Inter-firm collaboration

Inter-firm collaboration is described as a practice in which different firms collaborate formally or informally and make joint policies that affect all parties (Cambra-Fierro, Florin, Perez, & Whitelock, 2011; Jambou, Torre, Dermine-Brullot, & Bourdin, 2022). The phenomenon of inter-firm collaboration is not new (Vatne & Taylor, 2018). However, with the emergence of new technologies and globalization, it has become relatively easy to develop collaboration and gain higher returns with more effective collaboration. With inter-firm collaboration, firms create and maintain direct and indirect relationships (Zulu-Chisanga, Chabala, & Mandawa-Bray, 2020), and as a result, they become a part of a network which results in easy access to information, knowledge, and know-how of other networks (Loebbecke, Fenema, & Powell, 2016) with all the partnering firms acting as source and also as a destination for the information (Owen-Smith & Powell, 2004).

According to RBT, sustainable competitive advantage is based on tangible and intangible resources (Soliman & Noorliza, 2020) including inter-firm collaboration. This valuable, rare, and inimitable intangible resource has the potential to create a competitive advantage. Thus, the concept of inter-firm collaboration is aligned with the RBT of the firm. All the above-mentioned intangible resources can be utilized by firms for overcoming the problem of scientific knowledge, resources, and competencies (Cui, Tong, Teo, & Li, 2020). It improves the firm’s performance by decreasing production costs which makes it easier for firms to enter the international markets (Porter, 1980). Inter-firm collaboration glorifies the image of the organization which is helpful in the international market (Zhang & Pezeshkan, 2016). Firms can also choose different types of partners for exporting, depending upon their goals (Hernández-Espallardo, Sánchez-Pérez, & Segovia-López, 2011; Rialp-Criado & Rialp-Criado, 2018) that could enhance their performance in the international market. The success of SMEs significantly depends on the exploitation of knowledge that is created outside the firm (Forés & Camisón, 2016; Klein & Todesco, 2021). Like large-scale firms, SMEs can also build collaboration with other firms in the same industry and across the industries to improve their export performance (Lee, Park, Yoon, & Park, 2010). The main reason for SMEs to develop inter-firm collaboration is to overcome the constraint of resources (Oliver, 1990; Sarti, 2017). Inter-firm collaboration for SMEs results in greater external economies and effective new opportunity exploitation (Narula, 2004). It improves the firm knowledge of exporting to enhance the export performance (Lin & Chaney, 2007).

Firm export performance

Export performance is the firm accomplishment of its planned goals through export (Kostevc, 2022; Oura, Zilber, & Lopes, 2016). Firm export performance is continuous engagement in exporting with effectiveness and efficiency (He & Huang, 2020; Shoham, 1991). Different authors (Atkin, Khandelwal, & Osman, 2017; Calantone, Kim, Schmidt, & Cavusgil, 2006; Leung & Sharma, 2021) viewed firm export performance as an indicator of firm higher performance. Firm export performance is acknowledged as a multi-dimensional notion and is considered as the outcome of inter-firm collaboration (Blomqvist & Levy, 2006). Different tools have been proposed for measuring export performance including export intensity (Azar & Ciabuschi, 2017; Tookey, 1964), continuous engagement in export activity (Brooks & Rosson, 1982; Imran, Aziz, & Hamid, 2017), and profitability (Bilkey, 1982; Emőke-Szidónia, 2015).

From the RBT perspective, a firm can develop and create a sustainable competitive advantage based on its resources and capabilities (Barney, 2001). For better export performance, the firm should use its unique resources and capabilities. It is affected by both internal and external organizational factors that are rare, inimitable, and valuable. Internal factors are internal characteristics of a firm like production and marketing whereas external factors include phenomena like market and industry characteristics (Leonidou, Katsikeas, & Samiee, 2002). Therefore, for better export performance, the resources and capabilities an organization uses should be rare, inimitable, and valuable (Gueler & Schneider, 2021). The other factors that affect firm export performance include owners decision-making, management commitment, knowledge, skills, and business attitude along with a positive environment for exporting, uniqueness of products, and support from other organizations (Cavusgil & Zou, 1994; Wang & Olsen, 2002). These factors vary from firm to firm (unique), rare, and no other firm can copy them. Furthermore, the inter-firm collaboration also enhances the firm export performance as it provides knowledge and resources, the scarcity of which impedes export performance of a firm (Johanson & Vahlne, 1990; Paul, Parthasarathy, & Gupta, 2017). Thus, aligning the firm export performance with RBT. On the other hand, firm export performance affects the overall performance of firms and their reputation which eventually influences the overall industry export performance. Based on these arguments, the following hypotheses are developed:

H1: There is a positive relationship between inter-firm collaboration and industry export performance.

H2: Inter-firm collaboration is positively associated with the firm’s export performance.

Export performance of the industry

Industry export performance is the general achievement of export goals by an industry (Durmuşoğlu, Apfelthaler, Nayir, Alvarez, & Mughan, 2012; Mata, Falahat, Correia, & Rita, 2021). According to different researchers, industry export performance is dependent on inter-firm collaboration by making the partner firms more effective and efficient in terms of resource sharing, knowledge sharing, and collective working to enhance the industry exports (Bhavani & Tendulkar, 2001; Dodgson, 2018; Mokhtarzadeh, Mahdiraji, Jafarpanah, Jafari-Sadeghi, & Cardinali, 2020; Singh, 2009). Inter-firm collaboration enables the partnering organizations to build a relationship of trust and develops an environment where partner firms share resources to achieve effective firm as well as industry performance (Kohtamäki, Partanen, Parida, & Wincent, 2013; Mcevily, Perrone, & Zaheer, 2003). It also helps in improving the financial position of enterprises and positively affects the balance of payment (Balassa, 1978; Cooper, Hartley, & Harvey, 2018). Additionally, SMEs around the world mostly are resource constrained and do not have enough resources to export their products (Fletcher & Harris, 2012; Liem, Khuong, Khanh, & H, 2019); however, with effective collaboration, they can share resources, knowledge, and methods and create synergistic combinations to augment the overall export performance of the sector. All the above-given discussions support the RBT viewpoint for enhancing the export performance of the industry. Thus, the hypotheses developed are:

H3: The firm export performance is positively associated with industry export performance.

H4: The mediating effect of firm export performance on inter-firm collaboration and industry export performance.

Measurement of variables

The questionnaire for inter-firm collaboration consisted of an 18-items, 5-point likert scale adapted from the study of Hocevar, Jansen, and Thomas (2012). It contained items like ‘effective inter-firm collaboration is on high priority for our firm’ and ‘our organization’s procedures are flexible and responsive to the requirements of other firms ’. Inter-firm collaboration was measured using a single additive index that computed Cronbach’s α coefficient value of 0.83.

Industry export performance was measured using an instrument adapted from the same Hocevar’s study and contained 7-items, measured through 5-point likert scale. Sample items are ‘inter-firm collaboration increased export performance of the industry ‘ and ‘employees of our firm have the freedom to collaborate with other firms for enhancing the industry export performance ’. These items produced Cronbach’s α coefficient value of 0.79.

Firm export performance was also measured using an instrument adapted from the same study and contained a 9-items, 5-point likert scale. Sample items included items like ‘due to inter-firm collaboration, our firm export has increased’ and ‘after the inter-firm collaboration, our knowledge about foreign markets has been improved’ were used. For, firm export performance, the value of the coefficient of Cronbach α was calculated to be 0.81.

In addition to these variables, some variables were controlled for better estimation of relationships. Variables that were controlled are firms’ age, firms’ number of employees, as well as annual sales turnover. The age of the firm was coded as 1= under 4 years, 2=4 to 8 years, 3=8 to 12 years, 4=12 to 16 years, and 5=16 or more years. The number of employees was coded as 1= less than 50 employees, 2=51-100 employees, 3=101-150 employees, 4=151-200 employees, and 5= 201-250 employees. Annual sales turnover was coded as 1= less than 50 million rupees, 2= 50 million to less than 200 million rupees, 3=Rs. 200 million to less than 400 million rupees, 4= 400 million to less than 600 million rupees, and 5= 600 million to less than 800 million rupees.

Assessment of the measurement model

Confirmatory factor analysis was computed by utilizing AMOS for examining the scale validity. Convergent validity was tested using CR and AVE values. The results show that CR>0.07 which is the threshold value. Similarly, the AVE value was higher than the threshold value of 0.50 as well as CR is greater than the AVE which confirmed the discriminant validity of the construct. Results are presented in Table 1.

For testing overall model fitness, three different models were tested with different indicators. In the first model, the three variables related to current research were loaded on a single factor (χ² = 119.79; df = 109; p < .001; CFI = .79; GFI = .81 and SRMR = .19). Second model merged the inter-firm collaboration and industry export performance as a single factor and firm export performance was considered as the second variable (χ² = 129.21; df = 112; p < .001; CFI = .86; GFI = .87 and SRMR = .10). The Last model was a three-factor model with each variable of study considered as a separate factor (χ² = 141.12; df = 118; p < .001; CFI = .90; GFI = .91 and SRMR = .071). All the statistical results of χ², df, CFI, GFI, along with RMSEA for model-3 convincingly met the threshold values as the threshold value of GFI and CFI>= 0.90 (Hu & Bentler, 1999) and in the current study, the GFI and CFI resulted values were 0.91 and 0.90, respectively and the value of RMSEA was found to be 0.071 while recommended value is 0.08 or lesser (Hu & Bentler, 1999).

Descriptive analysis

Table 2 shows descriptive and correlation results. The descriptive statistics show that the average age of the firm was 3.14 with a standard deviation of 1.73 which means that on average, the age of the firm was greater than 12 years. The mean value of employees was 2.97 with an SD of 0.98 which implies that on average, each firm was heaving almost 100 employees. The mean of annual sales turnover was 2.12 with a mean of 1.03 which means that the annual sales turnover of sample firms was more than 50 million but less than 200 million. The correlation results in Table 2 confirmed the existence of a significantly positive association among all three constructs of interest of current research. The value of the coefficient of correlation (r) between inter-firm collaboration and firm export performance is 0.45, between industry export performance and inter-firm collaboration (0.32), and between industry export performance and firm’s export performance (0.43).

Mediation analyses

For testing the mediating effects, the Baron and Kenney 4 steps approach was used. Table 3 and Table 4 represent the results of mediation. Multiple regression analysis was utilized to test theBaron and Kenny (1986) 4 steps. As shown inTable 3, the association between inter-firm collaboration as well as industry export performance is significant and both are associated positively with each other (β = 0.17, t=5.73, p< 0.001) which confirms the first condition of Baron and Kenny and also confirmed the H1. The association between inter-firm collaboration and firm export performance is also confirmed (β =0.25, t= 9.76, p<0.001), so H2 is confirmed also. The third requirement of Baron and Kenny’s approach was confirmed with a significant association between the firm’s export performance as well as industry export performance (β =0.32, t= 10.14, p< 0.001) and founding on these outputs, H3 is statistically accepted.

For fourth condition, multiple regression analysis was done. Three models were tested. Model-I illustrated the impact of inter-firm collaboration on industry export performance. Controlled variables were added in model-II whereas in model-III mediating variable i.e. firm export performance was added.

In model-I, as shown in Table 4, inter-firm collaboration has a significant effect on industry export performance (β=.10, SE=0.05) and when the controlled variables were entered in the same relationship in model-II, the relationship remained significant (β=.12, SE=0.051). In model-III, firm export performance was introduced as a mediating variable which resulted in turning the association of inter-firm collaboration and industry export performance to insignificant (β=.0.05, SE=0.47) whereas the association among firm export performance as well as industry export performance was established as significant (β=.0.26, SE=0.024). This confirmed that firm export performance fully mediates the association between inter-firm collaboration and industry export performance. Thus, H4 is accepted.

As Baron and Kenny 4 step method only depicts the occurrence of mediation and does not predict its strength, so normal test method advocated byPreacher and Hayes (2008) was utilized to calculate the size along with the strength of the indirect effect. The results of the Preacher and Hayes approach (Z = 3.09, and p<0.001) confirmed the indirect effect that is (0.22-0.06=0.16).