A Three-Component Framework for Trade Show Performance Evaluation

Abstract

The purpose of this study was to propose and examine a three-component trade show evaluation framework on exhibitors’ and visitors’ performance that accounts for the relationships between all three key stakeholders (i.e., visitors, exhibitors, and organizers). After a review of previous literature on stakeholder theory and trade show performance evaluation, the visitor–exhibitor–organizer (VEO) framework was proposed to examine dimensions of overall satisfaction of trade show exhibitors and visitors. Based on the VEO framework, exhibitor and visitor performance evaluation models consist of three components that address three corresponding stakeholders: satisfaction with self-performance and satisfaction with the other two key stakeholders, respectively. To validate the framework, exhibitor and visitor models were tested using data from 514 visitors and 92 exhibitors. The results validated the VEO framework by indicating that the three key stakeholders must be accounted for when evaluating trade show performance. All three dimensions (i.e., satisfaction with self-performance, and the other two stakeholders) contributed to overall satisfaction and positive behavioral intention.

Keywords

trade show performance evaluation stakeholder theory

Customer satisfaction, one of the most studied constructs in tourism (Gursoy, McCleary, & Lepsito 2007; Neal & Gursoy, 2008), reflects the perceived quality of products or services (Pizam & Ellis, 1999) and is considered essential for the survival of all tourism businesses (Berkman & Gilson, 1986). Researchers have shown that customer satisfaction can lead to multiple indicators of business, including positive word-of-mouth (Zhang, Qu, & Ma, 2010), higher profitability (Kang & Schrier, 2011), and intention to return (Bowen & Chen, 2001; Jung, 2005). Much of the research using these indicators, however, has been conducted with customers and ignored other equally important stakeholders (Lee & Back, 2009). This myopic approach to studying customer satisfaction is especially problematic in one segment of the tourism industry—trade shows (Harris, 2000).

Trade shows are major marketing events that bring manufacturers, suppliers, distributors, and related services from a given industry or discipline to a single location to exhibit products and services and provide information for visitors and exhibitors (Geigenmüller & Bettis-Outland, 2012; Herbig, O’Hara, & Palumbo, 1997). Contributing billions of dollars to the economy and serving as the largest business-to-business, or B2B, marketing medium (Gopalakrishna, Roster, & Sridhar, 2010; Kinsman, 2015), trade shows provide exhibitors with the opportunity to meet with more professional buyers (i.e., trade show visitors; the majority of whom have high levels of purchase influence) in 1 hour than they normally would in a week (Gillette, 2001; Rosson & Seringhaus, 1995); enhance their corporate image; and carry out market research (Blythe, 2002; Munuera & Ruiz, 1999). Visitors who attend trade shows benefit from meeting with exhibitors and gathering information on market trends and new products and services (Geigenmüller & Bettis-Outland, 2012). Thus, trade shows constitute an important component of businesses’ marketing portfolios.

Despite their importance to multiple business sectors, the factors that contribute to trade show performance have received little attention from researchers. Those who have studied trade show performance have generally not used conceptual frameworks (Hansen, 2004) or accounted for multiple stakeholders. For example, researchers have focused on actual sales at the trade show, number of leads, and attraction efficiency (e.g., Alberca-Oliver, Rodríguez-Oromendía, & Parte-Esteban, 2015; Dekimpe, François, Gopalakrishna, Lilien, & van den Bulte, 1997; Gopalakrishna & Lilien, 1995; Kerin & Cron, 1987), claiming that they are indicators of performance success. They have not supported their claims with clear definitions of these indicators or provided evidence of reliability and validity. As a result, the trade show performance literature lacks a comprehensive conceptual framework of trade show performance as well as reliable and valid scales (Hansen, 2004).

Furthermore, while relationships between trade show visitors, exhibitors, and organizers have been acknowledged (Bruhn & Hadwich, 2005; Jin & Weber, 2013), most researchers have focused on one key stakeholder and ignored its interactions with the others (e.g., Berne & García-Uceda, 2008; Gopalakrishna & Lilien, 1995; Gottlieb, Brown, & Ferrier, 2014; Hansen, 1999; Reinhold, Reinhold, & Schmitz, 2010). Exceptions include studies by Geigenmüller and Bettis-Outland (2012), Herbig et al. (1997), Munuera and Ruiz (1999), and Jin, Weber, and Bauer (2012). These authors accounted for the interactions between two stakeholders and the impacts of their interactions on trade show performance. No studies on the intricate interactions between all three key stakeholders exist.

In response to the limitations of existing research on trade show performance, the objectives of this article are to (a) propose a three-component trade show evaluation framework on exhibitors’ and visitors’ performance that accounts for the relationships between all three key stakeholders (i.e., visitors, exhibitors, and organizers) and (b) empirically examine the proposed framework.

Literature Review

Trade Show Performance Evaluation

Evaluation research has been divided into three major areas: (a) analysis related to conceptualization and design (i.e., formative evaluation), (b) monitoring of program implementation (i.e., process evaluation), and (c) assessment of program effectiveness and efficiency (i.e., summative evaluation; Pearlman & Mollere, 2009; Rossi & Freeman, 1989). Trade show performance evaluation falls under the summative evaluation category and its focus is to assess the effectiveness of management and administration and provide recommendations for improvement.

Profitability and sustainability are most important to trade show managers/organizers. Thus, most trade show research has attempted to document profitability and sustainability from one of two perspectives—exhibitor or visitor. Hansen’s (2004) work is one of the most comprehensive studies on trade show performance from an exhibitor’s perspective (Seringhaus & Rosson, 2004). Hansen argued that trade show performance, which has traditionally been evaluated using outcome-based measures, ignores behavior-based measures. Thus, he set up a preliminary trade show performance construct, which included one outcome-based dimension (sales-related activities) and four behavior-based dimensions (information-gathering activities, image-building activities, motivation activities, and relationship-building activities). Apart from relationship-building activities, the other four dimensions are mostly about the exhibitors’ perception of self-performance. The role of organizers and visitors is largely missing in Hansen’s framework.

In a more recent study, Li (2007) focused on the relationship learning process at a trade show between exhibitors and visitors. Li contended that learning could occur between exhibitors and visitors and that it had a powerful influence on the performance outcomes as perceived by exhibitors. Although the relationship between visitors and exhibitors was emphasized in Li’s study, the other two interrelationships (visitors and organizers; exhibitors and organizers) were unaccounted for.

The visitor-oriented trade show evaluation literature has primarily focused on the expected benefits of trade shows for visitors. Munuera and Ruiz (1999), for example, suggested that trade shows provide a necessary platform for the business relationship between trade show organizers and visitors. Organizers offer various services, such as accommodation, entertainment, and business services, and the visitors are the buyers of those services. Berne and García-Uceda (2008), on the other hand, argued that visitors assess the performance of a trade show based on their perception of the basic features of the trade show, attainment of marketing objectives prior to and after a trade show, and the perceived costs relative to trade show attendance planning and budgeting. These three criteria do not account for the dynamic interactions between visitors and the other two key stakeholders at a trade show. Cox (1983) pointed out that visitors’ poor overall perception of a trade show is often attributable to problems with the personnel at exhibitors’ booths or, more specifically, when visitors fail to connect with the right types of booth personnel (Jung, 2005). Cox’s results suggest that the relationship between visitors and exhibitors (i.e., exhibitors’ ability to attract and connect with visitors and visitors’ knowledge of the exhibits) is a significant predictor of visitors’ overall satisfaction.

Although the role of organizers has been mentioned in the literature (see Berne & García-Uceda, 2008; Munuera & Ruiz, 1999) and the management and marketing issues facing organizers are crucial to the success of any trade show, few researchers have conducted systematic trade show evaluations from the organizer’s perspective. Organizers are the main propeller of the trade show industry and, as such, play an important role in the success of the industry. Berne and García-Uceda (2008) suggest that increased competition between trade show organizers will force them to differentiate themselves by offering user-oriented services. They also need to conduct trade show evaluations that will help them obtain more information from visitors and exhibitors to evaluate their own performance and guide their future improvement. In order to stay competitive, organizers need to have good relationships with visitors and exhibitors and create a favorable environment for interactions between visitors and exhibitors (Gopalakrishna et al., 2010).

A primary objective of trade show organizers is to create effective trade shows that result in positive outcomes for both exhibitors and visitors (Geigenmüller & Bettis-Outland, 2012). However, the amount of research into what makes an effective trade show and what contributes to visitors’ and exhibitors’ satisfaction is limited (Gottlieb, Brown, & Drennan, 2011).

Stakeholder Theory and Key Stakeholders in Trade Shows

The origins of stakeholder theory draw on sociology, economics, politics, and ethics (Mainardes, Alves, & Raposo, 2011). According to Freeman (1984), businesses must account for their relationships with key stakeholders in their external environment. The goal of stakeholder theory is to help organizations realize, analyze, and examine the characteristics of individuals or groups influencing or being influenced by organizational behavior (Mainardes et al., 2011).

In the context of trade shows the three key stakeholders are visitors, exhibitors, and organizers (Jin et al., 2012). Understanding them could allow trade show organizers to provide better service and attract more exhibitors and visitors to their shows. To achieve this goal, however, organizers must understand the behaviors of exhibitors and visitors and why and how they make certain decisions. This information will help organizers to modify their marketing campaign to better cater to the needs of the exhibitors, attract more visitors, and gain a strategic advantage in the marketplace (Oppermann & Chon, 1997). Today, exhibitors and visitors can choose from many different trade shows, all of which are experiencing a high level of competition and pressure to consider differentiation strategies (Berne & García-Uceda, 2008). To survive in this competitive environment, organizers must document a trade show’s potential to attract a large number of exhibitors and visitors (Cox, Sequeira, & Bock, 1986; Fenich, 2012).

Exhibitors tend to be interested in well-organized trade shows with high-quality visitors, while visitors want to meet with an adequate number of exhibitors and to obtain relevant information through organizers. Jago and Deery (2005) conducted semistructured interviews to explore the relationships between visitors, organizers, and international associations in the convention industry. They argued that most studies on convention site selection have ignored the impact of the relationships between the three key stakeholders. The same argument could apply to trade show performance evaluation. The value visitors derive from attending trade shows is strongly related to the support they receive from organizers in establishing and nurturing customer relationships with exhibitors (Geigenmüller & Bettis-Outland, 2012).

Most researchers have only just begun to touch upon the interactions between organizers, exhibitors, and visitors (i.e., stakeholders). They have failed to address how the resulting interactions affect stakeholders’ satisfaction with the trade show and their positive behavioral intention, the perceived value of trade shows, and the dimensionality of trade show performance (Geigenmüller & Bettis-Outland, 2012; Tafesse & Korneliussen, 2011). Thus, we intend to construct and validate a visitor–exhibitor–organizer (VEO) conceptual framework that emphasizes the relationships between the three stakeholders when conducting trade show performance evaluation (Figure 1). As noted, exhibitors’ overall satisfaction with a trade show consists of three components that address the three corresponding stakeholders: satisfaction with self-performance (i.e., exhibitors), satisfaction with the service provider (i.e., organizers), and satisfaction with the business interaction (i.e., visitors). Similarly, visitors’ satisfaction with trade show organizers and exhibitors, along with their satisfaction with self-performance, determine overall satisfaction with a trade show experience.

Figure 1

Proposed Visitor–Exhibitor–Organizer Framework on Trade Show Evaluation

Self-Performance

Exhibitors’ and visitors’ self-performance corresponds to their perception of their own performance at a trade show, which is the most common indicator of trade show performance and is usually measured against preset objectives (Gottlieb et al., 2014; Hansen, 2004). The majority of previous research on trade show performance uses self-performance as a proxy for exhibitors’ (e.g., Hansen, 2004; Kirchgeorg, Springer, & Kästner, 2009; Tafesse & Korneliussen, 2011; Tanner, 2002) or visitors’ overall performance (e.g., Bello, 1992; Berne & García-Uceda, 2008; Gottlieb et al., 2014). For the VEO framework, we acknowledge that self-performance is a significant component of trade show performance. Furthermore, we argue that valuable information would be lost if we only focused on self-performance and ignored the fact that other stakeholders also have a significant impact on trade show performance.

Service Provider

Through purchasing a booth at a trade show, exhibitors trust that trade show organizers will ensure that their needs are addressed (Munuera & Ruiz, 1999). These needs may be economic and relational in nature and involve elements such as logistics and problem solving (Geigenmüller & Bettis-Outland, 2012). Visitors, on the other hand, may seek social and business services from organizers (Munuera & Ruiz, 1999).

Rinallo, Borghini, and Golfetto (2010) argued that trade show organizers are better placed than exhibitors to manage the overall visitor experience. Thus, the service provided by trade show organizers is a significant part of both exhibitors’ and visitors’ trade show experience and, as a result, an important component of their overall satisfaction.

Interaction Between Exhibitors and Visitors

As customers of the trade show “product” that organizers “sell,” exhibitors and visitors are components of the product and their interaction at different stages of a trade show will enhance their performance (Jin & Weber, 2013). Exhibitors and visitors use trade shows to develop new business relationships and work on existing ones (Blythe, 2002). Berne and García-Uceda (2008) suggested that motives for attending a trade show among both visitors and exhibitors are generally similar and, as a result, providing a setting for interaction between exhibitors and visitors is essential for the success of a trade show.

Satisfaction

Overall satisfaction has been extensively discussed in the trade show literature (see Kang & Schrier, 2011; Lee & Back, 2009; Oh, 2000). Although it is valuable to know customers’ (i.e., visitors and exhibitors) overall satisfaction with their trade show experience, the major problem with using an overall satisfaction measure is that it does not address the specific dimensions of satisfaction and, as such, is of limited value to trade show organizers (Hansen, 2004).

In addition, studies focused on exhibitors’ satisfaction and positive behavioral intention have only accounted for exhibitors’ self-performance and/or the interactions between exhibitors and visitors (Jin et al., 2012; Li, 2007). They have generally not addressed the role of organizers in shaping exhibitors’ satisfaction and positive behavioral intention or visitors and their self-performance. Thus, the following hypotheses are proposed:

Hypothesis 1a: Exhibitors’ satisfaction with visitors is positively related to their overall satisfaction with the trade show.

Hypothesis 1b: Exhibitors’ satisfaction with self-performance is positively related to their overall satisfaction with the trade show.

Hypothesis 1c: Exhibitors’ satisfaction with organizers is positively related to their overall satisfaction with the trade show.

Hypothesis 2a: Visitors’ satisfaction with self-performance is positively related to their overall satisfaction with the trade show.

Hypothesis 2b: Visitors’ satisfaction with exhibitors is positively related to their overallsatisfaction with the trade show.

Hypothesis 2c: Visitors’ satisfaction with organizers is positively related to their overall satisfaction with the trade show.

Behavioral Intention

Behavioral intention refers to the stated likelihood to engage in a particular behavior (Oliver, 1980). Researchers have documented that customer satisfaction leads to positive behavioral intention, such as willingness to return and positive word-of-mouth (Cronin & Taylor, 1992; Dube, Renaghan, & Miller, 1994). When the two behavioral components are favorable, customers indicate that they are likely to revisit the service provider and positively comment on their experience. When the two behavioral components are negative, the opposite behaviors are likely to occur (Jani & Han, 2011; Peter & Olson, 2003).

With trade shows, Jung (2005) and Kang and Schrier (2011) found that visitors’ satisfaction has a positive influence on their intention to revisit and to positively comment on their experience. These positive outcomes contribute to an improved perception of the trade show and the host destination (Tanford, Montgomery, & Nelson, 2012; Zhang et al., 2010). Patterson and Spreng (1997) and Kang and Schrier (2011) found that exhibitors were more likely to return to a trade show in the future if the risk of uncertainty (e.g., whether their exhibition will be successful) had been reduced.

However, it is important to note that a high satisfaction level does not guarantee revisitation. Although satisfaction with a particular destination could be a necessary condition for explaining repeat visits, it is not sufficient to explain the phenomenon since many respondents report a high satisfaction level and do not return to the same destination (Gitelson & Crompton, 1984; Kozak, 2001). Other factors that influence intent to revisit include past experience with the destination (Gitelson & Crompton, 1984) and travel motivations (Yoon & Uysal, 2005). As for research on trade shows, previous studies showed a considerable amount of unexplained variance in behavioral intention with satisfaction as the independent variable (e.g., Gottlieb et al., 2011; Hansen, 2004), suggesting that other factors influence trade show exhibitors’ and visitors’ intent to revisit. Thus, trade show organizers may want to obtain information about attendee’s intention to revisit and their willingness to say positive things about the trade show. After all, organizers have to ensure that they can attract enough attendees over time to survive in the increasingly competitive trade show industry.

Studying the behaviors of repeat visitors will elicit invaluable market information for a trade show attempting to maintain its competitive edge (Huang & Hsu, 2009) and increase the number of repeat customers. On the other hand, in order to attract new exhibitors and visitors, trade show organizers need to facilitate positive word-of-mouth (Rosson & Seringhaus, 1995). Previously, researchers have only used satisfaction with one key stakeholder to predict positive behavioral intention (e.g., Kang & Schrier, 2011); they have not considered the impacts of all three key stakeholders. No matter how many sales leads exhibitors get during a trade show, if they do not receive adequate service from organizers, they might not be satisfied with their overall experience and might choose to skip the trade show the next year (Seringhaus & Rosson, 2004). Similarly, visitors might enjoy the most meticulous service from the organizer, but if they did not meet enough exhibitors, the whole experience would be considered unsatisfactory, leading to negative word-of-mouth (Gottlieb et al., 2011; Jung, 2005). Thus, this study intends to examine the key components that determine trade show visitors’ and exhibitors’ satisfaction and positive behavioral intention based on the VEO framework where all three key stakeholders are represented (Figures 2 and 3). Keeping this intention in mind, an exhibitor model and a visitor model were constructed and the following hypotheses were proposed:

Hypothesis 3: Exhibitors’ overall satisfaction, determined by exhibitors’ satisfaction with visitors, self-performance, and organizers, is positively related to their positive behavioral intention.

Hypothesis 4: Visitors’ overall satisfaction, determined by visitors’ satisfaction with self-performance, exhibitors, and organizers, is positively related to their positive behavioral intention.

Figure 2

Visitor–Exhibitor–Organizer Framework on Exhibitor Evaluation

Figure 3

Visitor–Exhibitor–Organizer Framework on Visitor Evaluation

In summary, we have met the first objective of this article, which was to propose a three-component trade show evaluation framework on exhibitors’ and visitors’ performance that accounts for the relationships between visitors, exhibitors, and organizers. The proposed framework is called the VEO conceptual framework (see Figure 1). The second objective was to empirically examine the VEO. This will be accomplished by examining exhibitors’ and visitors’ satisfaction and how it influences positive behavioral intention.

Method

Data Collection

Surveys are the most frequently used data collection method in trade show performance evaluation (e.g., Hansen, 2004; Seringhaus & Rosson, 2004; Tafesse & Korneliussen, 2011). To test the VEO conceptual framework, an exhibitor survey and a visitor survey at the same trade show (i.e., SEMICON West 2009) were processed and analyzed. Founded in 1971, SEMICON WEST is one of the leading trade shows in the semiconductor industry and a flagship annual event for the display of new products and technologies from across the microelectronics supply chain. SEMICON WEST 2009 was held in San Francisco from July 14th to July 16th and hosted 540 exhibitors and more than 10,000 visitors from more than 40 countries. An online survey system was established to collect data electronically. The exhibitor survey link was sent to all 540 exhibitors at the SEMICON WEST 2009 one month after the trade show; the visitor survey link was sent to verified buyers during the same time. Rather than collecting data on site, a 1-month delay allowed exhibitors and visitors to have sufficient exposure prior to, during, and after the trade show (Gopalakrishna & Lilien, 1995). To drive traffic to the online survey, SEMI (the organizer) reminded exhibitors and visitors during customer outreach visits, through the trade show exhibitor/visitor update, and in an e-mail follow-up newsletter to complete the online survey. To achieve anonymity and elicit honest feedback, no demographic information was collected (Stanton, 1998). The time period for visitors and exhibitors to submit responses was from August 20 to September 9, 2009.

Instrument

Satisfaction was measured on a 10-point Likert-type scale ranging from extremely unsatisfied (1) to extremely satisfied (10). The 10-point Likert-type scale offers more variance and a higher degree of measurement precision than a smaller Likert-type scale (e.g., 7-point or 5-point Likert-type scales). Furthermore, the 10-point Likert-type scale requires a smaller sample size for a given amount of reliability and statistical power and leaves more room for improvement (Wittink & Bayer, 2003). Exhibitors were asked to indicate their satisfaction with contractor services and their satisfaction with organizer’s customer service. A service contractor, also known as show manager, is anyone who provides a product or service for the exhibitors during the trade show (Fenich, 2012). Contractor services has been identified in the literature as part of the service provided by trade show organizers (e.g., Seringhaus & Rosson, 2004; Yuksel & Voola, 2010). Exhibitors’ satisfaction with visitors was measured on three aspects, visitors’ job level, purchasing authority, and job function using a 10-point Likert-type scale.

Previous studies on exhibitor trade show performance evaluation have mainly focused on motivations to participate (Barczyk, George, & William, 1989; Montgomery & Strick, 1995). In this study, satisfaction with achieving goals at the trade show was used to measure self-performance. Specifically, exhibitors were asked how satisfied they were in meeting their objectives at the trade show and their overall satisfaction with the trade show on a 10-point Likert-type scale.

Willingness to return and positive word-of-mouth were used as measures of exhibitors’ behavioral intention (Ainscough, 2005; Kim, Lee, & Yoo, 2006). To reduce respondents’ inclination to create similarities in their responses across the items and thus reduce multicollinearity (Wittink & Bayer, 2003), dichotomous questions were used to measure behavioral intention. Specifically, exhibitors were asked to provide yes or no answers to the following questions: (a) “Would you exhibit at this trade show in the future?” and (b) “Would you recommend this trade show to other companies?”

A single item on a 10-point Likert-type scale was used to measure visitors’ satisfaction with organizers, exhibitors, and self-performance, respectively. Although a single indicator latent variable is less common in psychological or marketing research, it is quite popular in sociology and economics (Hayduk & Littvay, 2012) and can be best handled by fixing its loading to one and leaving its variance free to be estimated (Kenny, Kashy, & Bolger, 1998). Visitors’ overall satisfaction was assessed by asking individuals to “Please rate your overall satisfaction with this trade show.” Behavioral intention was measured by asking visitors to provide yes or no answers to the following questions: (a) “Would you attend this trade show in the future?” and (b) “Would you recommend this trade show to others?”

Data Analysis

Data were entered into SPSS 21.0 and screened for entry errors, missing values, multivariate normality, and outliers that could impair data analyses. AMOS 21.0 was used to examine two models (i.e., exhibitor and visitor) and test the hypotheses through structural equation modeling (SEM) with the maximum likelihood method of estimation. Because SEM is designed to evaluate how well a proposed conceptual model fits the collected data (Yoon, Gursoy, & Chen, 2001) and measure the relationships among sets of construct variables (Turner & Reisinger, 2001; Yoon & Uysal, 2005), it was considered to be an appropriate statistical procedure for testing the proposed models. Since there are multiple dimension items in the exhibitor model, exhibitor’s overall satisfaction was constructed as a second-order factor that included three dimensions: satisfaction with organizers, satisfaction with self-performance, and satisfaction with visitors. The visitor model consisted of single-item factors. Thus, visitor’s overall satisfaction was constructed as a first-order factor that consisted of three items: satisfaction with organizers, satisfaction with self-performance, and satisfaction with exhibitors.

Correlation matrices, standard deviations, and goodness-of-fit statistics were referenced to examine the hypothesized models in SEM. In order to compare different paths, standardized solutions were used to report the results. Model fit was evaluated with three goodness-of-fit indices: the comparative fit index (CFI; Bentler, 1990), the root mean square error of approximation (RMSEA; Steiger, 1990), and the Tucker–Lewis index (TLI; Tucker & Lewis, 1973). Minimum TLIs and CFIs of .90 were required for model acceptance, and values of .95 or greater were regarded as an indication of good model fit. RMSEAs of less than .06 were indicators of a good-fitting model (Hu & Bentler, 1998).

Results

Exhibitors completed a total of 92 valid surveys. The response rate of 17% was considered satisfactory given the online nature of the survey (Pan, Woodside, & Meng, 2014). A total of 514 valid responses were received from visitors. The response rate for the visitor survey could not be calculated because the number of verified buyers was proprietary information held by the trade show organizer. SEM requires a sample size of at least 10 times the number of observed variables in the model (Assaker, Vinzi, & O’Connor, 2010; Hair, Black, Babin, Anderson, & Tatham, 2010). There are nine observed variables in the exhibitor model and six observed variables in the visitor model. Thus, the minimum sample size was 90 for the exhibitor model and 60 for the visitor model. The sample size was 92 for the exhibitor model and 514 for the visitor model, both of which exceeded the minimum requirement.

Correlation matrices of the exhibitor and visitor models are presented in Tables 1 and 2. Most variables were significantly correlated with each other and in the expected direction. Cronbach’s alphas were acceptable (.7 or higher), providing evidence of construct reliability.

Table 1

Correlation Coefficients of the Exhibitor Model

Variables	1	2	3	4	5	6	7	8	9
1. Sat. with contractor
2. Sat. with staff service	.57**
3. Sat. with self-performance	.24**	.40**
4. Sat. with function	.19	.37**	.47**
5. Sat. with purchase	.06	.26*	.50**	.83**
6. Sat. with ranks	.14	.31**	.45**	.80**	.82**
7. Overall sat.	.33**	.54**	.83**	.55**	.52**	.49**
8. Word-of-mouth	.11	.28**	.53**	.48**	.45**	.48**	.54**
9. Willingness to return	−.02	.12	.43**	.23**	.23*	.19	.44**	.54**
Mean	6.63	7.33	6.04	6.63	6.46	6.78	6.47	1.67	1.85
Standard deviation	2.09	1.72	2.11	1.99	2.21	1.92	2.05	.47	.36

Note: Sat. = Satisfaction. N = 92.

p < .05. **p < .01.

Table 2

Correlation Coefficients of the Visitor Model

Variables	1	2	3	4	5	6
1. Sat. with organizers
2. Sat. with self-performance	.31**
3. Sat. with exhibitors	.27**	.71**
4. Overall sat.	.34**	.89**	.78**
5. Word-of-mouth	.15**	.60**	.53**	.71**
6. Willingness to return	.18**	.49**	.44**	.59**	.70**
Mean	8.50	6.37	6.43	6.37	1.79	1.88
Standard deviation	1.69	2.08	2.02	2.27	.41	.32

Note: Sat. = satisfaction. N = 514.

p < .05. **p < .01.

To further examine the factor structure of the proposed models, confirmatory factor analysis of the eight items in the exhibitor model and five items in the visitor model were undertaken. Convergent validity refers to the degree to which two measures of theoretically correlated constructs are actually related and the following conditions must be met to establish convergent validity: (a) all item loadings need to be statistically significant, (b) composite reliability needs to be higher than .70, and (c) average variance extracted (AVE) needs to be higher than .50 (Anderson & Gerbing, 1988; Bagozzi & Yi, 1988; Fornell & Larcker, 1981). For both the exhibitor and visitor models, the confirmatory factor analysis results indicated that all item loadings were statistically significant (p < .05) and the goodness-of-fit statistics for the models were satisfactory: exhibitor model, χ²(16, N = 92) = 16.962, p = .388, CFI = .997, TLI = .995, RMSEA = .026; visitor model, χ²(4, N = 514) = 8.021, p = .091, CFI = .996, TLI = .990, RMSEA = .044 (Hu & Bentler, 1998). Composite reliabilities for the three dimensions in the exhibitor model and two dimensions in the visitor model exceeded the cutoff value of .70. All AVE values exceeded the cutoff value of .50. The relevant statistics are presented in Tables 3 and 4. Overall, the results established the convergent validity of the measurement scale.

Table 3

Exhibitor Model Confirmatory Factor Analysis Results

Dimension	Subdimension	Standardized Factor Loading	Composite Reliability	Average Variance Extracted
Visitor			.93	.82
	Job function	.91
	Purchase power	.92
	Rank	.89
Organizer			.79	.66
	Staff	1.00
	Contractor	.57
Self-performance			NA	NA
	Achieving objectives	1.00
Positive behavioral intention			.74	.59
	Word-of-mouth	.82
	Willingness to return	.67

Note: NA = not applicable.

Table 4

Visitor Model Confirmatory Factor Analysis Results

Dimension	Subdimension	Standardized Factor Loading	Composite Reliability	Average Variance Extracted
Overall satisfaction			.71	.68
	Self-performance	.90
	Organizer	.33
	Exhibitor	.79
Positive behavioral intention			.81	.92
	Word-of-mouth	.92
	Willingness to return	.76

To test the hypotheses, the goodness-of-fit indices for the proposed model were first examined. The CFI, TLI, and RMSEA of the exhibitor model were within the accepted cutoff values, χ²(23, N = 92) = 28.929, p = .183, CFI = .988, TLI = .981, RMSEA = .053 (Hu & Bentler, 1998). The variances of the satisfaction and positive behavioral intention constructs explained by exogenous variables (i.e., squared multiple correlation) ranged from .15 to .66. The standardized path coefficients are highlighted in Figure 4.

Figure 4

Structural Equation Modeling Results on the Exhibitor Model

The visitor model also exhibited a good fit. The CFI, TLI, and RMSEA fell within the accepted cutoff values, χ²(6, N = 514) = 21.136, p = .002, CFI = .993, TLI = .982, RMSEA = .070. The significant p value was because of the large sample size (Bentler & Bonett, 1980). The variances of the satisfaction and positive behavioral intention constructs explained by exogenous variables (squared multiple correlation) ranged from .06 to .68. The standardized path coefficients are highlighted in Figure 5.

Figure 5

Structural Equation Modeling Results on the Visitor Model

The standardized path coefficients associated with the eight hypotheses are shown in Table 5. All structural path estimates were significant. The signs of structural paths were consistent with the hypothesized relationships among the latent constructs.

Table 5

Hypotheses Testing

Paths	Standardized Coefficients	Standard Error	Critical Ratio	Hypothesis Testing
Exhibitor model
Hypothesis 1a: Sat. with visitors → Overall sat.	.15	.07	2.33*	Supported
Hypothesis 1b: Sat. with self-perf → Overall sat.	.66	.06	10.39**	Supported
Hypothesis 1c: Sat. with organizers → Overall sat.	.23	.11	3.44**	Supported
Hypothesis 3: Overall sat. → Positive behavioral intention	.66	.02	6.05**	Supported
Visitor model
Hypothesis 2a: Sat. with self-performance → Overall sat.	.68	.03	26.66**	Supported
Hypothesis 2b: Sat. with exhibitors → Overall sat.	.28	.03	11.04**	Supported
Hypothesis 2c: Sat. with organizers → Overall sat.	.06	.03	3.05*	Supported
Hypothesis 4: Overall sat. → Positive behavioral intention	.78	.01	22.77**	Supported

Note: Sat. = satisfaction.

p < .01. **p < .001.

In both the exhibitor and visitor models, satisfaction with self-performance was the dominant indicator of overall satisfaction. The standardized path coefficient from self-performance to overall satisfaction was .66 in the exhibitor model and .68 in the visitor model. It is important to note that the paths from satisfaction with the other two stakeholders to overall satisfaction were also significant. The standardized path coefficient from satisfaction with organizers to overall satisfaction in the exhibitor model was .23, while the same path was .06 in the visitor model. The interaction between exhibitors and visitors was quite consistent across the two models. For exhibitors, the standardized path coefficient from their satisfaction with visitors to overall satisfaction was .15, which is smaller than but close to the standardized path coefficient in the visitor model (.28).

For the exhibitor model, the squared multiple correlation value for overall satisfaction was .76, indicating that more than three quarters of the variance of overall satisfaction was explained by exhibitors’ satisfaction with the three components of the VEO framework. Also, 43% of the variance of positive behavioral intention was explained by the exogenous variables in the model, which is higher than the percentage of variance explained in previous studies on this subject (e.g., Kang & Schrier, 2011).

The visitor model showed even better predictive power. Eighty-four percent of the variance of overall satisfaction was explained by visitors’ satisfaction with the three components of the VEO framework. Sixty-one percent of the variance of positive behavioral intention was explained by the exogenous variables in the model, which is much higher than the percentage of variance explained in previous studies (e.g., Y. Kim, Lee, & Love, 2009; Tanford et al., 2012; Zhang et al., 2010).

Conclusions and Discussion

Applying stakeholder theory, we proposed the VEO conceptual framework and found that it works well in a trade show context and explained a good portion of variance in visitors’ and exhibitors’ overall satisfaction and positive behavioral intention. The results indicated that the three key stakeholders must be accounted for when evaluating exhibitors’ and visitors’ trade show performance. All three dimensions (i.e., satisfaction with self-performance, and the other two stakeholders) contributed to overall satisfaction and positive behavioral intention. If researchers only focus on one or two dimensions, as has been done previously, a great deal of explanatory power is lost, the results are less meaningful, and the recommendations for improving exhibitors’ and visitors’ trade show experience are less comprehensive.

Satisfaction with self-performance turned out to be the strongest predictor of overall satisfaction in both the exhibitor and visitor models, which confirmed the importance of self-performance discussed by Hansen (1999) and Li (2007). However, it is important to note that satisfaction with the other two groups was also essential to overall satisfaction. In the exhibitor model, satisfaction with organizers and satisfaction with visitors both contributed significantly to overall satisfaction, indicating that information would have been lost if the focus was only on exhibitors (Jin et al., 2012). The same argument applies to the visitor survey. Visitors’ satisfaction with exhibitors and organizers both contributed significantly to visitors’ overall satisfaction. Positive behavioral intention was also better explained when all three stakeholders were taken into consideration.

Theoretical Implications

An understanding of trade show performance from a multi-stakeholder perspective has been long overdue judging by the limited amount of research in this area (Gottlieb et al., 2014). A major theoretical contribution of this study is that it applied stakeholder theory on trade show performance evaluation and introduced a more comprehensive way of measuring exhibitors’ and visitors’ satisfaction. It is inconceivable that trade show organizers, exhibitors, or visitors can make sound decisions when an accepted body of knowledge about trade show performance is lacking (Tafesse & Korneliussen, 2011), which is particularly important as trade shows are no longer considered as mere selling opportunities (Hansen, 2004). The results indicated that exhibitors’ and visitors’ satisfaction are multidimensional constructs that include three components: satisfaction with self-performance and satisfaction with the other two key stakeholders, respectively. Thus, trade show exhibitors’ and visitors’ overall satisfaction depends not only on their self-performance but also on their perceptions of other key stakeholders (Jin et al., 2012). Self-performance is the most important predictor of visitors’ and exhibitors’ overall satisfaction and positive behavioral intention. In addition, understanding the interdependent relationships between stakeholders may help trade show organizers provide more services desired by visitors and exhibitors.

Managerial Implications

Trade show organizers, exhibitors, and visitors could use the VEO framework as a diagnostic tool for future improvement and to benchmark their performances across different time periods and/or against their competitors.

For organizers, the VEO conceptual framework will be invaluable to better understand the decision-making process of visitors and exhibitors and make managerial changes to improve their satisfaction and positive behavioral intention. Trade show organizers worldwide face tremendous competition for exhibitors and visitors and the success of a trade show is not only dependent on the number but also the financial consequences of exhibitors and visitors (Kirchgeorg et al., 2009). Trade show organizers should therefore offer superior trade show services that help a trade show differentiate itself from competitors and develop innovative concepts to accommodate exhibitors’ and visitors’ needs (Geigenmüller & Bettis-Outland, 2012).

The trade show industry is fully part of the experience economy and organizers can design better trade shows that improve exhibitors’ and visitors’ satisfaction by monitoring their experiences and creating more engaging experiences (Rinallo et al., 2010). For example, trade show organizers should research their exhibitors’ motivations, provide more services desired by exhibitors (e.g., assistance in marketing, presentations, and booth design, results of visitor satisfaction survey), enhance the quality of existing services, and identify and attract more visitors who have decision-making and buying authority (Bello, 1992). Similarly, to enhance visitors’ satisfaction level and positive behavioral intention trade show organizers should strive to: (a) better understand, and in turn help exhibitors better understand the objectives of trade show visitors (Kozak & Kayar, 2009); (b) provide a convincing spectrum of exhibits; and (c) provide better visitor services.

Trade show organizers could also use the VEO framework to design their postshow evaluation questionnaire. Based on the specific attributes of the trade show, organizers could develop specific items for each of the three dimensions (i.e., satisfaction with visitors, self-performance, and organizers) addressed on the exhibitor survey and different items for each of the three dimensions (i.e., satisfaction with self-performance, exhibitors, and organizers) addressed on the visitor survey. Also, rather than just asking about overall satisfaction, the results of a comprehensive postshow evaluation could help organizers identify the major problems with their trade show and allocate their limited resources to address the problems.

Trade show exhibitors and visitors could also use the VEO framework to reflect on their performance and determine whether or not to attend a trade show in the future. Participation in trade shows is expensive for both exhibitors and visitors, so they need to know what factors influence their performance (Alberca-Oliver et al., 2015). The VEO framework provides exhibitors and visitors with guidelines to correct inefficient management decisions and promote positive outcomes from the trade show. For example, our results indicated that the interaction quality between exhibitors and visitors is essential for the success of a trade show. Thus, exhibitors and visitors need to look beyond sales activities and facilitate the interaction as well as promote the quality and quantity of the interaction.

Limitations and Future Research

While the results of this study challenge researchers and practitioners interested in the trade show industry to think about the outcomes associated with the relationships that exist between key stakeholders, further research is required. First, to measure satisfaction with each of the three dimensions of the VEO framework, two or three items for the exhibitor model and a single item for the visitor model were used. In order to further establish the reliability and validity of the VEO framework and produce applicable managerial implications, multiple items need to be developed to represent each satisfaction dimension. For example, rather than asking visitors about their general perception of the organizer’s performance, researchers should question visitors about the specific services provided by the organizer such as accommodations, onsite services, and networking opportunities. Scale development procedures should follow to examine the composite reliability, content validity, convergent validity, discriminant validity, and predictive validity (Churchill, 1979; DeVellis, 2012; Fornell & Larcker, 1981), in order to fully establish the reliability and validity of the VEO framework and lay the groundwork for future studies on key stakeholders. Furthermore, this study applied the VEO framework on the performance of exhibitors and visitors. Future studies could examine the impacts the three dimensions (i.e., satisfaction with self-performance and the other two key stakeholders) have on trade show organizers’ performance. Since there are relatively few studies on the conceptualization of organizers’ self-performance and satisfaction with exhibitors and visitors, interviews with trade show organizers could be a first step toward understanding organizers’ perception of their relationships with exhibitors and visitors and how these relationships affect their satisfaction and decisions on the scope and content of the next trade show.

Second, the samples used in this study were self-selected rather than probability samples. The voluntary respondents are active exhibitors or visitors, and their opinions may differ from attendees who did not respond to the online survey. A probability sample should be used in the future in order to extrapolate the results to all trade show participants.

Third, an online survey was used in this study. Internet users tend to be younger and more highly educated than the general U.S. population (Purcell, Rainie, Mitchell, Rosenstiel, & Olmstead, 2010). Visitors and exhibitors at SEMICON 2009 were people in the semiconductor industry who are familiar with technology and the Internet, and most likely are highly educated. Thus, the use of an online survey in this study context may not have been an issue, but should be deliberated in future studies. Furthermore, web-based surveys are thought to provide high-quality samples for populations who are likely to frequent the Internet (University of Texas, Austin, 2010). So, again, using an online method of data collection in this study may have only slightly affected the representativeness of respondents.

Fourth, this study focused on one particular trade show in one industry. Trade show practices tend to vary across different market environments (Dekimpe et al., 1997). Caution should be taken when applying the results and conclusions to other trade shows. As a pilot study proposing the VEO framework, an objective of this study was to lay the groundwork with this new perspective. Furthermore, there are other stakeholders that might influence the satisfaction level of exhibitors and visitors, such as exhibition center and host city (Jin & Weber, 2013; Zhang, Leung, & Qu, 2007). Thus, future studies should integrate other stakeholders into the conceptual framework and apply the framework at trade shows in other industries and geographic locations.

Despite its limitations, this study has applied stakeholder theory on trade show performance evaluation and revealed and validated the VEO conceptual framework. The results have provided researchers and practitioners with new insight to the relationships that exist between the three key stakeholders and the outcomes of those relationships, all of which may have important impacts on the success of the trade show industry.

Footnotes

Yeqiang Lin, PhD (e-mail: yklin@calpoly.edu), is an assistant professor in the Department of Recreation, Parks, and Tourism Administration at California Polytechnic State University, San Luis Obispo, California. Jeff Jiang, PhD (e-mail: jjiang@csuchico.edu), is an associate professor in the Department of Recreation, Hospitality and Parks Management at California State University, Chico, California. Deborah Kerstetter, PhD (e-mail: debk1@psu.edu), is Professor Emerita in the Department of Recreation, Park, and Tourism Management at the Pennsylvania State University, University Park, Pennsylvania.

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