Abstract
Purpose
The purpose of this paper is to examine the influence of entrepreneurial orientation on the network and exhibitor’s performance. The entrepreneurial orientation is seen as a highly competitive factor for the company, which can foster its trade fair business.
Design/methodology/approach
A survey-based quantitative approach was adopted, including a questionnaire (n = 362) applied to companies participating in trade fairs. To arrive at results, the study developed structural equations modeling techniques, using SPSS 24 and AMOS 20 software.
Findings
The study demonstrates positive impacts of entrepreneurial orientation on network capability and consequent exhibitor’s non-sales performance and exhibitor’s sales performance. A conceptual model is presented.
Research limitations/implications
The study was carried out mainly on Portuguese companies, restricting its generalization. In addition, the exhibitor’s performance was measured based on the exhibitors’ level of satisfaction and not on real sales results.
Practical implications
The study offers a process which the results highlight such as innovativeness, proactivity, risk-taking, competitiveness and autonomy (dimensions of entrepreneurial orientation) as a mix of important ingredients for the exhibitor’s networking. The networking promotes intangible results (non-sales performance) that can generate sales (sales performance).
Originality/value
The study is the first research to apply entrepreneurial orientation in the trade fair context and it also presents a relationship between non-sales performance and sales performance.
Keywords
Citation
Silva, P., Teixeira Vale, V.T. and Moutinho, V.F. (2022), "What is the value of entrepreneurial orientation on the network and performance? An examination in trade fairs context", Innovation & Management Review, Vol. 19 No. 1, pp. 62-83. https://doi.org/10.1108/INMR-05-2020-0068
Publisher
:Emerald Publishing Limited
Copyright © 2021, Pedro Silva, Vera Teixeira Teixeira Vale and Victor Ferreira Moutinho
License
Published in Innovation & Management Review. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Trade fairs are important marketing tools (Gerschewski, Evers, Nguyen, & Froese, 2020), where many experts and businesspeople (buyers/sellers) can meet up face to face in the same space and for a short time (Locatelli, Silveira, & Mourão, 2019; Sarmento, Farhangmehr, & Simões, 2015). The exhibitors are trade fair participants who physically exhibit their products and/or services to visitors, under the guidance of a specific organizing entity (Silva, 2014).
Trade fairs are expensive actions that require exhibitors’ previous preparation (He, Li, Lin, & Liang, 2019; Nayak, 2019; Silva, 2014), so the performance of exhibitors has been a matter of growing concern (Çobanoğlu & Turaeva, 2014; Menon & Edward, 2017; Proszowska, 2018; Tafesse & Korneliussen, 2011; Tafesse & Skallerud, 2017). Although there are many studies on measuring the effectiveness of trade fairs for exhibitors (Çobanoğlu & Turaeva, 2014; Gopalakrishna & Lilien, 1995; Hansen, 2004; Menon & Edward, 2017; Proszowska, 2018; Tafesse & Korneliussen, 2011), measuring their performance is seen as a major difficulty (Cop & Kara, 2014; Kitchen, 2017). Tafesse and Skallerud (2017) found that in most recent articles, the researchers tend to use non-sales metrics to analyze the exhibitor’s performance while in the past, researchers mainly used sales-related metrics. Therefore, it will be more appropriate to integrate the analysis of the exhibitors’ performance in both sales and non-sales perspectives (Çobanoğlu & Turaeva, 2014; Hansen, 2004).
The main question is knowing how exhibitors can make the most of trade fairs. In this sense, entrepreneurial orientation emerged from literature as an important determinant for the development of business competence (Al Mamun, Fazal, & Muniady, 2019; Hooi, Ahmad, Amran, & Rahman, 2016; Martins & Rialp, 2013; Mantok, Sekhon, Sahi, & Jones, 2019; Rezvani, Lashgari, & Yadolahi Farsi, 2019). Particularly, Entrepreneurial Orientation can be a relevant resource for companies to operate in a competitive environment (Martins & Rialp, 2013) that is uncertain, dynamic and associated with social and business networks (Tajeddini, Martin, & Ali, 2020) such as trade fairs, where many rival firms are engaging (AUMA – Association of the German Trade Fair Industry, 2017; Maskell, 2014) and buyers/sellers interact and develop networking (Locatelli et al., 2019).
This way, incorporating entrepreneurial orientation in the context of trade fairs allows rekindling historically rooted theoretical perspectives such as innovation. “The stagnation in these perspectives is largely inexplicable from an industry (managerial practice) point of view and as such, warrants closer examination in the future” (Tafesse & Skallerud, 2017, p. 26). Moreover, currently, it is suggested that the companies create an entrepreneur/innovative culture within the organization so that companies can achieve their goals (Nunes & Russo, 2019).
Considering that the aim of this research was to study the impact of entrepreneurial orientation on exhibitor’s performance, this study is the first attempt to use the entrepreneurial orientation in the trade fair context and analyze its impact on the network and results of exhibitors, from a sales and non-sales perspective. So, this article aims to conduct an empirical study designing a comprehensive model, considering entrepreneurial orientation as a tool that can enhance the exhibitor’s performance.
The paper consists of six sections. Following the introduction, Section 2 presents the theory and hypotheses development about entrepreneurial orientation construct and describes its relationship (network capability) to exhibitors’ performance. Section 3 describes the methodology and empirical context where the survey was carried out. Section 4 reports the results and Section 5 discusses the findings. Finally, Section 6 presents the main conclusions, limitations and future research.
2. Theory and hypotheses development
2.1 Entrepreneurial orientation – concept
Entrepreneurial orientation is a general strategic posture toward entrepreneurship (Gupta & Gupta, 2015). Entrepreneurship is an act of innovation that involves empowering the existing resources of a new wealth-producing capacity (Drucker, 1985). However, entrepreneurship is presented in the literature in multiple perspectives, generating a multidimensional concept (Bula, 2012) and is used in many areas and contexts (Hoppe, 2016). However, regardless of the various applications, concepts and dimensions, the central issues in entrepreneurship involve uncertainty and risk-taking, innovation, perception and change (Essays, 2018).
In the business area, Miller (1983) states that an entrepreneurial company is one that is dedicated to product and market innovation, undertaking somewhat risky business and being proactive toward its competitors. Entrepreneurial orientation refers to the extent to which a company is entrepreneurial in its plans and activities, encompassing the company’s processes, structures and behaviors (Stam & Elfring, 2008). Lumpkin and Dess (2001) defined entrepreneurial orientation as the companies’ strategy-making process that engages in entrepreneurial activities (create new businesses, products, transformative decisions, etc.). However, Lumpkin and Dess (2001) pointed out that there is a difference between entrepreneurship and entrepreneurial orientation. The term entrepreneurial orientation refers to a series of dimensions toward organizational level (Lumpkin & Dess, 2001), that is, a company’s capabilities (Yoon, Kim, & Dedahanov, 2018).
In general, the literature suggests entrepreneurial orientation as a strategic stance at the company’s level encompassing three dimensions: risk, innovation and proactivity (Miller 1983; Miller & Friesen, 1982; Martins & Rialp, 2013; Mthanti & Ojah, 2017). The Innovation dimension can be interpreted as a tendency to engage creativity and experimentation by introducing new products/services and using technology through research and development in new processes (Mason, Floreani, Miani, Beltrame, & Cappelletto, 2015). Innovative practices can help increase the competitiveness of companies (Berne, Coda, Krakauer, & Donaire, 2019). The proactivity dimension is an anticipatory behavior seeking opportunities and characterized by the introduction of new products and services ahead of the competition (Mason et al., 2015). Moreover, a proactive attitude can facilitate the establishment and maintenance of network relationships with key stakeholders (Gerschewski et al., 2020). Finally, the Risk dimension involves bold action and adventure into the unknown, investing or committing significant resources to ventures in uncertain environments (Mason et al., 2015).
Recently, Fadda (2018) added two more dimensions: competitiveness and autonomy. The competitiveness dimension refers to the company’s attitude when dealing with competitors, which means continuously monitor and combat their rivals’ strategies. This concept partly clashes with Mason et al.’s (2015) proposal for proactivity. The autonomy dimension can be considered as a predisposition for the development of appropriate conditions and the subsequent implementation of innovative ideas (Fadda, 2018).
In summary:
Entrepreneurial orientation is a path that entrepreneurs take to create a “new entry,” which can be defined as the creation of a new business, new products or technology or a new market. It can also be defined as a set of strategies within a conceptual domain encompassing results at the organizational level, related to management preferences, beliefs and behaviors expressed through managers (Santos & Marinho, 2018, p. 121).
2.2 Entrepreneurial orientation as a tool for exhibitors
As mentioned initially, entrepreneurial activity currently contains multidimensionality of concepts (Bula, 2012) and is applied in various areas, circumstances and contexts (Hoppe, 2016). For instance, evidence from several recent studies shows that entrepreneurial orientation has a positive effect on business competence (Al Mamun et al., 2019; Hooi, et al., 2016; Knight, 2000; Martins & Rialp, 2013; Mantok et al., 2019). In fact, companies with a high degree of entrepreneurial orientation are more plausible to prosper (Maleki & Hajipour, 2020). Thereby, in general, entrepreneurial companies could operate more easily in demanding external environments against conservative companies (Martins & Rialp, 2013; Tajeddini et al., 2020). Therefore, as trade fairs are a highly competitive environment to exhibitors (AUMA – Association of the German Trade Fair Industry, 2017; Maskell, 2014), it is suitable to analyze and verify the entrepreneurial orientation of companies (exhibitors) participating in them.
Then, based on literature, it is interesting to study if the five dimensions – innovativeness, proactiveness, risk-taking (Fadda, 2018; Miller, 1983; Miller & Friesen, 1982; Martins & Rialp, 2013; Mthanti & Ojah, 2017; Yoon et al., 2018), competitiveness and autonomy (Fadda, 2018) – fit in trade fair environment. So, the following hypotheses are defined:
In the trade fair context, innovativeness contributes positively to the exhibitors’ entrepreneurial orientation.
In the trade fair context, proactiveness contributes positively to the exhibitors’ entrepreneurial orientation.
In the trade fair context, risk-taking contributes positively to the exhibitors’ entrepreneurial orientation.
In the trade fair context, competitiveness contributes positively to the exhibitors’ entrepreneurial orientation.
In the trade fair context, autonomy contributes positively to the exhibitors’ entrepreneurial orientation.
2.3 Entrepreneurial orientation as a networking determinant
Trade fairs generally attract thousands of experts and businesspeople (buyers/sellers), who can meet up face to face (networking) in the same space and at the same time (Locatelli et al., 2019; Sarmento et al., 2015). One of the great riches of the trade fairs is the possibility to create interactions, relationships, generate networking (Gopalakrishna, Malthouse, & Lawrence, 2019; Kitchen, 2017; Measson & Campbell-Hunt, 2015; Sarmento & Farhangmehr, 2016). However, exhibitors need to have tangible and intangible resources that allow them to facilitate interactions and promote close relations with the visitor (Rinallo, Bathelt, & Golfetto, 2017). Innovation is a major resource of the trade fair’s attractiveness (Sarmento et al., 2015), but Entrepreneurial Orientation is an important resource for networking development (Jiang, Liu, Fey, & Jiang, 2018; Strenge & Rank, 2018; Yoon et al., 2018) which has never been studied in the trade fair context. Therefore, exhibitors’ entrepreneurial orientation can have effects on their network capacity, defined as a “complex organizational capability oriented toward managing business relationships along all their main development stages” (Mitrega, Forkmann, Ramos, Henneberg, 2012, p. 739). In other words, network capability “is the ability to manage and gain benefits from external relationships” (Vinit, Ossi, Joakim, & Mats, 2017, p. 94), for example, customers, institutions, competitors, partners, etc.
Thus, it is hypothesized that in the context of the trade fair:
Entrepreneurial orientation of the exhibitor has positive effects on their network capability.
2.4 Network capability on exhibitor's performance
The interest of the trade fairs is to generate networking and convert contacts into results (Gopalakrishna et al., 2019; Measson & Campbell-Hunt, 2015; Sarmento & Farhangmehr, 2016). Companies need a network of relationships to share their values and objectives, to drive the Entrepreneurial Orientation toward the desired results (Ruiz-Ortega, Parra-Requena, & García-Villaverde, 2021). Particularly, network capacity can act as a determinant for company performance (Jiang, et al., 2018; Strenge & Rank, 2018; Yoon et al., 2018).
Performance is a process that aims to match the company’s strategies, corporate and functional objectives (Bititci, Carrie, & McDevitt, 1997; Al-Matari, Al-Swidi, & Hanim, 2014). Generally, companies’ performance refers to the links between accounting returns, stock market and growth (Vasconcelos & Oliveria, 2018). However, Murugesan, Gayathri, Vasanth, Lingaraja and Marxia (2016) report that a company’s performance can be determined by several dimensions: profitability, growth, market value, customer satisfaction, employee satisfaction, environmental performance, corporate governance and social performance. Abbas, Raza, Nurunnabi, Minai and Bano (2019) include as company’s performance factors: profit and sales goals, return on investment (ROI) goals, product quality, customer retention against competitors, reputation, employee turnover and new product development against the competition. Therefore, companies often define and aim to achieve certain goals to create, elevate, improve and sustain superior performance (Abbas et al., 2019; Eisenhardt & Martin, 2000).
In the trade fairs’ case, exhibitors can set different objectives: transactional (sales), informational (information sharing), social (relational), symbolic and cultural (Tafesse & Skallerud, 2017). Gopalakrishna and Lilien (1995) indicate as measures of the exhibitor’s performance:
attraction efficiency index (target visitor);
contact efficiency index (with audience visitors); and
conversion efficiency index (the ratio of actual sales conversations to the number of visitors who made contact).
Menon and Edward (2017) identified five dimensions of the exhibitor’s performance: sales performance, information gathering, networking, image building and motivations. Çobanoğlu and Turaeva (2014) point four measurement factors: image-building performance, sales-related performance, relationship-building performance and information-gathering performance.
From these authors, it can be extracted that exhibitors’ performance can be divided into two types: non-sales performance and sales performance (Menon & Edward, 2017). Curiously, trade fairs receive two types of customers/visitors: “Shopper” and “Total Visitors” (Rittichainuwat & Mair, 2012; Sarmento & Farhangmehr, 2016). The “Shopper” seeks product/service for future purchase intention. “Total Visitors” always want to be informed about new market trends and memorable experiences at trade fairs (Rittichainuwat & Mair, 2012; Sarmento & Farhangmehr, 2016).
Thus, in the present study, it is convenient to divide the exhibitor’s performance: non-sales performance and sales performance (Menon & Edward, 2017), being that non-sales performance are intangible results such as reputation, information gathering, relationships, etc., and sales performance are tangible results such as sales, profit, return on investment.
Generally, sales performance is a consequence of non-sales performance (Kotler & Keller, 2015). For example, relational variable influences sales performance (Hasaballah, Genc, Mohamad, & Ahmed, 2019) and knowledge management effects on the business success (Zebal, Ferdous, & Chambers, 2019).
When it comes to trade fairs, sales do not necessarily have to happen on the spot because the “Shopper” seeks product/service for future purchase intention and exhibitor’s performance is a process that does not end at the trade fair (Sarmento & Farhangmehr, 2016). In fact, generally, 1/3 of the exhibitors follow up on contacts after the trade fair (Kitchen, 2017).
Based on the above arguments, the hypotheses that will be tested are as follows:
Network capability of the exhibitors has positive effects on their non-sales performance.
Exhibitors’ non-sales performance has positive effects on their sales performance.
2.5 Conceptual model
Fadda (2018), Martins and Rialp (2013), Santos and Marinho (2018) and Yoon et al. (2018) explained the different dimensions of entrepreneurial orientation. Jiang et al. (2018), Strenge and Rank (2018), Yoon et al. (2018) demonstrated that entrepreneurial orientation has positive effects on network capability. Particularly in the context of trade fairs, companies seek to develop networking to obtain results (Gopalakrishna et al., 2019; Kitchen, 2017; Measson & Campbell-Hunt, 2015; Sarmento & Farhangmehr, 2016).
In fact, the exhibitor’s performance justifies his participation in the trade fair (Çobanoğlu & Turaeva, 2014; Menon & Edward, 2017; Proszowska, 2018; Tafesse & Korneliussen, 2011; Tafesse & Skallerud, 2017). Jiang et al. (2018), Strenge and Rank (2018) and Yoon et al. (2018) revealed that network capability can have positive effects on companies’ performance.
Rittichainuwat and Mair (2012), Sarmento and Farhangmehr (2016) demonstrated that trade fairs receive different visitors so the exhibitors’ results can be divided into sales performance and non-sales performance (Kitchen, 2017; Menon & Edward, 2017; Rittichainuwat & Mair, 2012; Sarmento & Farhangmehr, 2016). Sarmento and Farhangmehr (2016) reveal that sales performance can happen after the trade fair, as a result of non-sales performance (Kotler & Keller, 2015). Such a sequence informed the theoretical model of this study.
Figure 1 shows the model and hypothesized relationships.
3. Methodology
This study focuses on the trade fairs’ exhibitors. The questionnaire was prepared and addressed to the marketing and/or sales director of companies participating in trade fairs. A survey-based quantitative approach was adopted to analyze the relationship between the study’s variables.
3.1 Survey
Survey research is “the collection of information from a sample of individuals through their responses to questions” (Check & Schutt, 2012, p. 160). This type of research allows a variety of methods to recruit participants, collect data and use various methods of analysis such as questionnaires (Hair, Black, Babin, & Anderson, 2014).
Based on the literature review, a questionnaire was developed (see Table A1 in the Appendix). The instrument had a clear and direct format and comprised two parts, beginning with a presentation of the scope and objectives of the study.
The first part served to measure the constructs. The constructs that make up the conceptual model are:
Entrepreneurial orientation and its dimensions (subconstructs- innovativeness; proactiveness; risk-taking; competitiveness; autonomy);
Network capability;
Exhibitor’s sales performance; and
Exhibitor’s non-sales performance.
The items that measure the different constructs (although adapted to the context) were used from research instruments validated by different authors (Table A1).
However, to reinforce the validity of the content, a panel of experts composed of academics and industry practitioners was invited to review the initial items of the questionnaire. The cooperation of these experts was positive and helped to build an appropriate questionnaire for the study.
All variables were measured on five-point Likert scales, ranging from one (1) – totally disagree to five (5) – totally agree.
The second part contained questions related to the characteristics of the respondent companies such as type of company, size of the company (turnover), the intensity of participation in trade fairs, volume of exports (%) and the company’s country of origin.
3.2 Data collection
The population of this study was unknown, thus a database of the exhibitors’ lists was created from various trade fairs’ organizers such as Exponor (Portugal), FIL (Portugal), ExpoSalão-Batalha, as well as business associations such as ATP – Portuguese Textile and Clothing Association; APIMA – Portuguese Association of Furniture and Related Industries; APICCAPS – Portuguese Footwear, Components, Leather Goods Manufacturers’ Association; or public business support institutions: IAPMEI – Institute of Support to Small and Medium Enterprises and Innovation; and AICEP – Agency for Investment and Foreign Trade of Portugal. So, data was collected through the database created with companies participating in international trade fairs. The questionnaire was sent by email between 3rd and 31st January 2020, addressed to the marketing and/or sales directors of the companies present in the databases, resulting in 362 complete responses.
3.3 Data analysis
SPSS 24.0 and Amos 20.0 statistical programs were used for data analysis. This three-step stage was used to validate the scales and examine the dynamic relationships among the constructs of the study.
In the first step, despite them having been validated by previous authors but because of adaptations, exploratory factor analysis (EFA) with varimax rotation was used to purify the items. EFA is used to extract the right number of constructs and identify the underlying measurement items (Devellis, 2012).
In the second step, confirmatory factor analysis (CFA) with maximum likelihood estimation was conducted to validate the measurement scales of the constructs (Hair et al., 2014). Then, reliability and validity measures were tested and structural equation modeling (SEM) was performed to test the proposed model and hypotheses. SEM is used to determine if a certain model is valid and allows to associate several measures to a single latent construction (Hair et al., 2014; Marôco, 2014). Finally, the maximum likelihood procedure was used to estimate the measurement model and structural model. In addition, model fit indexes were examined for model fit (Hair et al., 2014).
4. Results
4.1 Sample profile
Descriptive analysis was done to obtain the profile of the respondent companies: 362 complete questionnaires were collected.
The sample size is in accordance with previous studies, for example, Fadda (2018); Kitchen, (2017); Rittichainuwat and Mair (2012); Sarmento and Farhangmehr (2016). In addition, the sample size is also adequate given the proportion of items used (Devellis, 2012). Table 1 provides detailed information about the companies/exhibitors.
4.2 Exploratory factorial analysis
Throughout EFA the theoretically interpretable and substantial factors must be maintained (Kim & Mueller, 1978). So, entrepreneurial orientation (innovativeness; proactiveness; risk-taking; competitiveness; autonomy); network capability; exhibitor’s non-sales performance; exhibitor’s sales performance were assessed. Table 2 shows the EFA findings.
Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) and Bartlett’s test of sphericity were evaluated to ensure the appropriateness of the data for EFA.
The results show that in general, the KMO coefficient was greater than 0.80 and Bartlett’s test was significant at the 0.05 level, indicating the adequacy of the items (Hair et al., 2014). The KMO coefficient was also analyzed for all constructs individually, showing adequate indicators.
Items with factor loadings lower than 0.50 or cross-loaded items were removed (P2 and C4) and the remaining items were factor analyzed again (Hair et al., 2014). So, the total variance explained is greater than 0.710, which exceeds the threshold value of 60%. Therefore, the total validity of the scales is reasonable (Hair et al., 2014).
Finally, Cronbach’s alpha was applied to test the reliability of the constructs, as shown in Table 2. The Cronbach’s alpha of all constructs is greater than 0.7, but that of the full scale is greater than 0.90. Therefore, AFE results indicate high internal consistency (Hair et al., 2014).
4.3 Confirmatory factor analysis
CFA was applied based on the output of EFA using Amos 20. CFA allows assessing the overall model fit for the full measurement model (Hair et al., 2014; Marôco, 2014). Nevertheless, a new analysis of the items was assessed to improve model fit indices. Therefore, based on Modification Index, we analyzed error/cross-loading correlations (Whittaker, 2012) and the items (IN1; IN4; P4; RT2; RT4; C1; A4; NW1; NW5 and ENP4) were excluded because of high error correlations (Whittaker, 2012).
Table 3 summarizes the final items and constructs. Through Cronbach’s alpha, it is verified that all items are scored in the same direction – appropriate reliability (Hair et al., 2014). However, there are two subconstructs (risk-taking = 0.592; competitiveness = 0.617) with low Cronbach’s alpha. Still, in the general composition of the main construct (entrepreneurial orientation = 0.848) Cronbach’s alpha presents adequate reliability (Hair et al., 2014).
Table 3 also shows the mean, which is a measure of central tendency and provides an indication of the average value of a distribution of responses to each item. In the same table, we present the standard deviation (SD) that shows the variation of the mean of each item (Barde & Barde, 2012). A low SD indicates that the data tends to be close to the mean (Barde & Barde, 2012), in this specific case the results are acceptable.
The structural equation allowed to test the hypotheses of relationships as illustrated in Figure 1. Consequently, several indicators were used to assess the model fit: X2/DF; CFI – comparative fit index; NFI – normed-fit index; TLI – Tucker Lewis index or NNFI – non-normed fit index; IFI – incremental fit index; GFI – goodness of fit index; AGFI – adjusted goodness of fit index; RFI – relative fit index; RMSEA – root mean square error of approximation; PNFI – parsimonious normed fit index and PGFI – parsimony goodness-of-fit index.
CFA results indicate an appropriate fit for the data: X2 = 275.768; DF = 162; X2/DF = 1.702 (Bollen, 1989); CFI = 0.969 (Jöreskog & Sörbom, 1993); NFI = 0.929 (Garver & Mentzer, 1999); GFI = 0.930 (Jöreskog & Sörbom, 1984); AGFI = 0.910 (Hooper, Coughlan, & Mullen, 2008); TLI = 0.964 (Tucker & Lewis, 1973); IFI = 0.970 (Bollen, 1989); RFI = 0.917 (Hair et al., 2014); RMSEA = 0.044 (Hair et al., 2014); PNFI = 0.792; and PGFI = 0.718 (Mulaik, James, Van Alstine, Bennet, Lind, & Stilwell, 1989). Then, the average variance extracted is more than 0.533, being recommended >0.50 (Bagozzi & Yi, 1988; Hair et al., 2014).
Based on several authors, the obtained results indicate a model considered to be well adjusted. The indicators demonstrate a great level of unidimensionality and convergent validity. Figure 1 shows the standardized estimation of the conceptual model.
Finally, in the CFA, CR – composite reliability, AVE – average variance extracted, MSV – maximum shared variance, ASV – average shared variance was used. Hair et al., (2014) suggest the following limits for these values: CR > 0.7; AVE > 0.5; MSV < AVE; ASV < AVE.
These values are expressed in Table 5, indicating an appropriate level of unidimensionality and convergent validity (Hair et al., 2014).
As we can see in Table 4, all AVE were greater than 0.50, providing additional support for convergent validity (Hair et al., 2014). The composite reliability of all scales was >0.80, providing an appropriate level (Fornell & Larcker, 1981; Hair et al., 2014). In addition, Fornell and Larcker (1981) and Roldán and Sánchez-Franco (2012) say that to guarantee discriminant validity, the square root of the AVE measures must be superior to all the correlations among all the constructs.
Accordingly, all values support a convergent validity (Fornell & Larcker, 1981; Hair et al., 2014), validating the model in its fullness.
4.4 Structural model
The structural model with all constructs and hypothesized relationships were evaluated.
A graphic presentation of the original findings is shown in Figure 1, with standardized coefficient estimates. It should be noted that when testing H1, H2, H3, H4 and H5, it was applied a second-order CFA because it allows to the assessment of a composite of common factor configuration (Van Riel, Henseler, Kemény, & Sasovova, 2017). Hence, this operation follows the indications of Fadda (2018) and Yoon et al. (2018) on the dimensions of entrepreneurial orientation – innovativeness, proactiveness, risk-taking; competitiveness and autonomy.
In the original estimated model, all hypotheses were supported, as shown in Figure 1 and on the next topic.
4.5 Hypotheses test
Kline (2016) affirms that hypothesized directional causal effects or direct effects represent the direct influence of one variable on another variable. So, the direct effect shows that “innovativeness” (β = 0.723; p < 0.001), “proactiveness” (β = 0.863; p < 0.001), “risk-taking” (β = 0.711; p < 0.001), “competitiveness” (β = 0.741; p < 0.001) and “autonomy” (β = 0.606; p < 0.001) contribute positively to “entrepreneurial orientation,” thus H1, H2, H3, H4 and H5 are supported.
Furthermore, the results of direct effects show that “entrepreneurial orientation” has positive and significant effects on “network capability” (β = 0.712; p < 0.001), so H6 is supported; and “network capability” has significant positive effects on “exhibitor’s non-sales performance” (β = 0.766; p < 0.001), “exhibitor’s non-sales performance” on “exhibitor’s sales performance” (β = 0.630; p < 0.001), thus H7 and H8 are also supported.
In short, all the hypotheses (H1, H2, H3, H4, H5, H6, H7 and H8) were supported.
5. Discussion and findings
5.1 Summary of results
The purpose of this article is to examine the influence of entrepreneurial orientation on the network and the exhibitor’s performance.
The study aimed to analyze the relationship between entrepreneurial orientation, network and exhibitor’s performance, by proposing and testing a conceptual model of the dynamic relationship among said variables.
Based on the CFA results, the study ensures that the factors innovativeness, proactiveness, risk-taking, competitiveness and autonomy have positive contributions as elements of the entrepreneurial orientation mix, in the trade fair context. The results also demonstrate that entrepreneurial orientation has positive effects on network capability. The exhibitor’s performance was divided into non-sale performance and sales performance. Finally, the results verify that network capability has effects on the exhibitor’s non-sale performance and non-sale performance has positive effects on the exhibitors’ sales performance. Therefore, all hypotheses were supported.
5.2 Theoretical contributions
First, this research possibly presents the first study to introduce the concept of entrepreneurial orientation in studies on trade fairs. Although the entrepreneurial orientation concept (Fadda, 2018; Miller, 1983; Miller & Friesen, 1982; Martins & Rialp, 2013; Mthanti & Ojah, 2017; Yoon et al., 2018) previously applied in different contexts, the results of the study prove that the entrepreneurial orientation mix of the exhibitors, based on its five dimensions (innovativeness, proactiveness, risk-taking, competitiveness and autonomy). In addition, the present study shows that entrepreneurial orientation is a useful resource for exhibitors to develop networking (Jiang et al., 2018; Ruiz-Ortega et al., 2021; Strenge & Rank, 2018; Yoon et al., 2018) with a view to obtaining results (Kitchen, 2017; Rittichainuwat & Mair, 2012; Ruiz-Ortega et al., 2021; Sarmento & Farhangmehr, 2016). In fact, the results indicate that the exhibitor’s performance depends on the network capability and the network capacity depends on the exhibitor’s entrepreneurial orientation.
Second, based on the recognized difficulty in measuring exhibitors’ performance (Cop and Kara, 2014; Kitchen, 2017), the present study divided the exhibitor’s performance into two perspectives – sales performance and non-sales performance (Çobanoğlu & Turaeva, 2014; Menon & Edward, 2017; Sarmento & Farhangmehr, 2016) – and assessed an empirical effect between the two perspectives. Thus, it was possible to confirm that sales performance depends on non-sales performance (Kotler & Keller, 2015) and can happen in the post-trade fair phase (Kitchen, 2017; Sarmento & Farhangmehr, 2016).
5.3 Managerial implications
The practical implications of this study can be summarized in a process, as shown in Figure 2.
The exhibitor can adopt an entrepreneurial orientation by investing in innovation, adopting a proactive and risk-taking attitude, betting on competitiveness and promoting his employees’ autonomy. It must start before the trade fair as the exhibitor should prepare his participation in advance (He et al., 2019; Nayak, 2019; Silva, 2014). Then, based on entrepreneurial orientation, the exhibitor can develop networking, generate bonds and commit (Jiang et al., 2018; Ruiz-Ortega et al., 2021; Strenge & Rank, 2018; Yoon et al., 2018) during the fair. Also, the exhibitor can network with other industry members and customers to increase his reputation, gather information, etc. – non-sales performance (Çobanoğlu & Turaeva, 2014; Menon & Edward, 2017; Sarmento & Farhangmehr, 2016). More so, lead generation is one of the most imperative benefits of trade fairs (Kitchen, 2017). All an exhibitor needs to do is get in touch with these leads right after the trade fair (Kitchen, 2017; Sarmento & Farhangmehr, 2016) and grow the customer base – sales performance.
Trade fairs offer an unparalleled opportunity for face-to-face interactions with a wide array of potential customers (Locatelli et al., 2019; Sarmento et al., 2015).
So, based on this study entrepreneurial orientation emerges as a resource or an important catalyst for exhibitors to operate successfully in competitive, uncertain and dynamic environments (Martins & Rialp, 2013; Tajeddini et al., 2020) like trade fairs (AUMA – Association of the German Trade Fair Industry, 2017; Maskell, 2014).
6. Conclusion, limitations and future research
The main objective of this study was to evaluate the impact of entrepreneurial orientation on the exhibitor’s performance. Eight hypotheses were formulated to achieve this objective: H1, H2, H3, H4, H5, H6, H7 and H8.
This research project started from a theoretical foundation developed in previous studies. The research itself found that entrepreneurial orientation can operate as a recipe for companies to operate effectively in a competitive environment such as trade fairs. The study also reveals that entrepreneurial orientation can help a company to develop its network capacity, allowing it to generate results. Developing a great contact network at the trade fair is essential for the exhibitor’s success. Even a good part of the negotiations is the result of networking developed at trade fairs.
Thus, far, the present study allowed the development of a validated model and allowed the assessment of hypotheses. CFA showed results that confirm all hypotheses.
The results which confirm H1, H2, H3, H4, H5 and H6 were important contributions to the study, as no previous research had analyzed these relationships in the context of the trade fair. These results highlight innovation, proactivity, risk-taking, competitiveness and autonomy as a mix of important ingredients for the exhibitor’s networking.
Additionally, the confirmation of H8 also reveals a new way to evaluate the exhibitor’s performance. More than establishing contacts, the company needs to keep them on its radar and interact productively to gain prestige, reputation and strengthen relationships. For that reason, trade fairs become a territory that remains well beyond the event itself, transforming the networking established at the trade fair into intangible assets (non-sales performance) that add competitive advantages capable of generating sales (sales performance).
Regarding the general objective of this study, which was to analyze the impact of entrepreneurial orientation on the exhibitor’s performance, the findings are useful and with practical implications, so the objective was achieved.
This research has some limitations that must be considered. First, a study was carried out mainly on Portuguese companies, restricting its generalization. Second, exhibitors’ performance was measured based on the exhibitors’ level of satisfaction and not on real sales results.
In relation to future research directions, this survey could also be replicated incorporating other countries. Another recommendation is to conduct a study that separately analyzes each dimension of entrepreneurial orientation in a trade fair context. Finally, future studies may relate additional constructs, for example, it would be interesting to study the entrepreneurial orientation of exhibitors toward organizational learning.
Figures
Characterization of respondent companies/exhibitors
| Elements of companies characterization | n | (%) | |
|---|---|---|---|
| Company type | Manufacturer/producer | 244 | 67.4 |
| Service | 63 | 17.4 | |
| Wholesaler | 14 | 3.9 | |
| Retailer | 11 | 3.0 | |
| Importer/exporter agent | 30 | 8.3 | |
| Total | 362 | 100.0 | |
| Company size (turnover) | <500,000€ | 82 | 22.7 |
| 500,000€–1,500,000€ | 66 | 18.2 | |
| 1,500,001–2,500,000€ | 40 | 11.0 | |
| 2,500,001€–5,000,000€ | 57 | 15.7 | |
| >5,000,000€ | 117 | 32.3 | |
| Total | 362 | 100.0 | |
| Participation intensity | Sporadically | 29 | 8.0 |
| 1 trade fair every 4 years | 6 | 1.7 | |
| 1 trade fair every 2 years | 14 | 3.9 | |
| 1 trade fair per year | 95 | 26.2 | |
| Several trade fairs a year | 218 | 60.2 | |
| Total | 362 | 100.0 | |
| Export | <10% | 101 | 27.9 |
| 11%–25% | 69 | 19.1 | |
| 26%–50% | 59 | 16.3 | |
| 51%–75% | 44 | 12.2 | |
| >75% | 89 | 24.6 | |
| Total | 362 | 100.0 | |
| Country | Portugal | 341 | 94.2 |
| Other countries (+9) | 21 | 5.8 | |
| Total | 362 | 100.0 | |
Source: Own elaboration
Exploratory factorial analyzes
| Constructs | COD. | Factor loadings | Indicators | |
|---|---|---|---|---|
| Innovativeness | IN1 | 0.650 | Cronbach’s α 0.839 KMO test 0.693 | Cronbach’s α 0.839 KMO test 0.886 |
| IN2 | 0.723 | |||
| IN3 | 0.751 | |||
| IN4 | 0.682 | |||
| Proactiveness | P1 | 0.475 | Cronbach’s α 0.856 KMO test 0.772 | |
| P2 | 0.444 | |||
| P3 | 0.567 | |||
| P4 | 0.597 | |||
| Risk-taking | RT1 | 0.600 | Cronbach’s α 0.757 KMO test 0.699 | |
| RT2 | 0.723 | |||
| RT3 | 0.751 | |||
| RT4 | 0.653 | |||
| Competitiveness | C1 | 0.713 | Cronbach’s α 0.744 KMO test 0.726 | |
| C2 | 0.735 | |||
| C3 | 0.621 | |||
| C4 | 0.298 | |||
| Autonomy | A1 | 0.809 | Cronbach’s α 0.857 KMO test 0.781 | |
| A2 | 0.797 | |||
| A3 | 0.750 | |||
| A4 | 0.771 | |||
| Network capability | NW1 | 0.816 | Cronbach’s α 0.877 KMO test 0.836 | |
| NW2 | 0.761 | |||
| NW3 | 0.655 | |||
| NW4 | 0.681 | |||
| NW5 | 0.736 | |||
| Exhibitor’s non-sales performance | ENP1 | 0.548 | Cronbach’s α 0.851 KMO test 0.781 | |
| ENP2 | 0.572 | |||
| ENP3 | 0.640 | |||
| ENP4 | 0.590 | |||
| Exhibitor’s sales performance | EP1 | 0.836 | Cronbach’s α 0.910 KMO test 0.735 | |
| EP2 | 0.882 | |||
| EP3 | 0.830 | |||
Source: Own elaboration Notes: Kaiser normalization varimax rotation method, Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) = 0.913, Bartlett’s test sig. 0.000. Cronbach’s α = 0.938
Mean, SD, variance and Cronbach’s alpha
| Constructs | Items’ code | Mean | SD | Loadings EFA | Loadings CFA | Total variance explained | Cronbach’s α | ||
|---|---|---|---|---|---|---|---|---|---|
| Entrepreneurial orientation | Innovativeness | IN2 | 3.54 | 1.134 | 0.723 | 0.774 | 0.918 | 0.911 | 0,848 |
| IN3 | 3.73 | 1.116 | 0.751 | 0.749 | |||||
| Proactiveness | P1 | 3.60 | 1.033 | 0.475 | 0.640 | 0.792 | 0.737 | ||
| P3 | 3.29 | 0.992 | 0.567 | 0.517 | |||||
| Risk-taking | RT1 | 2.56 | 1.113 | 0.600 | 0.620 | 0.710 | 0.592 | ||
| RT3 | 2.75 | 1.069 | 0.751 | 0.667 | |||||
| Competitiveness | C2 | 2.95 | 1.098 | 0.735 | 0.481 | 0.723 | 0.617 | ||
| C3 | 2.83 | 1.056 | 0.621 | 0.720 | |||||
| Autonomy | A1 | 3.02 | 1.170 | 0.809 | 0.827 | 0.729 | 0.813 | ||
| A2 | 3.18 | 1.163 | 0.797 | 0.842 | |||||
| A3 | 3.35 | 1.105 | 0.750 | 0.734 | |||||
| Network capability | NW2 | 4.27 | 0.882 | 0.761 | 0.726 | 0.763 | 0.842 | ||
| NW3 | 3.91 | 1.076 | 0.655 | 0.686 | |||||
| NW4 | 3.96 | 1.031 | 0.681 | 0.739 | |||||
| Exhibitor’s non-sales performance | ENP1 | 3.89 | 0.853 | 0.548 | 0.707 | 0.744 | 0.825 | ||
| ENP2 | 3.80 | 0.943 | 0.572 | 0.706 | |||||
| ENP3 | 4.19 | 0.778 | 0.640 | 0.711 | |||||
| Exhibitor’s sales performance | EP1 | 3.06 | 0.937 | 0.836 | 0.863 | 0.850 | 0.910 | ||
| EP2 | 3.22 | 0.952 | 0.882 | 0.887 | |||||
| EP3 | 3.23 | 1.037 | 0.830 | 0.830 | |||||
Source: Own elaboration
AVE, MSV, ASV and correlation matrix of constructs
| Construct | CR | AVE | MSV | ASV | 1 | 2 | 3 | 4 |
|---|---|---|---|---|---|---|---|---|
| 1 | 0.834 | 0.558 | 0.543 | 0.434 | 0.747 | |||
| 2 | 0.870 | 0.627 | 0.543 | 0.425 | 0.737 | 0.792 | ||
| 3 | 0.871 | 0.533 | 0.476 | 0.356 | 0.616 | 0.690 | 0.730 | |
| 4 | 0.914 | 0.780 | 0.381 | 0.283 | 0.617 | 0.506 | 0.462 | 0.883 |
Source: Own elaboration Notes: 1 – exhibitor’s non-sales performance, 2 – network capability, 3 – entrepreneurial orientation, 4 – exhibitor’s sales performance, *Diagonal elements (bold) show the square root of average variance extracted (AVE)
Items survey
| Code | tems | Reference |
|---|---|---|
| Innovativeness | ||
| IN1 | Our company tends to present new ideas, products/services at the trade fair | Based on Fadda (2018); Martins and Rialp (2013) and Yoon et al. (2018) |
| IN2 | Our company encourages all employees to change something to a successful trade fair | |
| IN3 | Our company encourages all employees to share changes or innovations for a successful trade fair | |
| IN4 | Our company considers the presentation of new products/services as fundamental to our success at the trade fair | |
| Proactiveness | ||
| P1 | Our company tends to introduce various methods to maintain a dominant position at the trade fair | Based on Fadda (2018); Martins and Rialp (2013) and Yoon et al. (2018) |
| P2 | Our company encourages employees to participate effectively to maintain a dominant position at the trade fair | |
| P3 | Our company is more proactive than the trade fair’s rivals | |
| P4 | Our company adopts a competitive posture at the trade fair | |
| Risk-taking | ||
| RT1 | Our company has a strong tendency for high risk (high return) projects | Based on Fadda (2018); Martins and Rialp (2013) and Yoon et al. (2018) |
| RT2 | Our company would like to undertake risky projects to improve our trade fair performance | |
| RT3 | Our company has a strong tendency to exploit opportunities in uncertain environments | |
| RT4 | Our company prefers success to stability | |
| Competitiveness | ||
| C1 | Our company tends to have a competitive attitude to monitor competitors’ actions at the trade fair | Based on Fadda (2018). |
| C2 | Our company tries to counter competitor strategies at the trade fair | |
| C3 | Our company uses conventional or unconventional methods to compete in the trade fair | |
| C4 | During the trade fair, our company researches the actions of competitors | |
| Autonomy | ||
| A1 | Our company encourages employees to act independently at the trade fair | Based on Fadda (2018). |
| A2 | Our company encourages employees to make important strategic decisions during the trade fair | |
| A3 | Our company encourages employees to implement key programs | |
| A4 | Our company encourages employees to be independent and responsible during the trade fair | |
| Network capability | ||
| NW1 | At the trade fair, our company bets on strong and close relationships with potential partners | Based on Jiang et al. (2018) and Yoon et al. (2018) |
| NW2 | At the trade fair, our company often communicates with current and potential customers and partners | |
| NW3 | At the trade fair, our company coordinates activities for strong and close relationships with potential customers and partners | |
| NW4 | At the trade fair, our company bets on partnerships effectively and positively | |
| NW5 | Our partners and customers trust us | |
| Exhibitor’s sales performance | ||
| EP1 | Profit performance | Abbas et al. (2019); Menon and Edward (2017) and Gopalakrishna and Lilien (1995) |
| EP2 | Sales performance | |
| EP3 | ROI goals | |
| Exhibitor’s non-sales performance | ||
| ENP1 | Information gathering | |
| ENP2 | Networking | |
| ENP3 | Reputation | |
| ENP4 | Customers satisfaction | |
Source: Own elaboration
Appendix
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