how the external environment affects enterprise behaviours (Hillman et al., 2009). This theory is mentioned in entrepreneurial financial management research, particularly regarding mergers, joint ventures, and alliance in firms that are interconnected because of the uncertain effect of external environments. Additionally, the theory is adopted to explain how entities in private financial market; for instance, startups and business incubators, get the benefit from networking (Galv˜ao et al., 2019).

Resource Dependence Theory, initially stated by Pfeffer and Salancik (1978), states that uncertain situations that may cause risks and failure are mitigated by the interconnection between firms, which act to manage interdependence. The theory states that business performance depends on resources and networks that can be acquired from the external environment through different social groupings and trading associations (Butler and Sohod, 1995). Small firms receive more benefits from co-operative relationships (Das et al., 1998). In practical terms, interconnection will be sustained when trust between different parties is established.

In the context of this study, Resource Dependence Theory is adopted to examine the benefits of relationships among enterprises in a symbiotic environment. In order to be sustainable, enterprises can acquire various resources, access information, and acquire physical P. Kijkasiwat et al.

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resources from the external environment by incorporating themselves into different kinds of networks such as competitive connections and industrial associations. Interconnecting with various networks is beneficial for firms to understand the actors within a network and recognise the focal entities which provide help and support. This resource is critical for the success of firms, but it is insufficient (Pfeffer and Salancik, 1978). Interdependence among MSMEs creates an opportunity to access and share resources, build permanent and constructive networks, and enjoy reciprocal benefits.

Transactions with the external environment can be in the form of horizontal, vertical, and diagonal interactions. While horizontal interconnection occurs between single enterprises on the same level, vertical interconnection is between different levels of entities such as seller-buyer, wholesaler-retailer, and manufacture-distributor. Diagonal relationships are widely seen when every entity at different levels or parties interconnect independently. Resource Dependency Theory explains how the external environment prompts firms to connect with each other, and how business performance is increased through the satisfaction of every part of a network (Andriof et al., 2017).

2.2. Impacts of symbiotic relationships on risk and return of MSMEs

Symbiosis is about living together (Dimijian, 2000), suggesting there are relationships between mutual units in a collaborative environment (Astley and Fombrun, 1983). In a financial context, the benefits of business connections are associated with risk and return components, relating to money inflows and outflows.

Both direct and indirect effects of interconnections and network relationships may occur. Based on a case study, Ashton (2011) investigates how a cluster of several manufacturing firms obtains reciprocal benefits in terms of sharing utilities. For small businesses, adopting the concept of symbiosis as a strategic tool can improve their performance (Rauch et al., 2016), survival rate, goodwill, growth potential, and reduce potential risk stemming from limitations of firm size (Banwo et al., 2015). Active engagement in symbiotic relationships may provide MSMEs with hedging against risks through different inter-firm activities producing a pooling effect.

Interpersonal skills regarding the ability to engage in social interactions with others is positively associated with a firm’s financial performance, particularly in new ventures (Semrau and Sigmund, 2012). Network capability helps small firms increase performance-related returns (Wales et al., 2013), and allows them to overcome the limitations of the firm (Ketchen et al., 2007).

Professional associations may provide useful impetus in fostering symbiosis through the provision of information and recommenda- tions to members. Networking increases the probability of generating an idea for an innovative venture (Dyer et al., 2008). Signalling through a trusted hub, such as the local Chamber of Commerce, reduces search costs and prompts actions to obtain rents that may otherwise have been missed. Greenwood et al. (2002) note that belonging to a professional association helps many MSMEs deal with legitimating issues. The association helps MSMEs affirm regulatory mechanisms that individual MSMEs have to follow.

MSMEs, like other entities, face both systematic risks and unsystematic risks, which affect individual enterprises’ performance (Hallikas et al., 2004). Support from networking organisations enable MSMEs to reduce unsystematic risks caused by internal factors, but systematic risks generated from external factors are also critical to operations. Diversification of risk in a manner that maintains a firm’s return is possible through symbiosis. Ford et al. (2002) suggest that risk hedging relates to ‘action, reaction, re-reaction based on a company’s network pictures, its own and other’s networking and the outcome of this’ (p.21). Adopting the private rules of the most powerful entity in a business relationship provides power for other enterprises in the network when interacting with the stronger party (Rindt and Mouzas, 2015). From previous studies, the first proposition is created:

P1: Symbiotic relationships can decrease risks of MSMEs.

MSMEs can diversify returns by connecting with different entities. Networking promotes trading opportunities and its impact depends on how firms develop and maintain relationships over time (Eberhard and Craig, 2013). The strength of business relationships among several MSMEs influences their internal diversification behaviour (Zimmerman et al., 2009). The interactions between MSMEs motivates firms to share resources and support collective activities in order to expand market distribution (Jack, 2005). Trust and loyalty play important roles in this form of diversification (Collins and Clark, 2003). Business-bank relations are likely to be pivotal to success (Refait-Alexandre and Serve, 2020). Strong relationships between banks and SMEs can reduce a firm’s credit constraints and provide intermediation services to support business activities (Mancusi et al., 2018). Detragiache et al. (2000) argue that having relationships with multiple banks (rather than building a relationship with one bank) can reduce liquidity risks and ensure more stable credit. MSMEs can also diversify service options when they are in contact with different lenders. MSMEs can leverage the different interest rates offered by a number of banks for refinancing to achieve maximum advantage. As an alternative to having more than one bank, which increases costs, sharing information about banks’ charges and services between MSMEs enhances each MSME’s nego- tiations with their bank. Many MSMEs leverage additional advantages from business cooperation in terms of bargaining and nego- tiation power. The trade-off between collective return and independence in making decisions is diminished. These interactions indicate stronger social relationships (Bono and McCullough, 2000). Based on the literature, this proposition is formulated:

P2: Symbiotic relationships can increase returns of MSMEs.

3. Methodology

3.1. Data and sample selection

The owners/managers operating MSMEs in Cambridge responded to a survey, which had been approved by the University of Waikato Ethics Committee, over a period of approximately two months (from 9 February to 3 May 2017). Cambridge is the largest

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town in the Waipa District, and the third largest urban area in the Waikato region (after Hamilton and Taupo). It is one of the towns in New Zealand with a high growth in population. The total of 1071 MSMEs in the Cambridge area is comprised of MSMEs in Cambridge North (213), Cambridge West (267) and Cambridge centre (591) (Statistic New Zealand, 2013). Yamane’s technique, at six percent of the margin of error, suggests that the sample of 200 MSMEs is appropriate (Yamane, 1967). Initially, the CEO of the Cambridge Chamber of Commerce recommended the members of the Chamber through business meetings as the potential research participants.

This process increased the number of participants who responded to the questionnaire. In order to avoid sampling bias, manager/- owners of shops in the town centre were also approached to see if they would agree to complete the questionnaire. The questionnaire comprises both close-ended and opened-ended questions (See Appendix). One section of the questionnaire, which focuses on business networking and symbiotic relationships, provides an opportunity for respondents to provide the names of business owners that they connect with. Table 1 presents descriptive statistics analysed from the 200 MSMEs.

To improve the depth of responses regarding how and why this connection relates to risk and return of MSMEs, ninety-six of the original sample of 200 MSMEs were interviewed again subsequently employing a semi-structured interview. These ninety-six in- terviewees who were selected after analysing the surveys were those who mentioned some core concepts that required more detailed exploration. Their responses to these interviews provide additional details about their business connections in each industrial cluster.

3.2. Analysis technique

A mixed-method approach, using both Partial Least Square Structure Equation Modelling (PLS-SEM) and thematic analysis was used to analyse the information from the participants. The analysis identifies what MSMEs convey about their networks and relationships with others, capturing both manifest information expressed directly and latent meanings beneath the surface of the explanations. The analysis consists of two parts. First, data accessed from survey responses are analysed, using PLS-SEM. This is an appropriate model for examining how symbiotic relationships associate with firm performance of MSMEs. As business symbiosis is difficult to define, measurement indicators are used to demonstrate the symbiosis. Network scores are calculated by adopting Social Network Analysis (SNA) as per Kilduff and Tsai (2003); Prell (2012) and Wasserman and Faust (1994). The participants mentioned the types of industry with which they have strong business relationships. Those industries were coded by using ANZSIC. Thereafter, the 79 groups were inputted into the computer using the software called GEPHI to determine the number of nodes contained in the graph. The targets explain the number of edges or connections between nodes. For example, firm 1 is a retail shop selling gifts, flowers, and recreational items, so it was coded as G424 (according to ANZSIC, G424 is in the group of Recreational Goods Retailing business). As an entrepreneur in firm 1 mentioned interactions with an interior design company, a target is M692 (Architectural business). Therefore, G424 is the source, and M692 is the target. According to the responses, there are 155 potential connections among the groups, so 155 edges which can be put into GEPHI. Coding was done one by one with the 200 samples.

Results from GEPHI shows some statistics for each business group; namely in degree (demonstrating the number of target groups Table 1

Descriptive statistics. This table presents the description of variables and definition of our dependent, independent variables.

Variables Category Number Mean Std. dev Min Max

Dependent variable Change in net profit (NP)

1=Makes a loss

200 2.68 .91 1 4

2=Makes no profit 3=Gains some profits 4=Gains significant profits Explanatory variables

Characteristics of business owners

Age of business owner (OWNER_ AGE) 1=less than 40

200 1.92 .72 1 3

2=41-60 3=More than 60

Gender of business owner (GENDER) 10==Male Female 200 .44 .49 0 1

Nationality of business owners (NATION) 10==New Zealander Non-new Zealander 200 .85 .35 0 1 Firm attributes

Firm age (FIRM_ AGE)

1=Less than 1 year

200 3.47 1.12 1 5

2=1-5 years 3=6-10 years 4=11-20 years 5=More than 20 years

Firm size (SIZE) 1 =Fewer than 5 employees (micro)

200 1.56 .82 1 3

2=6-9 employees (small) 3=More than 9 employees (medium)

Sector (SEC) 12==Service Non-service (Manufacturer & trading) 200 .52 .05 0 1

Location (LOC) 10==town centre beyond town centre 200 .58 .49 0 1

P. Kijkasiwat et al.

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which have been connected), and out degree (demonstrating the number of sources which connect to others). The higher that the number of out degree is, the higher the connection with others, and eigenvector score (measuring the importance of a node in a network based on a node’s connections) (Cassar and Rigdon, 2013; Surin et al., 2017). These statistical scores were fed into PLS-SEM as indicators of each construct. The indicative variables used to specify the network scores are demonstrated in Table 2. The formative measurement models were checked for any collinearity, reliability and validity of variables. After checking the variance inflation factor (VIF) and tolerance value, outer weights of each formative indicator, the indicators having outer weight of less than 0.60 were removed from the model. The validity of the structural model was evaluated, and the coefficient of determination (R2) was checked (Hair et al., 2016; Sarstedt et al., 2014).

The second part of the analysis was designed to obtain further in-depth information regarding how and why business symbiosis affects risk and return of MSMEs. Qualitative data analysis techniques were used to analyse the interview transcription. A qualitative approach can provide the reasons behind the survey responses, better understanding of the perceptions and emotions that underlie the survey responses (Lima et al., 2017). The interviews can provide greater insight into the thinking and feelings behind their answers.

Additionally, qualitative tools enable you to access the stories of the participants. This study uses Thematic analysis for the analysis. As explained in detail by Braun and Clarke (2006), provides guidelines for coding vague sentences and suggests how to link several codes to themes and report on them systematically. This process allows researchers to use flexible procedures with the data and employ both an inductive and a deductive approach. For an inductive approach, the study considers the new information which was not indicated in the questionnaire findings, but which emerged from interviews with the participants (Downey and Ireland, 1979). Coding data, based on participants’ narratives relating to their Cambridge context as they share experiences and philosophy, provide insights into business symbiosis. As the study investigates the impacts of symbiotic relationships in Cambridge, characteristics of the town, policy, plans, and principles created by local authorities affect the coding process. A deductive approach draws on theoretical constructs from financial frameworks and Resource Dependence Theory as well as social network frameworks relating to density, centrality and betweenness (Burt, 1992; Galv˜ao et al., 2019) and strength of ties (Burt, 1992; Granovetter, 1973). Taking account of Resource Dependence Theory, external environment (Hillman et al., 2009), competitive connections and industrial associations (Butler & Sohod, 1995), as well as financial and mental support were considered (Larson and Starr, 1993).

The use of several techniques helped to enhance the validity and trustworthiness of the findings. For data triangulation, the selection of MSMEs operating in various industries provide industrial stratification. This provides the opportunity to observe whether the same types of businesses provide convergent responses, while differing from those operating across different industries (Curran and Blackburn, 1994). In order to achieve triangulation, the researcher participated in multiple meetings and events organised by the Cambridge Chamber of Commerce to observe the interactions between owners/managers in Cambridge. The use of triangulation was for evaluating whether enterprise connections among businesses operating within the same industry are similar. This was reconfirmed by the lists of names given by business owners when asked about their business connections.

4. Empirical results and discussion 4.1. The symbiotic relationships of MSMEs

Network analysis provides an overview of the relationships based on the responses received. Table 3 lists the top 10 industry groups. The accommodation industry scores the highest out-degree, indicating that the accommodation sector connects with many businesses operating in other industries. The highest eigenvector indicates a strong centrality score. These findings extend the prior study of Wang et al. (2018) which examines diversity and position in inter-organizational networking. However, their study does not Table 2

Indicative variables. This table presents the operationalization of constructs.

Constructs Indicators Definitions Sources of measurement

Firm performance Change in profit Overall net profit of a firm over 12 months of 2015. Questionnaires: Self-administered response.

Interfirm relation- within industry

Eigenvector centrality Importance of enterprises in a network based on their

connections Questionnaires: Scores from GEPHI calculated

from name-generating responses.

Out-degree score

within industry Number of enterprises which connect to others

operating within the same industry. Questionnaires: Scores from GEPHI calculated from name-generating responses.

Interactivity within

industry Business transactions among enterprises within the

same industry. Questionnaires: Self-administered response.

Interfirm relations across industries

Out-degree score across

industries Number of enterprises which connect to others across

industries. Questionnaires: Scores from GEPHI calculated

from name-generating responses.

In-degree score across

industries Demonstrates the number of target enterprises which

have been connected across industries. Questionnaires: Scores from GEPHI calculated from name-generating responses.

Interactivity across

industries Business transactions among enterprise across

industries. Questionnaires: Self-administered response.

Business-bank relations One bank connection Lending relationship between a firm and a bank. Questionnaires: Self-administered response.

Business purpose

transaction Informs banking transactions among enterprises. Questionnaires: Self-administered response.

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Table 3

Statistical results of network measurement. This table presents the top ten values from Social Network Analysis.

In-degree Out-degree Eigenvector centrality Eccentricity Closeness centrality Betweenness centrality

Order Name Statistics Name Statistics Name Statistics Name Statistics Name Statistics Name Statistics

1 Accommodation 10.0 Recreational

Goods Retailing 19.0 Accommodation 1.0 Legal and Accounting Services

6.0 Amusement and Other Recreation Activities

1.0 Recreational

Goods Retailing 204.0 2 Building

Installation Services

7.0 Cafes, Restaurants and Takeaway Food Services

0.6 Personal Care

Services 5.0 Computer Systems

Design and Related Services

1.0 Accommodation 144.8

3 Architectural, Engineering and Technical Services

7.0 Specialised Food

Retailing 8.0 Other Personal

Services 0.5 Funeral,

Crematorium and Cemetery Services

5.0 Creative and Performing Arts Activities

129.7

4 Cafes, Restaurants and Takeaway Food Services

6.0 Medical Services 7.0 Other Transport

Support Services 0.5 Horse and Dog

Racing Activities 5.0 Automotive Repair

and Maintenance 1.0 Medical Services 108.3 5 Other Transport

Support Services 6.0 Pharmaceutical and Other Store- Based Retailing

7.0 Architectural, Engineering and Technical Services

0.4 Real Estate

Services 5.0 Machinery and

Equipment Repair and Maintenance

1.0 Building Installation Services

61.0

6 Recreational

Goods Retailing 5.0 Legal and Accounting Services

7.0 Internet Service Providers and Web Search Portals

0.4 Clothing, Footwear and Personal Accessories Retailing

0.9 Real Estate

Services 48.0

7 Medical Services 5.0 Other Social

Assistance Services 7.0 Scenic and Sightseeing Transport

0.4 Other Health Care

Services 5.0 Cafes, Restaurants

and Takeaway Food Services

0.8 Sport and Physical Recreation Activities

48.0

8 Pharmaceutical and Medicinal Product Manufacturing

4.0 Clothing, Footwear and Personal Accessories Retailing

0.3 Recreational

Goods Retailing 5.0 Hardware, Building and Garden Supplies Retailing

0.7 Other Social Assistance Services

47.0

9 Pharmaceutical and Other Store- Based Retailing

3.0 Accommodation 6.0 Grocery, Liquor and Tobacco Product Wholesaling

0.27 Medical Services 4.0 Market Research and Statistical Services

0.7 Architectural, Engineering and Technical Services

45.0

10 Personal Care

Services 3.0 Building

Installation Services

6.0 Supermarket and

Grocery Stores 0.3 Pharmaceutical and Other Store- Based Retailing

4.0 Accommodation 0.7 Pharmaceutical

and Other Store- Based Retailing

44.5

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demonstrate which entities in the network play an important role as a hub or centre transferring or receiving information from others.

Although some studies indicate which business is the central node in the network, these papers focus on business sites and distances from other entities in the context of internationalization (Wild, 2020), not on the businesses functional linkages in a local context.

The recreational goods retailing industry records the highest out-degree score, suggesting various types of industries with which businesses operating in the recreational goods retailing industry need to connect. Additionally, according to the highest betweenness centrality score, recreational goods retailers are the most important entities of the whole network as they act as the best signallers who transfer information to other entities in Cambridge. The highest eccentricity score, which was recorded for businesses operating in the Legal and Accounting Services Industry, reveals that this industry responds more readily to activities of other businesses rather than other industries. The highest score of closeness comes from businesses operating in the Amusement and Other recreation activities industry reflecting its capacity to connect with many businesses operating in other industries. The research findings shed light on the study of Partanen et al. (2018) which investigates industry-specific networks, as the current study provides a comprehensive picture of connections among MSMEs operating in different industries.

Fig. 1presents the overall picture of business symbiosis in Cambridge. A GEPHI diagram depicts seven main areas exhibiting a high density of connections. The web of business connections also indicates prominent nodes acting as hubs that transfer signals and information to others. First, a number of retail businesses connect and have business relationships with other different industries. From the web of contacts, businesses operating in the Recreational Goods Retailing Industry are associated with many businesses operating in the Accommodation Industry, the Knitted Product Manufacturing Industry, the Textile Fibre, and the Yarn and Woven Fabric Manufacturing Industry. Recreational goods retailers also connect with businesses operating in the Real Estate Services, the Funeral, Crematorium and Cemetery Services, the Personal Care Service Industry, and the Sport and Physical Recreation Activities Industry. In this cluster, MSMEs’ owners draw on the advantages of ‘the benefits of a small town’ where MSMEs owners know each other very well.

This is beneficial to the whole cluster, particularly for ‘cross-service activities’. The comment of one MSME owner illustrates this point:

“They do all the legal side of things for us regarding if there’s changes in law they keep us up to date. There’s a huge benefit on costings; they do big group buying sort of things. They have a funeral trust which we use, which stores money for people who want to prepay their funerals. There’s definitely good benefits being part of the trust.”

The second area of a high density of connections incorporates businesses operating in the Accommodation Industry, the Caf´e, Restaurant and Takeaway Food Services Industry, and the Recreational Goods Retailing Industry. The Accommodation Industry connects with businesses operating in the Transport Support Services Industry, the Motor Vehicle and Transport Equipment Rental and Hiring Industry, and the Waste Collection Services Industry. The main advantage of business connections in this cluster is generating the growth of the local community. As Cambridge is a scenic and tourist town, hotel owners frequently recommend good caf´e and restaurant options to their patrons. Likewise, transport companies can increase their customer numbers through their contact with

Fig. 1.Business symbiosis of MSMEs in Cambridge. This figure demonstrates the seven areas of high density of connection among MSMEs operated in different industries.

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people in the accommodation sector. These examples demonstrate ‘the benefits of referral’.

Third, GEPHI shows a high density of connection among businesses operating in the Caf´e, Restaurant and Takeaway Food Services Industry, the Dairy Product Manufacturing Industry, the Supermarket and Grocery Stores Industry, the Grain Mill and Cereal Product Manufacturing Industry, and the Bakery Product Manufacturing Industry. Many retailers in this cluster pay more attention to their suppliers who offer special services and cost reduction on products, as mentioned by one interviewee who owns a coffee shop:

“He’s always given me a discount because we get them all the time, every week. Pretty much from maybe a few months, he’s given us a better price because we order regularly. [Do they deliver to your shop for free?] Yes, he doesn’t charge the delivery costs or anything like that. He just couriers it to us, but he pays for the courier, so we just pay for the coffee. If we have maintenance on the coffee machine, you know, change the grinder blades, the water filter, all that sort of stuff he pays for. We don’t pay for any maintenance or repair for the machine, he pays for that.”

The fourth area of high density of connections encompasses firms operating in the Medical Services Industry, the Pharmaceutical and Medicinal Product Manufacturing Industry, the Pharmaceutical and Other Store-Based Retailing Industry, Hospitals, and the Sport and Physical Recreation Activities Industry. In this cluster, individual enterprises normally share knowledge, information and resources with each other in either a formal or informal manner. This helps small businesses to access knowledge and technology, increase business growth and market competitiveness and ‘reduces information searching costs. A comment from the interviews illustrates this point:

“Presenting and conference and something like that is another way to get and learn information.” My husband is a member of the professional association of massage therapists in New Zealand. [Is there any benefit from being a member?] Professional development, mainly. They get together every month, and they have maybe a guest speaker, networking with other therapists, talking about difficult cases, and then getting experts from overseas to come and do special training.”

The fifth high density connected area involves firms operating in the Building Installation Services Industry, the Architectural, Engineering and Technical Services Industry, the Hardware, Building and Garden Supplies Retailing Industry, the Gas Supply Industry, the Heavy and Civil Engineering Construction Industry, and the Furniture, Floor Coverings, Houseware and Textile Goods Retailing Industry.

The sixth group covers businesses operating in the Legal and Accounting Services Industry, Management and Other Consulting Services Industry and the Market Research and Statistical Services Industry. MSMEs in this cluster are service businesses who contact customers directly. The business connection helps MSMEs in the cluster to ‘reduce the time of service’, as a result of increased customer satisfaction. One Legal firm’s owner mentioned this:

“Because with having those good relationships, it means that you can trust somebody…So if they (customers) say they’re going to do something, you know that they will, or you know that they won’t, and then you know who (business partners) you can trust and who you can rely on, and maybe it allows you to cut some corners, make things happen a bit more quickly for the client.”

The seventh high density connection area is among businesses operating in the Horse and Dog Racing Activities Industry, the Veterinary Services Industry, and the School Education Industry. These findings offer a more comprehensive picture than previous studies. The paper contributes to the study of Chang and Webster (2019) which presents the positive impacts of industry networks on export performance without giving specific ideas on which industries connect or should be connected. Moreover, the findings give further explanation to the work of Galv˜ao et al. (2019) regarding formal and informal business connection and activities. Although some studies mention the association between one type of business and another type of business (Camanzi and Giua, 2020; de Carvalho et al., 2020; Majid et al., 2019), prior research does not demonstrate the industrial connections in a web of connections that incorporates every type of business.

4.2. The association between symbiotic relationships and business performance

Investigating connections among MSMEs with business returns related to the frequency of business performance, sheds light on the allocation of the variables in each symbiotic relationship. The symbiotic relationship variables, presented in Table 4, indicate that the

Table 4

Participant survey responses. This table presents the participant responses regarding the change in net profit of firms.

Symbiotic relationships Make loss Make no profit Gain profit

Connections with banks 9.5% 19.0% 71.4%

Connections with businesses operated within the same industry 13% 18.2% 68.8%

Connections with businesses operated across different industries 7.6% 20% 72.4%

Frequency of interaction with businesses operating within the same industry

Occasionally 7.3% 19.5% 73.2%

Frequently 7.8% 20.3% 71.8%

Frequency of interaction with businesses operating across different industries

Occasionally 16.4% 27.3% 56.4%

Frequently 11.2% 13.3% 75.5%

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highest percentage gains profit occurs in MSMEs having connections with banks, followed by connections with other firms within the same industry and then across different industries. These differences are significant at 10 percent significance level.

Table 5 shows symbiotic relationship variables with high correlations to firm profit. These variables are statistically significantly associated with firm profit at 10 percent significance level. Spearman’s rank correlation coefficients finding is supported by the interview responses, showing how these symbiotic relationships help MSMEs to reduce the element of risk. Results from PLS-SEM (Fig. 2) demonstrate that the relationships between businesses and banks have the strongest effect on business performance (path coefficient of -0.252, t Statistics =2.707). Factors such as Return on Assets (ROA), Return on Equity (ROE), Net Operating Profit (NOP) (Gorondutse et al., 2016) and knowledge exchanges are used to indicate the business performance (Ha et al., 2016). However, many MSMEs are not required to publish financial statements. These results are consistent with the findings of as the studies of Chege and Wang (2020), Mustafa and Yaakub (2018) and Centobelli et al. (2019) that confirm the positive impacts of connections on change in the net profit of firms.

Regarding the results from the thematic analysis, symbiotic relationships presented in Table 6 support a framework of risk and return where benefits of business connections in relation to cost reduction are observable in retail businesses and manufacturing firms.

Service business owners show a focus toward return creation drivers.

Close relations between MSMEs and banks appear as the norm in the sample. Fostering of and support for the relationships involves actions by banks to promote interactions between bankers and business owners/managers through visiting work premises, running workshops and minimising difficulties in applying for credit. These activities enable bankers to collect soft information on financial status, business owners’ attitudes, investment plans, and management skills of owners which are often hard to detect (Baas and Schrooten, 2006). The findings contribute to previous studies. Refait-Alexandre and Serve (2020) state that when SMEs’ owner/

managers have close relationships with banking staff, then they tend not to contact many banks. The findings of this paper support this idea that trustworthiness depends on the frequency of contact and interaction. This paper elaborates that trust between these entities enables quick transaction processes. Vegholm (2011) states that the relationships between bankers and MSME owners depend on how bankers understand MSMEs’ specific needs. MSMEs want practical solutions for accessing bank financial support, namely ‘information about accessing bank overdrafts and details about interest rates.’

Financial services here provide the opportunity for business owners to access workshops run by banks for helping MSMEs improve their financial management skills. This is consistent with Ang (1991) study which mentions that MSMEs can use technology and knowledge received from joining banking activities and mentoring programs to minimise transaction costs and increase firm performance.

4.3. How and why symbiotic relationships associate with risk and return

Within a risk and return framework, these symbiotic relationships facilitate individual businesses in the town to increase returns and to reduce costs and expenses of running businesses. The rationale for these interactions links with the several factors supporting or maintaining business networks. Five factors, identified in the symbiotic relationship, contribute to the MSMEs enhancing financial gains, viz., location proximity; two-way directions of relationships; trustworthiness; referral; and good corporate governance. MSMEs enhance financial gains where trustworthiness acts as fundamental capital. Trust, essentially regarded as a cost-free intangible asset, underpins the building and maintenance of relationships with others in the business community. Trust among owners/managers creates mental support, fortifies resources, knowledge sharing, and reduces information asymmetry supporting direct and indirect positive impacts on the entire performance of MSMEs. Table 7 presents this.

The presence of trust, in a business network, facilitates enhanced cooperation between MSMEs, particularly in the ‘two-way di- rection’ of relationships. These connections among MSMEs enable them to reduce information-searching costs, transaction and operating expenses, increase opportunities to add to stakeholders’wealth and improve business survival rates. These findings are consistent with a previous study stating that competitive firms have a greater need to maintain mutual relationships (Berchicci et al., 2011). An additional important aspect emerging from the interviews is how the sustainability of business association with other MSMEs requires good corporate governance, ensuring that there is no conflict between entities within a community.

Many MSMEs improve their profit and increase the number of customers because they refer customers to each other. ‘Location proximity’ enables signals to transfer more readily as ‘networking works well in a small town.’ Trade-off decisions by the majority of MSME owners/managers leverage the benefits of symbiotic relationships, overlooking the direct loss in income opportunities in favour of creating business partners to reap expanded mutual benefits. The value of referral is apparent between collaborating businesses, particularly where some customer requirements are difficult to meet. These interactivities enable every party to keep the money

Table 5

Spearman correlation with business performance. This table presents correlation coefficients of symbiotic relationship variables.

Symbiotic relationship variables Spearman’s rank correlation coefficients

Connection with businesses operating across different industries 0.1421*

Connection with businesses operating within the same industry 0.2050*

Frequency of interaction with businesses operating across different industries 0.2330*

Frequency of interaction with businesses operating within the same industry 0.1869*

Note:

* indicates 10 % significance level.

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Fig. 2. Structural model. This figure demonstrates the path algorithm of variables.

Table 6

Results from thematic analysis. This table shows the positive impacts of symbiotic relationships on the performance of MSMEs.

Increase elements of return Reduce elements of risk

Increase opportunity to:

• cooperate with experts ^Reduce:• advertising expenses

• increase sales and customer numbers • cost of goods sold

• receive information and to attend training or workshops

• enlarge market share and distribution. • delivery expenses

• transaction costs

• maintenance costs and restocking fee financial costs

• through good trade credit conditions

Table 7

Summary results from thematic analysis. This table states the information regarding insights about trust.

Trust in service businesses Trust in trading businesses

Relationships among businesses

•Trust enables quick operation processes (which can satisfy customers).

•Trustworthiness depends on the frequency of contact and interaction.

Relationships among businesses

• Trustworthiness maintained by on-time payment in trade relationships.

• Trustworthy suppliers are critical for retailers to reduce risks in purchasing over-priced products, yet increase the opportunity to receive credit terms.

• Trade associations can be places that allow business owners to meet and build trust among memberships.

Relationships between business owners and customers

•Trust provides opportunities for businesses to increase and maintain customer numbers.

•Being members of professional associations offer firms opportunities to increase creditability and trustworthiness.

Relationships between business owners and customers

• Trust links with the opportunities to increase and maintain customer numbers.

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circulating within the network. Many MSME owners indicate that they receive beneficial information through associating in trading organisations, sporting groups and personal networks. These actions increase the opportunity to share and exchange ideas or business strategies. Strengthening and improving business management offers opportunities to hedge risks and diversify market distribution, which participants indicate are positive sources of increased returns. Symbiotic relationships either among MSMEs or between MSMEs and banks could reduce information searching costs, and allow MSMEs to reduce risk associated with asymmetry of information (Ali et al., 2019).

5. Conclusion

This study investigates the impacts of symbiotic relationships on risk, return and value of MSMEs located in a small town with a view of contributing to possibilities of promoting the gains more widely should they prove to be credible and manageable. Policy decisions surrounding MSMEs provide the socio-economic framework to achieve the challenging balance between managing risks and undesirable activities with increasing employment, income and community. The Organisation for Economic Cooperation and Development (OECD) through multiple policy papers stresses the importance of the small business sector. Cooperation between businesses leverages potential symbiotic gains, but random acts of cooperation fall short of an ethos and environment supported by regulatory initiatives with flexibility and prompt amendment as enablers rather than constrainers.

Cambridge’s branding as Home of Champions stems from it being the base of high-performance sports’ institutes for rowing, canoeing and kayaking, cycling, rugby, mountain bikes and it is also the centre of thoroughbred and standard bred horse breeding.

Local business groups working with the Chamber of Commerce aspire to including sustainable businesses under the branding umbrella.

This study enhances understanding of phenomena, situations and interactivities in terms of symbiotic relationships and their impact.

Based on Resource Dependence Theory, the study finds that symbiotic relationships have positive impacts on the elements of risk and return of MSMEs. Business symbiosis enables MSMEs to reduce costs and expenditures as well as to increase returns, and to add value to business performance. From interviewing participants, location proximity, two-way relationships, trustworthiness, and good corporate governance support and maintain symbiotic relationships among MSMEs in Cambridge, while referrals are signals indicating how different MSMEs connect to each other.

This study contributes to the literature regarding strategic financial management and small business. By drawing on Resource Dependence Theory, the study provides a clear picture of connections among MSMEs across different industries, and demonstrates the value added in terms of improvement in returns which can be applied internationally. The findings of this study encourage MSMEs, and banks, government and policy makers to focus on factors relating to the concept of symbiosis and adopt them to improve returns and to reduce risk and uncertainty for MSMEs. Careful consideration of key factors before generating any action plans for both MSMEs and a community offers opportunities to increase net worth and wellbeing.

In general, related entities considering how to use ‘the advantages of a small town’ can apply this model. Where business sites of MSMEs are located in close proximity, the potential gains from a group of entrepreneurial spirits promoting personal interactions of MSME owners/managers seeds a symbiotic field. From our findings, this can start within the seven dense networks and spread across different networking areas. An organisation, such as the Chamber of Commerce, fulfilling the role as a key node, fosters the early stage engagement of other visible, viable and valuable nodes.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Appendix A

Survey of business symbiosis in MSMEs

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